Methods for determining optimal positive end-expiratory pressure in patients undergoing invasive mechanical ventilation: a scoping review

There is significant variability in the application of positive end-expiratory pressure (PEEP) in patients undergoing invasive mechanical ventilation. There are numerous studies assessing methods of determining optimal PEEP, but many methods, patient populations, and study settings lack high-quality evidence. Guidelines make no recommendations about the use of a specific method because of equipoise and lack of high-quality evidence. We conducted a scoping review to determine which methods of determining optimal PEEP have been studied and what gaps exist in the literature.

We searched five databases for primary research reports studying methods of determining optimal PEEP among adults undergoing invasive mechanical ventilation. Data abstracted consisted of the titration method, setting, study design, population, and outcomes.

Two hundred and seventy-one studies with 17,205 patients met the inclusion criteria, including 73 randomized controlled trials (RCTs) with 10,733 patients. We identified 22 methods. Eleven were studied with an RCT. Studies enrolled participants within an intensive care unit (ICU) (216/271, 80%) or operating room (55/271, 20%). Most ICU studies enrolled patients with acute respiratory distress syndrome (162/216, 75%). The three most studied methods were compliance (73 studies, 29 RCTs), imaging-based methods (65 studies, 11 RCTs), and use of PEEP-F_IO₂ tables (52 studies, 20 RCTs). Among ICU RCTs, the most common primary outcomes were mortality or oxygenation. Few RCTs assessed feasibility of different methods (n = 3). The strengths and limitations of each method are discussed.

Numerous methods of determining optimal PEEP have been evaluated; however, notable gaps remain in the evidence supporting their use. These include specific populations (normal lungs, patients weaning from mechanical ventilation) and using alternate outcomes (ventilator-free days and feasibility) and they present significant opportunities for future study.

Open Science Framework (https://osf.io/atzqc); first posted, 19 July 2022.