Predictors of weaning failure in ventilated intensive care patients: a systematic evidence map

Abstract

Ventilator weaning is of great importance for intensive care patients in order to avoid complications caused by prolonged ventilation. However, not all patients succeed in weaning immediately. Their spontaneous breathing may be insufficient, resulting in extubation failure and the subsequent need for reintubation. To identify patients at high risk for weaning failure, a variety of potential predictors has already been examined in individual studies and meta-analyses over the last decades. However, an overview of all the predictors investigated is missing. To provide an overview of empirically investigated predictors for weaning failure. A systematic evidence map was developed. To this end, we conducted a systematic search in the Medline, Cochrane, and CINAHL databases in December 2023 and added a citation search and a manual search in June 2024. Studies on predictors for weaning failure in adults ventilated in the intensive care unit were included. Studies on children, outpatients, non-invasive ventilation, or explanatory factors of weaning failure were excluded. Two reviewers performed the screening and data extraction independently. Data synthesis followed an inductive approach in which the predictors were thematically analyzed, sorted, and clustered. Of the 1388 records obtained, 140 studies were included in the analysis. The 112 prospective and 28 retrospective studies investigated a total of 145 predictors. These were assigned to the four central clusters ‘Imaging procedures’ (n = 22), ‘Physiological parameters’ (n = 61), ‘Scores and indices’ (n = 53), and ‘Machine learning models’ (n = 9). The most frequently investigated predictors are the rapid shallow breathing index, the diaphragm thickening fraction, the respiratory rate, the P/F ratio, and the diaphragm excursion. Predictors for weaning failure are widely researched. To date, 145 predictors have been investigated with varying intensity in 140 studies that are in line with the current weaning definition. It is no longer just individual predictors that are investigated, but more comprehensive assessments, indices and machine learning models in the last decade. Future research should be conducted in line with international weaning definitions and further investigate poorly researched predictors. Registration, Protocol: https://doi.org/10.17605/OSF.IO/2KDYU