Retrospective cohort study on factors associated with mortality in high-risk pediatric critical care patients in the Netherlands.

BACKGROUND: High-risk patients in the pediatric intensive care unit (PICU) contribute substantially to PICU-mortality. Complex chronic conditions (CCCs) are associated with death. However, it is unknown whether CCCs also increase mortality in the high-risk PICU-patient. The objective of this study is to determine if CCCs or other factors are associated with mortality in this group. METHODS: Retrospective cohort study from a national PICU-database (2006-2012, n = 30,778). High-risk PICU-patients, defined as patients < 18 years with a predicted mortality risk > 30% according to either the recalibrated Pediatric Risk of Mortality-II (PRISM) or the Paediatric Index of Mortality 2 (PIM2), were included. Patients with a cardiac arrest before PICU-admission were excluded. RESULTS: In total, 492 high-risk PICU patients with mean predicted risk of 24.8% (SD 22.8%) according to recalibrated PIM2 and 40.0% (SD 23.8%) according to recalibrated PRISM were included of which 39.6% died. No association was found between CCCs and non-survival (odds ratio 0.99; 95% CI 0.62-1.59). Higher Glasgow coma scale at PICU admission was associated with lower mortality (odds ratio 0.91; 95% CI 0.87-0.96). CONCLUSIONS: Complex chronic conditions are not associated with mortality in high-risk PICU patients.

Factors Associated With Mortality in Low-Risk Pediatric Critical Care Patients in The Netherlands.

OBJECTIVE: To determine differences between survivors and nonsurvivors and factors associated with mortality in pediatric intensive care patients with low risk of mortality. DESIGN: Retrospective cohort study. SETTING: Patients were selected from a national database including all admissions to the PICUs in The Netherlands between 2006 and 2012. PATIENTS: Patients less than 18 years old admitted to the PICU with a predicted mortality risk lower than 1% according to either the recalibrated Pediatric Risk of Mortality or the Pediatric Index of Mortality 2 were included. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: In total, 16,874 low-risk admissions were included of which 86 patients (0.5%) died. Nonsurvivors had more unplanned admissions (74.4% vs 38.5%; p < 0.001), had more complex chronic conditions (76.7% vs 58.8%; p = 0.001), were more often mechanically ventilated (88.1% vs 34.9%; p < 0.001), and had a longer length of stay (median, 11 [interquartile range, 5-32] d vs median, 3 [interquartile range, 2-5] d; p < 0.001) when compared with survivors. Factors significantly associated with mortality were complex chronic conditions (odds ratio, 3.29; 95% CI, 1.97-5.50), unplanned admissions (odds ratio, 5.78; 95% CI, 3.40-9.81), and admissions in spring/summer (odds ratio, 1.67; 95% CI, 1.08-2.58). CONCLUSIONS: Nonsurvivors in the PICU with a low predicted mortality risk have recognizable risk factors including complex chronic condition and unplanned admissions.

Validation of an adapted Pediatric Sepsis Score in children admitted to PICU with invasive infection and sepsis: a retrospective analysis of a Dutch national cohort.

We validated an adapted form of the Pediatric Sepsis Score (aPSS), a disease-specific severity score available within 60 min of PICU admission, in children with invasive infection. aPSS consist of all components of PSS except lactate. aPSS predicted mortality in children with invasive infection (n = 4096; AUC 0.70 (95% CI 0.67-0.73)) and in children with sepsis (n = 1690; AUC 0.71 (0.67-0.76)). aPSS can be an adequate tool to predict outcome in children admitted to PICU with invasive infection or sepsis, especially in situations where lactate is not available within 60 min.

Mortality prediction models for pediatric intensive care: comparison of overall and subgroup specific performance.

AIM: To validate paediatric index of mortality (PIM) and pediatric risk of mortality (PRISM) models within the overall population as well as in specific subgroups in pediatric intensive care units (PICUs). METHODS: Variants of PIM and PRISM prediction models were compared with respect to calibration (agreement between predicted risks and observed mortality) and discrimination (area under the receiver operating characteristic curve, AUC). We considered performance in the overall study population and in subgroups, defined by diagnoses, age and urgency at admission, and length of stay (LoS) at the PICU. We analyzed data from consecutive patients younger than 16 years admitted to the eight PICUs in the Netherlands between February 2006 and October 2009. Patients referred to another ICU or deceased within 2 h after admission were excluded. RESULTS: A total of 12,040 admissions were included, with 412 deaths. Variants of PIM2 were best calibrated. All models discriminated well, also in patients <28 days of age (neonates), with overall higher AUC for PRISM variants (PIM = 0.83, PIM2 = 0.85, PIM2-ANZ06 = 0.86, PIM2-ANZ08 = 0.85, PRISM = 0.88, PRISM3-24 = 0.90). Best discrimination for PRISM3-24 was confirmed in 13 out of 14 subgroup categories. After recalibration PRISM3-24 predicted accurately in most (12 out of 14) categories. Discrimination was poorer for all models (AUC < 0.73) after LoS of >6 days at the PICU. CONCLUSION: All models discriminated well, also in most subgroups including neonates, but had difficulties predicting mortality for patients >6 days at the PICU. In a western European setting both the PIM2(-ANZ06) or a recalibrated version of PRISM3-24 are suited for overall individualized risk prediction.