Demographics, management and outcome of females and males with acute respiratory distress syndrome in the LUNG SAFE prospective cohort study
Bibliographic record
Abstract
Rationale We wished to determine the influence of sex on the management and outcomes in acute respiratory distress syndrome (ARDS) patients in the Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE). Methods We assessed the effect of sex on mortality, intensive care unit and hospital length of stay, and duration of invasive mechanical ventilation (IMV) in patients with ARDS who underwent IMV, adjusting for plausible clinical and geographic confounders. Findings Of 2377 patients with ARDS, 905 (38%) were female and 1472 (62%) were male. There were no sex differences in clinician recognition of ARDS or critical illness severity profile. Females received higher tidal volumes (8.2±2.1 versus 7.2±1.6 mL·kg −1 ; p<0.0001) and higher plateau and driving pressures compared with males. Lower tidal volume ventilation was received by 50% of females compared with 74% of males (p<0.0001). In shorter patients (height ≤1.69 m), females were significantly less likely to receive lower tidal volumes. Surviving females had a shorter duration of IMV and reduced length of stay compared with males. Overall hospital mortality was similar in females (40.2%) versus males (40.2%). However, female sex was associated with higher mortality in patients with severe confirmed ARDS (OR for sex (male versus female) 0.35, 95% CI 0.14–0.83). Conclusions Shorter females with ARDS are less likely to receive lower tidal volume ventilation, while females with severe confirmed ARDS have a higher mortality risk. These data highlight the need for better ventilatory management in females to improve their outcomes from 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".