The Pediatric Risk of Hospital Admission Score: A Second-Generation Severity-of-Illness Score for Pediatric Emergency Patients
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».