Do ventilatory parameters influence outcome in patients with severe acute respiratory infection? Secondary analysis of an international, multicentre14-day inception cohort study
Bibliographic record
Abstract
To investigate the possible association between ventilatory settings on the first day of invasive mechanical ventilation (IMV) and mortality in patients admitted to the intensive care unit (ICU) with severe acute respiratory infection (SARI).In this pre-planned sub-study of a prospective, multicentre observational study, 441 patients with SARI who received controlled IMV during the ICU stay were included in the analysis.ICU and hospital mortality rates were 23.1 and 28.1%, respectively. In multivariable analysis, tidal volume and respiratory rate on the first day of IMV were not associated with an increased risk of death; however, higher driving pressure (DP: odds ratio (OR) 1.05; 95% confidence interval (CI): 1.01-1.1, p = 0.011), plateau pressure (Pplat) (OR 1.08; 95% CI: 1.04-1.13, p < 0.001) and positive end-expiratory pressure (PEEP) (OR 1.13; 95% CI: 1.03-1.24, p = 0.006) were independently associated with in-hospital mortality. In subgroup analysis, in hypoxemic patients and in patients with acute respiratory distress syndrome (ARDS), higher DP, Pplat, and PEEP were associated with increased risk of in-hospital death.In patients with SARI receiving IMV, higher DP, Pplat and PEEP, and not tidal volume, were associated with a higher risk of in-hospital death, especially in those with hypoxemia or ARDS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".