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Pediatr Crit Care Med. 2006 Jul;7(4):356-61.

Performance of Pediatric Risk of Mortality (PRISM), Pediatric Index of Mortality (PIM), and PIM2 in a pediatric intensive care unit in a developing country.

Author information

1
Department of Pediatrics, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India.

Abstract

OBJECTIVE:

To determine the discriminative ability and calibration of existing scoring systems in predicting the outcome (mortality) in children admitted to an Indian pediatric intensive care unit (PICU).

DESIGN:

Prospective cohort study.

SETTING:

Pediatric Intensive Care Unit, Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, from July 1, 2002, to July 31, 2003.

PATIENTS:

A total of 246 patients were admitted. After exclusion of 29 neonates and two patients who stayed in the PICU for <or=2 hrs, 215 patients were enrolled in the study. Of these 215 patients, 139 patients survived at the end of the PICU stay.

INTERVENTIONS:

None.

MEASUREMENTS AND MAIN RESULTS:

Discrimination between death and survival was assessed by calculating the area under the receiver operating characteristic curve for each model. The areas under the curve (95% confidence intervals) for Pediatric Risk of Mortality (PRISM), Pediatric Index of Mortality (PIM), and PIM2 were 0.80 (0.74-0.86), 0.82 (0.76-0.88), and 0.81 (0.75-0.87), respectively. The area under the receiver operating characteristic curves was significantly greater for older children compared with infants. The existing scores underpredicted the mortality; the standardized mortality ratios (SMRs) (95% confidence interval) using PRISM, PIM, and PIM2 models were 1.20 (0.94-1.50), 1.57 (1.24-1.96), and 1.57 (1.24-1.59), respectively. The SMRs were higher in children with severe malnutrition, those with underlying illness, and those with serum albumin <or=2.5 g/dL.

CONCLUSIONS:

The area under the receiver operating characteristic curve for all the models evaluated was >0.8. However, all the models underpredicted mortality. The likely reasons for this could be differences in the patient profile and greater load of severity of illness being managed with lesser resources--both physical and human--and differences in the quality of care.

[Indexed for MEDLINE]

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