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      Malnutrition in adult patients treated with venoarterial extracorporeal membrane oxygenation: A descriptive cohort study

      research-article
      , MS, RDN, LDN a , , , RDN, LDN a , , RDN, LDN a , , CCP b , , PharmD, BCCP c , , PharmD, BCCP c , , PhD, PT, CCS, FCCM d , , MD e , , MD f , , MD g , , MD g , , MD h
      JTCVS Open
      Elsevier
      VA ECMO, malnutrition, nutrition

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          Abstract

          Objective

          To evaluate malnutrition and its association with outcomes in adult patients requiring venoarterial (VA) extracorporeal membrane oxygenation (ECMO).

          Methods

          Patients cannulated for VA ECMO between January 1, 2020, and January 1, 2023, were screened. Patients on ECMO for <48 hours or without a nutritional evaluation were excluded. Demographic and anthropometric data were collected retrospectively. Malnutrition assessments were conducted using the Global Leadership Initiative on Malnutrition framework. Outcomes analyzed were duration of ECMO and in-hospital mortality. Patients were stratified by admission and discharge nutritional status for analysis. Baseline characteristics were controlled for with propensity score matching.

          Results

          Data from 197 patients was analyzed. The cohort was 68% male. The median duration of ECMO was 139.5 hours (interquartile range [IQR], 94.8-257 hours), and mortality was 35%. Thirty-three patients presented with malnutrition, and 61 developed hospital-acquired malnutrition, for an incidence of 47.7%. Malnutrition at any point was associated with longer duration of ECMO (median, 180 hours [IQR, 107.8-335.8 hours] vs 120 hours [IQR, 90-185.8 hours]; P < .001). Patients with hospital-acquired malnutrition required a 50% longer duration of ECMO (median, 182.5 hours [IQR, 101.5-367 hours] vs 123 hours [IQR, 90.8-211.5 hours]; P < .001). Preexisting malnutrition was associated with a nonsignificant increase in mortality (48.2% vs 32.9%; P = .13), which was similar after 3:1 propensity score matching (43.3% vs 35.4%; P = .44).

          Conclusions

          In adult patients, malnutrition appears to be associated with prolonged duration of VA ECMO. Adequately powered studies are needed to further investigate the relationship between malnutrition and mortality.

          Graphical Abstract

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          Most cited references37

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          An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

          The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects. I describe 4 different propensity score methods: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. I describe balance diagnostics for examining whether the propensity score model has been adequately specified. Furthermore, I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data. I describe different causal average treatment effects and their relationship with propensity score analyses.
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            Is Open Access

            Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies

            In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured baseline covariates. Propensity-score matching is increasingly being used to estimate the effects of exposures using observational data. In the most common implementation of propensity-score matching, pairs of treated and untreated subjects are formed whose propensity scores differ by at most a pre-specified amount (the caliper width). There has been a little research into the optimal caliper width. We conducted an extensive series of Monte Carlo simulations to determine the optimal caliper width for estimating differences in means (for continuous outcomes) and risk differences (for binary outcomes). When estimating differences in means or risk differences, we recommend that researchers match on the logit of the propensity score using calipers of width equal to 0.2 of the standard deviation of the logit of the propensity score. When at least some of the covariates were continuous, then either this value, or one close to it, minimized the mean square error of the resultant estimated treatment effect. It also eliminated at least 98% of the bias in the crude estimator, and it resulted in confidence intervals with approximately the correct coverage rates. Furthermore, the empirical type I error rate was approximately correct. When all of the covariates were binary, then the choice of caliper width had a much smaller impact on the performance of estimation of risk differences and differences in means. Copyright © 2010 John Wiley & Sons, Ltd.
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              • Abstract: not found
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              Guidelines for the Provision and Assessment of Nutrition Support Therapy in the Adult Critically Ill Patient: Society of Critical Care Medicine (SCCM) and American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.).

                Author and article information

                Contributors
                Journal
                JTCVS Open
                JTCVS Open
                JTCVS Open
                Elsevier
                2666-2736
                16 October 2024
                December 2024
                16 October 2024
                : 22
                : 38-46
                Affiliations
                [a ]Department of Clinical Nutrition, University of Maryland Medical Center, Baltimore, Md
                [b ]Department Perioperative Services, University of Maryland Medical Center, Baltimore, Md
                [c ]Department of Pharmaceutical Services, University of Maryland Medical Center, Baltimore, Md
                [d ]Department of Rehabilitation Services, University of Maryland Medical Center, Baltimore, Md
                [e ]Department of Cardiothoracic Surgery, University of Maryland Medical Center, Baltimore, Md
                [f ]Department of Medicine, University of Maryland School of Medicine, Baltimore, Md
                [g ]Division of Cardiac Surgery, University of Maryland School of Medicine, Baltimore, Md
                [h ]Department of Surgery, University of Maryland School of Medicine, Baltimore, Md
                Author notes
                []Address for reprints: Stacy Pelekhaty, MS, RDN, LDN, Department of Clinical Nutrition, University of Maryland Medical Center, 22. S Greene St, Baltimore, MD 21201. spelekhaty@ 123456umm.edu
                Article
                S2666-2736(24)00346-2
                10.1016/j.xjon.2024.09.029
                11704522
                f6c153f6-b3ff-4ff7-af52-5ae10ea0152c
                © 2024 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 25 April 2024
                : 17 September 2024
                : 19 September 2024
                Categories
                Special Issue on Enhanced Recovery After Surgery

                va ecmo,malnutrition,nutrition
                va ecmo, malnutrition, nutrition

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