Performance of the pediatric index of mortality 2 (PIM-2) in cardiac and mixed intensive care units in a tertiary children's referral hospital in Italy

Background: Mortality rate of patients admitted to Intensive Care Units is a widely adopted outcome indicator. Because of large case-mix variability, comparisons of mortality rates must be adjusted for the severity of patient illness at admission. The Pediatric Index of Mortality 2 (PIM-2) has been widely adopted as a tool for adjusting mortality rate by patients' case mix. The objective of this study was to assess the performance of PIM-2 in children admitted to intensive care units after cardiac surgery, other surgery, or for other reasons. Methods: This was a prospective cohort study, conducted in a 607 inpatient-bed tertiary-care pediatric hospital in Italy, with three pediatric intensive care Units (PICUs) and one cardiac Unit (CICU). In 2009-11, all consecutive admissions to PICUs/CICU of children aged 0-16 years were included in the study. Discrimination and calibration measures were computed to assess PIM-2 performance. Multivariable logistic regression analysis was used to assess the association of patients' main reason for intensive care admission (cardiac-surgical, other-surgical, medical), age, Unit and year with observed mortality, adjusting for PIM-2 score. Results: PIM-2 data collection was completed for 91.2% of total PICUs/CICU patient admissions (2912), and for 94.8% of patients who died in PICUs/CICU (129). Overall observed mortality was 4.4% (95% CI, 3.7-5.2), compared to 6.4% (95% CI, 5.5-7.3) expected mortality. Standardised mortality ratio was 0.7 (95% CI: 0.6-0.8). PIM-2 discrimination was fair (area under the curve, 0.79; 95% CI: 0.75-0.83). Calibration was less satisfactory, mainly because of the over two-fold overprediction of deaths in the highest risk group (114.7 vs 53; p < 0.001), and particularly in cardiac-surgical patients. Multivariable logistic analysis showed that risk of death was significantly reduced in cardiac-surgical patients and in those aged 1 month to 12 years, independently from PIM-2. Conclusions: The children age distribution and the proportion of cardiac-surgical patients should be taken into account when interpreting SMRs estimated using the PIM-2 prediction model in different Units. A new calibration study of PIM-2 score might be needed, and more appropriate cardiac-focused risk-adjustment models should be developed. The role of age on risk of death needs to be further explored

Influence of maternal obesity and gestational weight gain on maternal and foetal lipid profile

Fatty acids (FAs) are fundamental for a foetus\u2019s growth, serving as an energy source, structural constituents of cellular membranes and precursors of bioactive molecules, as well as being essential for cell signalling. Long-chain polyunsaturated FAs (LC-PUFAs) are pivotal in brain and visual development. It is of interest to investigate whether and how specific pregnancy conditions, which alter fatty acid metabolism (excessive pre-pregnancy body mass index (BMI) or gestational weight gain (GWG)), affect lipid supply to the foetus. For this purpose, we evaluated the erythrocyte FAs of mothers and offspring (cord-blood) at birth, in relation to pre-pregnancy BMI and GWG. A total of 435 mothers and their offspring (237 males, 51%) were included in the study. Distribution of linoleic acid (LA) and \u3b1-linolenic acid (ALA), and their metabolites, arachidonic acid, dihomogamma linoleic (DGLA) and ecosapentanoic acid, was significantly different in maternal and foetal erythrocytes. Pre-pregnancy BMI was significantly associated with maternal percentage of MUFAs (Coeff: -0.112; p = 0.021), LA (Coeff: -0.033; p = 0.044) and DHA (Coeff. = 0.055; p = 0.0016); inadequate GWG with DPA (Coeff: 0.637; p = 0.001); excessive GWG with docosaexahenoic acid (DHA) (Coeff. = -0.714; p = 0.004). Moreover, pre-pregnancy BMI was associated with foetus percentage of PUFAs (Coeff: -0.172; p = 0.009), omega 6 (Coeff: -0.098; p = 0.015) and DHA (Coeff: -0.0285; p = 0.036), even after adjusting for maternal lipids. Our findings show that maternal GWG affects maternal but not foetal lipid profile, differently from pre-pregnancy BMI, which influences both