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      Determinants of long-term outcome in ICU survivors: results from the FROG-ICU study

      research-article
      1 , 28 , , 2 , 3 , 4 , 5 , 1 , 6 , 7 , 8 , 9 , 10 , 1 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 1 , 24 , 25 , 26 , 27 , 1
      Critical Care
      BioMed Central
      Post-intensive care syndrome, Long-term survival, Biomarkers, Score, Discharge

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          Abstract

          Background

          Intensive care unit (ICU) survivors have reduced long-term survival compared to the general population. Identifying parameters at ICU discharge that are associated with poor long-term outcomes may prove useful in targeting an at-risk population. The main objective of the study was to identify clinical and biological determinants of death in the year following ICU discharge.

          Methods

          FROG-ICU was a prospective, observational, multicenter cohort study of ICU survivors followed 1 year after discharge, including 21 medical, surgical or mixed ICUs in France and Belgium. All consecutive patients admitted to intensive care with a requirement for invasive mechanical ventilation and/or vasoactive drug support for more than 24 h following ICU admission and discharged from ICU were included. The main outcome measure was all-cause mortality at 1 year after ICU discharge. Clinical and biological parameters on ICU discharge were measured, including the circulating cardiovascular biomarkers N-terminal pro-B type natriuretic peptide, high-sensitive troponin I, bioactive-adrenomedullin and soluble-ST2. Socioeconomic status was assessed using a validated deprivation index (FDep).

          Results

          Of 1570 patients discharged alive from the ICU, 333 (21%) died over the following year. Multivariable analysis identified age, comorbidity, red blood cell transfusion, ICU length of stay and abnormalities in common clinical factors at the time of ICU discharge (low systolic blood pressure, temperature, total protein, platelet and white cell count) as independent factors associated with 1-year mortality. Elevated biomarkers of cardiac and vascular failure independently associated with 1-year death when they are added to multivariable model, with an almost 3-fold increase in the risk of death when combined (adjusted odds ratio 2.84 (95% confidence interval 1.73–4.65), p < 0.001).

          Conclusions

          The FROG-ICU study identified, at the time of ICU discharge, potentially actionable clinical and biological factors associated with poor long-term outcome after ICU discharge. Those factors may guide discharge planning and directed interventions.

          Trial registration

          ClinicalTrials.gov NCT01367093. Registered on 6 June 2011.

          Electronic supplementary material

          The online version of this article (10.1186/s13054-017-1922-8) contains supplementary material, which is available to authorized users.

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          Most cited references21

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          • Book: not found

          Applied Logistic Regression

            Bookmark
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            • Abstract: found
            • Article: not found

            Use and misuse of the receiver operating characteristic curve in risk prediction.

            The c statistic, or area under the receiver operating characteristic (ROC) curve, achieved popularity in diagnostic testing, in which the test characteristics of sensitivity and specificity are relevant to discriminating diseased versus nondiseased patients. The c statistic, however, may not be optimal in assessing models that predict future risk or stratify individuals into risk categories. In this setting, calibration is as important to the accurate assessment of risk. For example, a biomarker with an odds ratio of 3 may have little effect on the c statistic, yet an increased level could shift estimated 10-year cardiovascular risk for an individual patient from 8% to 24%, which would lead to different treatment recommendations under current Adult Treatment Panel III guidelines. Accepted risk factors such as lipids, hypertension, and smoking have only marginal impact on the c statistic individually yet lead to more accurate reclassification of large proportions of patients into higher-risk or lower-risk categories. Perfectly calibrated models for complex disease can, in fact, only achieve values for the c statistic well below the theoretical maximum of 1. Use of the c statistic for model selection could thus naively eliminate established risk factors from cardiovascular risk prediction scores. As novel risk factors are discovered, sole reliance on the c statistic to evaluate their utility as risk predictors thus seems ill-advised.
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              • Article: not found

              Long-term complications of critical care.

              As critical care advances and intensive care unit mortality declines, the number of survivors of critical illness is increasing. These survivors frequently experience long-lasting complications of critical care. As a result, it is important to understand these complications and implement evidence-based practices to minimize them. Database searches and review of relevant medical literature. Critical illness and intensive care unit care influence a wide range of long-term patient outcomes, with some impairments persisting for 5-15 yrs. Impaired pulmonary function, greater healthcare utilization, and increased mortality are observed in intensive care survivors. Neuromuscular weakness and impairments in both physical function and related aspects of quality of life are common and may be long-lasting. These complications may be reduced by multidisciplinary physical rehabilitation initiated early and continued throughout the intensive care unit care stay and by providing patient education for self-rehabilitation after hospital discharge. Common neuropsychiatric complications, including cognitive impairment and symptoms of depression and posttraumatic stress disorder, are frequently associated with intensive care unit sedation, delirium or delusional memories, and long-term impairments in quality of life. Survivors of critical illness are frequently left with a legacy of long-term physical, neuropsychiatric, and quality of life impairments. Understanding patient and intensive care risk factors can help identify patients who are most at risk of these complications. Furthermore, modifiable risk factors and beneficial interventions are increasingly being identified to help inform practical management recommendations to reduce the prevalence and impact of these long-term complications.
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                Author and article information

                Contributors
                +33 1 49 95 80 71 , etienne.gayat@aphp.fr
                alain.cariou@aphp.fr
                nicolas.deye@aphp.fr
                antoine.vieillard-baron@aphp.fr
                s-jaber@chu-montpellier.fr
                charles.damoisel@aphp.fr
                qin.lu@aphp.fr
                xavier.monnet@aphp.fr
                Isablle.rennuit@aphp.fr
                elie.azoulay@aphp.fr
                marc.leone@ap-hm.fr
                heikel.oueslati@aphp.fr
                Bertrand.guidet@aphp.fr
                diane.friedman@aphp.fr
                antoine.tesniere@aphp.fr
                romain.sonneville@aphp.fr
                philippe.montravers@aphp.fr
                spilifloury@orange.fr
                jean.yves.lefrant@chu-nimes.fr
                jacques.duranteau@aphp.fr
                pierre-francois.laterre@uclouvain.be
                nicolas.brechot@aphp.fr
                karine.chevreul@aphp.fr
                bernard.cholley@aphp.fr
                matthieu.m.legrand@gmail.com
                jean-marie.launay@aphp.fr
                eric.vicaut@aphp.fr
                m.singer@ucl.ac.uk
                matthieu.resche-rigon@univ-paris-diderot.fr
                alexandre.mebazaa@aphp.fr
                Journal
                Crit Care
                Critical Care
                BioMed Central (London )
                1364-8535
                1466-609X
                18 January 2018
                18 January 2018
                2018
                : 22
                : 8
                Affiliations
                [1 ]Department of Anesthesiology, Critical Care and Burn Unit, Hôpitaux Universitaires Saint Louis—Lariboisière, Assistance Publique—Hôpitaux de Paris, Université Paris Diderot—Paris 7, Sorbonne Paris Cité, UMR-S 942, INSERM, Paris, France
                [2 ]Medical Intensive Care Unit, Cochin University Hospital, Assistance Publique—Hôpitaux de Paris, Paris Descartes University, Paris Cardiovascular Research Center-INSERM U970 (PARCC), Paris Sudden Death Expertise Center, Paris, France
                [3 ]Medical Intensive Care Unit, Hôpitaux Universitaires Saint Louis—Lariboisière, Assistance Publique—Hôpitaux de Paris, Université Paris Diderot—Paris 7, Sorbonne Paris Cité, UMR-S 942, INSERM, Paris, France
                [4 ]ISNI 0000 0001 2175 4109, GRID grid.50550.35, Intensive Care Unit, , University Hospital Ambroise Paré, Assistance Publique—Hopitaux de Paris, ; 26930 Boulogne-Billancourt, France
                [5 ]Intensive Care Unit, Anaesthesia and Critical Care Department, Saint Eloi Teaching Hospital, Centre Hospitalier Universitaire Montpellier, Montpellier University, Montpellier, France
                [6 ]ISNI 0000 0001 2150 9058, GRID grid.411439.a, Multidisciplinary Intensive Care Unit, Department of Anesthesiology and Critical Care Medicine, , La Pitié-Salpêtrière Hospital, Assistance Publique Hôpitaux de Paris, UPMC Paris 6, ; Paris, France
                [7 ]ISNI 0000 0001 2181 7253, GRID grid.413784.d, Medical Intensive Care Unit, , Bicêtre Hospital, Paris-Sud University Hospitals, Inserm UMR_S999, Paris-Sud University, ; Le Kremlin-Bicêtre, France
                [8 ]ISNI 0000 0000 8595 4540, GRID grid.411599.1, Department of Anesthesiology and Critical Care, , Beaujon Hospital, Assistance Publique Hôpitaux de Paris University, ; Clichy, France
                [9 ]Medical Intensive Care Unit, Hôpital Saint-Louis, ECSTRA Team, Biostatistics and Clinical Epidemiology, UMR 1153 (Center of Epidemiology and Biostatistics Sorbonne Paris Cité, CRESS), INSERM, Université Paris Diderot Sorbonne, Paris, France
                [10 ]Service d’anesthésie et de réanimation, Hôpital Nord, Assistance Publique—Hôpitaux de Marseille, Aix Marseille Université, Marseille, France
                [11 ]Service de Réanimation Médicale, Hôpital Saint-Antoine, Assistance Publique—Hôpitaux de Paris, Université Pierre et Marie Curie, Paris, France
                [12 ]ISNI 0000 0001 2175 4109, GRID grid.50550.35, General Intensive Care, , Raymond Poincaré University Hosptal, Assistance Publique—Hopitaux de Paris, ; Garches, France
                [13 ]Department of Anesthesiology and Intensive Care, Cochin University Hospital, Assistance Publique—Hôpitaux de Paris, Paris Descartes University, Paris Cardiovascular Research Center-INSERM U970 (PARCC), Paris Sudden Death Expertise Center, Paris, France
                [14 ]Department of Intensive Care Medicine and Infectious Diseases, Univ Paris Diderot, Sorbonne Paris Cité, Assistance Publique—Hôpitaux de Paris, Hôpital Bichat-Claude, Paris, France
                [15 ]Department of Anesthesiology and Intensive Care, Bichat University Hospital, Assistance Publique—Hôpitaux de Paris, Université Paris Diderot—Paris 7, Sorbonne Paris Cité, Paris, France
                [16 ]ISNI 0000 0004 0638 9213, GRID grid.411158.8, Department of Anesthesiology and Intensive Care Medicine, , University Hospital of Besancon, ; 25000 Besancon, France
                [17 ]ISNI 0000 0004 0593 8241, GRID grid.411165.6, Department of Anesthesiology, Emergency and Critical Care Medicine, , Nimes University Hospital, ; 30029 Nîmes, France
                [18 ]Physiology Department, EA 2992, Faculté de Médecine de Nîmes, Université Montpellier 1, 30029 Nîmes, France
                [19 ]ISNI 0000 0001 2175 4109, GRID grid.50550.35, Département d’Anesthésie-Réanimation, , Hôpital de Bicêtre, Université Paris-Sud, Hôpitaux Universitaires Paris-Sud, Assistance Publique—Hôpitaux de Paris, ; Le Kremlin Bicêtre, Paris, France
                [20 ]Medical–Surgical Intensive Care Unit, Cliniques Saint-Luc, Brussels, Belgium
                [21 ]Medical Intensive Care Unit, Hôpital Pitié-Salpêtrière, Assistance Publique—Hôpitaux de Paris, Sorbonne Pierre-Marie Curie University Paris, INSERM, UMRS_1166-ICAN, Institute of Cardiometabolism and Nutrition and CIC 1421—Paris Est, Paris, France
                [22 ]URC-Eco, Assistance Publique—Hôpitaux de Paris, Sorbonne Paris Cité, Université Paris Diderot, ECEVE, INSERM, Paris, France
                [23 ]Department of Anesthesiology and Critical Care Medicine, Hôpital Européen Georges Pompidou, APHP, Université Paris Descartes, Sorbonne Paris Cite, Paris, France
                [24 ]Service de Biochimie, Hôpitaux Universitaires Saint Louis—Lariboisière, Assistance Publique—Hôpitaux de Paris, Université Paris Diderot—Paris 7, Sorbonne Paris Cité, UMR-S 942, INSERM, Paris, France
                [25 ]Unité de Recherche Clinique, Hôpitaux Universitaires Saint Louis—Lariboisière, Assistance Publique—Hôpitaux de Paris, Université Paris Diderot—Paris 7, Sorbonne Paris Cité, UMR-S 942, INSERM, Paris, France
                [26 ]ISNI 0000000121901201, GRID grid.83440.3b, Bloomsbury Institute of Intensive Care Medicine, , University College London, Cruciform Building, ; Gower St, London, WC1E 6BT UK
                [27 ]Service de Biostatistique et Information Médicale, Hôpitaux Universitaires Saint Louis—Lariboisière, Assistance Publique—Hôpitaux de Paris, Université Paris Diderot—Paris 7, Sorbonne Paris Cité, ECSTRA Team, INSERM, Paris, France
                [28 ]ISNI 0000 0001 2217 0017, GRID grid.7452.4, Department of Anesthesiology and Intensive Care, , University Paris Diderot, INSERM UMR-S 942, Saint Louis—Lariboisière University Hospitals, ; 2 rue Ambroise Paré, 75010 Paris, France
                Author information
                http://orcid.org/0000-0002-3334-3849
                Article
                1922
                10.1186/s13054-017-1922-8
                5774139
                29347987
                53fff048-5ec6-40e0-8452-3a8c56cf6b79
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 7 August 2017
                : 8 December 2017
                Funding
                Funded by: PHRC National
                Award ID: AON 10-216
                Award Recipient :
                Funded by: Société Française d'Anesthésie - Réanimation
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                Emergency medicine & Trauma
                post-intensive care syndrome,long-term survival,biomarkers,score,discharge

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