Practice of diagnosis and management of acute respiratory distress syndrome in mainland China: a cross-sectional study
Bibliographic record
Abstract
Background: Although acute respiratory distress syndrome (ARDS) has been recognized for more than 50 years, limited information exists about the incidence and management of ARDS in mainland China. To evaluate the potential for improvement in management of patients with ARDS, this study was designed to describe the incidence and management of ARDS in mainland China. Methods: National prospective multicenter observational study over one month (August 31st to September 30th, 2012) of all patients who fulfilled the Berlin or American European Consensus Conference (AECC) definition of ARDS in 20 intensive care units, with data collection related to the management of ARDS, patient characteristics and outcomes. Results: Of the 1,814 patients admitted during the enrollment period, 149 (8.2%) and 147 (8.1%) patients were diagnosed by AECC and Berlin definition, respectively. Lung protective strategy with low tidal volume (Vt) (≤8 mL/kg) and limitation of the plateau pressure (Pplat) (≤30 cmH2O) was performed in 75.2% patients. And, 36%, 21.1% and 4.1% patients with severe, moderate and mild ARDS had the driving pressure more than 14 cmH2O (P<0.05). Pplat and driving pressure increased significantly in patients with a higher degree of ARDS severity (P=0.002 and P<0.001, respectively), but Vt were comparable in the three groups (P>0.05). In severe ARDS, patient median positive end expiratory pressure (PEEP) was 10.0 (8.0–11.3) cmH2O and median FiO2 was 90%. A recruitment maneuver was performed in 35.5% of the patients, and 8.7% of patients with severe ARDS received prone position. Overall hospital mortality was 34.0%. Hospital mortality was 21.8% for mild, 31.1% for moderate, and 60.0% for patients with severe ARDS (P=0.004). Conclusions: Despite general acceptance of low Vt and limited Pplat, high driving pressure, low PEEP and low use of adjunctive measures may still be a concern in mainland China, especially in patients with severe ARDS. Trial Registration: ClinicalTrials.gov NCT01666834; date of registration release: August 14th 2012.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".