Evaluating the Effects of an Enhanced Strength Training Program in Remote Cardiological Rehabilitation: A Shift from Aerobic Dominance-A Pilot Randomized Controlled Trial.

(1) Background: Cardiac rehabilitation often emphasizes aerobic capacity while overlooking the importance of muscle strength. This study evaluated the impact of an enhanced remote strength training program (RCR-ST) on cardiac rehabilitation. (2) Methods: In this randomized prospective study (RCT registration number SMC-9080-22), 50 patients starting cardiac rehabilitation were assessed for muscle strength, aerobic capacity, and self-reported outcomes at baseline and after 16 weeks. Participants were divided into two groups: the RCR-ST group received a targeted resistance training program via a mobile app and smartwatch, while the control group received standard care with general resistance training advice. (3) Results: The RCR-ST group demonstrated significant improvements in muscle endurance, notably in leg extension and chest press exercises, with increases of 92% compared to 25% and 92% compared to 13% in the control group, respectively. Functional assessments (5-STS and TUG tests) also showed marked improvements in agility, coordination, and balance. Both groups improved in cardiorespiratory fitness, similarly. The RCR-ST group reported enhanced physical health and showed increased engagement, as evidenced by more frequent use of the mobile app and longer participation in the rehabilitation program (p < 0.05). (4) Conclusions: Incorporating a focused strength training regimen in remote cardiac rehabilitation significantly improves muscle endurance and patient engagement. The RCR-ST program presents a promising approach for optimizing patient outcomes by addressing a crucial gap in traditional rehabilitation protocols that primarily focus on aerobic training.

The Clinical SYNTAX score predicts survival better than the SYNTAX score in coronary revascularization.

BACKGROUND: The Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery (SYNTAX) trial showed that the SYNTAX score (SS) is a useful tool for customizing revascularization treatment for patients with multivessel coronary disease. In the past decade, the Clinical SS (CSS) has emerged as a comprehensive tool. This novel tool considers the SS as well as patient clinical parameters such as age, creatinine clearance, and ejection fraction, which were shown to be relevant for patient prognosis. Thus, in the current work we set out to compare the survival predictive values of the SS versus the CSS and their future application in real-world implementation of the revascularization guidelines. METHODS: This study was a subanalysis of data collected in a prospective national registry in Israel that enrolled consecutive patients with left main and/or 2- to 3-vessel coronary artery disease involving the proximal or mid-left anterior descending artery; the MULTI-vessel Coronary Artery Disease (MULTICAD). The revascularization method was chosen by the physicians taking care of the patients at each hospital and the patients were followed for 5 years. Patients were categorized according to their SS, the CSS, and their revascularization method (primary coronary intervention [PCI] vs coronary artery bypass grafting [CABG]) and patient survival were compared. RESULTS: A total of 585 patients were enrolled in the study and were followed for 5 years. The median CSS was 27, with 288 patients showing a CSS ≥27, with a mean CSS of 47.85 and a mean SS of 29.05. At 3 and 5 years post-treatment, the CSS ≥27 group had a lower survival probability, CSS ≥27 was associated with a lower survival probability among patients who underwent PCI compared with those who underwent CABG. More specifically, the high-CSS CABG group had a 5-year mortality rate of 16.8%, whereas the high-CSS PCI group had a 5-year mortality rate of 32.2%. In a comparison of SS with CSS for the 5-year mortality outcome prediction, CSS was superior to SS with a higher area under the curve. CONCLUSIONS: This prospective registry of real-world revascularization strategies in patients with multivessel disease showed that CSS is a better predictive tool of postrevascularization survival than SS. Moreover, it showed that surgical revascularization in patients with CSS ≥27 is associated with better all-cause mortality outcome after CABG as compared with after PCI. This attests to the need for a score that considers clinical parameters in a real-world scenario.

Artificial Intelligence Assessment of Biological Age From Transthoracic Echocardiography: Discrepancies with Chronologic Age Predict Significant Excess Mortality.

BACKGROUND: Age and sex can be estimated using artificial intelligence on the basis of various sources. The aims of this study were to test whether convolutional neural networks could be trained to estimate age and predict sex using standard transthoracic echocardiography and to evaluate the prognostic implications. METHODS: The algorithm was trained on 76,342 patients, validated in 22,825 patients, and tested in 20,960 patients. It was then externally validated using data from a different hospital (n = 556). Finally, a prospective cohort of handheld point-of-care ultrasound devices (n = 319; ClinicalTrials.gov identifier NCT05455541) was used to confirm the findings. A multivariate Cox regression model was used to investigate the association between age estimation and chronologic age with overall survival. RESULTS: The mean absolute error in age estimation was 4.9 years, with a Pearson correlation coefficient of 0.922. The probabilistic value of sex had an overall accuracy of 96.1% and an area under the curve of 0.993. External validation and prospective study cohorts yielded consistent results. Finally, survival analysis demonstrated that age prediction ≥5 years vs chronologic age was associated with an independent 34% increased risk for death during follow-up (P < .001). CONCLUSIONS: Applying artificial intelligence to standard transthoracic echocardiography allows the prediction of sex and the estimation of age. Machine-based estimation is an independent predictor of overall survival and, with further evaluation, can be used for risk stratification and estimation of biological age.