Protective intraoperative ventilation with higher versus lower levels of positive end-expiratory pressure in obese patients (PROBESE): study protocol for a randomized controlled trial
Bibliographic record
Abstract
Postoperative pulmonary complications (PPCs) increase the morbidity and mortality of surgery in obese patients. High levels of positive end-expiratory pressure (PEEP) with lung recruitment maneuvers may improve intraoperative respiratory function, but they can also compromise hemodynamics, and the effects on PPCs are uncertain. We hypothesized that intraoperative mechanical ventilation using high PEEP with periodic recruitment maneuvers, as compared with low PEEP without recruitment maneuvers, prevents PPCs in obese patients. The PRotective Ventilation with Higher versus Lower PEEP during General Anesthesia for Surgery in OBESE Patients (PROBESE) study is a multicenter, two-arm, international randomized controlled trial. In total, 2013 obese patients with body mass index ≥35 kg/m 2 scheduled for at least 2 h of surgery under general anesthesia and at intermediate to high risk for PPCs will be included. Patients are ventilated intraoperatively with a low tidal volume of 7 ml/kg (predicted body weight) and randomly assigned to PEEP of 12 cmH 2 O with lung recruitment maneuvers (high PEEP) or PEEP of 4 cmH 2 O without recruitment maneuvers (low PEEP). The occurrence of PPCs will be recorded as collapsed composite of single adverse pulmonary events and represents the primary endpoint. To our knowledge, the PROBESE trial is the first multicenter, international randomized controlled trial to compare the effects of two different levels of intraoperative PEEP during protective low tidal volume ventilation on PPCs in obese patients. The results of the PROBESE trial will support anesthesiologists in their decision to choose a certain PEEP level during general anesthesia for surgery in obese patients in an attempt to prevent PPCs. ClinicalTrials.gov identifier: NCT02148692. Registered on 23 May 2014; last updated 7 June 2016.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".