Methodological update in Medicina Intensiva

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Sirgo Rodríguez, M. Chico Fernández, F. Gordo Vidal, M. García Arias, M.S. Holanda Peña, B. Azcarate Ayerdi, E. Bisbal Andrés, A. Ferrándiz Sellés, P.J. Lorente García, M. García García, P. Merino de Cos, J.M. Allegue Gallego, A. García de Lorenzo y Mateos, J. Trenado Álvarez, P. Rebollo Gómez, M.C. Martín Delgado" "autores" => array:17 [ 0 => array:2 [ "nombre" => "G." "apellidos" => "Sirgo Rodríguez" ] 1 => array:2 [ "nombre" => "M." "apellidos" => "Chico Fernández" ] 2 => array:2 [ "nombre" => "F." "apellidos" => "Gordo Vidal" ] 3 => array:2 [ "nombre" => "M." "apellidos" => "García Arias" ] 4 => array:2 [ "nombre" => "M.S." "apellidos" => "Holanda Peña" ] 5 => array:2 [ "nombre" => "B." "apellidos" => "Azcarate Ayerdi" ] 6 => array:2 [ "nombre" => "E." "apellidos" => "Bisbal Andrés" ] 7 => array:2 [ "nombre" => "A." "apellidos" => "Ferrándiz Sellés" ] 8 => array:2 [ "nombre" => "P.J." "apellidos" => "Lorente García" ] 9 => array:2 [ "nombre" => "M." 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"apellidos" => "Martín Delgado" ] 16 => array:1 [ "colaborador" => "Planning, Organization and Management Group of the Sociedad Española de Medicina Intensiva Crítica y Unidades Coronarias (SEMICYUC)" ] ] ] ] ] "idiomaDefecto" => "en" "Traduccion" => array:1 [ "es" => array:9 [ "pii" => "S0210569117303613" "doi" => "10.1016/j.medin.2017.12.002" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "es" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0210569117303613?idApp=WMIE" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173572718300468?idApp=WMIE" "url" => "/21735727/0000004200000003/v1_201803310417/S2173572718300468/v1_201803310417/en/main.assets" ] "en" => array:19 [ "idiomaDefecto" => true "cabecera" => "Series in Intensive Medicine: Methodological update in Medicina Intensiva" "titulo" => "Methodological update in Medicina Intensiva" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "180" "paginaFinal" => "183" ] ] "autores" => array:1 [ 0 => array:3 [ "autoresLista" => "J.L. García Garmendia" "autores" => array:1 [ 0 => array:3 [ "nombre" => "J.L." "apellidos" => "García Garmendia" "email" => array:1 [ 0 => "joseluis.garciagarmendia@sjd.es" ] ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Servicio de Cuidados Críticos y Urgencias, Hospital San Juan de Dios del Aljarafea, Bormujos, Sevilla, Spain" "identificador" => "aff0005" ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Actualización en metodología en Medicina Intensiva" ] ] "textoCompleto" => "The series of methodology we start in Medicina Intensiva tries to bring the clinician closer to different methodological issues that we have considered relevant in the research setting of critically ill patients.Critical disease has some special conditions when it comes to generating scientific knowledge.<a class="elsevierStyleCrossRef" href="#bib0040">1</a> On the one hand, the amount of monitoring and the availability of tests in these patients provides a great deal of analyzable information. Also, the high impact of physiopathological aspects allows us to go deep into applied basic research. Due to the patients’ fast progression and rates of survival, variable mortality is commonly used, generating high interest and clinical relevance to clinical researches. On the other hand, the velocity of changes, complexity, and interrelation of variables and simultaneous treatments, working schedules, and difficulties trying to find homogeneous enough patients in one single center elevates the requirements of study designs, and resources needed.<a class="elsevierStyleCrossRef" href="#bib0045">2</a>All these challenges lead to two (2) fundamental issues. On the one hand, the need to find tools for statistical analysis adjusted to data, and possible designs with critically ill patients, which is why new and diverse approaches are needed. On the other hand, it is important to improve methodological training for research purposes and also for the interpretation of results. In this series we do not wish to write a statistical treaty, but draw an interesting picture including general aspects of result interpretation as advanced topics among which we will find new strategies of analysis, or big data.In one comparative analysis of the statistical techniques used in 3 journals dedicated to the critically ill patient (Medicina Intensiva, Intensive Care Medicine, and Critical Care Medicine), we analyzed the methodological procedures used in one recent sample of the original manuscripts published during 2016 and 2017 (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>). Other than the differences seen in the number of original manuscripts published per issue, and in the presence of Spanish authors in the three (3) journals, we found significant differences in the type of studies conducted and in the complexity of the methodology used. Although the three journals mostly use observational studies, compared to the other two journals, Intensive Care Medicine includes a higher percentage of clinical trials, being such trials rare in Medicina Intensiva (4.6%). In Medicina Intensiva, the percentage of multicenter studies is lower than in the other two journals, and there are not too many estimates of the size of the sample either, probably due to the fact that fewer clinical trials are published.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>On the statistical analyses, the number of tests used is much lower in Medicina Intensiva than it is in the other two journals, although in the most common methods we did not find any significant differences, except in the multiple linear regression analysis. Where we did find a clear difference is in the use of more advanced statistical methods, almost inexistent in the original manuscripts from Medicina Intensiva, but present in one third of the originals from Intensive Care Medicine and Critical Care Medicine. The greater use of advanced tests has become a common practice and is a clear improvement compared to similar assessments made in high-impact factor journals some 20 years ago.<a class="elsevierStyleCrossRef" href="#bib0050">3</a>In sum, we found a significant difference in the level of design complexity and statistical analysis in the manuscripts submitted to Medicina Intensiva compared to the other two (2) journals.On the other hand, in one review conducted on a sample of 62 original manuscripts submitted for publication to Medicina Intensiva from 2016 through 2017, we found a series of methodological problems that are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> being the most common ones, per frequency of appearance, the inadequate definition of variables, the mistakes made in the description of results, the fact that conclusions did not match the results, the lack of statistical analysis (multivariate models, above all), the existence of not very clear designs, the inadequate presentation of the goal, selection biases, and the use of inadequate statistical tests for analysis. These problems have also been found in other publications<a class="elsevierStyleCrossRef" href="#bib0055">4</a> and, in this sense, the use of reviewers trained in statistics during the review process has proven a useful tool to improve the quality of the articles published<a class="elsevierStyleCrossRef" href="#bib0060">5</a> and implies some sort of ethical commitment.<a class="elsevierStyleCrossRef" href="#bib0065">6</a><elsevierMultimedia ident="tbl0010"></elsevierMultimedia>It is, therefore, evident that there is margin for improvement in methodological design, and in the analysis and interpretation of results in all research studies submitted to our journal. The Editorial Committee of Medicina Intensiva, directed by Dr. Garnacho Montero, understands that this journal needs to draw and promote studies of high methodological quality that, in time, will improve the impact factor and promote the submission of new quality studies.<a class="elsevierStyleCrossRef" href="#bib0070">7</a> Within this virtuous circle setting, this series is born in an attempt to improve the quality of our investigations.This series begins with a general reflection on the particularities that affect the studies of critically ill patients, and we will be discussing the difficulties, different approaches, and new strategies defined to make scientific knowledge move forward. Also, we will be analyzing the interpretation of statistical results in its most basic and advanced aspects, trying to facilitate an adequate understanding of the terminology used in the most common scientific literature. This paper is a review of common methodological errors made in clinical research, some of which can be more or less innocent, but all will undoubtedly help the reader keep a critical view of the information presented here. We will also be reviewing a fundamental aspect known as the bioethics of clinical research–very important for the editorial team,<a class="elsevierStyleCrossRef" href="#bib0070">7</a> a historical summary will be presented here, followed by an analysis of the different ethical requirements that are mandatory in the clinical research of critically ill patients.When we open up the arsenal of statistical tools available, three (3) reviews can be conducted: one review on the techniques used to determine the causality of observational studies with an emphasis on propensity score analysis; a second review on new techniques of alternative analysis such as hybrid studies, nested case–control studies, recursive partitions, or competitive events, one article discussing the development of systematic reviews, and meta-analyses as sources of knowledge. Lastly, we have addressed a popular issue these days by including an update on big data–the tool that will probably revolutionize the way we understand the clinical information available, and, ultimately, condition the way we make decisions.We hope that the readers of Medicina Intensiva find this series of methodology interesting, and a source of inspiration to keep moving forward in the fascinating world of clinical research in the critically ill patient.Conflict of interestThe authors declare no conflict of interests associated with this article whatsoever." "textoCompletoSecciones" => array:1 [ "secciones" => array:6 [ 0 => array:3 [ "identificador" => "xres1010496" "titulo" => "Abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0005" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec969900" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1010497" "titulo" => "Resumen" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0010" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec969901" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Conflict of interest" ] 5 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2017-12-13" "fechaAceptado" => "2017-12-15" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec969900" "palabras" => array:6 [ 0 => "Critically ill patient" 1 => "Methodology" 2 => "Statistical analysis" 3 => "Statistical interpretation" 4 => "Peer review" 5 => "Methodological errors" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec969901" "palabras" => array:6 [ 0 => "Paciente crítico" 1 => "Metodología" 2 => "Análisis estadísticos" 3 => "Interpretación estadística" 4 => "Revisión por pares" 5 => "Errores metodológicos" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "Research in the critically ill is complex by the heterogeneity of patients, the difficulties to achieve representative sample sizes and the number of variables simultaneously involved. However, the quantity and quality of records is high as well as the relevance of the variables used, such as survival. The methodological tools have evolved to offering new perspectives and analysis models that allow extracting relevant information from the data that accompanies the critically ill patient. The need for training in methodology and interpretation of results is an important challenge for the intensivists who wish to be updated on the research developments and clinical advances in Intensive Medicine." ] "es" => array:2 [ "titulo" => "Resumen" "resumen" => "La investigación en el enfermo crítico es compleja por la heterogeneidad de los pacientes, por las dificultades para alcanzar tamaños de muestra representativos y por la cantidad de variables que intervienen de manera simultánea. Sin embargo, se beneficia de la cantidad y calidad de registros, así como de la relevancia de las variables utilizadas, como la supervivencia. Las herramientas metodológicas han evolucionado ofreciendo nuevas perspectivas y modelos de análisis que permiten extraer información relevante de la riqueza de datos que acompaña al enfermo crítico. La necesidad de formación en metodología y en interpretación de resultados constituye un importante reto para los intensivistas que deseen estar al día en las líneas de investigación y en los nuevos avances de la Medicina Intensiva." ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: García Garmendia JL. Actualización en metodología en Medicina Intensiva. Med Intensiva. 2018;42:180–183." ] ] "multimedia" => array:2 [ 0 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "SD: standard deviation. ROC: receiver operating characteristics." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Medicina Intensiva \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Intensive Care Medicine \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Critical Care Medicine \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">p \t\t\t\t\t\t\n \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n=65 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n=67 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n=80 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Period analyzed \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2016–2017 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">January–May 2016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Issues studied (n) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Originals per issue, average (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.6 (0.8)<a class="elsevierStyleCrossRefs" href="#tblfn0005">a,b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5.6 (1.6)<a class="elsevierStyleCrossRefs" href="#tblfn0010">b,c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">16 (2.8)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p<0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Impact factor, 2016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1231 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12,015 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7050 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Non-applicable \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Originals with Spanish authors, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">56 (86.2)<a class="elsevierStyleCrossRefs" href="#tblfn0005">a,b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 (7.5)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">6 (7.5)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p<0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top"></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Type of study, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">46 (70.8)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">34 (50.7)<a class="elsevierStyleCrossRefs" href="#tblfn0010">b,c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p<0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Observational \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">57 (71.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Quasi-experimental \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (12.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4 (6.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2 (2.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Clinical trial \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3 (4.6)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">21 (31.3)<a class="elsevierStyleCrossRefs" href="#tblfn0010">b,c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13 (16.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Diagnostic test \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (12.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (11.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Simulation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0 (0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3 (3.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top"></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Multicenter, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">22 (33.8)<a class="elsevierStyleCrossRefs" href="#tblfn0005">a,b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">38 (56.7)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">46 (57.5)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.007 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Analysis of mortality, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">27 (41.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">41 (61.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">47 (58.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.045 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Estimate of the sample size, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 (7.7)<a class="elsevierStyleCrossRefs" href="#tblfn0005">a,b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">28 (41.8)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">20 (25.0)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p<0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="5" align="left" valign="top">Statistical analyses</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Comparison of percentages, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">52 (80) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">56 (83.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">57 (71.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.176 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"> Comparison of quantitative variables, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">55 (84.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">55 (82.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">60 (75) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.315 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Comparison of repeated measurements, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7 (10.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8 (11.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">9 (11.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.977 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Kaplan–Meier, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">11 (16.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15 (22.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13 (16.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.591 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Simple regression, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1 (1.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4 (6.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7 (8.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.173 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Multiple linear regression, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1 (1.5)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7 (10.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">13 (16.3)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.013 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Logistics regression, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">26 (40.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">27 (40.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">38 (47.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.577 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Cox regression, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7 (10.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15 (22.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12 (15.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.182 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Propensity score, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1 (1.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4 (6.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7 (8.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.173 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">ROC curves, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12 (18.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">9 (13.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14 (17.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.706 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Correlation analysis, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 (7.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 (7.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">11 (13.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.345 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Concordance analysis, n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 (7.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3 (4.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">5 (6.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.743 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Other tests,<a class="elsevierStyleCrossRef" href="#tblfn0020">d</a> n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1 (1.5)<a class="elsevierStyleCrossRefs" href="#tblfn0005">a,b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">23 (34.3)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">21 (26.3)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p<0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Number of tests per original manuscript, media (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">2.9 (1.2)<a class="elsevierStyleCrossRefs" href="#tblfn0005">a,b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.5 (1.4)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.5 (1.4)<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">p=0.007 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1711491.png" ] ] ] "notaPie" => array:4 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "p<0.05 (Bonferroni correction) versus Intensive Care Medicine." ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "p<0.05 (Bonferroni correction) versus Critical Care Medicine." ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "c" "nota" => "p<0.05 (Bonferroni correction) versus Medicina Intensiva." ] 3 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "d" "nota" => "Methods used: Bayesian analysis (1), qualitative analysis (1), clusters analysis (2), analysis of the main components (2), multiple concordance analysis (1), mediation analysis (1), factorial analysis (1), fractal analysis (1), decision tree (1), generalized estimating equations (2), phi statistics (1), gradient boosted machine (1), G-Study (1), Inverse probability treatment weighting (IPWT) (2), jointpoint regression (1), K-nearest neighbors (1), Locally weighted scatterplot smoothing (LOWESS) (2), Modified early warning systems (MEWS) (1), negative binomial model (1), generalized linear model (12), generalized mixed linear model (2), structural marginal model (4), simulation models (2), Montecarlo (2), network maps (1), neural network (1), Cochran-Armitage trend test (2), random forest (1), binomial regression (1), Poisson regression (5), competitive risks (2), temporal series (4), support vector machine (1) and Cuzick's test (1)." ] ] ] "descripcion" => array:1 [ "en" => "Comparative analysis of the statistical methodology used in the original manuscripts published in three (3) journals within the intensive care setting." ] ] 1 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "Number of originals analyzed=62." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Methodological problems \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Frequency \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">Goal</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Poorly expressed goal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21.0% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">Variables</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Poorly defined variables \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48.4% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Lack of variables of interest \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.7% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">Design</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Poorly defined design \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">22.6% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Inadequate design \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.5% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Inadequate definition of the study type \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">6.5% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">Target population</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Poorly defined population \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.7% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Old study \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.2% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Period of study missing \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.6% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">Sample</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Selection bias \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21.0% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Insufficient sample size \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">17.7% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Observer bias \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.1% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Size of the sample not estimated \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.1% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Sample error \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.6% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Lack of flow chart \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.6% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">Results</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Descriptive with errors \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">41.9% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Lack of statistical analysis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">25.8% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Inadequate statistical test \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">21.0% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Poorly used interquartile range<a class="elsevierStyleCrossRef" href="#tblfn0025">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">19.4% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Contradictory data \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.3% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Lack of comparisons of interest \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.3% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Lack of standardized mortality ratio \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.1% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Lack of confidence intervals \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4.8% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Inadequate subgroup analysis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.2% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Unnecessary comparisons \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.2% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">Interpretation</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Interpretation of non-significant results<a class="elsevierStyleCrossRef" href="#tblfn0030">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.1% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Errors interpreting the analysis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.7% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top"></td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">Conclusions</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Conclusions not matching the results \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">27.4% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Lack of conclusions \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3.2% \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1711492.png" ] ] ] "notaPie" => array:2 [ 0 => array:3 [ "identificador" => "tblfn0025" "etiqueta" => "a" "nota" => "The interquartile range (IQR) is the difference between percentiles 75th and 25th." ] 1 => array:3 [ "identificador" => "tblfn0030" "etiqueta" => "b" "nota" => "Erroneous interpretation of non-significant differences: “Differences are found, but they happen to be non-significant”." ] ] ] "descripcion" => array:1 [ "en" => "Main methodological problems found in the first review of original manuscripts submitted to Medicina Intensiva from 2016 through 2017." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:7 [ 0 => array:3 [ "identificador" => "bib0040" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Conceptos de bioestadística en el paciente crítico" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "J.L. García Garmendia" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "LibroEditado" => array:3 [ "titulo" => "Manual de Medicina Intensiva" "edicion" => "5.ª ed." "serieFecha" => "2016" ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0045" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Exploring obstacles to critical care trials in the UK: a qualitative investigation" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "N. Pattison" 1 => "N. Arulkumaran" 2 => "S. Humphreys" 3 => "T. Walsh" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1177/1751143716663749" "Revista" => array:6 [ "tituloSerie" => "J Intensive Care Soc" "fecha" => "2017" "volumen" => "18" "paginaInicial" => "36" "paginaFinal" => "46" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28979535" "web" => "Medline" ] ] ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0050" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The use of statistical methods in 2 medical journals with high impact factor" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "L.C. Silva Ayçaguer" 1 => "C. Pérez Nieves" 2 => "I. 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Series in Intensive Medicine: Methodological update in Medicina Intensiva

Methodological update in Medicina Intensiva

Actualización en metodología en Medicina Intensiva

J.L. García Garmendia

Servicio de Cuidados Críticos y Urgencias, Hospital San Juan de Dios del Aljarafea, Bormujos, Sevilla, Spain

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    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">The series of methodology we start in Medicina Intensiva tries to bring the clinician closer to different methodological issues that we have considered relevant in the research setting of critically ill patients&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Critical disease has some special conditions when it comes to generating scientific knowledge&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">1</span></a> On the one hand&#44; the amount of monitoring and the availability of tests in these patients provides a great deal of analyzable information&#46; Also&#44; the high impact of physiopathological aspects allows us to go deep into applied basic research&#46; Due to the patients&#8217; fast progression and rates of survival&#44; variable mortality is commonly used&#44; generating high interest and clinical relevance to clinical researches&#46; On the other hand&#44; the velocity of changes&#44; complexity&#44; and interrelation of variables and simultaneous treatments&#44; working schedules&#44; and difficulties trying to find homogeneous enough patients in one single center elevates the requirements of study designs&#44; and resources needed&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">2</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">All these challenges lead to two &#40;2&#41; fundamental issues&#46; On the one hand&#44; the need to find tools for statistical analysis adjusted to data&#44; and possible designs with critically ill patients&#44; which is why new and diverse approaches are needed&#46; On the other hand&#44; it is important to improve methodological training for research purposes and also for the interpretation of results&#46; In this series we do not wish to write a statistical treaty&#44; but draw an interesting picture including general aspects of result interpretation as advanced topics among which we will find new strategies of analysis&#44; or big data&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">In one comparative analysis of the statistical techniques used in 3 journals dedicated to the critically ill patient &#40;Medicina Intensiva&#44; <span class="elsevierStyleItalic">Intensive Care Medicine</span>&#44; and <span class="elsevierStyleItalic">Critical Care Medicine</span>&#41;&#44; we analyzed the methodological procedures used in one recent sample of the original manuscripts published during 2016 and 2017 &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46; Other than the differences seen in the number of original manuscripts published per issue&#44; and in the presence of Spanish authors in the three &#40;3&#41; journals&#44; we found significant differences in the type of studies conducted and in the complexity of the methodology used&#46; Although the three journals mostly use observational studies&#44; compared to the other two journals&#44; <span class="elsevierStyleItalic">Intensive Care Medicine</span> includes a higher percentage of clinical trials&#44; being such trials rare in Medicina Intensiva &#40;4&#46;6&#37;&#41;&#46; In Medicina Intensiva&#44; the percentage of multicenter studies is lower than in the other two journals&#44; and there are not too many estimates of the size of the sample either&#44; probably due to the fact that fewer clinical trials are published&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0025" class="elsevierStylePara elsevierViewall">On the statistical analyses&#44; the number of tests used is much lower in Medicina Intensiva than it is in the other two journals&#44; although in the most common methods we did not find any significant differences&#44; except in the multiple linear regression analysis&#46; Where we did find a clear difference is in the use of more advanced statistical methods&#44; almost inexistent in the original manuscripts from Medicina Intensiva&#44; but present in one third of the originals from <span class="elsevierStyleItalic">Intensive Care Medicine</span> and <span class="elsevierStyleItalic">Critical Care Medicine</span>&#46; The greater use of advanced tests has become a common practice and is a clear improvement compared to similar assessments made in high-impact factor journals some 20 years ago&#46;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">3</span></a></p><p id="par0030" class="elsevierStylePara elsevierViewall">In sum&#44; we found a significant difference in the level of design complexity and statistical analysis in the manuscripts submitted to Medicina Intensiva compared to the other two &#40;2&#41; journals&#46;</p><p id="par0035" class="elsevierStylePara elsevierViewall">On the other hand&#44; in one review conducted on a sample of 62 original manuscripts submitted for publication to Medicina Intensiva from 2016 through 2017&#44; we found a series of methodological problems that are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> being the most common ones&#44; per frequency of appearance&#44; the inadequate definition of variables&#44; the mistakes made in the description of results&#44; the fact that conclusions did not match the results&#44; the lack of statistical analysis &#40;multivariate models&#44; above all&#41;&#44; the existence of not very clear designs&#44; the inadequate presentation of the goal&#44; selection biases&#44; and the use of inadequate statistical tests for analysis&#46; These problems have also been found in other publications<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">4</span></a> and&#44; in this sense&#44; the use of reviewers trained in statistics during the review process has proven a useful tool to improve the quality of the articles published<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">5</span></a> and implies some sort of ethical commitment&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">6</span></a></p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0040" class="elsevierStylePara elsevierViewall">It is&#44; therefore&#44; evident that there is margin for improvement in methodological design&#44; and in the analysis and interpretation of results in all research studies submitted to our journal&#46; The Editorial Committee of Medicina Intensiva<span class="elsevierStyleSmallCaps">&#44;</span> directed by Dr&#46; Garnacho Montero&#44; understands that this journal needs to draw and promote studies of high methodological quality that&#44; in time&#44; will improve the impact factor and promote the submission of new quality studies&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">7</span></a> Within this virtuous circle setting&#44; this series is born in an attempt to improve the quality of our investigations&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">This series begins with a general reflection on the particularities that affect the studies of critically ill patients&#44; and we will be discussing the difficulties&#44; different approaches&#44; and new strategies defined to make scientific knowledge move forward&#46; Also&#44; we will be analyzing the interpretation of statistical results in its most basic and advanced aspects&#44; trying to facilitate an adequate understanding of the terminology used in the most common scientific literature&#46; This paper is a review of common methodological errors made in clinical research&#44; some of which can be more or less innocent&#44; but all will undoubtedly help the reader keep a critical view of the information presented here&#46; We will also be reviewing a fundamental aspect known as the bioethics of clinical research&#8211;very important for the editorial team&#44;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">7</span></a> a historical summary will be presented here&#44; followed by an analysis of the different ethical requirements that are mandatory in the clinical research of critically ill patients&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">When we open up the arsenal of statistical tools available&#44; three &#40;3&#41; reviews can be conducted&#58; one review on the techniques used to determine the causality of observational studies with an emphasis on propensity score analysis&#59; a second review on new techniques of alternative analysis such as hybrid studies&#44; nested case&#8211;control studies&#44; recursive partitions&#44; or competitive events&#44; one article discussing the development of systematic reviews&#44; and meta-analyses as sources of knowledge&#46; Lastly&#44; we have addressed a popular issue these days by including an update on big data&#8211;the tool that will probably revolutionize the way we understand the clinical information available&#44; and&#44; ultimately&#44; condition the way we make decisions&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">We hope that the readers of Medicina Intensiva find this series of methodology interesting&#44; and a source of inspiration to keep moving forward in the fascinating world of clinical research in the critically ill patient&#46;</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conflict of interest</span><p id="par0060" class="elsevierStylePara elsevierViewall">The authors declare no conflict of interests associated with this article whatsoever&#46;</p></span></span>"
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          "identificador" => "xres1010496"
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    "fechaRecibido" => "2017-12-13"
    "fechaAceptado" => "2017-12-15"
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          "clase" => "keyword"
          "titulo" => "Keywords"
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            0 => "Critically ill patient"
            1 => "Methodology"
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            0 => "Paciente cr&#237;tico"
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            2 => "An&#225;lisis estad&#237;sticos"
            3 => "Interpretaci&#243;n estad&#237;stica"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Research in the critically ill is complex by the heterogeneity of patients&#44; the difficulties to achieve representative sample sizes and the number of variables simultaneously involved&#46; However&#44; the quantity and quality of records is high as well as the relevance of the variables used&#44; such as survival&#46; The methodological tools have evolved to offering new perspectives and analysis models that allow extracting relevant information from the data that accompanies the critically ill patient&#46; The need for training in methodology and interpretation of results is an important challenge for the intensivists who wish to be updated on the research developments and clinical advances in Intensive Medicine&#46;</p></span>"
      ]
      "es" => array:2 [
        "titulo" => "Resumen"
        "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">La investigaci&#243;n en el enfermo cr&#237;tico es compleja por la heterogeneidad de los pacientes&#44; por las dificultades para alcanzar tama&#241;os de muestra representativos y por la cantidad de variables que intervienen de manera simult&#225;nea&#46; Sin embargo&#44; se beneficia de la cantidad y calidad de registros&#44; as&#237; como de la relevancia de las variables utilizadas&#44; como la supervivencia&#46; Las herramientas metodol&#243;gicas han evolucionado ofreciendo nuevas perspectivas y modelos de an&#225;lisis que permiten extraer informaci&#243;n relevante de la riqueza de datos que acompa&#241;a al enfermo cr&#237;tico&#46; La necesidad de formaci&#243;n en metodolog&#237;a y en interpretaci&#243;n de resultados constituye un importante reto para los intensivistas que deseen estar al d&#237;a en las l&#237;neas de investigaci&#243;n y en los nuevos avances de la Medicina Intensiva&#46;</p></span>"
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        "etiqueta" => "&#9734;"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0035">Please cite this article as&#58; Garc&#237;a Garmendia JL&#46; Actualizaci&#243;n en metodolog&#237;a en Medicina Intensiva&#46; Med Intensiva&#46; 2018&#59;42&#58;180&#8211;183&#46;</p>"
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          "leyenda" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">SD&#58; standard deviation&#46; ROC&#58; receiver operating characteristics&#46;</p>"
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col">Medicina Intensiva&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col">Intensive Care Medicine&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col">Critical Care Medicine&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col"><span class="elsevierStyleItalic">p</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>65&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>67&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>80&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Period analyzed</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2016&#8211;2017&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2016&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">January&#8211;May 2016&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Issues studied &#40;n&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">18&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Originals per issue&#44; average &#40;SD&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;6 &#40;0&#46;8&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0005"><span class="elsevierStyleSup">a&#44;b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5&#46;6 &#40;1&#46;6&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0010"><span class="elsevierStyleSup">b&#44;c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">16 &#40;2&#46;8&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Impact factor&#44; 2016</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1231&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">12&#44;015&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">7050&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Non-applicable&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Originals with Spanish authors&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">56 &#40;86&#46;2&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0005"><span class="elsevierStyleSup">a&#44;b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5 &#40;7&#46;5&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">6 &#40;7&#46;5&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Type of study&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">46 &#40;70&#46;8&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">34 &#40;50&#46;7&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0010"><span class="elsevierStyleSup">b&#44;c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Observational&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">57 &#40;71&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Quasi-experimental&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8 &#40;12&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">4 &#40;6&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2 &#40;2&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Clinical trial&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3 &#40;4&#46;6&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">21 &#40;31&#46;3&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0010"><span class="elsevierStyleSup">b&#44;c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13 &#40;16&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Diagnostic test&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8 &#40;12&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8 &#40;11&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5 &#40;6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Simulation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0 &#40;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">0 &#40;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3 &#40;3&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Multicenter&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">22 &#40;33&#46;8&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0005"><span class="elsevierStyleSup">a&#44;b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">38 &#40;56&#46;7&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">46 &#40;57&#46;5&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;007&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Analysis of mortality&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">27 &#40;41&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">41 &#40;61&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">47 &#40;58&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;045&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleItalic">Estimate of the sample size&#44; n &#40;&#37;&#41;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5 &#40;7&#46;7&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0005"><span class="elsevierStyleSup">a&#44;b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">28 &#40;41&#46;8&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">20 &#40;25&#46;0&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="5" align="left" valign="top"><span class="elsevierStyleItalic">Statistical analyses</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Comparison of percentages&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">52 &#40;80&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">56 &#40;83&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">57 &#40;71&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;176&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span> Comparison of quantitative variables&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">55 &#40;84&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">55 &#40;82&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">60 &#40;75&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;315&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Comparison of repeated measurements&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">7 &#40;10&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">8 &#40;11&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">9 &#40;11&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;977&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Kaplan&#8211;Meier&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">11 &#40;16&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">15 &#40;22&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13 &#40;16&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;591&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Simple regression&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1 &#40;1&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">4 &#40;6&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">7 &#40;8&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;173&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Multiple linear regression&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1 &#40;1&#46;5&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">7 &#40;10&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">13 &#40;16&#46;3&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;013&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Logistics regression&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">26 &#40;40&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">27 &#40;40&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">38 &#40;47&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;577&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Cox regression&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">7 &#40;10&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">15 &#40;22&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">12 &#40;15&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;182&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Propensity score&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1 &#40;1&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">4 &#40;6&#46;0&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">7 &#40;8&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;173&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>ROC curves&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">12 &#40;18&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">9 &#40;13&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">14 &#40;17&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;706&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Correlation analysis&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5 &#40;7&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5 &#40;7&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">11 &#40;13&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;345&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Concordance analysis&#44; n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5 &#40;7&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3 &#40;4&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">5 &#40;6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;743&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Other tests&#44;<a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">d</span></a> n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">1 &#40;1&#46;5&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0005"><span class="elsevierStyleSup">a&#44;b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">23 &#40;34&#46;3&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">21 &#40;26&#46;3&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Number of tests per original manuscript&#44; media &#40;SD&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">2&#46;9 &#40;1&#46;2&#41;<a class="elsevierStyleCrossRefs" href="#tblfn0005"><span class="elsevierStyleSup">a&#44;b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;5 &#40;1&#46;4&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;5 &#40;1&#46;4&#41;<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>0&#46;007&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
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              "nota" => "<p class="elsevierStyleNotepara" id="npar0015"><span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05 &#40;Bonferroni correction&#41; versus Medicina Intensiva<span class="elsevierStyleSmallCaps">&#46;</span></p>"
            ]
            3 => array:3 [
              "identificador" => "tblfn0020"
              "etiqueta" => "d"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0020">Methods used&#58; Bayesian analysis &#40;1&#41;&#44; qualitative analysis &#40;1&#41;&#44; clusters analysis &#40;2&#41;&#44; analysis of the main components &#40;2&#41;&#44; multiple concordance analysis &#40;1&#41;&#44; mediation analysis &#40;1&#41;&#44; factorial analysis &#40;1&#41;&#44; fractal analysis &#40;1&#41;&#44; decision tree &#40;1&#41;&#44; generalized estimating equations &#40;2&#41;&#44; phi statistics &#40;1&#41;&#44; gradient boosted machine &#40;1&#41;&#44; G-Study &#40;1&#41;&#44; Inverse probability treatment weighting &#40;IPWT&#41; &#40;2&#41;&#44; jointpoint regression &#40;1&#41;&#44; K-nearest neighbors &#40;1&#41;&#44; Locally weighted scatterplot smoothing &#40;LOWESS&#41; &#40;2&#41;&#44; Modified early warning systems &#40;MEWS&#41; &#40;1&#41;&#44; negative binomial model &#40;1&#41;&#44; generalized linear model &#40;12&#41;&#44; generalized mixed linear model &#40;2&#41;&#44; structural marginal model &#40;4&#41;&#44; simulation models &#40;2&#41;&#44; Montecarlo &#40;2&#41;&#44; network maps &#40;1&#41;&#44; neural network &#40;1&#41;&#44; Cochran-Armitage trend test &#40;2&#41;&#44; random forest &#40;1&#41;&#44; binomial regression &#40;1&#41;&#44; Poisson regression &#40;5&#41;&#44; competitive risks &#40;2&#41;&#44; temporal series &#40;4&#41;&#44; support vector machine &#40;1&#41; and Cuzick&#39;s test &#40;1&#41;&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Comparative analysis of the statistical methodology used in the original manuscripts published in three &#40;3&#41; journals within the intensive care setting&#46;</p>"
        ]
      ]
      1 => array:8 [
        "identificador" => "tbl0010"
        "etiqueta" => "Table 2"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at2"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:3 [
          "leyenda" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Number of originals analyzed<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>62&#46;</p>"
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Methodological problems&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Frequency&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Goal</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Poorly expressed goal&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">21&#46;0&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Variables</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Poorly defined variables&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">48&#46;4&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Lack of variables of interest&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&#46;7&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Design</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Poorly defined design&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">22&#46;6&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Inadequate design&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">6&#46;5&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Inadequate definition of the study type&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">6&#46;5&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Target population</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Poorly defined population&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">17&#46;7&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Old study&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;2&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Period of study missing&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;6&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Sample</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Selection bias&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">21&#46;0&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Insufficient sample size&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">17&#46;7&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Observer bias&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;1&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Size of the sample not estimated&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;1&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Sample error&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;6&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Lack of flow chart&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&#46;6&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Result</span>s</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Descriptive with errors&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">41&#46;9&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Lack of statistical analysis&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">25&#46;8&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Inadequate statistical test&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">21&#46;0&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Poorly used interquartile range<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">19&#46;4&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Contradictory data&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">11&#46;3&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Lack of comparisons of interest&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">11&#46;3&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Lack of standardized mortality ratio&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&#46;1&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Lack of confidence intervals&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">4&#46;8&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Inadequate subgroup analysis&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;2&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Unnecessary comparisons&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;2&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Interpretation</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Interpretation of non-significant results<a class="elsevierStyleCrossRef" href="#tblfn0030"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">16&#46;1&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Errors interpreting the analysis&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">9&#46;7&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="table-entry  " colspan="2" align="left" valign="top"><span class="elsevierStyleItalic">Conclusions</span></td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Conclusions not matching the results&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">27&#46;4&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span>Lack of conclusions&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">3&#46;2&#37;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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                0 => "xTab1711492.png"
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          "notaPie" => array:2 [
            0 => array:3 [
              "identificador" => "tblfn0025"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0025">The interquartile range &#40;IQR&#41; is the difference between percentiles 75th and 25th&#46;</p>"
            ]
            1 => array:3 [
              "identificador" => "tblfn0030"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0030">Erroneous interpretation of non-significant differences&#58; &#8220;Differences are found&#44; but they happen to be non-significant&#8221;&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Main methodological problems found in the first review of original manuscripts submitted to Medicina Intensiva from 2016 through 2017&#46;</p>"
        ]
      ]
    ]
    "bibliografia" => array:2 [
      "titulo" => "References"
      "seccion" => array:1 [
        0 => array:2 [
          "identificador" => "bibs0015"
          "bibliografiaReferencia" => array:7 [
            0 => array:3 [
              "identificador" => "bib0040"
              "etiqueta" => "1"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Conceptos de bioestad&#237;stica en el paciente cr&#237;tico"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:1 [
                            0 => "J&#46;L&#46; Garc&#237;a Garmendia"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:1 [
                      "LibroEditado" => array:3 [
                        "titulo" => "Manual de Medicina Intensiva"
                        "edicion" => "5&#46;&#170; ed&#46;"
                        "serieFecha" => "2016"
                      ]
                    ]
                  ]
                ]
              ]
            ]
            1 => array:3 [
              "identificador" => "bib0045"
              "etiqueta" => "2"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Exploring obstacles to critical care trials in the UK&#58; a qualitative investigation"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "N&#46; Pattison"
                            1 => "N&#46; Arulkumaran"
                            2 => "S&#46; Humphreys"
                            3 => "T&#46; Walsh"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1177/1751143716663749"
                      "Revista" => array:6 [
                        "tituloSerie" => "J Intensive Care Soc"
                        "fecha" => "2017"
                        "volumen" => "18"
                        "paginaInicial" => "36"
                        "paginaFinal" => "46"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28979535"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            2 => array:3 [
              "identificador" => "bib0050"
              "etiqueta" => "3"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "The use of statistical methods in 2 medical journals with high impact factor"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:3 [
                            0 => "L&#46;C&#46; Silva Ay&#231;aguer"
                            1 => "C&#46; P&#233;rez Nieves"
                            2 => "I&#46; Cuellar Wong"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:1 [
                      "Revista" => array:6 [
                        "tituloSerie" => "Gac Sanit"
                        "fecha" => "1995"
                        "volumen" => "9"
                        "paginaInicial" => "189"
                        "paginaFinal" => "195"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/7558632"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            3 => array:3 [
              "identificador" => "bib0055"
              "etiqueta" => "4"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Common statistical and research design problems in manuscripts submitted to high-impact medical journals"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "S&#46; Fernandes-Taylor"
                            1 => "J&#46;K&#46; Hyun"
                            2 => "R&#46;N&#46; Reeder"
                            3 => "A&#46;H&#46; Harris"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1186/1756-0500-4-304"
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Article information

ISSN: 21735727
Original language: English

DOI:10.1016/j.medine.2017.12.007

The statistics are updated each day

Year/Month	Html	Pdf	Total

2024 November	4	8	12
2024 October	39	36	75
2024 September	32	32	64
2024 August	37	34	71
2024 July	51	37	88
2024 June	39	41	80
2024 May	43	34	77
2024 April	49	41	90
2024 March	48	29	77
2024 February	37	43	80
2024 January	31	31	62
2023 December	23	37	60
2023 November	25	37	62
2023 October	31	23	54
2023 September	23	33	56
2023 August	18	16	34
2023 July	27	30	57
2023 June	25	17	42
2023 May	39	38	77
2023 April	26	22	48
2023 March	73	34	107
2023 February	44	45	89
2023 January	20	18	38
2022 December	63	38	101
2022 November	56	50	106
2022 October	64	40	104
2022 September	27	28	55
2022 August	32	49	81
2022 July	35	60	95
2022 June	24	27	51
2022 May	31	54	85
2022 April	41	45	86
2022 March	43	66	109
2022 February	28	53	81
2022 January	37	44	81
2021 December	39	59	98
2021 November	32	34	66
2021 October	52	84	136
2021 September	24	50	74
2021 August	22	37	59
2021 July	24	31	55
2021 June	31	38	69
2021 May	32	63	95
2021 April	83	99	182
2021 March	58	37	95
2021 February	47	28	75
2021 January	29	33	62
2020 December	35	25	60
2020 November	25	17	42
2020 October	25	29	54
2020 September	41	21	62
2020 August	29	21	50
2020 July	29	27	56
2020 June	26	20	46
2020 May	20	11	31
2020 April	31	17	48
2020 March	18	14	32
2020 February	47	24	71
2020 January	32	26	58
2019 December	32	23	55
2019 November	28	16	44
2019 October	28	16	44
2019 September	24	18	42
2019 August	30	20	50
2019 July	23	22	45
2019 June	21	12	33
2019 May	33	28	61
2019 April	16	19	35
2019 March	13	18	31
2019 February	20	26	46
2019 January	24	32	56
2018 December	43	51	94
2018 November	39	58	97
2018 October	79	20	99
2018 September	37	17	54
2018 August	30	13	43
2018 July	8	4	12
2018 June	0	1	1

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