Current Concepts: Comprehensive "Cardiovascular Health" Rehabilitation-An Integrated Approach to Improve Secondary Prevention and Rehabilitation of Cardiovascular Diseases

Cardiac rehabilitation and adverse events among adult patients with simple congenital heart disease and heart failure

Aims

Improved care has resulted in prolonged survival of patients with congenital heart disease (ConHD), increasing age-related cardiovascular comorbidities. Although cardiovascular rehabilitation (CR) represents evidence-based care for heart failure (HF), the clinical impact of CR in patients with ConHD who developed HF during adulthood is unclear. We investigated 12-month mortality and morbidity in patients with simple ConHD diagnosed with HF with CR versus without CR.

Methods

A retrospective cohort study was conducted for the time period February 2004 - February 2024. Utilizing TriNetX, a global federated health research network, a real-world dataset of simple ConHD patients was acquired to compare patients with vs. without (controls) prescription for exercise-based CR. Patients were propensity-score matched for age, sex, ethnicity, comorbidities, procedures, and medication. The primary outcome was a composite of all-cause mortality, ischemic stroke, and acute coronary syndrome (major adverse cardiovascular events; MACE) within 12 months.

Results

Following propensity score matching, the total cohort consisted of 6,866 simple ConHD patients with HF. CR was associated with significantly lower odds for MACE (odds ratio (OR) 0.61 [95 % confidence interval (CI): 0.54-0.69]) and its individual components all-cause mortality (OR 0.40 [95 % CI 0.33-0.47]) and ischemic stroke (OR 0.75 [95 % CI 0.64-0.88]), but not acute coronary syndrome (OR 1.24 [95 % CI 0.91-1.69]).

Conclusion

CR was associated with significantly lower 12-month MACE in patients with simple ConHD with concomitant HF compared to usual care.

Adherence to an integrated care pathway for stroke is associated with lower risk of major cardiovascular events: A report from the Athens Stroke Registry

BACKGROUND

A recent European Society of Cardiology (ESC) Council on Stroke position paper proposed a holistic integrated care management approach for stroke patients, to improve cardiovascular outcomes. The impact of implementing the ABCstroke pathway 'concept' on clinical outcomes has never been estimated before. In order to investigate the potential effect of ABCstroke pathway adherence to cardiovascular outcomes post stroke, we performed a post-hoc analysis from the Athens Stroke Registry.

METHODS AND RESULTS

This analysis was performed in the Athens Stroke Registry, which includes all consecutive patients with acute first-ever ischemic stroke. The Kaplan-Meier product limit was used to estimate the cumulative hazard of each outcome according to adherence with the ABCstroke pathway. We studied 2513 patients [median (IQR) age 71 (62-78) years; 37.7 % female] with ischemic stroke with median follow-up period of 30 (6-75) months. Full adherence to the ABC pathway was identified in 156 (6.2 %) of the patients, while 192 (7.6 %) did not adhere to any of the therapeutic pillars of ABCstroke. Full adherence to ABC treatment pathway was associated with significant reduction of stroke recurrence, compared to patients with no or partial adherence (aHR: 0.61; 95 %CI: 0.37-0.99), as well as a lower risk of MACE (HR: 0.59; 0.39-0.88) and death (aHR: 0.22; 95 %CI: 0.12-0.41).

CONCLUSION

Full adherence to the ABCstroke pathway based on the current guidelines was evident in only 6.2 % of our ischaemic stroke cohort but was independently associated with lower risks of stroke recurrence, major cardiovascular events and mortality. This highlights a potential opportunity to improve clinical outcomes post-stroke with a holistic or integrated care management approach.

Validating the predictive ability of the 2MACE score for major adverse cardiovascular events in patients with atrial fibrillation: results from phase II/III of the GLORIA-AF registry

The 2MACE score was specifically developed as a risk-stratification tool in atrial fibrillation (AF) to predict cardiovascular outcomes. We evaluated the predictive ability of the 2MACE score in the GLORIA-AF registry. All eligible patients from phase II/III of the prospective global GLORIA-AF registry were included. Major adverse cardiac events (MACEs) were defined as the composite outcome of stroke, myocardial infarction and cardiovascular death. Cox proportional hazards were used to examine the relationship between the 2MACE score and study outcomes. Predictive capability of the 2MACE score was investigated using receiver-operating characteristic curves. A total of 25,696 patients were included (mean age 71 years, female 44.9%). Over 3 years, 1583 MACEs were recorded. Patients who had MACE were older, with more cardiovascular risk factors and were less likely to be managed using a rhythm-control strategy. The median 2MACE score in the MACE and non-MACE groups were 2 (IQR 1-3) and 1 (IQR 0-2), respectively (p < 0.001). The 2MACE score was positively associated with an increase in the risk of MACE, with a score of ≥ 2 providing the best combination of sensitivity (69.6%) and specificity (51.6%), HR 2.47 (95% CI, 2.21-2.77). The 2MACE score had modest predictive performance for MACE in patients with AF (AUC 0.655 (95% CI, 0.641-0.669)). Our analysis in this prospective global registry demonstrates that the 2MACE score can adequately predict the risk of MACE (defined as myocardial infarction, CV death and stroke) in patients with AF. Clinical trial registration: http://www.clinicaltrials.gov . Unique identifiers: NCT01468701, NCT01671007 and NCT01937377.

Cardiovascular disease (CVD) outcomes and associated risk factors in a medicare population without prior CVD history: an analysis using statistical and machine learning algorithms

There is limited information on predicting incident cardiovascular outcomes among high- to very high-risk populations such as the elderly (≥ 65 years) in the absence of prior cardiovascular disease and the presence of non-cardiovascular multi-morbidity. We hypothesized that statistical/machine learning modeling can improve risk prediction, thus helping inform care management strategies. We defined a population from the Medicare health plan, a US government-funded program mostly for the elderly and varied levels of non-cardiovascular multi-morbidity. Participants were screened for cardiovascular disease (CVD), coronary or peripheral artery disease (CAD or PAD), heart failure (HF), atrial fibrillation (AF), ischemic stroke (IS), transient ischemic attack (TIA), and myocardial infarction (MI) for a 3-yr period in the comorbid history. They were followed up for up to 45.2 months. Analyses included descriptive approaches in terms of incidence rates and density ratios, and inferential in terms of main effect statistical/complex machine learning modeling. The contemporary risk factors of interest spanned across the domains of comorbidity, lifestyle, and healthcare utilization history. The cohort consisted of 154,551 individuals (mean age 68.8 years; 62.2% female). The overall crude incidence rate of CVD events was 9.9 new cases per 100 person-years. The highest rates among its component outcomes were obtained for CAD or PAD (3.6 for each), followed by HF (2.2) and AF (1.8), then IS (1.3), and finally TIA (1.0) and MI (0.9).Model performance was modest in terms of discriminatory power (C index: 0.67, 95%CI 0.667-0.674 for training; and 0.668, 95%CI 0.663-0.673 for validation data), equal agreement between predicted and observed events for calibration purposes, and good clinical utility in terms of a net benefit of 15 true positives per 100 patients relative to the All-patient treatment strategy. Complex models based on machine learning algorithms yielded incrementally better discriminatory power and much improved goodness-of-fitness tests from those based on main effect statistical modeling. This Medicare population represents a highly vulnerable group for incident CVD events. This population would benefit from an integrated approach to their care and management, including attention to their comorbidities and lifestyle factors, as well as medication adherence.