Chest radiographs in acute respiratory distress syndrome: an Achilles' heel of the Berlin criteria?
Bibliographic record
Abstract
Background: Despite the high mortality and economic burden associated with the acute respiratory distress syndrome (ARDS), the role of chest radiograph (CXR) in ARDS diagnosis and prognosis remains uncertain. The purpose of this study is to elucidate clinical characteristics that distinguish ARDS patients from those without ARDS, especially in patients where CXRs are indicative of ARDS. Methods: Secondary analysis of a prospective observational study with 454 postoperative septic patients under mechanical ventilation (MV). Patients were stratified in two groups depending on whether they met the Berlin criteria for ARDS. Primary outcome was identification of clinical characteristics differentiating patients with ARDS confirmed by CXR from non-ARDS patients. Secondary outcome was 60-day in-hospital mortality of postoperative sepsis-induced ARDS. Results: One hundred thirty-nine patients (30.6%) had CXRs compatible with ARDS, although ARDS was confirmed in only 45 patients (9.9%). Emergency surgery (OR 6.6), abdominal source of infection (OR 6.0), pneumonia (OR 8.2), and higher lactate (OR 3.9) were clinical features associated with ARDS development confirmed by CXR. ARDS was an independent risk factor for 60-day mortality (OR 1.8). Conclusion: Although CXR criteria for ARDS diagnosis could be replaced in future definitions, its importance for ARDS diagnosis should not be underestimated.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".