Measurement properties of RDAI and RACS and their suitability as outcome measures in bronchiolitis trials
Bibliographic record
Abstract
The Respiratory Distress Assessment Instrument (RDAI) and Respiratory Assessment Change Score (RACS) are frequently used in bronchiolitis clinical trials, but evidence is scarce on their suitability as outcome measures.We investigated their reliability,validity,and responsiveness. We used data from two bronchiolitis studies conducted in 8 Canadian pediatric emergency departments (ED).We assessed RDAI test-retest agreement and inter-rater reliability using limits of agreement (LoA) and Intraclass Correlation Coefficients (ICC).RDAI construct validity was evaluated by testing hypotheses on its scores association with respiratory rate,SatO2,and hospitalization, using correlation coefficients and multivariable analysis.We assessed RDAI/RACS responsiveness using anchors of change based on these constructs and measures such as the area under the curve (AUC). 1765 participants were included. RDAI test-retest LoA were -3.80 - 3.64 (20% of the range of the scale),inter-rater ICC was 0.93.Correlation of baseline RDAI scores with respiratory rate was 0.38, p<0.001. RDAI scores increased in lower SatO2 categories (p<0.001).Higher RDAI scores were associated with hospitalization (OR 1.36 [95% CI 1.26-1.47]);scores differed between participants discharged,admitted,or staying in the ED (p<0.001).Formulated hypotheses for responsiveness were confirmed,with moderate responsiveness (RDAI:AUC 0.64 to 0.70; RACS:AUC 0.72). RDAI has good discriminative properties, but its considerable test-retest measurement error limits its use as a trial outcome measure.RDAI and RACS are fairly valid and responsive measures of acute respiratory distress, but don′t encompass all elements of bronchiolitis severity.
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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 | 0.573 | 0.604 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".