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Record W2945803548 · doi:10.1213/ane.0000000000004197

Prospective External Validation of the Pediatric Risk Assessment Score in Predicting Perioperative Mortality in Children Undergoing Noncardiac Surgery

2019· article· en· W2945803548 on OpenAlexaff
Eleonore Valencia, Steven J. Staffa, David Faraoni, James A. DiNardo, Viviane G. Nasr

Bibliographic record

VenueAnesthesia & Analgesia · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineReceiver operating characteristicPerioperativeYouden's J statisticConfidence intervalRisk assessmentCohortFramingham Risk ScoreArea under the curveRisk of mortalityProspective cohort studyInternal medicineSurgery

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.261
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2019
Admission routes1
Has abstractyes

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