Browsing by Author "Ambrosetti, M"
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- Cardiac Rehabilitation Availability and Density Around the GlobePublication . Turk-Adawi, K; Supervia, M; Lopez-Jimenez, F; Pesah, E; Ding, R; Britto, RR; Bjarnason-Wehrens, B; Derman, W; Abreu, A; Babu, AS; Santos, CA; Jong, SK; Cuenza, L; Yeo, TJ; Scantlebury, D; Andersen, K; Gonzalez, G; Giga, V; Vulic, Du; Vataman, E; Cliff, J; Kouidi, E; Yagci, I; Kim, C; Benaim, B; Estany, ER; Fernandez, R; Radi, B; Gaita, D; Simon, A; Chen, SY; Roxburgh, B; Martin, JC; Maskhulia, L; Burdiat, G; Salmon, R; Lomelí, H; Sadeghi, M; Sovova, E; Hautala, A; Tamuleviciute-Prasciene, E; Ambrosetti, M; Neubeck, L; Asher, E; Kemps, H; Eysymontt, Z; Farsky, S; Hayward, J; Prescott, E; Dawkes, S; Santibanez, C; Zeballos, C; Pavy, B; Kiessling, A; Sarrafzadegan, N; Baer, C; Thomas, R; Hu, D; Grace, SLBackground: Despite the epidemic of cardiovascular disease and the benefits of cardiac rehabilitation (CR), availability is known to be insufficient, although this is not quantified. This study ascertained CR availability, volumes and its drivers, and density. Methods: A survey was administered to CR programs globally. Cardiac associations and local champions facilitated program identification. Factors associated with volumes were assessed using generalized linear mixed models, and compared by World Health Organization region. Density (i.e. annual ischemic heart disease [IHD] incidence estimate from Global Burden of Disease study divided by national CR capacity) was computed. Findings: CR was available in 111/203 (54.7%) countries; data were collected in 93 (83.8% country response; N = 1082 surveys, 32.1% program response rate). Availability by region ranged from 80.7% of countries in Europe, to 17.0% in Africa (p < .001). There were 5753 programs globally that could serve 1,655,083 patients/year, despite an estimated 20,279,651 incident IHD cases globally/year. Volume was significantly greater where patients were systematically referred (odds ratio [OR] = 1.36, 95% confidence interval [CI] = 1.35-1.38) and programs offered alternative models (OR = 1.05, 95%CI = 1.04-1.06), and significantly lower with private (OR = .92, 95%CI = .91-.93) or public (OR = .83, 95%CI = .82-84) funding compared to hybrid sources.Median capacity (i.e., number of patients a program could serve annually) was 246/program (Q25-Q75 = 150-390). The absolute density was one CR spot per 11 IHD cases in countries with CR, and 12 globally. Interpretation: CR is available in only half of countries globally. Where offered, capacity is grossly insufficient, such that most patients will not derive the benefits associated with participation.
- Frailty and Cardiac Rehabilitation: a Call to Action from the EAPC Cardiac Rehabilitation SectionPublication . Vigorito, C; Abreu, A; Ambrosetti, M; Belardinelli, R; Corrà, U; Cupples, M; Davos, C; Hoefer, S; Iliou, MC; Schmid, JP; Voeller, H; Doherty, PFrailty is a geriatric syndrome characterised by a vulnerability status associated with declining function of multiple physiological systems and loss of physiological reserves. Two main models of frailty have been advanced: the phenotypic model (primary frailty) or deficits accumulation model (secondary frailty), and different instruments have been proposed and validated to measure frailty. However measured, frailty correlates to medical outcomes in the elderly, and has been shown to have prognostic value for patients in different clinical settings, such as in patients with coronary artery disease, after cardiac surgery or transvalvular aortic valve replacement, in patients with chronic heart failure or after left ventricular assist device implantation. The prevalence, clinical and prognostic relevance of frailty in a cardiac rehabilitation setting has not yet been well characterised, despite the increasing frequency of elderly patients in cardiac rehabilitation, where frailty is likely to influence the onset, type and intensity of the exercise training programme and the design of tailored rehabilitative interventions for these patients. Therefore, we need to start looking for frailty in elderly patients entering cardiac rehabilitation programmes and become more familiar with some of the tools to recognise and evaluate the severity of this condition. Furthermore, we need to better understand whether exercise-based cardiac rehabilitation may change the course and the prognosis of frailty in cardiovascular patients.
- The European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) Tool: a Digital Training and Decision Support System for Optimized Exercise Prescription in Cardiovascular Disease. Concept, Definitions and Construction MethodologyPublication . Hansen, D; Dendale, P; Coninx, K; Vanhees, L; Piepoli, M; Niebauer, J; Cornelissen, V; Pedretti, R; Geurts, E; Ruiz, G; Corrà, U; Schmid, JP; Greco, E; Davos, C; Edelmann, F; Abreu, A; Rauch, B; Ambrosetti, M; Braga, S; Barna, O; Beckers, P; Bussotti, M; Fagard, R; Faggiano, P; Garcia-Porrero, E; Kouidi, E; Lamotte, M; Neunhäuserer, D; Reibis, R; Spruit, M; Stettler, C; Takken, T; Tonoli, C; Vigorito, C; Völler, H; Doherty, PBackground Exercise rehabilitation is highly recommended by current guidelines on prevention of cardiovascular disease, but its implementation is still poor. Many clinicians experience difficulties in prescribing exercise in the presence of different concomitant cardiovascular diseases and risk factors within the same patient. It was aimed to develop a digital training and decision support system for exercise prescription in cardiovascular disease patients in clinical practice: the European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool. Methods EXPERT working group members were requested to define (a) diagnostic criteria for specific cardiovascular diseases, cardiovascular disease risk factors, and other chronic non-cardiovascular conditions, (b) primary goals of exercise intervention, (c) disease-specific prescription of exercise training (intensity, frequency, volume, type, session and programme duration), and (d) exercise training safety advices. The impact of exercise tolerance, common cardiovascular medications and adverse events during exercise testing were further taken into account for optimized exercise prescription. Results Exercise training recommendations and safety advices were formulated for 10 cardiovascular diseases, five cardiovascular disease risk factors (type 1 and 2 diabetes, obesity, hypertension, hypercholesterolaemia), and three common chronic non-cardiovascular conditions (lung and renal failure and sarcopaenia), but also accounted for baseline exercise tolerance, common cardiovascular medications and occurrence of adverse events during exercise testing. An algorithm, supported by an interactive tool, was constructed based on these data. This training and decision support system automatically provides an exercise prescription according to the variables provided. Conclusion This digital training and decision support system may contribute in overcoming barriers in exercise implementation in common cardiovascular diseases.