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Protein Energy Malnutrition Is Associated with Worse Outcomes in Sepsis—A Nationwide Analysis
Protein-energy malnutrition (PEM), resulting from depleted energy and nutrient stores, compromises the body’s defense systems and may exacerbate sepsis and its impact. However, population-based studies examining the association of PEM on the prevalence and health-care burden of sepsis are lacking. T...
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Published in: | Journal of the Academy of Nutrition and Dietetics 2019-12, Vol.119 (12), p.2069-2084 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Protein-energy malnutrition (PEM), resulting from depleted energy and nutrient stores, compromises the body’s defense systems and may exacerbate sepsis and its impact. However, population-based studies examining the association of PEM on the prevalence and health-care burden of sepsis are lacking.
To investigate the relationship between PEM and sepsis, influence of PEM on clinical outcomes of sepsis, and impact of PEM on trends in sepsis mortality.
The primary study is a retrospective cohort analysis of the 2012-2014 National Inpatient Sample (NIS) patient discharge records. Secondary analyses are cross-sectional study on the 2014 NIS and trend analysis on 2007-2014 NIS.
The primary study included adult inpatient hospitalizations for sepsis in the United States.
Mortality, complicated sepsis, and 10 other metrics of clinical outcomes and health care utilization.
First, patients with sepsis (2014 NIS) were stratified into two groups: uncomplicated (without shock) and complicated (with shock). The adjusted odds ratio of having sepsis (total, uncomplicated, and complicated) was estimated with PEM as predictor using logistic regressions (binomial and multinomial). Second, among patients with sepsis (2012-2014 NIS), PEM cases were matched to cases without PEM (no-PEM) using a greedy-algorithm based propensity-matching methodology (1:1), and the outcomes were measured with conditional regression models. Finally, the trend in mortality from sepsis was calculated, stratified by PEM status, as an effect modifier, using Poisson models (2007-2014 NIS). All models accounted for the complex sampling methodology (SAS 9.4).
In 2014, PEM was associated with higher odds for sepsis (3.97 [3.89 to 4.05], P |
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ISSN: | 2212-2672 2212-2680 |
DOI: | 10.1016/j.jand.2019.04.019 |