Timing of Low Tidal Volume Ventilation and Intensive Care Unit Mortality in Acute Respiratory Distress Syndrome. A Prospective Cohort Study
Bibliographic record
Abstract
RATIONALE: Reducing tidal volume decreases mortality in acute respiratory distress syndrome (ARDS). However, the effect of the timing of low tidal volume ventilation is not well understood. OBJECTIVES: To evaluate the association of intensive care unit (ICU) mortality with initial tidal volume and with tidal volume change over time. METHODS: Multivariable, time-varying Cox regression analysis of a multisite, prospective study of 482 patients with ARDS with 11,558 twice-daily tidal volume assessments (evaluated in milliliter per kilogram of predicted body weight [PBW]) and daily assessment of other mortality predictors. MEASUREMENTS AND MAIN RESULTS: An increase of 1 ml/kg PBW in initial tidal volume was associated with a 23% increase in ICU mortality risk (adjusted hazard ratio, 1.23; 95% confidence interval [CI], 1.06-1.44; P = 0.008). Moreover, a 1 ml/kg PBW increase in subsequent tidal volumes compared with the initial tidal volume was associated with a 15% increase in mortality risk (adjusted hazard ratio, 1.15; 95% CI, 1.02-1.29; P = 0.019). Compared with a prototypical patient receiving 8 days with a tidal volume of 6 ml/kg PBW, the absolute increase in ICU mortality (95% CI) of receiving 10 and 8 ml/kg PBW, respectively, across all 8 days was 7.2% (3.0-13.0%) and 2.7% (1.2-4.6%). In scenarios with variation in tidal volume over the 8-day period, mortality was higher when a larger volume was used earlier. CONCLUSIONS: Higher tidal volumes shortly after ARDS onset were associated with a greater risk of ICU mortality compared with subsequent tidal volumes. Timely recognition of ARDS and adherence to low tidal volume ventilation is important for reducing mortality. Clinical trial registered with www.clinicaltrials.gov (NCT 00300248).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".