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Record W1972461520 · doi:10.1542/peds.2004-0586

The Pediatric Risk of Hospital Admission Score: A Second-Generation Severity-of-Illness Score for Pediatric Emergency Patients

2005· article· en· W1972461520 on OpenAlexaff
James M. Chamberlain, Kantilal M. Patel, Murray M. Pollack

Bibliographic record

VenuePEDIATRICS · 2005
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsChildren’s Health Research Institute
FundersAgency for Healthcare Research and Quality
KeywordsMedicineEmergency medicineSeverity of illnessIllness severityHospital admissionPediatricsIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop and validate a second-generation severity-of-illness score that is applicable to pediatric emergency patients. The Pediatric Risk of Admission (PRISA) score was developed in a single hospital and was recalibrated and validated in 2, previous, small studies from academic pediatric hospitals. This study was performed to develop and validate a score in a larger sample of diverse hospitals. METHODS: Emergency departments (EDs) were block randomly selected as part of a study on ED quality on the basis of 3 care characteristics: annual patient volume (high or low compared with national median), presence or absence of a pediatric emergency medicine subspecialist, and presence or absence of residents. Patients were selected randomly on the basis of daily arrival logs. Medical records were photocopied, and abstracted data included demographic, historical, physiologic, and therapeutic information. The total sample was randomly divided into a 75% development sample and a 25% validation sample. Univariate and multivariate analyses were used to model the risk of mandatory admission, admissions for which preidentified, inpatient medical resources were used. The resulting multiple logistic regression model coefficients were converted to integer scores. Calibration (Hosmer-Lemeshow goodness of fit) and discrimination (area under the ROC curve) were used to measure performance. As a measure of construct validity, proportions of patients in ordered risk intervals were correlated with the outcomes of admission, mandatory admission, and ICU admission. RESULTS: Sixteen EDs enrolled 11664 patients. Mean patient age (+/-SD) was 6.8 +/- 5.8 years, and 53% were male. Nine percent arrived by emergency medical services, and 6.9% were admitted. The most common diagnoses were minor injuries, otitis media, and fever. The multivariate analysis yielded a score with 7 historical variables, 8 physiologic variables, 1 therapy (oxygen) term, and 1 interaction term. Calibration was excellent. In the development sample, 442 mandatory admissions were predicted and 442 were observed (total chi2 = 2.275), and in the validation sample, 136.6 were predicted and 145 were observed (chi2 = 8.575). The area under the receiver operator characteristic curve was 0.82 +/- 0.01 (SE) in the development sample and 0.77 +/- 0.02 in the validation sample. In ordered predicted risk intervals, the proportion of patients with admissions, mandatory admissions, and ICU admissions increased in a linear manner. CONCLUSIONS: The second-generation PRISA II score for pediatric ED patients has been developed and validated in a large sample of diverse hospitals. Performance characteristics indicate that PRISA II will be useful for institutional comparisons, benchmarking, and controlling for severity of illness when enrolling patients in clinical trials.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.293
Teacher spread0.259 · 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 teacher head, 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

Citations75
Published2005
Admission routes1
Has abstractyes

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