Información de la revista
Vol. 46. Núm. 4.
Páginas 179-191 (abril 2022)
Compartir
Compartir
Descargar PDF
Más opciones de artículo
Visitas
10563
Vol. 46. Núm. 4.
Páginas 179-191 (abril 2022)
Original
Acceso a texto completo
Predictive factors of six-week mortality in critically ill patients with SARS-CoV-2: A multicenter prospective study
Factores predictivos de la mortalidad a las seis semanas en pacientes críticos con SARS-CoV-2: estudio multicéntrico prospectivo
Visitas
10563
Á. Estellaa,
Autor para correspondencia
litoestella@hotmail.com

Corresponding author.
, J.L. Garcia Garmendiab, C. de la Fuentec, J.F. Machado Casasd, M.E. Yustee, R. Amaya Villarf, M.A. Estechag, L. Yaguez Mateosh, M.L. Cantón Bulnesi, A. Lozaj, J. Morak, L. Fernández Ruizl, B. Díez del Corral Fernándeza, M. Rojas Amezcuam, M.I. Rodriguez Higuerasn, I. Díaz Torreso, M. Recuerda Núñezo, M. Zaheri Beryanakip, F. Rivera Espinarq, D.F. Matallana Zapatar..., S.G. Moreno Canoa, B. Gimenez Beltrána, N. Muñozs, A. Sainz de Baranda Piñerot, P. Bustelo Buenot, E. Moreno Barrigao, J.J. Rios Torou, M. Pérez Ruiza, C. Gómez Gonzálezf, A. Breval Floress, A. de San José Bermejo Gómezv, M.A. Ruiz Cabello Jimenezw, M. Guerrero Marính, A. Ortega Ordialesk, J. Tejero-Arangurene, C. Rodriguez Mejíasd, J. Gomez de Oñax, C. de la Hozx, D. Ocaña Fernándezy, S. Ibañez Cuadroso, J. Garnacho Monteroz, On behalf of the Work Group of Infectious Disease (GTEI) de la Sociedad Andaluza de Medicina Intensiva y Unidades coronarias SAMIUC Ver más
a Intensive Care Unit, Hospital Universitario de Jerez, Jerez, Spain
b Intensive Care Unit, Hospital San Juan de Dios del Aljarafe, Bormujos, Sevilla, Spain
c Intensive Care Unit, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain
d Intensive Care Unit, Hospital Universitario Virgen de las Nieves de Granada, Granada, Spain
e Intensive Care Unit, Hospital Universitario Clínico San Cecilio de Granada, Granada, Spain
f Intensive Care Unit, Hospital Universitario Virgen del Rocio de Sevilla, Sevilla, Spain
g Intensive Care Unit, Hospital Universitario Virgen de la Victoria de Málaga, Málaga, Spain
h Intensive Care Unit, Hospital Universitario de Jaén, Jaén, Spain
i Intensive Care Unit, Hospital Universitario Virgen Macarena de Sevilla, Sevilla, Spain
j Intensive Care Unit, Hospital Universitario Virgen de Valme, Sevilla, Spain
k Intensive Care Unit, Hospital Universitario Regional de Málaga, Málaga, Spain
l Intensive Care Unit, Hospital San Juan de la Cruz Úbeda, Úbeda, Jaén, Spain
m Intensive Care Unit, Hospital Infanta Margarita de Cabra, Cabra, Spain
n Intensive Care Unit, Hospital Universitario Torrecárdenas Almería, Almería, Spain
o Intensive Care Unit, Hospital Universitario de Puerto Real, Puerto Real, Spain
p Intensive Care Unit, Hospital de Antequera, Antequera, Spain
q Intensive Care Unit, Hospital de Montilla, Montilla, Córdoba, Spain
r Intensive Care Unit, Hospital Infanta Elena de Huelva, Hospital Quirón Huelva, Huelva, Spain
s Intensive Care Unit, Hospital de la Cruz Roja de Córdoba, Córdoba, Spain
t Intensive Care Unit, Hospital HLA Puerta del Sur de Jerez, Jerez, Spain
u Intensive Care Unit, Hospital de Ronda, Ronda, Spain
v Intensive Care Unit, Hospital San Juan de Dios de Córdoba, Córdoba, Spain
w Intensive Care Unit, Hospital de Pozoblanco, Pozoblanco, Córdoba, Spain
x Intensive Care Unit, Hospital de Poniente, Almería, Spain
y Intensive Care Unit, Hospital La Inmaculada Huercal-Overa de Almería, Almería, Spain
z Intensive Care Unit, Hospital Universitario Virgen de la Macarena Sevilla, Sevilla, Spain
Ver más
Este artículo ha recibido
Información del artículo
Resumen
Texto completo
Bibliografía
Descargar PDF
Estadísticas
Figuras (2)
Tablas (4)
Table 1. Baseline characteristics and univariate analysis with 6 weeks mortality.
Table 2. Laboratory findings of all critically ill patients on day 1 and 3 of ICU admission.
Table 3. Relationship between Delta SOFA score 0–72h and mortality.
Table 4. Multivariate Cox regression analysis of variables associated with mortality at 6 weeks with Propensity Score for lopinavir/ritonavir.
Mostrar másMostrar menos
Material adicional (1)
Abstract
Objective

The objective of the study is to identify the risk factors associated with mortality at six weeks, especially by analyzing the role of antivirals and munomodulators.

Design

Prospective descriptive multicenter cohort study.

Setting

26 Intensive care units (ICU) from Andalusian region in Spain.

Patients or participants

Consecutive critically ill patients with confirmed SARS-CoV-2 infection were included from March 8 to May 30.

Interventions

None.

Variables

Variables analyzed were demographic, severity scores and clinical condition. Support therapy, drug and mortality were analyzed. An univariate followed by multivariate Cox regression with propensity score analysis was applied.

Results

495 patients were enrolled, but 73 of them were excluded for incomplete data. Thus, 422 patients were included in the final analysis. Median age was 63 years and 305 (72.3%) were men. ICU mortality: 144/422 34%; 14 days mortality: 81/422 (19.2%); 28 days mortality: 121/422 (28.7%); 6-week mortality 152/422 36.5%. By multivariable Cox proportional analysis, factors independently associated with 42-day mortality were age, APACHE II score, SOFA score at ICU admission >6, Lactate dehydrogenase at ICU admission >470U/L, Use of vasopressors, extrarenal depuration, %lymphocytes 72h post-ICU admission <6.5%, and thrombocytopenia whereas the use of lopinavir/ritonavir was a protective factor.

Conclusion

Age, APACHE II, SOFA>value of 6 points, along with vasopressor requirements or renal replacement therapy have been identified as predictor factors of mortality at six weeks.

Administration of corticosteroids showed no benefits in mortality, as did treatment with tocilizumab.

Lopinavir/ritonavir administration is identified as a protective factor.

Keywords:
SARS-CoV-2
ICU
Corticosteroids
Tocilizumab
Lopinavir/ritonavir
Resumen
Objetivo

Identificar los factores de riesgo asociados con la mortalidad a las seis semanas.

Diseño

Estudio prospectivo multicéntrico.

Ámbito

Se incluyeron a 26 pacientes de la Unidad de Cuidados Intensivos (UCI) de Andalucía.

Pacientes o participantes

Pacientes ingresados en UCI por neumonía grave por SARS-CoV-2 del 8 de marzo al 30 de mayo de 2020.

Intervenciones

Ninguna.

Variables de interés principales

Características demográficas, clínicas y escalas de gravedad. Se analizaron tratamientos de soporte, fármacos y la mortalidad.

Resultados

Se incluyeron 495 pacientes, 73 fueron excluidos por incompletos y 422 pacientes se incorporaron en el análisis final. La mediana de edad fue de 63 años, 305 (72,3%) eran hombres. La mortalidad en la UCI fue: 144/422 34%; mortalidad a los 14 días: 81/422 (19,2%); mortalidad a los 28 días: 121/422 (28,7%); mortalidad a las seis semanas 152/422 36,5%.

Los factores asociados con la mortalidad a los 42 días fueron la edad, APACHE II, SOFA > 6 y LDH al ingreso > 470 U/L, uso de vasopresores, necesidad de técnicas de reemplazo de la función renal, porcentaje de linfocitos a las 72 horas del ingreso en UCI < 6,5%, y trombocitopenia, mientras que el uso de lopinavir/ritonavir fue identificado como un factor protector.

Conclusiones

La edad, gravedad y fracaso orgánico junto con la necesidad de terapias de soporte fueron identificadas como factores predictores de mortalidad a las seis semanas.

La administración de corticoesteroides a dosis altas no mostró beneficios en la mortalidad, al igual que el tratamiento con tocilizumab, lopinavir/ritonavir se identificaron como un factor protector.

Palabras clave:
SARS-CoV-2
UCI
Corticoides
Tocilizumab
Lopinavir/ritonavir
Texto completo
Introduction

Past december, the first cases of respiratory infection caused by SARS-CoV-2 were documented in the Chinese city of Wuhan, observing as a percentage of patients developing the most serious clinical forms requiring respiratory support treatment with invasive mechanical ventilation.1 Already, in the first series of published patients it was found that between 10% and 20% of hospital admissions would develop Acute Respiratory Distress Syndrome (ARDS) and/or multiple-organ failure,2 charging special importance the role that intensive care units are occupying in the pandemic. Since then, the expansion of the epidemic has been global causing a serious unprecedented health crisis in the history of modern medicine. In the middle of October, more than 71 million cases are surpassed with more than one million and six thousand deaths documented by the World Health Organization.3 Andalusia is the Spanish Autonomous Community with the largest population in Spain, with 8.446.561 inhabitants. From March to May 2020, more than 6000 patients were admitted to hospital, exceeding 12% of ICU admissions. The Working Group on Infectious Diseases of the Andalusian Society of Intensive Medicine and Coronary Units (SAMIUC) has worked dynamically and continuously since the beginning of March, when the first patient was admitted in ICU occurred, by prospectively registering and monitoring ICU admitted cases with a fundamentally clinical objective so that the exchange of clinical information among the Andalusian ICU, in the form of a weekly newsletter, allowed to expand and share the limited clinical experience available at the beginning of the health emergency with the aim of improving the healthcare of critically ill patients infected by SARS-CoV-2. This study is the result of this collaborative project. It has been scarcely studied predictors of short term mortality 6 weeks after ICU admission now that many studies have been published with short-term mortality data and in many of them patients were still admitted in ICU.

The objective of the study is to identify the risk factors associated with mortality at six weeks, especially by analyzing the role of antivirals and immunomodulators in both the total cohort of patients and those who needed respiratory support with invasive mechanical ventilation.

Methods

This is a prospective descriptive multicenter cohort study. Twenty-six intensive care units (ICU) participate in the study from Andalusian region in Spain.

Study population

Consecutive critically ill patients with confirmed SARS-CoV-2 infection admitted to the participants ICU were included from March 8 to May 30.

Inclusion criteria: Patients older than 18 years, acute infection by SARS-CoV-2 confirmed by RT-PCR and admitted to the ICU, and a potential surveillance time of 6 weeks at least.

Exclusion criteria: pregnant woman, patients with SARS-CoV-2 but admitted to ICU for other reason not related to COVID-19, and patients or relatives who declined to participate in the study.

Because of the nature and contact restrictions of this pandemic disease, the informed consent was obtained from the patient when it was possible or from the relatives by a phone call with or without a complementary mail, and it was registered in the medical history. The Ethical Committee of Investigation in Cádiz [SAM-COVUCI-2020-01] approved the study protocol.

Variables: We analyzed demographic, epidemiological, comorbidities collected in the electronic medical history, body mass index, time from onset of symptoms, microbiological diagnoses, defining bacterial coinfection as an acute bacterial infection at clinical onset presentation of viral pneumonia with an isolate from respiratory tract or blood culture and/or a positive pneumococcal urinary antigen, time from hospital admission to ICU admission, severity scores and clinical condition at ICU admission, laboratory determinations at ICU admission and 72h after, respiratory function at ICU admission and 72h after, need for support therapy in ICU (high flow oxygen, non-invasive and invasive ventilation, prone position therapy, extrarenal depuration, extracorporeal membrane oxygenation), drug therapy (chloroquine, antiviral, interleukin-6 inhibitors, steroids, antibiotics), and mortality (ICU, early at 14 days, 28 days and 6 weeks mortality [main outcome]).

Statistical analysis

The design of the analysis comprised an univariate followed by multivariate Cox regression with propensity score analysis for the whole population and for the group of intubated patients, and a complementary decision tree analysis for the whole population with 6-weeks mortality as the outcome variable.

A descriptive analysis was made using absolute frequencies for qualitative variables and mean with standard deviation (SD) or median with percentiles 25th and 75th (p25–p75) when appropriate. For the univariate analysis, we used Chi-square or exact Fisher test when appropriate for qualitative variables and Student t-test or Mann–Whitney U test for parametric or nonparametric variables.

All comparisons were two-tailed, and signification was established on p<0.05. Mortality related variables were determined using Cox proportional hazards multivariate analysis. We include those variables with p<0.20 in the univariate analysis and other that were considered to be clinically relevant for this study, like the drug therapy. Hazard ratios and 95% confidence intervals were calculated. Sample size calculation was made with the assumptions of a 50% mortality rate and 20 significant variables in the univariate analysis. With the requirement of 10 events for each analyzed variable, we calculated a simple size of 400 patients. Continuous variables significantly different in the univariate analysis were transformed in dichotomic variables using a ROC curve analysis, determining the cutoff point with maximum sensitivity and specificity. Missing values in these new variables were assigned to be negative values in order to facilitate the multivariate analysis, if the number of missing values was less than 10%. Because of the potential imbalances in the characteristics of treatment groups, we assessed the probability of receiving lopinavir/ritonavir by a logistic regression model to calculate a propensity score (PS). We included variables a p less than 0.20 in the univariate analysis. This approach was determined to minimize the risks of confounding by indication of this drug. The covariates finally included in this PS were APACHE II score and respiratory rate in the ICU. This PS was included as a covariate in the multivariate Cox regression analysis for 42-days mortality.

A classification of regression tree (CRT) analysis was also made to characterize risk groups for 42-days mortality, with a maximum of 5 levels, minimum parental level of 50 cases and minimum childsize of 10 cases, and a cross validation with 20 sample folds.

Results

In the study period, 723 were admitted in Andalusian ICU, 495 patients were enrolled in this study but 73 of them were excluded for incomplete data. Thus, 422 patients were included in the final analysis (Fig. 1). Median age was 63 years (54–71) and 305 (72.3%) were men. ICU mortality: 144/422 34%; 14 days mortality: 81/422 (19.2%); 28 days mortality: 121/422 (28.7%); 6-week mortality 152/422 36.5%. Table 1 compares demographics and clinical characteristics of those who died with those alive on day 42. As expected, those who died were significantly older and with higher APACHE II and SOFA scores. Moreover, level of consciousness (evaluated by GCS) was worse in those who were not alive at day 42.

Figure 1.

Flowchart of the study participants.

(0.16MB).
Table 1.

Baseline characteristics and univariate analysis with 6 weeks mortality.

  n  Dead at 42 days(n=152)  Survivor at 42 days(n=270)  OR (CI 95%)  p 
Age [years], mean (SD)  419  65.6 (11.0)  59.4 (11.8)    <0.001 
Age groups, n (%)  419        <0.001 
18–45 years    6 (4)  35 (13)   
46–60 years    34 (22.8)  95 (35.2)  2.09 (0.81–5.40)   
61–75 years    85 (57)  125 (46.3)  3.97 (1.60–9.84)   
>75 years    24 (16.1)  15 (5.6)  9.33 (3.17–27.5)   
Sex (male), n (%)  420  118 (78.1)  187 (69.5)  1.57 (0.99–2.50)  0.057 
Body mass index, mean (SD)  356  29.1 (5.2)  29.2 (5.4)    0.859 
COPD, n (%)  422  9 (5.9)  16 (5.9)  1.00 (0.43–2.32)  0.998 
Renal disease, n (%)  422  21 (13.8)  23 (8.5)  1.72 (0.92–3.23)  0.087 
Cirrhosis, n (%)  422  7 (4.6)  4 (1.5)  3.21 (0.92–11.2)  0.063 
Onco haematological disease, n (%)  422  13 (8.6)  17 (6.3)  1.39 (0.66–2.95)  0.387 
APACHE II score at ICU admission, mean (SD)  410  16.4 (9.6)  11.0 (5.0)    <0.001 
SOFA score at ICU admission, mean (SD)  398  6.6 (3.0)  4.9 (2.7)    <0.001 
GCS score at ICU admission, mean (SD)  419  13.9 (3.2)  14.8 (1.4)    <0.001 
SOFA score 72h post-ICU admission, mean (SD)  386  8.0 (2.7)  5.7 (2.8)    <0.001 
High flow oxygen, n (%)  420  52 (34.4)  143 (53.2)  0.46 (0.31–0.70)  <0.001 
Non-invasive ventilation, n (%)  420  12 (7.9)  24 (8.9)  0.88 (0.43–1.82)  0.732 
High flow oxygen or non-invasive ventilation before intubation, n (%)  407  54 (36.2)  86 (33.3)  1.14 (0.75–1.74)  0.552 
Endotracheal intubation, n (%)  422  146 (96.1)  196 (72.6)  9.19 (3.89–21.69)  <0.001 
Vasopressors, n (%)  419  143 (94.7)  190 (70.9)  7.34 (3.43–15.68)  <0.001 
Days with vasopressors, median (p25–p75)  314  7 (4–14)  6 (3–10)    0.027 
Extrarenal depuration, n (%)  415  33 (22.3)  17 (6.4)  4.22 (2.26–7.89)  <0.001 
Bacterial infection at presentation, n (%)  416  24 (16.1)  31 (11.6)  1.46 (0.82–2.60)  0.194 
Nosocomial infection, n (%)  410  54 (36.7)  95 (36.1)  1.03 (0.68–1.56)  0.902 
Days from ICU admission to VAP, median (p25–p75)  101  9 (6–13)  12 (8–19)    0.005 
Catheter related infection. n (%)  415  27 (18.1)  47 (17.7)  1.03 (0.61–1.74)  0.908 
Lopinavir/ritonavir, n (%)  421  136 (90.1)  254 (94.1)  0.57 (0.27–1.19)  0.131 
Remdesivir, n (%)  421  2 (1.3)  6 (2.2)    0.518 
Interferon β 1b, n (%)  421  72 (47.7)  130 (48.1)    0.927 
Chloroquine, n (%)  410  119 (81.5)  219 (83.0)    0.712 
Tocilizumab, n (%)  410  64 (43.5)  102 (38.8)    0.347 
Empiric antimicrobial therapy, n (%)  420  140 (92.7)  248 (92.2)  1.08 (0.51–2.30)  0.847 
Days of empiric antimicrobial therapy, median (p25–p75)  377  6 (4–8)  6 (4–8)    0.314 
Steroids therapy, n (%)  420  99 (66.9)  161 (59.9)  1.36 (0.89–2.06)  0.156 
Days from symptoms to hospital admission, median (p25–p75)  417  7 (4–9)  7 (4–9)    0.379 
Days from symptoms to microbiological diagnose, median (p25–p75)  413  7 (4–10)  7 (5–9)    0.813 
Days from hospital to ICU admission, median (p25–p75)  412  1 (0–3)  2 (1–4)    0.020 
Days from symptoms to therapy, median (p25–p75)  398  7 (5–10)  7 (5–10)    0.961 
ICU stay, median (p25–p75)  421  13 (6–23)  16 (8–31)    0.012 

APACHE: Age, Physiology, Chronic Health Evaluation; CI: confidence interval; COVID: coronavirus disease; COPD: chronic obstructive pulmonary disease; DAP: diastolic arterial pressure; ECMO: extracorporeal membrane oxygenation; ER: emergency room; FiO2: fraction of inspired oxygen; GCS: Glasgow Coma Score; ICU: Intensive Care Unit; MAP: mean arterial pressure; OR: odds ratio; PaO2: partial pressure of Oxygen; PEEP: positive end-expiratory pressure; SAP: systolic arterial pressure; Sat: saturation; SD: standard deviation; SOFA: Sequential Organ Failure assessment; VAP. ventilator-associated pneumonia.

The laboratory findings of all critically ill patients on day 1 and 3 are summarized in Table 2. The median PaO2/FiO2 ratio on day 1 was not statistically different in those who died compared with survivors, but it was significantly lower on day 3 in those who died. Percentage of lymphocytes, neutrophils/lymphocytes ratio, and platelets were statistically different on day 1 and day 3.

Table 2.

Laboratory findings of all critically ill patients on day 1 and 3 of ICU admission.

  At ICU admission72h post-ICU admission
  n  Dead at 42 days(n=152)  Survivor at 42 days (n=270)  p  n  Dead at 42 days(n=152)  Survivor at 42 days (n=270)  p 
PaO2/FiO2, mean (SD)  319  134.1 (74.7)  140.6 (77.0)  0.450  305  189.4(75.5)  2089 (78.0)  0.031 
Delta PaO2/FiO2 72–24h, median (p25–p75)          298  10 (−42 to 67)  30 (−32 to 81)  0.253 
Leucocytes [×109/L], mean (SD)  418  11.2 (8.7)  9.9 (6.0)  0.104  393  11.8 (11.4)  9.6 (6.5)  0026 
Neutrophils [×109/L], mean (SD)  418  9.6 (7.3)  8.5 (5.5)  0.086  390  9.7 (7.4)  8.0 (5.2)  0.014 
% Neutrophils [×109/L], mean (SD)  416  86.4 (8.6)  84.7 (8.1)  0.046  390  84.7(13.1)  81.9(8.8)  0.015 
Lymphocytes [×106/L], mean (SD)  409  637.5 (397.1–932.5)  773.0 (490.0–996.0)  0.663  383  595 (365–922)  720 (479–1034)  0.002 
% Lymphocytes, mean (SD)  409  8.1 (5.4)  9.7 (6.3)  0.013  384  7.6 (6.4)  10.3 (6.3)  <0.001 
Ratio neutrophils/lymphocytes, mean (SD)  409  18.3 (19.0)  13.9 (12.4)  0.013  382  20.4 (22.4)  12.3 (9.9)  <0.001 
Platelets [×109/L], mean (SD)  418  229.1(108.1)  252.1 (111.5)  0.040  388  228.1 (102.1)  290.2 (115.1)  <0.001 
Creatinine [mg/dL], mean (SD)  412  1.26 (1.01)  1.06 (0.76)  0.020  397  1.61 (1.13)  1.10 (0.92)  <0.001 
Urea [mg/dL], mean (SD)  375  61.1(39.9)  48.5 (36.5)  0.003  353  80.4 (47.0)  58.4 (40.0)  <0.001 
Lactate dehydrogenase [U/L], mean (SD)  388  635.7(577.2)  465.9 (195.2)  0.001  353  532.8 (427.6)  405.9 (172.6)  0.002 
Creatine kinase [U/L], median (p25–p75)  321  141 (69–281)  104 (53–181)  0.025  299  119 (47–329)  90 (48–291)  0.144 
Aspartate aminotransferase [U/L], median (p25–p75)  385  54 (36–91)  48 (33–78)  0.074  359  47 (25–84)  45 (29–70)  0.794 
Alanine aminotransferase [U/L], median (p25–p75)  366  39 (24–59)  40 (27–64)  0.325  337  37 (22–53)  44 (28–68)  0.018 
Procalcitonin [ng/mL], median (p25–p75)  333  0.34 (0.17–0.94)  0.23 (0.11–0.50)  0.001  274  0.70 (0.26–2.07)  0.27 (0.10–0.74)  <0.001 
C-reactive protein [mg/L], mean (SD)  407  178.5 (109.9)  165.0 (110.4)  0.239  375  160.8 (131.5)  114.4 (110.3)  <0.001 
Lactate [mmol/L], median (p25–p75)  371  1.70 (1.15–2.85)  1.33 (1.00–1.90)  0.001  322  2.38 (2.65)  2.0 (2.89)  0.244 
Fibrinogen [mg/dL], mean (SD)  296  702.8 (639.2)  706.1 (730.2)  0.969  260  626.0 (279.4)  595.6 (256.5)  0.383 
D-dimer [ng/mL], median (p25–p75)  376  1723 (894–4113)  1160 (660–2500)  0.001  360  3619 (1600–16537)  1934 (993–4662)  <0.001 

Approximately, one-third of the patients were admitted to the ICU from the Emergency Department (138 patients; 32.7%) and the rest from the general ward. Median time from viral symptom onset to hospital admission was 86–11 days. Median time from hospitalization to ICU admission was 21–4 days. Three quadrants were involved on the chest X-ray in 78 patients (18.5%) and the four quadrants in 244 patients (57.8%). Microbiologically documented co-infection at ICU admission was diagnosed in 55 (13%) patients.

The majority of the patients were treated with lopinavir/ritonavir (n=390) and/or hydroxychloroquine (n=338). Remdesivir was used in a very small number of patients (n=8). Interferon beta-1b was used in 202 patients. High doses of corticosteroids (methylprednisolone2mg(kg/day). were administered in 260 (61.6%) patients whereas 166 patients received tocilizumab. Both drugs were used in 126 (29.9%) patients. Tables 1–4 of the supplementary material, show the comparison of different variables in patients treated and not treated with lopinavir/ritonavir, hydroxychloroquine, tocilizumab or Interferon beta-1b.

Overall, 342 (81%) patients were intubated. Vasopressors were used in 333 (78.9%) patients. Fifty (11.8%) patients required renal replacement therapy. One-hundred and forty-nine individuals (35.3%) developed at least one nosocomial infection in the ICU. The most frequent infections were: VAP (103 patients; 24.4%) and catheter-related bloodstream infections (74 patients; 17.5%).

By multivariable Cox proportional analysis, factors independently associated with 42-day mortality were age, APACHE II score, SOFA score at ICU admission >6, lactate dehydrogenase at ICU admission >470U/L, Use of vasopressors, extrarenal depuration, %lymphocytes 72h post-ICU admission <6.5%, and thrombocytopenia whereas the use of lopinavir/ritonavir was a protective factor (Table 3). Because of the noted imbalances in baseline characteristics and clinical situation at admission to the ICU, a Cox regression model was developed introducing the probability calculated by the propensity score in an attempt to ameliorate the impact of observed differences. This analysis also identified therapy with lopinavir/ritonavir as a protective factor for 6-week mortality. “Delta SOFA score 0–72h was significantly related to mortality in univarian analysis in all patients and mechanically ventilated patients. However, it is not independently associated with mortality at 42 days in both groups of patients (Table 6, supplementary material).”

Table 3.

Relationship between Delta SOFA score 0–72h and mortality.

All patients  n  Dead at 42 days(n=152)  Survivor at 42 days (n=270)  OR (CI 95%)  p 
Delta SOFA score 72h – ICU admission, mean (SD)  272  1.8 (2.7)  0.7 (2.6)    <0.001 
Delta SOFA score 72h – ICU admission>0, n (%)  422  78 (43.6)  101 (56.4)  1.76 (1.18–2.64)  0.006 
Mechanically ventilated patients  n  Dead at 42 days(n=146)  Survivor at 42 days (n=196)  OR (CI 95%)  p 
Delta SOFA score 72h – ICU admission, mean (SD)  308  1.7 (2.8)  0.9 (2.8)    <0.001 
Delta SOFA score 72h – ICU admission>0, n (%)  342  78 (51.3)  74 (48.7)  1.76 (1.18–2.64)  0.006 
Patients on mechanical ventilation

In intubated patients (n=342), ICU mortality: 142/342 (41.5%); 14 days-mortality 77/342 (22.5%); 28 days mortality: 115/342(33.6%), 6-week Mortality 146/342 (42.7%). The median time from ICU admission to intubation was 0 days [0–1]). Table 4 depicts the clinical features of those patients who required invasive mechanical ventilation and their laboratory parameters on day 1 and 3 are shown in Table 5 (supplementary material). As in the entire group, those who died were significantly older and with higher APACHE II and SOFA scores at admission. No substantial imbalances in patients’ comorbidities were observed.

Table 4.

Multivariate Cox regression analysis of variables associated with mortality at 6 weeks with Propensity Score for lopinavir/ritonavir.

Variables  All patientsPatients on Mechanical ventilation
  HR (CI 95%)  p  HR (CI 95%)  p 
Age (years)  1.04 (1.02–1.06)  <0.001  1.05 (1.03–1.07)  <0.001 
Cirrhosis      2.37 (1.02–5.53)  0.045 
APACHE II  1.04 (1.02–1.07)  0.002  1.03 (1.02–1.05)  <0.001 
SOFA score at ICU admission >6a  1.43 (1.01–2.03)  0.043     
Lactate dehydrogenase at ICU admission >470U/La  1.57 (1.10–2.23)  0.013     
First PEEP after intubation >12a      2.05 (1.37–3.05)  <0.001 
PaO2/FiO2 24h post-intubation <160a      1.67 (1.13–2.46)  0.011 
SOFA score 72h post-ICU admission >6a      1.73 (1.12–2.67)  0.014 
%Lymphocytes 72h post-ICU admission <6.5%a  1.61 (1.13–2.30)  0.009     
Neutrophils/lymphocytes ratio 72h post-ICU admission >14a      1.02 (1.01–1.03)  <0.001 
Platelets 72h post-ICU admission <150×109/La  1.89 (1.18–3.03)  0.012  2.53 (1.51–4.27)  <0.001 
D-dimer 72h post-ICU admission >3.400mg/La      1.67 (1.14–2.47)  0.009 
Use of vasopressors  4.04 (1.73–944).  0.001     
Extrarenal depuration  1.85 (1.21–2.84)  0.004  1.79 (1.13–2.82)  0.011 
Use of lopinavir/ritonavir  0.52 (0.29–0.93)  0.029     
Propensity score    0.586     

APACHE II: acute physiology, age and Chronic Health Evaluation score; HR: hazard ratio; FiO2: fraction of inspired oxygen; ICU: intensive care unit; PEEP: positive end-expiratory pressure; SOFA: Sequential Organ Failure Assessment.

a

Binary variables calculated using ROC curves. Missing values treated as negative values. See Table 3s in Supplementary Material.

The median PaO2/FiO2 ratio on day 1 was 170 [115–236]. The use of ECMO was marginal in this series (only 4 patients; two died). Conversely, proning positioning was used in almost two-thirds of the patients (251/341; 73.6%). Tracheostomy was performed in 43.4% of the intubated patients (145/334).

By multivariable Cox proportional analysis, factors independently associated with 42-day mortality were age, cirrhosis, APACHE II score, First PEEP after intubation >12cmH2O, PaO2/FiO2 24h post-intubation <160, extrarenal depuration, neutrophils/lymphocytes ratio 72h post-ICU admission >14, D-dimer 72h post-ICU admission >3.400mg/L, and thrombocytopenia (Table 3). Of note, use of lopinavir/ritonavir was not included in this model as a protective factor of 1.01 (0.49–2.08) p=0.98.

Classification of regression tree (CRT)

A decision tree to depict the risk groups for 42-days mortality (Fig. 2) was built based on CRT analysis. It reached an overall percentage of correct classification of 69.7%. The established risk groups were on a range from 6.1% (APACHE II score12+Age62+PaO2/FiO2>160) to 84.6% (APACHE II score>12+Extrarenal depuration). Patients with APACHE II score>12 were ever classified with mortality at 6 weeks higher than 49%.

Figure 2.

The decision tree based on CRT analysis reached an overall percentage of correct classification of 69.7%. The established risk groups were on a range from 6.1% (APACHE II score12+Age62+PaO2/FiO2>160) to 84.6% (APACHE II score>12+Extrarenal depuration). Patients with APACHE II score>12 were ever classified with mortality at 6 weeks higher than 49%.

(0.63MB).
Discussion

Most published studies to date about critically ill patients with SARS-CoV-2 infection has been retrospective series of patients. This study, by its prospective and multicenter design, with more than 420 patients analyzed, representatively reflects the clinical profile and prognosis of the most severe form of clinical presentation of SARS-CoV-2 pneumonia. It seems transcendent to identify prognosis-related factors to optimize the use of health resources and guide better clinical management. We suggest using clinical tools for helping clinicians, such as the decision-making tree documented in the results in difficult decision-making. We were able to identify a subgroup of patients with very high mortality, there are few critical pathologies in which only with an APACHE II>12 and the need for extrarenal depuration therapies can be associated with a high mortality. This information may be useful to be considered in decision-making on limitation of life support treatment.

One third of patients admitted to ICU died, with higher mortality of 43% observed, in patients receiving mechanical ventilation. This mortality is below that described in a recent meta-analysis4 that included more than 14,000 patients in 44 studies, which estimates mortality in ventilated patients by a percentage greater than 80%. Although remarkable heterogeneity was observed in the selected studies, weaknesses in the follow-up of those patients still admitted, and most studies came from the Asian continent, where the published series point to a worrying high mortality in mechanically ventilated patients.5–8 The Spanish publications documented to date express short series of no more than 50 patients coinciding with the clinical profile, ventilatory requirements and prognosis described in our study.9–13 Published series of Italian patients from the Lombardy region14 document mortality similar to that observed in our study, and in the New York area, a study describes a mortality of 24.5% in mechanically ventilated patients, these results should be analyzed considering the limitation that at that time most continued receivinfg mechanical ventilation, 72.2% of patients, and had only been discharged from ICU a 3.3% of patients, so mortality can be expected to be higher.15 In the Seattle series, they documented 50% mortality and there are still being mechanically ventilated patients when they published it.16

In a novel way, lopinavir/ritonavir administration is identified as a protective factor. This finding deserves to be interpreted wisely, since there were no differences in the univariant analysis, turns out to be significant in the multivariate analysis of the total cohort of patients but not in the subgroup that received mechanical ventilation. This is the only study group up to our knowledge that provides this evidence. To control the potential weaknesses of an obervational study in an environment changing treatment guidelines, we have performed a propensity score analysis, which was included in the final model maintaining as a protective factor the treatment with lopinavir/ritonavir.

Of course, this finding should be endorsed in randomized studies, but it opens up a possibility of treatment in this entity with so few therapeutic options. The clinical trial of Cao B y cols17 conducted in 199 patients showed no benefits in treatment, but we must take into account that the population studied is notably far from the clinical profile of critically ill represented in our series. Only one patient was included in the defined category 6 who contemplates hospitalization with mechanical ventilation, ECMO or both treatments and only 15% within category 5 requiring high flow oxygen therapy or non-invasive ventilation. In addition, randomization occurred 13 days after the onset of symptoms, an average time significantly longer than documented in our series that was 8 days, it seems key as has happened in other infectious diseases for other causes that the administration of antibiotic or antiviral treatment achieves the best benefits as soon as possible are administered.18,19

Recently, RECOVERY study results about lopinavir/ritonavir has been published, conducted at 176 hospitals in the United Kingdom, this study does not demonstrate benefits in terms of survival, but we have to discuss the eligibility of participants with a high number of losses because they did not have treatment available, do not consider it appropriate or were receiving other treatments. In addition, the percentage of critically ill patients was very low and the days after the onset of symptoms when treatment was prescribed exceeded one week.20

Unfortunately, the newly demonstrated benefits in viral load reduction, clinical improvement and modulation of inflammatory response with combined administration of lopinavir/ritonavir with interferon and ribavirin21 barely anecdotally contemplated the inclusion of critically ill patients in their study.

We have not observed benefits in all other antiviral treatments used, hydroxychloroquine and interferon, although the use of remdesivir was minorityly used due to restrictions on its access to critical patients in the early months of the pandemic.

The benefits currently demonstrated22 were not seen in the subgroup of patients receiving mechanical ventilation although it should be noted that it was not the primary objective of the study. The need for clinical trials specifically targeting the critically ill with respiratory infection with SARS-CoV-2 infection has become a long-awaited necessity.

Administration of corticosteroids at high doses, the percentage of use of which was more than half of patients, showed no benefits in mortality, as did treatment with tocilizumab who received more than one third of patients. Although there are described clinical experiences that point to a potential benefit of tocilizumab in mechanically ventilated patients,23 we do not observe this effect, a significant limitation of the comparative study of Somers and cols is that the comparative groups were not homogeneous by noting significant differences in age and presence of chronic pathology prior to in addition to lower levels of D-dimer in the treated group. Pending the final publication of the results of the phase 3 COVACTA clinical trial, it appears that COVACTA has not demonstrated benefits in terms of survival.24

The use of corticosteroids in our patient series corresponds to the prior period of publication of the clinical trial that has associated the administration of dexamethasone at doses of 6mg with mortality benefits,25 a guideline that is far from that currently recommended was used. Research continues on the potential benefit that could be associated with higher doses of corticosteroid treatment.26 Our findings coincide with the lack of solid evidence currently supporting the widespread use of these treatments in critical patients.

During the recruitment period, empiricism capitalized on treatments of severe forms of the disease, eager to obtain new evidence from ongoing clinical trials,27 this has conditioned significant variability in clinical practice.28 Aware of this reality we present in a novel way a decision-making tree analysis based on the main factors related independently to mortality.

Age, severity at ICU admission measured by APACHE II and organic failure determined by a SOFA>value of 6 points, along with vasopressor requirements or renal replacement therapy have been identified as predictor factors of mortality at six weeks, in line with findings from other published series.5,7,8 With regard to laboratory tests, we must comment as a limitation that the levels of ferritin, whose role in severe SARS-CoV-2 infection is to be clarified,29 and interleukin-6,30 that we know have been linked to the inflammatory response and severity of the disease, were not collected in the database. Registration began in the early days of the pandemic, so most of the participating centres did not have the possibility of measuring them and the prospective design of the study conditioned that we had not incorporated it later. They have been identified as prognostic factors presenting with lymphopenia at admission and/or elevated levels of lactate dehydrogenase (LDH) related to increased mortality. The presence of lymphopenia at admission has been linked to the need to ICU admission,31,32 but there are also authors who associate it with greater severity, need for mechanical ventilation and increased mortality.33,34 Higher levels of LDH have been reported in the most severe forms of SARS-CoV-2 infection and have even correlated the drop in their levels with the negativization of the virus PCR and a better prognosis,35 although there are references linking high levels of LDH with the most severe forms of clinical presentation36,37 we present as an independent mortality factor that their admission levels are higher than 470U/L.

In the multivariate analysis carried out in the subpopulation of mechanically ventilated patients have been identified as independent mortality factors at six weeks age, severity measured by APACHE II upon ICU admission, history of cirrhosis, the need for renal replacement therapies and thrombopenia along with the persistence of organic failure at 72h of admission as measured by SOFA>6. In addition, to the severity of respiratory failure determined by PEEP needs within the first 24h after intubation and PaO2/FiO2 ratio less than 160. Mortality described in our series approaches, being somewhat higher, to the estimation of Berlin definition of respiratory distress,38 that established in moderate grades with PaO2/FiO2 between 100 and 200 mortality of 32%; 95% CI, 29–34% increasing to 45%; 95% CI, 42–48% in those classified as severe with PaO2/FiO2 less than 100.

With regard to laboratory tests, D dimer levels >3400mg/L and neutrophil/lymphocyte ratio >14–72h of ICU entry are identified as mortality factors. These findings at 72h of ICU admission express a lack of response to support treatments instituted when entering ICU and therefore partly a therapeutic failure associated with increased mortality.

The neutrophil/lymphocyte ratio has been used as an inflammatory state factor with prognostic value in various pathologies,39,40 not all of an infectious nature, although it is in sepsis that it has been identified as a prognostic factor,41 the fact that the most severe forms of clinical presentation of SARS-CoV-2 infection develop sepsis can justify our results that identify this marker at 72h with the highest mortality when it is >of 14. There are authors who have described this parameter as an independent mortality factor in respiratory infection due to SARS-CoV-2, especially in males,42 a recent meta-analysis43 identifies it as a prognostic factor in this disease.

In a novel way, we provide this finding in critical patients, aware that this is an inexpensive laboratory measure, accessible in most ICU, and reflecting the intensity of the inflammatory response and we have identified it as an independent mortality factor.

D dimer levels at hospital admission have been linked as a predictor of mortality,7,44,45 from an analytical point of view it remains to be explained what the cut-off points are, their need to be adjusted by age46 and it seems mandatory that the units of measurement and how to obtain it from the different studies be specified in order to be compared.47 High levels at 72h of admission were associated in our series to higher mortality.

The main limitation of the study derives from the timing of the study's design, which being at first of pandemic time, no variables that were later demonstrated to have predicted value were included in the study protocol. We do not have the levels of ferritin, interleukin 6 nor was treatment was collected with anticoagulant therapy. Other limitations were the lack of a standard definition of comorbidities and the definition used to classify bacterial co-infection, with the proposed criteria it is not possible to detect co-infection due to atypical bacteria. From the point of view of statistical analysis we acknowledge a limitation derived from the use of the transformation of quantitative variables into dichotomous variables to facilitate multivariate analysis, by the assumption of lost values as negative. Another limitation given the abruptness of the pandemic is the absence of unified criteria for ICU admission and drug use, which can make it difficult to interpret the data. However, we consider this to be currently the widest series of critical patients collected prospectively and highly representatively for the multicenter participation involving most of the ICU in our community, belonging to hospitals of different levels of care. Identifying mortality-related factors at six weeks in critically ill patients will help the clinician stratify risk and make decisions. The uncertainty of clinical practice in this new disease48 can be fought applying contingency plan for the intensive care services49 based on the documentation of clinical experiences such as the one we present, and from them with the design of research studies in well-designed critical patients aimed at solving challenges about treatment that remain unresolved today.

Authors’ contribution

AE is the project coordinator, designed the study protocol and contacted the researchers. He managed approval by the Ethics Committee of Inquiry. AE has collected data from researchers and JLGG has performed statistical analysis. AE, JLGG and JG have written the contents of the manuscript. All researchers have participated in the inclusion of cases and have reviewed the version of the manuscript.

Ethics approval

Because of the nature and contact restrictions of this pandemic disease, the informed consent was obtained from the patient when it was possible or from the relatives by a phone call with or without a complementary mail, and it was registered in the medical history. The Ethical Committee of Investigation in Cádiz [SAM-COVUCI-2020-01] approved the study protocol.

Funding

None declared.

Conflict of interest

None declared.

Acknowledgements

The study coordinator would like to thank Ms. Monica Saldaña on behalf of the SAMIUC Infectious Diseases Working Group for their help in designing the study protocol in the worst days of the pandemic.

References
[1]
N. Zhu, D. Zhang, W. Wang, X. Li, B. Yang, J. Song, et al.
China Novel Coronavirus Investigating and Research Team. A novel coronavirus from patients with pneumonia in China, 2019.
N Engl J Med, 382 (2020), pp. 727-733
[2]
N. Chen, M. Zhou, X. Dong, J. Qu, F. Gong, Y. Han, et al.
Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan China: a descriptive study.
[3]
Organización Mundial de la Salud. WHO Coronavirus Disease (COVID-19) Dashboard. Retrieved 14 December 2020. https://covid19.who.int/.
[4]
N. Potere, E. Valeriani, M. Candeloro, M. Tana, E. Porreca, A. Abbate, et al.
Acute complications and mortality in hospitalized patients with coronavirus disease 2019: a systematic review and meta-analysis.
[5]
J. Xu, X. Yang, L. Yang, X. Zou, Y. Wang, Y. Wu, et al.
Clinical course and predictors of 60-day mortality in 239 critically ill patients with COVID-19: a multicenter retrospective study from Wuhan, China.
Crit Care, 24 (2020 Jul 6), pp. 394
[6]
J. Hua, C. Qian, Z. Luo, Q. Li, F. Wang.
Invasive mechanical ventilation in COVID-19 patient management: the experience with 469 patients in Wuhan.
[7]
F. Zhou, T. Yu, R. Du, G. Fan, Y. Liu, Z. Liu, et al.
Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan China: a retrospective cohort study.
Lancet, 395 (2020), pp. 1054-1062
[8]
X. Yang, Y. Yu, J. Xu, H. Shu, J. Xia, H. Liu, et al.
Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan China: a single-centered, retrospective, observational study.
Lancet Respir Med, 8 (2020), pp. 475-481
[9]
A. Rodríguez, G. Moreno, J. Gómez, R. Carbonell, E. Picó-Plana, C. Benavent Bofill, et al.
Severe infection due to the SARS-CoV-2 coronavirus: experience of a tertiary hospital with COVID-19 patients during the 2020 pandemic.
Med Intensiva, 44 (2020), pp. 525-533
[10]
P. Ramírez, M. Gordón, M. Martín-Cerezuela, E. Villarreal, E. Sancho, M. Padrós, et al.
Acute respiratory distress syndrome due to COVID-19. Clinical and prognostic features from a medical Critical Care Unit in Valencia, Spain.
Med Intensiva, (2020),
[11]
Serrano-Martínez JL, Machado-Casas JF, Redondo-Orts M, Manzano-Manzano F, Castaño-Pérez J, Pérez-Villares JM. Características y resultados de una serie de 59 pacientes con neumonía grave por COVID-19 ingresados en UCI. Med Intensiva [Internet]. Available from: http://www.medintensiva.org/es-caracteristicas-resultados-una-serie-59-avance-S0210569120301844 [cited 2020 August 25].
[12]
P. Vidal-Cortés, L. Del Río-Carbajo, J. Nieto-Del Olmo, E. Prol-Silva, A.I. Tizón-Varela, A. Rodríguez-Vázquez, et al.
COVID-19 and Acute Respiratory Distress Syndrome Impact of corticosteroid treatment and predictors of poor outcome.
Rev Esp Quimioter, (2020),
[13]
H. Barrasa, J. Rello, S. Tejada, A. Martín, G. Balziskueta, C. Vinuesa, et al.
SARS-CoV-2 in Spanish Intensive Care Units: early experience with 15-day survival in Vitoria.
Anaesth Crit Care Pain Med, 39 (2020), pp. 553-561
[14]
G. Grasselli, A. Zangrillo, A. Zanella, M. Antonelli, L. Cabrini, A. Castelli, et al.
Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region Italy.
[15]
S. Richardson, J.S. Hirsch, M. Narasimhan, J.M. Crawford, T. McGinn, K.W. Davidson, et al.
Presenting characteristics comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area.
JAMA, 323 (2020), pp. 2052-2059
[16]
P.K. Bhatraju, B.J. Ghassemieh, M. Nichols, R. Kim, K.R. Jerome, A.K. Nalla, et al.
Covid-19 in critically ill patients in the Seattle Region – case series.
N Engl J Med, 382 (2020), pp. 2012-2022
[17]
B. Cao, Y. Wang, D. Wen, W. Liu, J. Wang, G. Fan, et al.
A trial of lopinavir-ritonavir in adults hospitalized with severe covid-19.
N Engl J Med, 382 (2020), pp. 1787-1799
[18]
P. Daniel, C. Rodrigo, T.M. Mckeever, M. Woodhead, S. Welham, W.S. Lim.
Time to first antibiotic and mortality in adults hospitalised with community-acquired pneumonia: a matched-propensity analysis.
[19]
T.M. Uyeki, H.H. Bernstein, J.S. Bradley, J.A. Englund, T.M. File, A.M. Fry, et al.
Clinical practice guidelines by the Infectious Diseases Society of America: 2018 update on diagnosis, treatment, chemoprophylaxis, and institutional outbreak management of seasonal influenza.
Clin Infect Dis, 68 (2019), pp. 895-902
[20]
RECOVERY Collaborative Group.
Lopinavir–ritonavir in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial.
[21]
I.F. Hung, K.C. Lung, E.Y. Tso, R. Liu, T.W. Chung, M.Y. Chu, et al.
Triple combination of interferon beta-1b, lopinavir-ritonavir, and ribavirin in the treatment of patients admitted to hospital with COVID-19: an open-label, randomised, phase 2 trial.
Lancet, 395 (2020), pp. 1695-1704
[22]
J.H. Beigel, K.M. Tomashek, L.E. Dodd.
Remdesivir for the treatment of Covid-19 — preliminary report.
[23]
E.C. Somers, G.A. Eschenauer, J.P. Troost, J.L. Golob, T.N. Gandhi, L. Wang, et al.
Tocilizumab for treatment of mechanically ventilated patients with COVID-19.
Clin Infect Dis, (2020),
[25]
P. Horby, W.S. Lim, J.R. Emberson, M. Mafham, J.L. Bell, L. Linsell, et al.
Dexamethasone in hospitalized patients with covid-19 – preliminary report.
[26]
L.P. Maskin, G.L. Olarte, F. Palizas Jr., A.E. Velo, M.F. Lurbet, I. Bonelli, et al.
High dose dexamethasone treatment for Acute Respiratory Distress Syndrome secondary to COVID-19: a structured summary of a study protocol for a randomised controlled trial.
[27]
Á. Estella, J. Garnacho-Montero.
From empiricism to scientific evidence in antiviral treatment in severe cases of coronavirus infection in times of epidemic [published online ahead of print, 2020 Apr 22].
Med Intensiva, S0210–5691 (2020), pp. 30116-30119
[28]
E. Azoulay, J. de Waele, R. Ferrer, T. Staudinger, M. Borkowska, P. Povoa, et al.
International variation in the management of severe COVID-19 patients.
Crit Care, 24 (2020), pp. 486
[29]
J. Feld, D. Tremblay, S. Thibaud, A. Kessler, L. Naymagon.
Ferritin levels in patients with COVID-19: a poor predictor of mortality and hemophagocytic lymphohistiocytosis [published online ahead of print, 2020 Aug 13].
Int J Lab Hematol, (2020),
[30]
J. Zhu, J. Pang, P. Ji, Z. Zhong, H. Li, B. Li, et al.
Elevated interleukin-6 is associated with severity of COVID-19: a meta-analysis.
[31]
B.E. Fan, V.C.L. Chong, S.S.W. Chan, G.H. Lim, K.G.E. Lim, G.B. Tan, et al.
Hematologic parameters in patients with COVID-19 infection.
[32]
C. Huang, Y. Wang, X. Li, L. Ren, J. Zhao, Y. Hu, et al.
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.
Lancet, 395 (2020), pp. 497-506
[33]
W.J. Guan, Z.Y. Ni, Y. Hu, W.H. Liang, C.Q. Ou, J.X. He, et al.
Clinical characteristics of coronavirus disease 2019 in China.
N Engl J Med, 382 (2020), pp. 1708-1720
[34]
Y. Deng, W. Liu, K. Liu, Y.Y. Fang, J. Shang, L. Zhou, et al.
Clinical characteristics of fatal and recovered cases of coronavirus disease 2019 (COVID-19) in Wuhan, China: a retrospective study.
[35]
F. Zhou, T. Yu, R. Du, G. Fan, Y. Liu, Z. Liu, et al.
Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan China: a retrospective cohort study.
Lancet, 395 (2020), pp. 1054-1062
[36]
J. Yuan, R. Zou, L. Zeng, S. Kou, J. Lan, X. Li, et al.
The correlation between viral clearance and biochemical outcomes of 94 COVID-19 infected discharged patients.
Inflamm Res, 69 (2020), pp. 599-606
[37]
Z. Zheng, F. Peng, B. Xu, J. Zhao, H. Liu, J. Peng, et al.
Risk factors of critical & mortal COVID-19 cases: a systematic literature review and meta-analysis.
J Infect, 81 (2020), pp. e16-e25
[38]
ARDS Definition Task Force, V.M. Ranieri, G.D. Rubenfeld, B.T. Thompson, N.D. Ferguson, E. Caldwell, et al.
Acute respiratory distress syndrome: the Berlin Definition.
JAMA, 307 (2012), pp. 2526-2533
[39]
M.E. Afari, T. Bhat.
Neutrophil to lymphocyte ratio (NLR) and cardiovascular diseases: an update.
Expert Rev Cardiovasc Ther, 14 (2016), pp. 573-577
[40]
S. Çalışkan, M. Sungur, S. Kaba, E. Özsoy, O. Koca, M.İ. Öztürk.
Neutrophil-to-lymphocyte ratio in renal cell carcinoma patients.
Folia Med (Plovdiv), 60 (2018), pp. 553-557
[41]
Z. Huang, Z. Fu, W. Huang, K. Huang.
Prognostic value of neutrophil-to-lymphocyte ratio in sepsis: a meta-analysis.
Am J Emerg Med, 38 (2020), pp. 641-647
[42]
Y. Liu, X. Du, J. Chen, Y. Jin, L.H.X.H. Peng, et al.
Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19.
J Infect, 81 (2020), pp. e6-e12
[43]
F.A. Lagunas-Rangel.
Neutrophil-to-lymphocyte ratio and lymphocyte-to-C-reactive protein ratio in patients with severe coronavirus disease 2019 (COVID-19): a meta-analysis [published online ahead of print, 2020 Apr 3].
[44]
Y. Yao, J. Cao, Q. Wang, Q. Shi, K. Liu, Z. Luo, et al.
D-dimer as a biomarker for disease severity and mortality in COVID-19 patients: a case control study.
Intensive Care, 8 (2020), pp. 49
[45]
L. Zhang, X. Yan, Q. Fan, H. Liu, X. Liu, Z. Liu, et al.
D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19.
J Thromb Haemost, 18 (2020), pp. 1324-1329
[46]
L. Roncon, M. Zuin, P. Zonzin.
Age-adjusted D-dimer cut-off levels to rule out venous thromboembolism in COVID-19 patients.
Thromb Res, 190 (2020), pp. 102
[47]
E.J. Favaloro, J. Thachil.
Reporting of D-dimer data in COVID-19: some confusion and potential for misinformation.
Clin Chem Lab Med, 58 (2020), pp. 1191-1199
[48]
E. Díaz, R. Amézaga Menéndez, P. Vidal Cortés, M.G. Escapa, B. Suberviola, A. Serrano Lázaro, et al.
Pharmacological treatment of COVID-19: narrative review of the Working Group in Infectious Diseases and Sepsis (GTEIS) and the Working Groups in Transfusions and Blood Products (GTTH).
[49]
P. Rascado Sedes, M.A. Ballesteros Sanz, M.A. Bodí Saera, L.F. Carrasco Rodríguez-Rey, A. Castellanos Ortega, M. Catalán González, et al.
Contingency plan for the intensive care services for the COVID-19 pandemic.
Med Intensiva, (2020),
Copyright © 2021. Elsevier España, S.L.U. y SEMICYUC
Descargar PDF
Idiomas
Medicina Intensiva
Opciones de artículo
Herramientas
Material suplementario
es en

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?