Prognostic factors for development of acute respiratory distress syndrome following traumatic injury: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Our purpose was to summarise the prognostic associations between various clinical risk factors and development of acute respiratory distress syndrome (ARDS) following traumatic injury. METHODS: We conducted this review in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) guidelines. We searched six databases from inception through December 2020. We included English language studies describing the clinical risk factors associated with development of post-traumatic ARDS, as defined by either the American-European Consensus Conference or Berlin definition. We pooled adjusted odds ratios for prognostic factors using the random effects method. We assessed risk of bias using the QUIPS (Quality in Prognosis Studies) tool and certainty of findings using GRADE (Grading of Recommendations Assessment, Development and Evaluation) methodology. RESULTS: We included 39 studies involving 5 350 927 patients. We identified the amount of crystalloid resuscitation as a potentially modifiable prognostic factor associated with development of post-traumatic ARDS (adjusted OR 1.19, 95% CI 1.15-1.24 for each additional litre of crystalloid administered within the first 6 h after injury; high certainty). Non-modifiable prognostic factors with a moderate or high certainty of association with post-traumatic ARDS included increasing age, non-Hispanic White race, blunt mechanism of injury, presence of head injury, pulmonary contusion or rib fracture and increasing chest injury severity. CONCLUSIONS: We identified one important modifiable factor, the amount of crystalloid resuscitation within the first 24 h of injury, and several non-modifiable factors associated with development of post-traumatic ARDS. This information should support the judicious use of crystalloid resuscitation in trauma patients and may inform development of risk stratification tools.
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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 | 0.021 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.037 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".