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      Frailty and Outcomes After Myocardial Infarction: Insights From the CONCORDANCE Registry

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          Abstract

          Background

          Little is known about the prognostic implications of frailty, a state of susceptibility to stressors and poor recovery to homeostasis in older people, after myocardial infarction ( MI).

          Methods and Results

          We studied 3944 MI patients aged ≥65 years treated at 41 Australian hospitals from 2009 to 2016 in the CONCORDANCE ( Australian Cooperative National Registry of Acute Coronary Care, Guideline Adherence and Clinical Events ) registry. Frailty index ( FI) was determined using the health deficit accumulation method. All‐cause and cardiac‐specific mortality at 6 months were compared between frail ( FI >0.25) and nonfrail ( FI ≤0.25) patients. Among 1275 patients with ST‐segment–elevation MI (STEMI), 192 (15%) were frail, and among 2669 non‐STEMI ( NSTEMI) patients, 902 (34%) were frail. Compared with nonfrail counterparts, frail STEMI patients received 30% less reperfusion therapy and 22% less revascularization during index hospitalization; frail NSTEMI patients received 30% less diagnostic angiography and 39% less revascularization. Unadjusted 6‐month all‐cause mortality ( STEMI: 13% versus 3%; NSTEMI: 13% versus 4%) and cardiac‐specific mortality ( STEMI: 6% versus 1.4%, NSTEMI: 3.2% versus 1.2%) were higher among frail patients. After adjustment for known prognosticators, FI was significantly associated with higher 6‐month all‐cause ( STEMI: odds ratio: 1.74 per 0.1 FI [95% confidence interval, 1.37–2.22], P<0.001; NSTEMI: odds ratio: 1.62 per 0.1 FI [95% confidence interval, 1.40–1.87], P<0.001) but not cardiac‐specific mortality ( STEMI: P=0.99; NSTEMI: P=0.93).

          Conclusions

          Frail patients receive lower rates of invasive cardiac care during MI hospitalization. Increased frailty was independently associated with increased postdischarge all‐cause mortality but not cardiac‐specific mortality. These findings inform identification of frailty during MI hospitalization as a potential opportunity to address competing risks for mortality in this high‐risk population.

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          Most cited references19

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          Longitudinal data analysis for discrete and continuous outcomes.

          Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.
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            Frailty in relation to the accumulation of deficits.

            This review article summarizes how frailty can be considered in relation to deficit accumulation. Recalling that frailty is an age-associated, nonspecific vulnerability, we consider symptoms, signs, diseases, and disabilities as deficits, which are combined in a frailty index. An individual's frailty index score reflects the proportion of potential deficits present in that person, and indicates the likelihood that frailty is present. Although based on a simple count, the frailty index shows several interesting properties, including a characteristic rate of accumulation, a submaximal limit, and characteristic changes with age in its distribution. The frailty index, as a state variable, is able to quantitatively summarize vulnerability. Future studies include the application of network analyses and stochastic analytical techniques to the evaluation of the frailty index and the description of other state variables in relation to frailty.
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              Frailty is independently associated with short-term outcomes for elderly patients with non-ST-segment elevation myocardial infarction.

              For the large and growing population of elderly patients with cardiovascular disease, it is important to identify clinically relevant measures of biological age and their contribution to risk. Frailty is an emerging concept in medicine denoting increased vulnerability and decreased physiological reserves. We analyzed the manner in which the variable frailty predicts short-term outcomes for elderly non-ST-segment elevation myocardial infarction patients. Patients aged ≥ 75 years, with diagnosed non-ST-segment elevation myocardial infarction were included at 3 centers, and clinical data including judgment of frailty were collected prospectively. Frailty was defined according to the Canadian Study of Health and Aging Clinical Frailty Scale. The impact of the comorbid conditions on risk was quantified by the coronary artery disease-specific index. Of 307 patients, 149 (48.5%) were considered frail. By multiple logistic regression, frailty was found to be strongly and independently associated with risk for the primary composite outcome (death from any cause, myocardial reinfarction, revascularization due to ischemia, hospitalization for any cause, major bleeding, stroke/transient ischemic attack, and need for dialysis up to 1 month after inclusion) (odds ratio, 2.2; 95% confidence interval, 1.3-3.7), in-hospital mortality (odds ratio, 4.6; 95% confidence interval, 1.3-16.8), and 1-month mortality (odds ratio, 4.7; 95% confidence interval, 1.7-13.0). Frailty is strongly and independently associated with in-hospital mortality, 1-month mortality, prolonged hospital care, and the primary composite outcome. The combined use of frailty and comorbidity may constitute an ultimate risk prediction concept in regard to cardiovascular patients with complex needs.
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                Author and article information

                Contributors
                bagaia@smh.ca
                Journal
                J Am Heart Assoc
                J Am Heart Assoc
                10.1002/(ISSN)2047-9980
                JAH3
                ahaoa
                Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
                John Wiley and Sons Inc. (Hoboken )
                2047-9980
                12 September 2018
                18 September 2018
                : 7
                : 18 ( doiID: 10.1002/jah3.2018.7.issue-18 )
                : e009859
                Affiliations
                [ 1 ] Terrence Donnelly Heart Centre St Michael's Hospital Toronto Ontario Canada
                [ 2 ] University of Toronto Ontario Canada
                [ 3 ] Duke Clinical Research Institute Durham NC
                [ 4 ] Division of Geriatric Medicine St Michael's Hospital Toronto Ontario Canada
                [ 5 ] Women's College Research Institute and Cardiovascular Division Women's College Hospital and Peter Munk Cardiac Centre University Health Network Toronto Ontario Canada
                [ 6 ] Canadian VIGOUR Centre University of Alberta Edmonton Canada
                [ 7 ] School of Public Health University of Sydney Clinical Research Centre Sydney Local Health District Sydney Australia
                [ 8 ] ANZAC Institute Westmead Clinical School Sydney Medical School University of Sydney Australia
                [ 9 ] Department of Cardiology Royal Prince Alfred Hospital Sydney Australia
                [ 10 ] University of New South Wales Sydney Australia
                [ 11 ] Department of Cardiology Flinders University Adelaide Australia
                [ 12 ] Department of Cardiology Concord Hospital University of Sydney Sydney Australia
                Author notes
                [*] [* ] Correspondence to: Akshay Bagai, MD, MHS, Terrence Donnelly Heart Center, St. Michael's Hospital, University of Toronto, Ontario, Canada. E‐mail: bagaia@ 123456smh.ca
                Article
                JAH33497
                10.1161/JAHA.118.009859
                6222944
                30371219
                715f8f02-f394-4fd8-a727-6f83443f4760
                © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 18 May 2018
                : 06 August 2018
                Page count
                Figures: 5, Tables: 4, Pages: 11, Words: 6944
                Funding
                Funded by: Heart Foundation of Australia
                Funded by: Sanofi Aventis
                Funded by: Astra Zeneca
                Funded by: Eli Lilly
                Funded by: Boehringer Ingelheim
                Funded by: Merck Sharp
                Funded by: Dohme Joint Venture
                Categories
                Original Research
                Original Research
                Coronary Heart Disease
                Custom metadata
                2.0
                jah33497
                18 September 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.4.7.1 mode:remove_FC converted:18.09.2018

                Cardiovascular Medicine
                frailty,health services research,myocardial infarction,outcomes,mortality/survival,quality and outcomes

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