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Original article
Available online 29 September 2026

Reintubation in the ICU, a non-solved problem. What can a decade of automated data show us?

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Sara Manriquea,b,c,1, Pau Ortsa,b,c,1, Gonzalo Sirgoa,b,c, Laura Péreza, Julen Berruetaa,b,c, Alejandro García-Martíneza,c, María Bodía,b,c,d,
Corresponding author
mbodi.hj23.ics@gencat.cat

Corresponding author.
a Unidad de Cuidados Intensivos, Hospital Universitario de Tarragona Joan XXIII, Tarragona, Spain
b Universitat Rovira I Virgili, Tarragona, Spain
c Institut de Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, Tarragona, Spain
d Centro de Investigación Biomédica Red Enfermedades Respiratorias (CIBERES), Tarragona, Spain
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Abstract
Objective

To identify risk factors for reintubation in critically ill patients after planned extubation using clinical data automatically extracted from the clinical information system.

Design

A retrospective observational study was conducted.

Setting

Intensive Care Unit (ICU) of Joan XXIII University Hospital (Tarragona, Spain) (2014–2024).

Patients

Adult patients admitted to the ICU who required invasive mechanical ventilation (IMV) for more than 48 h.

Interventions

Automated extraction of clinical, ventilatory, hemodynamic, and laboratory test data (Centricity Critical Care®). Median, maximum, and minimum values were calculated within predefined time windows of 6 and 24 h prior to extubation.

Main variables of interest

Reintubation rate, pressure support (PS), heart rate (HR), prior administration of antibiotics, ICU stay, incidence of ventilator-associated pneumonia (VAP), and mortality.

Results

The overall reintubation rate was 11%. Multivariate analysis showed that higher mean PS (OR: 1.36; 95%CI: 1.10–1.67) and higher HR (OR: 1.22; 95%CI: 1.00–1.49) in the previous 6 h were independent predictors of reintubation. Antibiotic administration in the previous 24 h showed a protective effect (OR: 0.55; 95%CI: 0.37−0.82). The model achieved an AUC of 0.63 (95%CI, bootstrap: 0.52−0.72). Reintubated patients had a longer ICU stay, a higher incidence of VAP, and greater mortality.

Conclusions

Higher heart rate and pressure support values before extubation were associated with an increased risk of reintubation, whereas antibiotic therapy within 24 h before extubation appeared to have a protective effect. The automated analysis of longitudinal data obtained from electronic health records allowed the identification of clinically plausible associations related to reintubation.

Keywords:
Reintubation
Intensive care unit
Mechanical ventilation
Clinical information systems
Data quality
Predictive modeling
Clinical decision support
Automated data extraction
Applied informatics in intensive care
Resumen
Objetivo

Identificar factores de riesgo de reintubación en pacientes críticos tras una extubación planificada, utilizando datos clínicos extraídos automáticamente del sistema de información clínica.

Diseño

Estudio observacional retrospectivo.

Ámbito

Unidad de Cuidados Intensivos del Hospital Universitario Joan XXIII (2014–2024).

Pacientes

Adultos ingresados en la UCI que requirieron ventilación mecánica invasiva (VMI) durante más de 48 horas.

Intervenciones

Extracción automatizada de datos (Centricity Critical Care®). Se calcularon medianas, máximos o mínimos en ventanas predefinidas de 6 y 24 horas previas a la extubación.

Variables de interés principales

Tasa de reintubación, presión de soporte (PS), frecuencia cardíaca (FC), administración previa de antibióticos, estancia en la UCI, incidencia de neumonía asociada a ventilación (NAV) y mortalidad.

Resultados

La tasa global de reintubación fue del 11%. Mediante análisis multivariante, una PS más alta (OR: 1,36; IC 95%: 1,10−1,67) y una mayor FC (OR: 1,22; IC 95%: 1,00–1,49) en las 6 horas previas predijeron de forma independiente la reintubación. Administrar antibióticos en las 24 horas anteriores mostró un efecto protector (OR: 0,55; IC 95%: 0,37−0,82). El modelo alcanzó un AUC de 0,63 (IC bootstrap al 95%: 0,52−0,72). Los pacientes reintubados presentaron mayor estancia en la UCI, mayor incidencia de NAV y mayor mortalidad.

Conclusiones

Valores más elevados de FC y PS previos a la extubación se asociaron con un mayor riesgo de reintubación, mientras que la antibioterapia de las 24 horas previas parece tener un efecto protector. El análisis automatizado de datos longitudinales provenientes de registros electrónicos permitió identificar asociaciones clínicamente plausibles relacionadas con la reintubación.

Palabras clave:
Reintubación
Unidad de cuidados intensivos
Ventilación mecánica
Sistemas de información clínica
Calidad de los datos
Modelización predictiva
Apoyo a la toma de decisiones clínicas
Extracción automatizada de datos
Informática aplicada a los cuidados intensivos

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