Long-term benefits of cardiac rehabilitation after incomplete percutaneous revascularization

Background Incomplete revascularization versus complete revascularization in patients undergoing percutaneous coronary intervention (PCI) is associated with higher risk of mortality and major adverse cardiac events. Cardiac rehabilitation (CR) is one of the most important evidence-based interventions for secondary prevention after ischemic heart disease. However, it has been less studied in patients with incomplete PCI. Purpose The aim of our study was to evaluate the effects of CR on long-term clinical outcomes after incomplete PCI. Methods Unicentric, descriptive and analitical study. We included 285 patients who underwent incomplete PCI at our hospital from 2004 to 2011. We compared those who participated in a CR program with those who refused to. We analyzed events occurring during a median follow-up of 11 years. Results This study included 285 patients, 121 (42.5%) participated in the CR program. Attending to baseline characteristics, there were significant differences in prevalence of male gender (88.4% vs 67.7%, p=0.000) and DM (69.4% vs 51.8%, p=0.003), which were more prevalent in CR group; they were also significantly younger (58.81 vs 66.34 years, p=0.000). Acute myocardial infarction (AMI) was the most common indication for PCI in those who attended CR, whereas in the other group it was unstable angina. Using univariate logistic analysis, CR participation was found to be associated with significantly reduced heart failure readmissions (14.2% vs 31.7%; OR 0.356; IC95% 0.193- 0.656; p=0.001), all-cause mortality (21.5% vs 56.7%; OR 0.209; IC95% 0.123- 0.356; p=0.000) and cardiovascular mortality (5.8% vs 26.8%; OR 0.167; IC95% 0.072- 0.387; p 0.000). No significant differences were observed in re-AMI (20.8% vs 26.4%, p=0.280) nor incidence of stroke (5.8% vs 9.8%, p=0.226) during the follow-up. The multivariate regression showed as well that CR was associated with a lower rate of all-cause and cardiovascular mortality and heart failure readmissions. Other predictors of clinical outcomes were NYHA stage, age >65 years and LVEF <40%. Conclusion CR is an excellent strategy for reducing hospital readmissions and mortality during long-term follow-up in patients with incomplete PCI. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Hospital Universitario de Valme, Sevilla, Spain Baseline characteristics

An evidence-based data science perspective on the prediction of heart failure readmissions

The prevention of unplanned 30-day readmissions of patients discharged with a diagnosis of heart failure (HF) remains a profound challenge among hospital enterprises. Despite the many models and indices developed to predict which HF patients will readmit for any unplanned cause within 30 days, predictive success has been meager. Using simulations of HF readmission models and the diagnostics most often used to evaluate them (C-statistics, ROC curves), we demonstrate common factors that have contributed to the lack of predictive success among studies. We reveal a greater need for precision and alternative metrics such as partial C-statistics and precision-recall curves and demonstrate via simulations how those tools can be used to better gauge predictive success. We suggest how studies can improve their applicability to hospitals and call for a greater understanding of the uncertainty underlying 30-day all-cause HF readmission. Finally, using insights from sampling theory, we suggest a novel uncertainty-based perspective for predicting readmissions and non-readmissions.

A Patient-Centric Care Approach to Facilitate the Design of an Artificial Intelligence Application in Geriatric Care Management of Heart Failure Readmissions

The examination of human factors’ role in moderating medical interventions and hospitalizations and/or rehospitalization of heart failure (HF) patients. Objectives: The primary purpose of this study is two-fold: 1) to show relevant human factors influencing the rehospitalization of persons with heart failure by developing a systematic algorithm generated from the cited randomized trials; and 2) to examine how the self-care principles, such as choice/efficacy, restfulness, healing environment, activity, trust, interpersonal relationships, outlook, and nutrition, may reduce heart failure readmissions. Methods: The meta-analytic approach generated a theoretically relevant and empirically validated self-care management decision support protocol for HF. Statistical modeling of the effects of eight human factors for the reduction of HF readmissions was presented. Findings: The systematic review and meta-analysis approach documents the results of randomized clinical trials that affect heart failure hospitalization by selected human factors. A patient-centered decision support system was developed to facilitate the self-care management of heart failure. Discussion: Our research generates systematic knowledge about the importance of human-factor principles in the provision of geriatric care for heart failure. Using shared decision-making strategies under the population health management approach could enhance the quality of care and reduce costly readmissions of heart failure, particularly for elderly patients.