1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Predictors of brain infarction in adult patients on extracorporeal membrane oxygenation: an observational cohort study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Non-hemorrhagic brain infarction (BI) is a recognized complication in adults treated with extracorporeal membrane oxygenation (ECMO) and associated with increased mortality. However, predictors of BI in these patients are poorly understood. The aim of this study was to identify predictors of BI in ECMO-treated adult patients. We conducted an observational cohort study of all adult patients treated with venovenous or venoarterial (VA) ECMO at our center between 2010 and 2018. The primary endpoint was a computed tomography (CT) verified BI. Logistic regression models were employed to identify BI predictors. In total, 275 patients were included, of whom 41 (15%) developed a BI. Pre-ECMO Simplified Acute Physiology Score III, pre-ECMO cardiac arrest, VA ECMO and conversion between ECMO modes were identified as predictors of BI. In the multivariable analysis, VA ECMO demonstrated independent risk association. VA ECMO also remained the independent BI predictor in a sub-group analysis excluding patients who did not undergo a head CT scan during ECMO treatment. The incidence of BI in adult ECMO patients may be higher than previously believed and is independently associated with VA ECMO mode. Larger prospective trials are warranted to validate these findings and ascertain their clinical significance.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation

          The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome

            The efficacy of venovenous extracorporeal membrane oxygenation (ECMO) in patients with severe acute respiratory distress syndrome (ARDS) remains controversial.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission

              Objective To develop a model to assess severity of illness and predict vital status at hospital discharge based on ICU admission data. Design Prospective multicentre, multinational cohort study. Patients and setting A total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002. Measurements and results ICU admission data (recorded within ±1 h) were used, describing: prior chronic conditions and diseases; circumstances related to and physiologic derangement at ICU admission. Selection of variables for inclusion into the model used different complementary strategies. For cross-validation, the model-building procedure was run five times, using randomly selected four fifths of the sample as a development- and the remaining fifth as validation-set. Logistic regression methods were then used to reduce complexity of the model. Final estimates of regression coefficients were determined by use of multilevel logistic regression. Variables selection and weighting were further checked by bootstraping (at patient level and at ICU level). Twenty variables were selected for the final model, which exhibited good discrimination (aROC curve 0.848), without major differences across patient typologies. Calibration was also satisfactory (Hosmer-Lemeshow goodness-of-fit test Ĥ=10.56, p=0.39, Ĉ=14.29, p=0.16). Customised equations for major areas of the world were computed and demonstrate a good overall goodness-of-fit. Conclusions The SAPS 3 admission score is able to predict vital status at hospital discharge with use of data recorded at ICU admission. Furthermore, SAPS 3 conceptually dissociates evaluation of the individual patient from evaluation of the ICU and thus allows them to be assessed at their respective reference levels. Electronic Supplementary Material Electronic supplementary material is included in the online fulltext version of this article and accessible for authorised users: http://dx.doi.org/10.1007/s00134-005-2763-5
                Bookmark

                Author and article information

                Contributors
                riccardo.iacobelli@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                15 February 2021
                15 February 2021
                2021
                : 11
                : 3809
                Affiliations
                [1 ]GRID grid.24381.3c, ISNI 0000 0000 9241 5705, Department of Pediatric Perioperative Medicine and Intensive Care, ECMO Centre Karolinska, Astrid Lindgren Children’s Hospital, , Karolinska University Hospital, ; 171 76 Stockholm, Sweden
                [2 ]GRID grid.24381.3c, ISNI 0000 0000 9241 5705, Department of Neurosurgery, , Karolinska University Hospital, ; Stockholm, Sweden
                [3 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Clinical Neuroscience, , Karolinska Institutet, ; Stockholm, Sweden
                [4 ]GRID grid.24381.3c, ISNI 0000 0000 9241 5705, Department of Neurology, , Karolinska University Hospital, ; Stockholm, Sweden
                [5 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Physiology and Pharmacology, , Karolinska Institutet, ; Stockholm, Sweden
                Author information
                http://orcid.org/0000-0001-7536-3795
                Article
                83157
                10.1038/s41598-021-83157-5
                7884423
                33589664
                61fa72bb-9742-409f-9c64-3e7a74d03c2c
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 July 2020
                : 28 January 2021
                Funding
                Funded by: Karolinska Institute
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                stroke,risk factors,epidemiology,circulation,respiration
                Uncategorized
                stroke, risk factors, epidemiology, circulation, respiration

                Comments

                Comment on this article