Extubation Failure in Critically Ill COVID-19 Patients: Risk Factors and Impact on In-Hospital Mortality

Abstract

Purpose: We sought to identify clinical factors that predict extubation failure (reintubation) and its prognostic implications in critically ill COVID-19 patients. Materials and Methods: Retrospective, multi-center cohort study of hospitalized COVID-19 patients. Multivariate competing risk models were employed to explore the rate of reintubation and its determining factors. Results: Two hundred eighty-one extubated patients were included (mean age, 61.0 years [±13.9]; 54.8% male). Reintubation occurred in 93 (33.1%). In multivariate analysis accounting for death, reintubation risk increased with age (hazard ratio [HR] 1.04 per 1-year increase, 95% confidence interval [CI] 1.02 -1.06), vasopressors (HR 1.84, 95% CI 1.04-3.60), renal replacement (HR 2.01, 95% CI 1.22-3.29), maximum PEEP (HR 1.07 per 1-unit increase, 95% CI 1.02 -1.12), paralytics (HR 1.48, 95% CI 1.08-2.25) and requiring more than nasal cannula immediately post-extubation (HR 2.19, 95% CI 1.37-3.50). Reintubation was associated with higher mortality (36.6% vs 2.1%; P < 0.0001) and risk of inpatient death after adjusting for multiple factors (HR 23.2, 95% CI 6.45-83.33). Prone ventilation, corticosteroids, anticoagulation, remdesivir and tocilizumab did not impact the risk of reintubation or death. Conclusions: Up to 1 in 3 critically ill COVID-19 patients required reintubation. Older age, paralytics, high PEEP, need for greater respiratory support following extubation and non-pulmonary organ failure predicted reintubation. Extubation failure strongly predicted adverse outcomes.

Association of vasopressors with mortality in critically ill patients with COVID-19: A systematic review and meta-analysis

“…All the 33 included studies were observational in their design [20-52]. The studies originated from multiple countries, with 13 of coming from institutions located in the USA [20,21,23,32-35,38,42,43,45,48,51].…”

“…All the 33 included studies were observational in their design [20-52]. The studies originated from multiple countries, with 13 of coming from institutions located in the USA [20,21,23,32-35,38,42,43,45,48,51]. Nineteen studies included only patients admitted in the ICU [20,22,24,25,27,30-32,35-39,43-47,52], five studies included patients admitted in a COVID-19-dedicated HDU [28,29,33,34,42], eight studies included patients who were admitted in both HDU and ICU [21,23,26,40,41,48,49,51], and one study included Emergency Department patients who were later admitted either in the HDU of ICU [50].…”

“…Thirty studies included data about patients who received vs . patients who did not receive vasopressors [20-37,39-48,50,52]. Moreover, three studies included patients who received angiotensin-II [38,49,51] and, out of those, two compared the use of angiotensin-II with other vasopressors [49,51] (Appendix C2).…”

Predictors for extubation failure in COVID-19 patients using a machine learning approach

“…However, given the complex interplay of many patient and treatment related characteristics in extubation success, a single parameter rarely provides sufficient accuracy to guide decision making [ 5 ]. Moreover, it remains largely unclear whether these parameters are similar for COVID-19 patients [ 6 ].…”

A Simple Weaning Model Based on Interpretable Machine Learning Algorithm for Patients With Sepsis: A Research of MIMIC-IV and eICU Databases

“…Although the low-level PEEP strategy did not have a significant effect on improving ventilator weaning in a cohort study ( 28 ), it still has the potential to promote ventilator weaning ( 29 ). There is increasing evidence that high levels of PEEP are a risk factor in reducing the likelihood of WS ( 19 , 30 ). As we have considered, high levels of PEEP lead to lung congestion and increase the respiratory burden of patients ( 31 ), which may explain why high levels of PEEP play a positive role in the weaning process ( Figure 5B ).…”