Niklas Ekerstad1,2, Dariush Javadzadeh3, Karen P Alexander4, Olle Bergström5, Lars Eurenius6, Mats Fredrikson7, Gudny Gudnadottir8, Claes Held9, Karin Hellström Ängerud10, Radwan Jahjah11,12, Tomas Jernberg13, Ewa Mattsson14, Kjell Melander15, Linda Mellbin16, Monica Ohlsson17, Annica Ravn-Fischer18, Lars Svennberg19, Troels Yndigegn20, Joakim Alfredsson11,12. 1. Department of Health, Medicine and Caring Sciences, Unit of Health Care Analysis and National Centre for Priorities in Health, Linköping University, Sandbäcksgatan 7, 58183 Linköping, Sweden. 2. The Research and Development Unit, NU Hospital Group, Trollhättan, Sweden. 3. Department of Cardiology, NU Hospital Group, Trollhättan, Sweden. 4. Duke Clinical Research Institute, Duke University, Durham, NC, USA. 5. Department of Medicine, Växjö County Hospital, Växjö, Sweden. 6. Department of Clinical Physiology, Karolinska University Hospital, Stockholm, Sweden. 7. Department of Biomedical and Clinical Sciences, Faculty of Medicine and Health, Linköping University, Linköping, Sweden. 8. Section of Geriatrics, Department of Acute Medicine and Geriatrics, Sahlgrenska University Hospital, Gothenburg, Sweden. 9. Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden. 10. Department of Nursing, Heart Centre, Umeå University, Umeå, Sweden. 11. Department of Cardiology, Unit of Cardiovascular Sciences, Linköping University, Linköping, Sweden. 12. Department of Health, Medicine and Caring Sciences, Unit of Cardiovascular Sciences, Linköping University, Linköping, Sweden. 13. Department of Clinical Sciences, Danderyd University Hospital, Karolinska Institutet, Stockholm, Sweden. 14. Department of Cardiology, Skåne University Hospital, Lund, Sweden. 15. Department of medicine, Kalix Hospital, Kalix, Sweden. 16. Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden. 17. Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden. 18. Department of Cardiology, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. 19. Department of Cardiology, County Hospital of Gävle, Region Gävleborg, Sweden. 20. Department of Cardiology, Lund University, Lund, Sweden.
Abstract
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%) (all P < 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% CI 1.41-3.02). 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.
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%) (all P < 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% CI 1.41-3.02). 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.
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