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Record W2898345156 · doi:10.1097/pcc.0000000000001764

Performance of Pediatric Mortality Prediction Scores for PICU Mortality and 90-Day Mortality*

2018· article· en· W2898345156 on OpenAlexaboutno aff
An Jacobs, Marine Flechet, Ilse Vanhorebeek, Sören Verstraete, Catherine Ingels, Michaël P. Casaer, Gerardo Soto‐Campos, Sascha Verbruggen, Koen Joosten, Fabián Güiza, Greet Van den Berghe

Bibliographic record

VenuePediatric Critical Care Medicine · 2018
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineReceiver operating characteristicPediatric intensive care unitRisk of mortalityPediatricsMortality rateConfidence intervalEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The use of mortality prediction scores in clinical trials in the PICU is essential for comparing patient groups. Because of the decline in PICU mortality over the last decades, leading to a shift toward later deaths, recent trials use 90-day mortality as primary outcome for estimating mortality and survival more accurately. This study assessed and compared the performance of two frequently used PICU mortality prediction scores for prediction of PICU and 90-day mortality. DESIGN: This secondary analysis of the randomized controlled Early versus Late Parenteral Nutrition in the Pediatric Intensive Care Unit trial compared the discrimination (area under the receiver operating characteristic curve) and calibration of the Pediatric Index of Mortality 3 and the Pediatric Risk of Mortality III scores for prediction of PICU and 90-day mortality. SETTING: Three participating PICUs within academic hospitals in Belgium, the Netherlands, and Canada. PATIENTS: One-thousand four-hundred twenty-eight critically ill patients 0-17 years old. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Although Pediatric Index of Mortality 3 only includes information available at the time of PICU admission, thus before any intervention in the PICU, it showed good discrimination (area under the receiver operating characteristic curve, 0.894; 95% CI, 0.892-0.896) and good calibration (no deviation from the diagonal, p = 0.58) for PICU mortality. Pediatric Risk of Mortality III, which involves the worst values for the evaluated variables during the first 24 hours of PICU stay, was statistically more discriminant (area under the receiver operating characteristic curve, 0.920; 95% CI, 0.918-0.921; p = 0.04) but poor in calibration (significant deviation from the diagonal; p = 0.04). Pediatric Index of Mortality 3 and Pediatric Risk of Mortality III discriminated equally well between 90-day mortality and survival (area under the receiver operating characteristic curve, 0.867; 95% CI, 0.866-0.869 and area under the receiver operating characteristic curve, 0.882; 95% CI, 0.880-0.884, respectively, p = 0.77), but Pediatric Risk of Mortality III was not well calibrated (p = 0.04), unlike Pediatric Index of Mortality 3 (p = 0.34). CONCLUSIONS: Pediatric Index of Mortality 3 performed better in calibration for predicting PICU and 90-day mortality than Pediatric Risk of Mortality III and is not influenced by intervention or PICU quality of care. Therefore, Pediatric Index of Mortality 3 seems a better choice for use in clinical trials with 90-day mortality as primary outcome.

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)0.033
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 score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.064
GPT teacher head0.390
Teacher spread0.326 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

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