Open this publication in new window or tab >>Department of Clinical Physiology, Karolinska University Hospital, Stockholm, Sweden.
Department of Biomedical and Clinical Sciences, Faculty of Medicine and Health, Linköping University, Linköping, Sweden.
Section of Geriatrics, Department of Acute Medicine and Geriatrics, Sahlgrenska University Hospital, Gothenburg, Sweden.
Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden.
Umeå University, Faculty of Medicine, Department of Nursing.
Department of Cardiology, Unit of Cardiovascular Sciences, Linköping University, Linköping, Sweden;Department of Health, Medicine and Caring Sciences, Unit of Cardiovascular Sciences, Linköping University, Linköping, Sweden.
Department of Clinical Sciences, Danderyd University Hospital, Karolinska Institutet, Stockholm, Sweden.
Department of Cardiology, Skåne University Hospital, Lund, Sweden.
Department of medicine, Kalix Hospital, Kalix, Sweden.
Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden.
Department of Cardiology, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Department of Cardiology, County Hospital of Gävle, Region Gävleborg, Sweden.
Department of Cardiology, Lund University, Lund, Sweden.
Department of Cardiology, Unit of Cardiovascular Sciences, Linköping University, Linköping, Sweden;Department of Health, Medicine and Caring Sciences, Unit of Cardiovascular Sciences, Linköping University, Linköping, Sweden.
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2022 (English)In: European Heart Journal: Acute Cardiovascular Care, ISSN 2048-8726, E-ISSN 2048-8734, Vol. 11, no 2, p. 89-98Article in journal (Refereed) Published
Abstract [en]
Aims: Data on the prognostic value of frailty to guide clinical decision-making for patients with myocardial infarction (MI) are scarce. To analyse the association between frailty classification, treatment patterns, in-hospital outcomes, and 6-month mortality in a large population of patients with MI.
Methods and results: An observational, multicentre study with a retrospective analysis of prospectively collected data using the SWEDEHEART registry. In total, 3381 MI patients with a level of frailty assessed using the Clinical Frailty Scale (CFS-9) were included. Of these patients, 2509 (74.2%) were classified as non-vulnerable non-frail (CFS 1–3), 446 (13.2%) were vulnerable non-frail (CFS 4), and 426 (12.6%) were frail (CFS 5–9). Frailty and non-frail vulnerability were associated with worse in-hospital outcomes compared with non-frailty, i.e. higher rates of mortality (13.4% vs. 4.0% vs. 1.8%), cardiogenic shock (4.7% vs. 2.5% vs. 1.9%), and major bleeding (4.5% vs. 2.7% vs. 1.1%) (allP < 0.001), and less frequent use of evidence-based therapies. In Cox regression analyses, frailty was strongly and independently associated with 6-month mortality compared with non-frailty, after adjustment for age, sex, the GRACE risk score components, and other potential risk factors [hazard ratio (HR) 3.32, 95% confidence interval (CI) 2.30–4.79]. A similar pattern was seen for vulnerable non-frail patients (fully adjusted HR 2.07, 95% CI1.41–3.02).
Conclusion: Frailty assessed with the CFS was independently and strongly associated with all-cause 6-month mortality, also after comprehensive adjustment for baseline differences in other risk factors. Similarly, non-frail vulnerability was independently associated with higher mortality compared with those with preserved functional ability.
Place, publisher, year, edition, pages
Oxford University Press, 2022
Keywords
Myocardial infarction, Clinical Frailty Scale, Risk prediction, Mortality
National Category
Nursing
Identifiers
urn:nbn:se:umu:diva-191685 (URN)10.1093/ehjacc/zuab114 (DOI)000753112100003 ()34905049 (PubMedID)2-s2.0-85128238129 (Scopus ID)
2022-01-212022-01-212023-08-28Bibliographically approved