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Published in: Journal of Clinical Monitoring and Computing 2/2023

06-01-2023 | Review Paper

Individualized positive end-expiratory pressure guided by respiratory mechanics during anesthesia for the prevention of postoperative pulmonary complications: a systematic review and meta-analysis

Authors: Li Zhou, Hongmei Li, Mingjuan Li, Li Liu

Published in: Journal of Clinical Monitoring and Computing | Issue 2/2023

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Abstract

The optimization of positive end-expiratory pressure (PEEP) according to respiratory mechanics [driving pressure or respiratory system compliance (Crs)] is a simple and straightforward strategy. However, its validity to prevent postoperative pulmonary complications (PPCs) remains unclear. Here, we performed a meta-analysis to assess such efficacy. We searched PubMed, Embase, and the Cochrane Library to identify randomized controlled trials (RCTs) that compared personalized PEEP based on respiratory mechanics and constant PEEP to prevent PPCs in adults. The primary outcome was PPCs. Fourteen studies with 1105 patients were included. Compared with those who received constant PEEP, patients who received optimized PEEP exhibited a significant reduction in the incidence of PPCs (RR = 0.54, 95% CI 0.42 to 0.69). The results of commonly happened PPCs (pulmonary infections, hypoxemia, and atelectasis but not pleural effusion) also supported individualized PEEP group. Moreover, the application of PEEP based on respiratory mechanics improved intraoperative respiratory mechanics (driving pressure and Crs) and oxygenation. The PEEP titration method based on respiratory mechanics seems to work positively for lung protection in surgical patients undergoing general anesthesia.
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Literature
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Metadata
Title
Individualized positive end-expiratory pressure guided by respiratory mechanics during anesthesia for the prevention of postoperative pulmonary complications: a systematic review and meta-analysis
Authors
Li Zhou
Hongmei Li
Mingjuan Li
Li Liu
Publication date
06-01-2023
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 2/2023
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-022-00960-9

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