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[Standardized mortality with PIM2 score in a pediatric intensive care unit in Morelos, Mexico]
Mario Morales-García, Jorge Luis Mata-Martínez, David González-Flores
1Universidad Autónoma del Estado de Morelos, Facultad de Medicina, Unidad de Investigación Clínica y Epidemiológica. Cuernavaca, Morelos, México.
Insights
Pediatric intensive care unit (PICU) mortality in Mexico was evaluated using the PIM2 score. Observed deaths aligned with PIM2 predictions, indicating the score
Area of Science:
- Pediatric Critical Care Medicine
- Epidemiology
- Health Services Research
Background:
Mortality in pediatric intensive care units (PICUs) is elevated, with limited information generated from Mexico.
Objective:
To identify the standardized mortality (SM) at the Hospital del Niño Morelense's (HNM) (Child from Morelos' Hospital) PICU.
Material And Methods:
Electronic records of seriously ill patients admitted at the HNM's PICU during 2014 (n = 130) were used. SM was calculated using the observed mortality and the probability of death by PIM2. The area under the ROC curve (AUC) was used to identify the discriminatory capacity of PIM2, and the Hosmer Lemeshow (HL) test to calibrate it. By using odds ratios (OR) and 95% confidence intervals (95% CI), risk factors of mortality were identified.
Results:
There were no differences between observed mortality and expected mortality with PIM2 (17.7%; HL p = 0.17), resulting in a SM of 1. The AUC of PIM2 was 0.76 (95% CI, 0.68 0.83). Risk factors associated to mortality were: admission due to medical diagnosis (OR 3.22; 95% CI, 1.08 10.76), absence of pupillary light reflex (OR 7.36; 95% CI, 1.81 29.68), high risk diagnosis according to PIM2 (OR 3.85; 95% CI, 1.16 12.03), and coming from the Emergency Room showed a borderline result (OR 2.80; 95% CI, 0.98 8.69; chi-squared, p = 0.04).
Conclusions:
Mortality observed in the HNM's PICU during 2014 was elevated, but similar to predicted mortality by PIM2 score, with a SM of 1. PIM2 is a validated score used all over the world, which is useful to predict the expected mortality in PICUs.
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