Agreement between Alternative Classifications of Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
To examine the agreement between two classifications of acute respiratory distress syndrome (ARDS) that are used interchangeably in clinical practice and clinical research, we classified 118 patients taking part in a randomized trial with respect to the presence of ARDS using the North American-European Consensus Committee (NAECC) and the Lung Injury Severity Score (LISS) criteria. The incidence of ARDS using NAECC criteria was 55.1% (95% confidence interval, 46.1% to 64.1%), and using the LISS criteria 61.9% (95% confidence interval, 53.1% to 70.6%). The p value on the difference between these proportions was 0.07. Raw agreement, chance-corrected agreement (kappa), and chance-independent agreement (phi) on the study occurrence of ARDS using the two classifications were, respectively, 0.73 (95% CI, 0.65 to 0.81), 0.46 (95% CI, 0.32 to 0.61), and 0.63 (95% CI, 0.41 to 0.79). No single component of either index contributed to disagreement to an appreciably greater extent than other components. Baseline characteristics and outcomes were similar among patients who developed ARDS according to either classification. We conclude that NAECC and LISS classifications resulted in similar estimates of the incidence of ARDS in this clinical trial, though patients were frequently classified as having ARDS with only one model. These discordant classifications had no prognostic importance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.002 |
| 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".