Heart Disease Patients Research Articles

Application of the Unbalanced Ensemble Algorithm for Prognostic Prediction Outcomes of All-Cause Mortality in Coronary Heart Disease Patients Comorbid with Hypertension.

This study sought to develop an unbalanced-ensemble model that could accurately predict death outcomes of patients with comorbid coronary heart disease (CHD) and hypertension and evaluate the factors contributing to death. Medical records of 1058 patients with coronary heart disease combined with hypertension and excluding those acute coronary syndrome were collected. Patients were followed-up at the first, third, sixth, and twelfth months after discharge to record death events. Follow-up ended two years after discharge. Patients were divided into survival and nonsurvival groups. According to medical records, gender, smoking, drinking, COPD, cerebral stroke, diabetes, hyperhomocysteinemia, heart failure and renal insufficiency of the two groups were sorted and compared and other influencing factors of the two groups, feature selection was carried out to construct models. Owing to data unbalance, we developed four unbalanced-ensemble prediction models based on Balanced Random Forest (BRF), EasyEnsemble, RUSBoost, SMOTEBoost and the two base classification algorithms based on AdaBoost and Logistic. Each model was optimised using hyperparameters based on GridSearchCV and evaluated using area under the curve (AUC), sensitivity, recall, Brier score, and geometric mean (G-mean). Additionally, to understand the influence of variables on model performance, we constructed a SHapley Additive explanation (SHAP) model based on the optimal model. There were significant differences in age, heart rate, COPD, cerebral stroke, heart failure and renal insufficiency in the nonsurvival group compared with the survival group. Among all models, BRF yielded the highest AUC (0.810; 95% CI, 0.778-0.839), sensitivity (0.990; 95% CI, 0.981-1.000), recall (0.990; 95% CI, 0.981-1.000), and G-mean (0.806; 95% CI, 0.778-0.827), and the lowest Brier score (0.181; 95% CI, 0.178-0.185). Therefore, we identified BRF as the optimal model. Furthermore, red blood cell count (RBC), body mass index (BMI), and lactate dehydrogenase were found to be important mortality-associated risk factors. BRF combined with advanced machine learning methods and SHAP is highly effective and accurately predicts mortality in patients with CHD comorbid with hypertension. This model has the potential to assist clinicians in modifying treatment strategies to improve patient outcomes.

3D regional evaluation of right ventricular myocardial work from cineCT.

Regional myocardial work (MW) is not measured in the right ventricle (RV) due to a lack of high spatial resolution regional strain (RS) estimates throughout the ventricle. We present a cineCT-based approach to evaluate regional RV performance and demonstrate its ability to phenotype three complex populations: end-stage LV failure (HF), chronic thromboembolic pulmonary hypertension (CTEPH), and repaired tetralogy of Fallot (rTOF). 49 patients (19 HF, 11 CTEPH, 19 rTOF) underwent cineCT and right heart catheterization (RHC). RS was estimated from full-cycle ECG-gated cineCT and combined with RHC pressure waveforms to create regional pressure-strain loops; endocardial MW was measured as the loop area. Detailed, 3D mapping of RS and MW enabled spatial visualization of strain and work strength, and phenotyping of patients. HF patients demonstrated more overall impaired strain and work compared to the CTEPH and rTOF cohorts. For example, the HF patients had more akinetic areas (median: 9%) than CTEPH (median: <1%, p=0.02) and rTOF (median: 1%, p<0.01) and performed more low work (median: 69%) than the rTOF cohort (median: 38%, p<0.01). The CTEPH cohort had more impairment in the septal wall; <1% of the free wall and 16% of the septal wall performed negative work. The rTOF cohort demonstrated a wide distribution of strain and work, ranging from hypokinetic to hyperkinetic strain and low to medium-high work. Impaired strain (-0.15≤RS) and negative work were strongly-to-very strongly correlated with RVEF (R=-0.89, p<0.01; R=-0.70, p<0.01 respectively), while impaired work (MW≤5 mmHg) was moderately correlated with RVEF (R=-0.53, p<0.01). Regional RV MW maps can be derived from clinical CT and RHC studies and can provide patient-specific phenotyping of RV function in complex heart disease patients. Evaluating regional variations in right ventricular (RV) performance can be challenging, particularly in patients with significant impairments due to the need for 3D spatial coverage with high spatial resolution. ECG-gated cineCT can fully visualize the RV and be used to quantify regional strain with high spatial resolution. However, strain is influenced by loading conditions. Myocardial work (MW) - measured clinically derived as the ventricular pressure-strain loop area - is considered a more comprehensive metric due to its independence of preload and afterload. In this study, we sought to develop regional RV myocardial work (MW) assessments in 3D with high spatial resolution by combining cineCT-derived regional strain with RV pressure waveforms from right heart catheterization (RHC). We developed our method using data from three clinical cohorts who routinely undergo cineCT and RHC: patients in heart failure, patients with chronic thromboembolic pulmonary hypertension, and adults with repaired tetralogy of Fallot.We demonstrate that regional strain and work provide different perspectives on RV performance. While strain can be used to evaluate apparent function, similar profiles of RV strain can lead to different MW estimates. Specifically, MW integrates apparent strain with measures of afterload, and timing information helps to account for dyssynchrony. As a result, CT-based assessment of RV MW appears to be a useful new metric for the care of patients with dysfunction.

Association of social support and health status outcomes in peripheral artery disease

ObjectiveA critical goal in the care of patients with peripheral artery disease (PAD) is to optimize their health status; that is, their symptoms, function, and quality of life. Social support has been proposed to be a predictor of disease-specific health status in patients with PAD. However, the prevalence of low perceived social support, the association with health status outcomes, and the interaction with other biopsychosocial variables, is unknown. Our aim was to assess the association of baseline perceived social support with health status at 12 months in patients with PAD. MethodsThe Patient-Centered Outcomes Related Treatment Practices in Peripheral Arterial Disease: Investigating Trajectories (PORTRAIT) registry, which enrolled patients with PAD in the United States, the Netherlands, and Australia from 2011 to 2015, was used. Perceived social support was assessed at baseline with the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) Social Support Inventory (ESSI), and disease-specific (Peripheral Artery Disease Questionnaire [PAQ]) and generic health status (Euro-Quality of Life Visual Analog Scale [VAS] and EQ-5D-3L Index) questionnaires were assessed at baseline and 12 months. Low social support was defined as a score of ≤3 on two items and an ESSI score of ≤18. A hierarchical mixed level linear regression model adjusting for biopsychosocial variables was used to assess the association between low perceived social support and the ESSI score with health status at 12 months. ResultsA total of 949 patients were included (mean age, 67.64 ± 9.32 years; 37.9% female), with low social support being present in 18.2%. Patients with low social support were more likely to not be married or to be living alone (50.0% vs 77.5%; P < .001); have more financial constraints; have more depressive, stress, and anxiety symptoms; and have lower disease-specific and generic health status at baseline and at 12 months. In the unadjusted model, low social support was associated with a −7.02 (95% confidence interval [CI], −10.97 to −3.07) point reduction in the PAQ, −7.43 (95% CI, −10.33 to −4.54) in the VAS, and −0.06 (95% CI, −0.09 to −0.03) in the EQ-5D-3L Index. Adjusting for biopsychosocial factors minimally attenuated these associations (PAQ: −6.52; 95% CI, −10.55 to −2.49; P = .002; VAS: −5.39; 95% CI, 8.36 to −2.42; P < .001; EQ-5D-3L Index: −0.04; 95% CI, −0.07 to 0.01; P = .022). The ESSI per-point score was associated with a decrease of 0.51 (95% CI, 0.18-0.85; P = .003) in PAQ and 0.46 (95% CI, 0.12-0.61; P = .004) in the VAS. ConclusionsAmong patients with PAD, low social support was frequent and associated with a lower health status at 1 year independent of other biopsychosocial variables. Improving social support could improve health status and outcomes in PAD.

Integrating risks and benefits: pretransplant assessment and patient selection for heart transplantation in adult congenital heart disease.

The number of adult congenital heart disease (ACHD) patients presenting for consideration of heart transplantation continues to grow. Comprehensive pretransplant assessment and thoughtful patient selection are of critical importance to mitigate perioperative and posttransplant morbidity and mortality in this population. There is increasing evidence that patient outcomes after the onset of heart failure in the ACHD population are poor while overall transplant outcomes for ACHD patients have improved over time. Delineation of factors associated with better versus worse posttransplant outcomes is an area of ongoing research. Several studies have found that delayed patient referral, anatomic complexity and the presence of noncardiac organ dysfunction may increase peri-transplant and posttransplant risk. Pretransplant assessment and patient selection in ACHD patients should focus on mitigating perioperative and early posttransplant risk. Anatomic complexity, noncardiac organ dysfunction, and referral timing after the onset of heart failure can contribute to poor posttransplant outcomes and should inform patient selection.

Extracellular vesicles loaded with ApoB-100 protein affect the occurrence of coronary heart disease in patients after injury of spinal cord

Spinal cord injury (SCI) patients have an increased susceptibility to coronary heart disease (CHD) due to dysregulated lipid deposition. We conducted a comprehensive investigation to gain insights into the specific roles of Apolipoprotein B-100 (APOB-100) in the development of CHD in patients suffering from SCI. First, we established an SCI rat model through semitransection. APOB-100 expression in plasma exosomes obtained from patients were determined. Subsequently, we found APOB-100 affected macrophage polarization when treating co-cultured neurons/macrophages lacking Sortilin with extracellular vesicles derived from SCI rats, where APOB-100 co-immunoprecipitated with Sortilin. Moreover, APOB-100 upregulation reduced neuronal cell viability and triggered apoptosis by upregulating Sortilin, leading to a decline in the Basso, Beattie, and Bresnahan (BBB) scale, exacerbation of neuron injury, increased macrophage infiltration, and elevated blood lipid-related indicators in SCI rats, which could be reversed by silencing Sortilin. In conclusion, APOB-100 from post-SCI patients' extracellular vesicles upregulates Sortilin, thereby endangering those patients to CHD.

Screening for Chronic Obstructive Pulmonary Disease in Patients with Coronary Artery Disease at a Tertiary Care Hospital

Chronic Obstructive Pulmonary Disease is a common, preventable and treatable disease that is characterized by persistent respiratory symptoms and airflow limitation that is due to airway and/or alveolar abnormalities usually caused by significant exposure to noxious gases or particles and influenced by host factors, including abnormal lung development. COPD was the 4th most common cause of death globally, and it was anticipated to rise to the 3rd position by 2020 or sooner. Over 80% of these patients go undiagnosed. COPD and CAD frequently co-exist and interact due to various reasons like similar risk factors and pathogenesis. Although there are global studies on the prevalence of COPD in CAD patients, data from India are scarce. This study aims to find the prevalence of COPD among CAD patients and find the correlation between the occurrence of COPD and cardiac status. This study was conducted as a prospective observational cross-sectional study at Chettinad Hospital and Research Institute in India. 293 patients with angiographically proven CAD underwent pulmonary function evaluation by spirometry to assess the prevalence of COPD. Recent 2D-ECHO was also correlated. The study found that 18.77% of 293 Coronary Artery Disease (CAD) patients had COPD and 3.07% had PRISM( preserved ratio impaired spirometry, a new term coined), making it one of the few studies to report the prevalence of PRISM among CAD patients. Outside of India, studies have found that COPD prevalence ranges from 7% to 33.6% among ischemic heart disease patients. Impairment of spirometry positively correlated with the severity of CAD. Our study found a considerable frequency of missed COPD diagnoses. Hence, we recommend that when CAD is diagnosed, the initial evaluation should include a complete history of respiratory symptoms, clinical examination, and spirometry to assess pulmonary function, particularly in those who have risk factors such as smoking and the use of biomass fuel so as to identify COPD at an early stage and treat it. Identifying PRISM can help prevent its progression to COPD by making the required lifestyle modifications. A multidisciplinary approach is advised for all those diagnosed to have CAD.

Impact of eccentric cycling in coronary rehabilitation program: a pragmatic randomized controlled trial versus conventional rehabilitation.

This randomized controlled trial examined the feasibility of adding eccentric exercise to a conventional cardiac rehabilitation program (CCRP) for coronary heart disease patients. Ninety-three patients were randomly assigned to either the MIX group (eccentric ergometer + CCRP) or the CON group (concentric ergometer + CCRP) for 7 weeks. Training effectiveness was assessed based on "good responders" showing improved functional capacities, such as 6-minute walk test (6MWT) distance and maximal voluntary contraction of the plantar flexors (ankle MVC). Safety was monitored with a visual analog scale for muscle soreness, perceived exertion, and heart rate during training. The proportion of good responders was similar between groups (26% in MIX, 29% in CON, P=0.744). Both groups improved in 6MWT (CON: 12.6%, MIX: 16.14%) and ankle MVC (CON: 15.5%, MIX: 11.30%), with no significant differences. Exercise tolerance did not differ significantly between the groups, but perceived effort was significantly lower in the MIX group (P<0.0001) compared to the CON group. Integrating eccentric exercise into cardiac rehabilitation is safe and well-tolerated. Nevertheless, this study did not find significant advantages over conventional programs for coronary heart disease patients. Further research should explore specific patient groups or conditions where eccentric exercise may be more beneficial, emphasizing personalized prescriptions and gradual workload progression for better cardiac rehabilitation outcomes.

Growth differentiation factor-15 predicts all-cause death and major adverse cardiovascular events in patients with coronary heart disease: a prospective cohort study.

The prognostic value of growth differentiation factor-15 (GDF-15) in predicting long-term adverse outcomes in coronary heart disease (CHD) patients remains limited. Our study examines the association between GDF-15 and adverse outcomes over an extended period in CHD patients and firstly assesses the incremental prognostic effect of incorporating GDF-15 into the Framingham risk score (FRS)-based model. This single-center prospective cohort study included 3,321 patients with CHD categorized into 2,479 acute coronary syndrome (ACS) (74.6%) and 842 non-ACS (25.4%) groups. The median age was 61.0 years (range: 53.0-70.0), and 917 (27.6%) were females. Mortality and major adverse cardiovascular events (MACEs) included cardiovascular mortality, myocardial infarction (MI), stroke, and heart failure (HF) (inclusive of HF episodes requiring outpatient treatment and/or hospital admission). Cox regression models assessed the associations between GDF-15 and the incidence of all-cause mortality and MACEs. Patients were stratified into three groups based on GDF-15 levels: the first tertile group (< 1,370 ng/L), the second tertile group (1,370-2,556 ng/L), and the third tertile group (> 2,556 ng/L). The C-index, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA) were used to assess incremental value. Over a median 9.4-year follow-up, 759 patients (22.9%) died, and 1,291 (38.9%) experienced MACEs. The multivariate Cox model indicated that GDF-15 was significantly associated with all-cause mortality (per ln unit increase, HR = 1.49, 95% CI: 1.36-1.64) and MACEs (per ln unit increase, HR = 1.29, 95% CI: 1.20-1.38). These associations persisted when GDF-15 was analyzed as an ordinal variable (p for trend < 0.05). Subgroup analysis of ACS and non-ACS for the components of MACEs separately showed a significant association between GDF-15 and both cardiovascular mortality and HF, but no association was observed between GDF-15 and MI /stroke in both ACS and non-ACS patients. The addition of GDF-15 to the FRS-based model enhanced the discrimination for both all-cause mortality (∆ C-index = 0.009, 95% CI: 0.005-0.014; IDI = 0.030, 95% CI: 0.015-0.047; continuous NRI = 0.631, 95% CI: 0.569-0.652) and MACEs (∆ C-index = 0.009, 95% CI: 0.006-0.012; IDI = 0.026, 95% CI: 0.009-0.042; continuous NRI = 0.593, 95% CI: 0.478-0.682). DCA suggested that incorporating GDF-15 into the FRS-based model demonstrated higher net benefits compared to FRS-based models alone (All-cause mortality: FRS-based model: area under the curve of DCA (AUDC) = 0.0903, FRS-based model + GDF-15: AUDC = 0.0908; MACEs: FRS-based model: AUDC = 0.1806, FRS-based model + GDF-15: AUDC = 0.1833). GDF-15 significantly associates with the long-term prognosis of all-cause mortality and MACEs in CHD patients and significantly improves the prognostic accuracy of the FRS-based model for both outcomes.

Efficacy and Safety of Warfarin Utilisation in Rheumatic Heart Disease Patients With Mechanical Heart Valves in Remote Northwest Queensland

Efficacy and Safety of Warfarin Utilisation in Rheumatic Heart Disease Patients With Mechanical Heart Valves in Remote Northwest Queensland

The Effectiveness of Early Detection of Heart Disease and Health Promotion on Attitude and Lifestyle Changes of Residents At Risk Of Heart Disease Post-Covid-19 Pandemic

During the Covid-19 pandemic, heart disease patients were at very high risk of experiencing severe complications if exposed to the virus. One important effort in preventing cardiovascular diseases is to identify the cardiovascular risk factors in each individual. There are several models for detecting risk, one of which is the Jakarta Cardiovascular Score. Health promotion is also an effort to manage modifiable risk factors for heart disease. Health promotion is expected to prevent risky behaviors that lead to an increase in heart disease incidence in the long term. This study aims to assess the effectiveness of early detection and health promotion in changing the attitudes and lifestyles of residents at risk of heart disease post-Covid-19 pandemic. The research method used in this study is a quasi-experimental design with one group of 30 respondents. The study was conducted in the working area of the Pasar Minggu District Health Center in Jakarta. The results showed that after the intervention, which included early detection and health promotion, there was a change in attitude by 0.8 points, from 88.13 (before intervention) to 88.95 (after intervention). The T-test results showed a p-value of 0.004, indicating a statistically significant difference between before and after the intervention. The respondents' lifestyle also changed by 5.5 points, from 66.03 (before intervention) to 71.62 (after intervention), with a p-value of 0.004, indicating a statistically significant difference between before and after the intervention.

An ensemble machine learning model for predicting one-year mortality in elderly coronary heart disease patients with anemia

ObjectiveThis study was designed to develop and validate a robust predictive model for one-year mortality in elderly coronary heart disease (CHD) patients with anemia using machine learning methods.MethodsDemographics, tests, comorbidities, and drugs were collected for a cohort of 974 elderly patients with CHD. A prospective analysis was performed to evaluate predictive performances of the developed models. External validation of models was performed in a series of 112 elderly CHD patients with anemia.ResultsThe overall one-year mortality was 43.6%. Risk factors included heart rate, chronic heart failure, tachycardia and β receptor blockers. Protective factors included hemoglobin, albumin, high density lipoprotein cholesterol, estimated glomerular filtration rate (eGFR), left ventricular ejection fraction (LVEF), aspirin, clopidogrel, calcium channel blockers, angiotensin converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs), and statins. Compared with other algorithms, an ensemble machine learning model performed the best with area under the curve (95% confidence interval) being 0.828 (0.805–0.870) and Brier score being 0.170. Calibration and density curves further confirmed favorable predicted probability and discriminative ability of an ensemble machine learning model. External validation of Ensemble Model also exhibited good performance with area under the curve (95% confidence interval) being 0.825 (0.734–0.916) and Brier score being 0.185. Patients in the high-risk group had more than six-fold probability of one-year mortality compared with those in the low-risk group (P < 0.001). Shaley Additive exPlanation identified the top five risk factors that associated with one-year mortality were hemoglobin, albumin, eGFR, LVEF, and ACEIs/ARBs.ConclusionsThis model identifies key risk factors and protective factors, providing valuable insights for improving risk assessment, informing clinical decision-making and performing targeted interventions. It outperforms other algorithms with predictive performance and provides significant opportunities for personalized risk mitigation strategies, with clinical implications for improving patient care.

Clinical Effect of Combination Therapy of Milrinone and Nifedipine in Treating Chronic Pulmonary Heart Disease

Objective: To analyze the therapeutic effect achieved and the occurrence of adverse reactions in patients with chronic pulmonary heart disease treated with milrinone combined with nifedipine. Methods: 120 cases of chronic pulmonary heart disease patients treated in the hospital from May 2023 to February 2024 were selected as research subjects, and based on the randomized numerical table method, the 120 patients were divided into the study group and the comparison group, and the treatment of milrinone combined with nifedipine was carried out for 60 patients in the study group, and the conventional treatment was carried out for 60 patients in the comparison group, so as to make a comparison on the therapeutic effect and the occurrence of adverse reactions of patients in the two groups. The therapeutic effects and adverse reactions of the two groups were compared. Results: After receiving medication of milrinone combined with nifedipine, the patients in the study group had an exertional lung capacity of 68.12 ± 5.63% and a maximal expiratory volume of 82.41 ± 7.84 L/min, which were significantly higher than those in the comparison group, and the total rate of adverse reactions of the patients in the study group was 1.67%, which was significantly lower than that of the comparison group, with a P value of &lt; 0.05, which is statistically significant. Conclusion: In the implementation of treatment for patients with chronic pulmonary heart disease, the treatment of milrinone combined with nifedipine can significantly improve the patient’s exertional lung capacity and maximum expiratory volume, and the chance of adverse reactions in patients will also be significantly reduced.

Immature Surfactant Protein Type B and Surfactant Protein Type D Correlate with Coronary Heart Disease in Patients with Type 2 Diabetes.

Different specific surfactant proteins (SPs) have been associated with various pathological conditions, not only of the respiratory system, but also more recently with cardiovascular diseases, such as heart failure. The aim of the present study was to evaluate the role of SP-A, SP-D, and the precursor protein of SP-B (proSP-B) in the pathogenesis of cardiovascular damage in patients affected by type 2 diabetes (T2D). The study considered 31 patients with T2D (DN group), 34 patients with both T2D and coronary heart disease (CHD) (DC group), and 30 patients without diabetes but with a diagnosis of CHD (NC group). SP-A, SP-D, and proSP-B concentrations were determined in plasma samples, and were statistically compared using parametric and multivariate methods. Higher plasma concentrations of SP-D and proSP-B were found in patients affected by both T2D and CHD (DC group), and in patients with CHD without diabetes (NC group), in comparison to T2D patients (DN group). A significant correlation, both with linear regression (r = 0.3565, p = 0.001) and Principal Component Analysis (PCA), was found between the plasma levels of SP-D and proSP-B in the overall cohort of patients. No differences in SP-A were observed among the three groups of subjects. The present study extends the knowledge on the role of plasma SPs' levels as possible indicators of the risk of CHD being linked to T2D disease progression.

Evaluation of the compliance of diet plans and nutritional advice generated by artificial intelligence with guidelines for cardiac patients

Abstract Introduction In response to the increasing demand for personalization in cardiac dietetics, tools based on artificial intelligence (AI) are gaining popularity. We assess the compliance of AI-generated nutritional advice and diet plans with current dietary standards. Objective The study aims to evaluate whether nutritional advice and diet plans created by AI for heart disease patients align with the recommended caloric intake and macronutrient ratios, based on current dietary guidelines. Methods Using selected AI tools, nutritional advice and diet plans were generated for defined dietary scenarios corresponding to specific cardiac diagnoses. The analysis included assessing the caloric content and macronutrient composition (protein, fat, carbohydrates) compared to current guidelines. Results The analysis showed that the majority of the AI-generated diet plans and nutritional advice were compliant with dietary recommendations, with an &amp;gt;75% compliance rate for caloric content and macronutrient ratios. However, instances of non-compliance were discovered, suggesting a need for further adjustment of AI algorithms. Conclusions AI tools demonstrate potential in creating personalized diet plans for cardiac patients but require optimization to fully meet current dietary guidelines. The study highlights the importance of integrating dietary knowledge into the design process of AI tools, which is crucial for providing high-quality nutritional support.

Feasibility and effectiveness of cardiac telerehabilitation for older adults with coronary heart disease patients: a pilot randomized controlled trial

Abstract Background Cardiac rehabilitation is a standard and multidisciplinary treatment of exercise promotion, patient education, risk factor management, and psychosocial counseling for people with coronary heart disease (CHD) that is underutilized due to disparities in access, referral, and participation. Empirical studies suggest that cardiac telerehabilitation (CTR) have safety and efficacy comparable to traditional in-person CR, however, older adults are under-reported with effectiveness, feasibility, and usability of CTR for this population remains unclear . Purpose This study investigates the effects, usability, and feasibility of 12-week CTR on health outcomes of older people with CHD. Design A pilot randomized controlled trial with qualitative process evaluation. Methods The study randomized 43 older adults with CHD to the 12-week CTR intervention or usual care. Guided by Social Cognitive Theory, intervention group participants received individualized in-person assessment and orientation session, followed by CTR usage at home. Participants were encouraged to visit the CR website for self-learning and data uploading, use the pedometer for daily step tracking, and chat with peers and CR nurse via social media for problem-solving and mutual support. Data were collected at baseline (T0), six-week (T1), and 12-week (T2). Results Participants in the CTR intervention group showed significant improvement in daily steps (T1: β=4126.58, p=0.001; T2: β=5285, p=0.01) and health-promoting lifestyle profile (T1: β= 23.26, p&amp;lt;.001; T2: β=12.18, p=0.008) across study endpoints. No significant difference was observed regarding self-efficacy, quality of life, psychological symptoms, and body weight and blood pressure. Twenty participants completed the intervention, with 100% used social media for tele-consultation, 90% used the pedometer for tele-monitoring, 40% (n=8) used the website. Improving awareness on rehabilitation and a clear action focus were considered as key enablers while physical discomforts and difficulties in using the technology were described as main barriers. Conclusions The CTR is effective in improving physical activity and healthy behaviors for older adults. Considering the variation in individual cardiovascular risk factors, full-scale RCT with larger sample is needed to determine the effect of CTR on psychological symptoms, body weight and blood pressure, and quality of life. Strategies to improve user intervention usage is needed.

Enhancing self-care in elderly patients: the impact of WhatsApp reminder messages at the Heart and Vascular Center

The importance of reminder messages lies in improving self-care among heart disease patients. At the Heart and Vascular Center, many patients, both those under ongoing care and those recently treated, do not consistently engage in self-care activities. Reminder messages can encourage adherence to medication regimens. This study aimed to investigate the effectiveness of WhatsApp reminder messages on the self-care of elderly patients at the Heart and Vascular Center. The research employed a quasi-experimental design with a two-group pre- and post-test control design. Using a probability sampling technique with simple random sampling, the study required 16 new patients in each group. The instrument used was the Self-Care Heart Failure Index (SCHFI) questionnaire, consisting of 22 questions. Data analysis was performed using the Mann-Whitney test. The results indicated that WhatsApp reminder messages are effective in enhancing patient self-care at the Heart and Vascular Center at Premier Hospital Surabaya (p-value&lt;0.001). The Mann-Whitney test results post-intervention showed a p-value of 0.013, confirming the effectiveness of WhatsApp reminder messages in improving self-care among patients. This study demonstrated a significant positive influence of WhatsApp reminder messages on the self-care of elderly patients at the Heart and Vascular Center. These messages are an effective tool for improving patient self-care practices at Premier Hospital Surabaya.

A Global Perspective on Cardiovascular Risk Factors by Educational Level in CHD Patients: SURF CHD II.

Clinical guidelines recommend lifestyle modifications and medication use to control cardiovascular risk factors in coronary heart disease (CHD) patients. However, risk factor control remains challenging especially in patients with lower educational level. To assess inequalities by educational level in the secondary prevention of CHD in the Survey of Risk Factors in Coronary Heart Disease (SURF CHD II). SURF CHD II is a cross-sectional clinical audit on secondary prevention of CHD, conducted during routine clinical visits in 29 countries. The easy-to-perform design of the survey facilitates its implementation in settings with limited resources. We reported risk factor recording, attainment of guideline-defined risk factor targets, and treatment in CHD patients. Differences by educational level in target attainment and treatment were assessed with logistic regression stratified for high- (HIC), upper middle- (UMIC), and lower middle-income (LMIC) countries. SURF CHD II included 13,884 patients from 2019 to 2022, of which 25.0% were female and 18.6% had achieved only primary school level. Risk factor recording ranged from 22.2% for waist circumference to 95.6% for smoking status, and target attainment from 15.9% for waist circumference to 78.7% for smoking. Most patients used cardioprotective medications and 50.5% attended cardiac rehabilitation.Patients with secondary or tertiary education were more likely to meet targets for smoking, LDL cholesterol and physical activity in HICs and LMICs; for physical activity and triglycerides in UMICs; but less likely to meet targets for blood pressure in HICs and LDL <1.4mmol/L in UMICs. Higher education was positively associated with medication use and cardiac rehabilitation participation. CHD patients generally have poor attainment of risk factor targets, but patients with a higher educational level are generally more likely to participate in cardiac rehabilitation, use medication, and meet targets. Target attainment and participation in cardiac rehabilitation are poor in CHD patients globally.Patients with higher education are more likely to meet risk factor targets, showing health inequities in secondary prevention of CHD.The association between education and risk factor target attainment and treatment varies with country income level.

Klasifikasi Penyakit Jantung Menggunakan Algoritma ANN dengan Persentase diatas 70%

Heart disease is one of the biggest causes of death in the world. This research examines the use of the Artificial Neural Network (ANN) algorithm to classify heart disease based on 303 medical data of heart disease patients obtained from the Kaggle dataset center. The data used includes medical parameters such as age, gender, blood pressure, cholesterol levels and other examination results. Various ANN architectures were tested to find the optimal configuration in terms of the number of hidden layers and neurons in each layer. Model performance is evaluated using metrics such as accuracy, precision, recall, and F1-score. From the results of the performance measurement research, an accuracy rate of 97.06%, precision of 92.30%, recall of 92.30%, and F1-Score of 92.30% were obtained.

The Prevalence and Factors Associated with Coronary Heart Disease in Patients with Gout.

. The aim of this study was to determine the prevalence of CHD and factors associated with CHD in patients (pts) with gout. . The study involved 286 male patients with gout, age 51.2 [42.8; 59.4] years (ys), disease duration 6.2 [3.8; 12.1] ys. All patients underwent standard clinical examination screening traditional risk factors (TRFs) of CVDs. We estimated the adjusted odds ratio (OR) and 95% confidence interval (95% CI). . CHD was found in 111 out of the 286 pts (38.8%), MI had a history in 29.7%. Compared to individuals with CHD, participants without CHD were older (56.7[52.1; 61.1] vs 46.2[40.6; 53.4] ys), had longer duration of gout (9.3[4.7; 15.1] vs 5.6[3.3; 9.7] ys) (for all p < 0.05). Abdominal obesity (OR, 3.6; 95% CI, 1.2-10.9), family history of CHD (OR, 2.2; 95% CI, 1.3-3.7), disease duration of gout more 10 ys (OR, 2.8; 95% CI, 1.6-4.7), age of gout onset < 35 ys (OR, 5.5; 95% CI, 2.6-11.7), intraosseous tophi (OR, 3.03; 95% CI, 1.8-5.01), nephrolithiasis (OR, 1.7; 95% CI, 1.04-3.04), renal failure (OR, 5.6; 95% CI, 2.7-11.4), serum total cholesterol (TC), (OR, 1.6; 95% CI, 1.0-2.8), serum creatinine (OR, 2.5; 95% CI, 1.2-5.1), increased the risk for CHD in patients with a gout. . The prevalence of CHD was 38.8% among individuals with gout (one-third of patients had a history of MI 29.7%). Our study showed that both TRFs of CVD and the severity of gout and a history of renal failure contribute to the development of CHD in patients with gout.

Association of TyG index with aortic valve calcification in valvular heart disease patients.

In recent years, triglyceride glucose (TyG) index, as a popular metabolic index, has been proposed as an alternative index of insulin resistance, and it has been proved to be associated with many cardiovascular diseases, but the relationship between it and aortic valve calcification is still unknown. A total of 450 aortic valve disease patients were enrolled in this study, including 361 patients with aortic valve calcification (AVC) (calcification group) and 89 patients without (control group). According to the severity of AVC, patients with AVC included severe calcification, moderate calcification and low calcification. The TyG index was calculated based on fasting triglyceride and fasting blood glucose levels. The TyG index in the calcification group was significantly higher than that in the control group (P < .05), and with the increase of the degree of calcification, the TyG index showed an increasing trend. The univariate and multivariate logistic regression analysis showed TyG index has a high predictive value for the presence of AVC (OR (95% CI): 1.743 (1.036-2.933)) and severe AVC (OR (95% CI): 1.608 (1.143-2.262)). In assessing the predictive value of the TyG index distribution width for AVC, with the first quartile as a reference, the last quartile of the TyG index had significant predictive value for the presence of AVC and severe AVC. TyG index was significantly associated with the presence and severity of AVC, suggesting that TyG index may be a valid predictor of AVC.