- Pediatrics
-
Clinical implications of discrepancies in predicting pediatric mortality between Pediatric Index of Mortality 3 and Pediatric Logistic Organ Dysfunction-2
-
Eui Jun Lee, Bongjin Lee, You Sun Kim, Yu Hyeon Choi, Young Ho Kwak, June Dong Park
-
Acute Crit Care. 2022;37(3):454-461. Published online July 29, 2022
-
DOI: https://doi.org/10.4266/acc.2021.01480
-
-
 Abstract
 PDF
- Background
Pediatric Index of Mortality 3 (PIM 3) and Pediatric Logistic Organ Dysfunction-2 (PELOD-2) are validated tools for predicting mortality in children. Research suggests that these tools may have different predictive performance depending on patient group characteristics. Therefore, we designed this study to identify the factors that make the mortality rates predicted by the tools different.
Methods
This retrospective study included patients (<18 years) who were admitted to a pediatric intensive care unit from July 2017 to May 2019. After defining the predicted mortality of PIM 3 minus the predicted mortality rate of PELOD-2 as “difference in mortality prediction,” the clinical characteristics significantly related to this were analyzed using multivariable regression analysis. Predictive performance was analyzed through the Hosmer-Lemeshow test and area under the receiver operating characteristic curve (AUROC).
Results
In total, 945 patients (median [interquartile range] age, 3.0 [0.0–8.0] years; girls, 44.7%) were analyzed. The Hosmer-Lemeshow test revealed AUROCs of 0.889 (χ2=10.187, P=0.313) and 0.731 (χ2=6.220, P=0.183) of PIM 3 and PELOD-2, respectively. Multivariable linear regression analysis revealed that oxygen saturation, partial pressure of CO2, base excess, platelet counts, and blood urea nitrogen levels were significant factors. Patient condition-related factors such as cardiac bypass surgery, seizures, cardiomyopathy or myocarditis, necrotizing enterocolitis, cardiac arrest, leukemia or lymphoma after the first induction, bone marrow transplantation, and liver failure were significantly related (P<0.001).
Conclusions
Both tools predicted observed mortality well; however, caution is needed in interpretation as they may show different prediction results in relation to specific clinical characteristics.
|
KSCCM
