Reintubation in the ICU, a non-solved problem. What can a decade of automated data show us?: Reintubación en UCI, un problema sin resolver. ¿Qué nos puede decir una década de datos automatizados?

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.