Prospective External Validation of the Pediatric Risk Assessment Score in Predicting Perioperative Mortality in Children Undergoing Noncardiac Surgery
Bibliographic record
Abstract
BACKGROUND: Early identification of children at high risk for perioperative mortality could lead to improved outcomes; however, there is a lack of well-validated risk prediction tools. The Pediatric Risk Assessment (PRAm) score is a new model to prognosticate perioperative risk of mortality in pediatric patients undergoing noncardiac surgery. It was derived from the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) Pediatric database. In this study, we aimed to externally validate the PRAm score at 1 large institution. METHODS: A PRAm score was prospectively assigned by the primary anesthesia team to children ≤18 years of age undergoing noncardiac surgery between July 2017 and July 2018 at a tertiary care pediatric hospital. The primary outcome was the PRAm score's ability to predict 30-day mortality. The area under the receiver operating characteristic (ROC) curve was utilized to determine discriminative ability. Sensitivity and specificity at varying cutoffs were considered. Youden J index and the gray zone approach were applied to determine the optimal PRAm cutoff for predicting 30-day mortality. RESULTS: Among the 13,530 cases included in the external validation cohort, the incidence of 30-day mortality was 0.21% (29/13,530). The PRAm score was found to predict 30-day mortality with an area under the curve (AUC) of 0.956 (95% confidence interval [CI], 0.938-0.974; P < .001). Youden J index determined the optimal PRAm score threshold to be ≥5 with a sensitivity of 86% and a specificity of 91%. The gray zone identified an inconclusive risk of mortality in 6.93% (938/13,530) of patients who had PRAm scores of 4 or 5 (sensitivity or specificity <90%, respectively), therefore refining the optimal cutoff point to be a PRAm score of ≥6. The incidence of mortality for patients with an American Society of Anesthesiologists Physical Status (ASA PS) ≤3 (0.06%, 8/13,530) increased 8-fold for those with an ASA PS of ≤3 and a PRAm score of ≥6. CONCLUSIONS: The PRAm score is a simple and objective tool that has excellent ability to predict perioperative risk of mortality in pediatric patients undergoing noncardiac surgery and can be easily used by clinicians. The application of the PRAm score could have important implications on the safety and quality of care delivered to infants and children and on the resource utilization in the pediatric health care system.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".