External Validation of Brief Resolved Unexplained Events Prediction Rules for Serious Underlying Diagnosis
Bibliographic record
Abstract
Importance: The American Academy of Pediatrics (AAP) higher-risk criteria for brief resolved unexplained events (BRUE) have a low positive predictive value (4.8%) and misclassify most infants as higher risk (>90%). New BRUE prediction rules from a US cohort of 3283 infants showed improved discrimination; however, these rules have not been validated in an external cohort. Objective: To externally validate new BRUE prediction rules and compare them with the AAP higher-risk criteria. Design, Setting, and Participants: This was a retrospective multicenter cohort study conducted from 2017 to 2021 and monitored for 90 days after index presentation. The setting included infants younger than 1 year with a BRUE identified through retrospective chart review from 11 Canadian hospitals. Study data were analyzed from March 2022 to March 2024. Exposures: The BRUE prediction rules. Main Outcome and Measure: The primary outcome was a serious underlying diagnosis, defined as conditions where a delay in diagnosis could lead to increased morbidity or mortality. Results: Of 1042 patients (median [IQR] age, 41 [13-84] days; 529 female [50.8%]), 977 (93.8%) were classified as higher risk by the AAP criteria. A total of 79 patients (7.6%) had a serious underlying diagnosis. For this outcome, the AAP criteria demonstrated a sensitivity of 100.0% (95% CI, 95.4%-100.0%), a specificity of 6.7% (95% CI, 5.2%-8.5%), a positive likelihood ratio (LR+) of 1.07 (95% CI, 1.05-1.09), and an AUC of 0.53 (95% CI, 0.53-0.54). The BRUE prediction rule for discerning serious diagnoses displayed an AUC of 0.60 (95% CI, 0.54-0.67; calibration intercept: 0.60), which improved to an AUC of 0.71 (95% CI, 0.65-0.76; P < .001; calibration intercept: 0.00) after model revision. Event recurrence was noted in 163 patients (15.6%). For this outcome, the AAP criteria yielded a sensitivity of 99.4% (95% CI, 96.6%-100.0%), a specificity of 7.3% (95% CI, 5.7%-9.2%), an LR+ of 1.07 (95% CI, 1.05-1.10), and an AUC of 0.58 (95% CI, 0.56-0.58). The AUC of the prediction rule stood at 0.67 (95% CI, 0.62-0.72; calibration intercept: 0.15). Conclusions and Relevance: Results of this multicenter cohort study show that the BRUE prediction rules outperformed the AAP higher-risk criteria on external geographical validation, and performance improved after recalibration. These rules provide clinicians and families with a more precise tool to support decision-making, grounded in individual risk tolerance.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".