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Available online 20 January 2025
The value of local validation of a predictive model. A nomogram for predicting failure of non-invasive ventilation in patients with SARS-COV-2 pneumonia
El valor de la validación local de un modelo predictivo. Nomograma para la predicción del fracaso de ventilación no invasiva en pacientes con neumonía por SARS-COV-2
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Héctor Hernández Garcésa,
Corresponding author
hektorhernandez84@gmail.com

Corresponding author.
, Alberto Belenguer Muncharaza, Francisco Bernal Juliánb, Irina Hermosilla Semikinab, Luis Tormo Rodríguezb, Estefanía Granero Gasamansb, Clara Viana Marcob, Rafael Zaragoza Crespoa
a Intensive Care Unit, Hospital Universitario Doctor Peset, Av Gaspar Aguilar 90, 46017 Valencia, Spain
b Intensive Care Unit, Hospital General Universitario de Castellón, Av Benicassim 128, Castellón, Spain
This item has received
Received 17 September 2024. Accepted 10 November 2024
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Tables (3)
Table 1. Chracteristics of patients with successful or failed NIV and group differences.
Table 2. Vital signs, arterial blood gas parameters, treatment variables at baseline and 24 h after NIV initiation, and main variables in patients with successful or failed NIV in both cohorts.
Table 3. AUC for variables model in the training and validation model.
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Abstract
Objective

We aimed to determine predictors of non-invasive ventilation (NIV) failure and validate a nomogram to identify patients at risk of NIV failure.

Design

Observational, analytical study of a retrospective cohort from a single center, compared with an external cohort (March 2020 to August 2021).

Setting

Two intensive care units (ICUs).

Patients

Patients with pneumonia due to severe acute respiratory syndrome (SARS-CoV-2) and NIV > 24 h (154 and 229 in each cohort).

Interventions

The training cohort identified NIV failure predictors. A nomogram, created via logistic regression, underwent validation with the Hosmer-Lemeshow (HL), calibration curve and test and area under the curve (AUC). Its external validity was tested using AUC.

Main variables of interest

Demographics, comorbidities, severity scores, NIV settings, vital signs, blood gases, and oxygenation at the start and 24 h after NIV, NIV failure.

Results

NIV failure was 37.6% and 18% in the training and validation cohorts, respectively. Risk factors for NIV failure inluded age, obesity, sequential organ failure assessment (SOFA) score at admission, and heart rate (HR) and heart rate, acidosis, consciousness, oxygenation, respiratory rate (HACOR) 24 h post-NIV. The model's HL test result was 0.861, with an AUC of 0.89 (confidence interval [CI] 0.839–0.942); validation AUC was 0.547 (CI 0.449–0.645).

Conclusions

A predictive model using age, obesity, SOFA score, HR, and HACOR at 24 h predicts NIV failure in our COVID-19 patients but may not apply to other ICUs.

Keywords:
Acute respiratory failure
ARDS
COVID-19
Orotracheal intubation
Resumen
Objetivo

Determinar los predictores de fracaso de ventilación no invasiva (VNI) y validar un nomograma para identificar el riesgo de fracaso de VNI.

Diseño

Estudio observacional, analítico de una cohorte retrospectiva de un centro, comparada con una cohorte externa (marzo 2020 a agosto 2021).

Ámbito

Dos unidades de cuidados intensivos (UCI).

Pacientes

Pacientes con neumonía por síndrome respiratorio agudo grave (SARS-COV-2) y VNI>24 h (154 y 229 en cada cohorte).

Intervenciones

Regresión logística para la detección de factores de riesgo de fracaso de VNI en una cohorte de entrenamiento, y elaboración de nomograma para identificar el riesgo de fracaso de VNI. Validación mediante el test de Hosmer-Lemeshow (HL), curva de calibración y área bajo la curva (AUC). Validación externa mediante el AUC.

Variables de interés principales

Demográficas, comorbilidades, scores de severidad, configuración de VNI, constantes vitales, gasométricas y oxigenación al inicio 24 h de VNI, fracaso de VNI.

Resultados

El fracaso de VNI fue del 37,6% y 18% en la cohorte de entrenamiento y validación respectivamente. Los factores relacionados con el fracaso de VNI fueron edad, obesidad, seguential organ failure assessment (SOFA) al ingreso y, frecuencia cardiaca (FC) y acidosis, consciencia, oxigenación y frecuencia respiratoria (HACOR) 24 h post-VNI. El test HL del modelo resultó de 0.861, con AUC 0.89 (intervalo confianza [IC] 0.839−0.942). AUC de validación externa 0.547 (CI 0.449−0.645)

Conclusiones

Un modelo predictivo utilizando edad, obesidad, SOFA score y, FC y HACOR a las 24 h predice el fallo de VNI en nuestros pacientes con COVID-19, pero podría no aplicarse a otras UCIs.

Palabras clave:
Fracaso respiratorio agudo
SDRA
COVID-19
Intubación orotraqueal

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