Hospital Incidence and Outcomes of the Acute Respiratory Distress Syndrome Using the Kigali Modification of the Berlin Definition
Bibliographic record
Abstract
RATIONALE: Estimates of the incidence of the acute respiratory distress syndrome (ARDS) in high- and middle-income countries vary from 10.1 to 86.2 per 100,000 person-years in the general population. The epidemiology of ARDS has not been reported for a low-income country at the level of the population, hospital, or intensive care unit (ICU). The Berlin definition may not allow identification of ARDS in resource-constrained settings. OBJECTIVES: To estimate the incidence and outcomes of ARDS at a Rwandan referral hospital using the Kigali modification of the Berlin definition: without requirement for positive end-expiratory pressure, hypoxia cutoff of SpO2/FiO2 less than or equal to 315, and bilateral opacities on lung ultrasound or chest radiograph. METHODS: We screened every adult patient for hypoxia at a public referral hospital in Rwanda for 6 weeks. For every patient with hypoxia, we collected data on demographics and ARDS risk factors, performed lung ultrasonography, and evaluated chest radiography when available. MEASUREMENTS AND MAIN RESULTS: Forty-two (4.0%) of 1,046 hospital admissions met criteria for ARDS. Using various prespecified cutoffs for the SpO2/FiO2 ratio resulted in almost identical hospital incidence values. Median age for patients with ARDS was 37 years, and infection was the most common risk factor (44.1%). Only 30.9% of patients with ARDS were admitted to an ICU, and hospital mortality was 50.0%. Using traditional Berlin criteria, no patients would have met criteria for ARDS. CONCLUSIONS: ARDS seems to be a common and fatal syndrome in a hospital in Rwanda, with few patients admitted to an ICU. The Berlin definition is likely to underestimate the impact of ARDS in low-income countries, where resources to meet the definition requirements are lacking. Although the Kigali modification requires validation before widespread use, we hope this study stimulates further work in refining an ARDS definition that can be consistently used in all settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".