Performance effectiveness of pediatric index of mortality 2 (PIM2) and pediatricrisk of mortality III (PRISM III) in pediatric patients with intensive care in single institution: Retrospective study.
10.3345/kjp.2008.51.11.1158
- Author:
Hui Seung HWANG
1
;
Na Young LEE
;
Seung Beom HAN
;
Ga Young KWAK
;
Soo Young LEE
;
Seung Yun CHUNG
;
Jin Han KANG
;
Dae Chul JEONG
Author Information
1. Department of Pediatrics, College of Medicine, The Catholic University of Korea. dcjeong@catholic.ac.kr
- Publication Type:Original Article
- Keywords:
Mortality;
Pediatric;
Intensive care unit
- MeSH:
Blood Gas Analysis;
Child;
Discrimination (Psychology);
Humans;
Critical Care;
Intensive Care Units;
Logistic Models;
Medical Records;
Retrospective Studies;
ROC Curve;
Survivors
- From:Korean Journal of Pediatrics
2008;51(11):1158-1164
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: To investigate the discriminative ability of pediatric index of mortality 2 (PIM2 ) and pediatric risk of mortality III (PRISM III) in predicting mortality in children admitted into the intensive care unit (ICU). METHODS: We retrospectively analyzed variables of PIM2 and PRISM III based on medical records with children cared for in a single hospital ICU from January 2003 to December 2007. Exclusions were children who died within 2 h of admission into ICU or hopeless discharge. We used Students t test and ANOVA for general characteristics and for correlation between survivors and non-survivors for variables of PIM2 and PRISM III. In addition, we performed multiple logistic regression analysis for Hosmer-Lemeshow goodness-of-fit, receiver operating characteristic curve (ROC) for discrimination, and calculated standardized mortality ratio (SMR) for estimation of prediction. RESULTS: We collected 193 medical records but analyzed 190 events because three children died within 2 h of ICU admission. The variables of PIM2 correlated with survival, except for the presence of post-procedure and low risk. In PRISM III, there was a significant correlation for cardiovascular/neurologic signs, arterial blood gas analysis but not for biochemical and hematologic data. Discriminatory performance by ROC showed an area under the curve 0.858 (95% confidence interval; 0.779-0.938) for PIM2, 0.798 (95% CI; 0.686-0.891) for PRISM III, respectively. Further, SMR was calculated approximately as 1 for the 2 systems, and multiple logistic regression analysis showed chi-square(13)=14.986, P=0.308 for PIM2, chi-square(13)=12.899, P=0.456 for PRISM III in Hosmer-Lemeshow goodness-of-fit. However, PIM2 was significant for PRISM III in the likelihood ratio test chi-square(4)=55.3, P<0.01). CONCLUSION: We identified two acceptable scoring systems (PRISM III, PIM2 ) for the prediction of mortality in children admitted into the ICU. PIM2 was more accurate and had a better fit than PRISM III on the model tested.
