Back to Search
Start Over
Calibration of the paediatric index of mortality in UK paediatric intensive care units
- Publication Year :
- 2002
-
Abstract
- Aim—To test a paediatric intensive care mortality prediction model for UK use. Method—Prospective collection of data from consecutive admissions to five UK paediatric intensive care units (PICUs), representing a broad cross section of paediatric intensive care activity. A total of 7253 admissions were analysed using tests of the discrimination and calibration of the logistic regression equation. Results—The model discriminated and calibrated well. The area under the ROC plot was 0.84 (95% CI 0.819 to 0.853). The standardised mortality ratio was 0.87 (95% CI 0.81 to 0.94). There was remarkable concordance in the performance of the paediatric index of mortality (PIM) within each PICU,and in the performance of the PICUs as assessed by PIM. Variation in the proportion of admissions that were ventilated or transported from another hospital did not aVect the results. Conclusion—We recommend that UK PICUs use PIM for their routine audit needs. PIM is not aVected by the standard of therapy after admission to PICU, the information needed to calculate PIM is easy to collect, and the model is free. (Arch Dis Child 2001;84:125‐128)
- Subjects :
- Pediatrics
medicine.medical_specialty
Letter
Concordance
Health Status
PIM2
Logistic regression
Intensive Care Units, Pediatric
Severity of Illness Index
law.invention
law
Predictive Value of Tests
hemic and lymphatic diseases
Severity of illness
Infant Mortality
Medicine
Humans
Prospective Studies
Hospital Mortality
Child
Mathematical Computing
business.industry
Infant
Intensive care unit
Infant mortality
United Kingdom
Standardized mortality ratio
ROC Curve
Predictive value of tests
Child, Preschool
Pediatrics, Perinatology and Child Health
Calibration
General and Specialist Paediatrics
Regression Analysis
Risk Adjustment
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....ef8c77b66b16c83acb88205713e8025a