Gender-specific risks for incident cancer in patients with different heart failure phenotypes.

BACKGROUND: There is conflicting evidence regarding whether heart failure (HF) increases the risk of developing cancer. OBJECTIVE: This study aimed to assess the association between HF and incident cancer, considering gender differences and HF phenotypes. METHODS: This retrospective study was conducted on data of adult individuals, free of cancer at baseline, from the First Affiliated Hospital of Wenzhou Medical University between January 2009 and February 2023. The patients with HF were categorized as HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF). The primary outcome was incident cancer, including obesity-related, tobacco-related, lung, colorectal and breast cancers. RESULTS: Of 33 033 individuals enrolled, 16 722 were diagnosed with HF, including 10 086 (60.3%) with HFpEF and 6636 (39.7%) with HFrEF. During a median follow-up period of 4.6 years (inter-quartile range: 2.6-7.3), incident cancer was diagnosed in 10.5% (1707 patients) of the non-HF group and 15.1% (2533 individuals) of the HF group. After adjusting for potential confounding factors, patients with HF had a 58% increased risk of cancer than those without HF [adjusted hazard ratio (HR) 1.58, 95% confidence interval (CI) 1.48-1.69, P < 0.001]. This risk was consistent across genders (female: adjusted HR 1.95, 95% CI 1.74-2.18, P < 0.001; male: adjusted HR 1.41, 95% CI 1.30-1.54, P < 0.001) and HF phenotypes (HFpEF: adjusted HR 1.69, 95% CI 1.57-1.81, P < 0.001; HFrEF: adjusted HR 1.32, 95% CI 1.20-1.46, P < 0.001). CONCLUSIONS: Both HFpEF and HFrEF are associated with an increased risk of incident cancer. This correlation maintains its validity across genders.

Approach to cardiac masses: Thinking inside and outside the box.

In this editorial we comment on the article by Huffaker et al, published in the current issue of the World Journal of Clinical Cases. Cardiac masses encompass a broad range of lesions, potentially involving any cardiac structure, and they can be either neoplastic or non-neoplastic. Primitive cardiac tumors are rare, while metastases and pseudotumors are relatively common. Cardiac masses frequently pose significant diagnostic and therapeutic challenges. Multimodality imaging is fundamental for differential diagnosis, treatment, and surgical planning. In particular cardiac magnetic resonance (CMR) is currently the gold standard for noninvasive tissue characterization. CMR allows evaluation of the relationship between the tumor and adjacent structures, detection of the degree of infiltration or expansion of the mass, and prediction of the possible malignancy of a mass with a high accuracy. Different flow charts of diagnostic work-up have been proposed, based on clinical, laboratory and imaging findings, with the aim of helping physicians approach the problem in a pragmatic way ("thinking inside the box"). However, the clinical complexity of cancer patients, in particular those with rare syndromes, requires a multidisciplinary approach and an open mind to go beyond flow charts and diagnostic algorithms, in other words the ability to "think outside the box".

Universal Cardiovascular Disease Risk Assessment in Pregnancy: Call to Action JACC: Advances Expert Panel.

The United States has the highest maternal mortality rate among developed countries, with cardiovascular disease (CVD) being one of the leading causes of maternal deaths. Diagnosing CVD during pregnancy may be challenging as symptoms of normal pregnancy overlap with those of CVD. Delays in recognition and response to the diagnosis of CVD is a missed opportunity for timely intervention to improve maternal outcomes. Implementing universal CVD risk assessment for all pregnant and postpartum patients across clinical care settings presents a pivotal opportunity to address this issue. Integrating a validated risk assessment tool into routine obstetric care, clinicians, including obstetricians, primary care, and emergency healthcare providers, can enhance awareness of cardiovascular risk and facilitate early CVD diagnosis. Consensus among stakeholders underscores the importance of screening and education on cardiovascular health strategies for pregnant and postpartum patients to reduce CVD-related maternal mortality. This comprehensive approach offers a pathway to identify at-risk individuals and intervene promptly, potentially saving lives and advancing maternal healthcare equity.

Cardiac toxicity of HER-2 targeting antibody-drug conjugates: overview and clinical implications.

Antibody-drug conjugates (ADCs) have recently emerged as a promising therapeutic option that combine the specificity of monoclonal antibodies and the cytotoxic effect of chemotherapy. With numerous ADCs approved and on the market, a particular concern of ADCs that target HER-2 has been their cardiac side effects, in view of the crucial role of HER-2 in cardiac development and physiology. While rarely toxic and generally safe, numerous publications have outlined the consistent association of trastuzumab emtansine (T-DM1) and trastuzumab deruxtecan (T-DXd) with the development of cardiac toxicity. Despite not being clinically relevant in most cases, cardiac baseline evaluation, monitoring and early detection of cardiac adverse events remain pivotal with HER-2 targeting ADCs. This review aims to summarize and better characterize the complete cardiac toxicity profile of HER-2 ADCs, with the goal of improving clinical understanding of this adverse event, leading to better recognition, monitoring and management.

[Box: see text].

Inflammation in Chemotherapy-Induced Cardiotoxicity.

PURPOSE OF REVIEW: In this review we describe the role of inflammation in chemotherapy-induced cardiotoxicity with a particular focus on anthracycline-induced cardiomyopathy (AIC). First, we discuss inflammation associated with anthracyclines at a cellular level. Next, we discuss the clinical implications of these inflammatory mechanisms for early detection and cardioprotective strategies in patients undergoing anthracycline treatment. RECENT FINDINGS: Key inflammatory pathways identified in AIC include cytokine release, upregulation of the innate immune system via toll-like receptors, and activation of the inflammasome. Emerging evidence suggests a role for inflammatory biomarkers in detecting subclinical AIC. Advanced imaging techniques, such as cardiac PET with novel tracers targeting inflammation, may enhance early detection. Both traditional cardioprotective strategies and novel anti-inflammatory therapies show potential in preventing and treating AIC. Understanding the inflammatory mechanisms involved in AIC provides new opportunities for early detection and targeted cardioprotective strategies in patients undergoing anthracycline treatment and informs our understanding of other forms of chemotherapy-induced cardiotoxicity.

Physical activity before and after cancer diagnosis and mortality risk in three large prospective cohorts.

PURPOSE: Physical activity (PA) can improve cancer survival; however, whether the timing of PA differentially affects mortality risk is unclear. We evaluated the association between PA levels pre- and post-diagnosis and mortality risk in the Women's Health Study (WHS), Physicians' Health Study (PHS)-I, and PHS-II prospective cohorts. METHODS: We categorized PA pre- and post-diagnosis as active (WHS: ≥ 7.5 metabolic equivalent (MET)-h/week; PHS: vigorous PA ≥ 2-4 times/week) or inactive. We analyzed changes in pre- and post-diagnosis PA levels as four joint categories: (1) Inactive → Inactive, (2) Active → Inactive, (3) Inactive → Active, and (4) Active → Active, on mortality risk using multivariable Cox proportional hazards regression. RESULTS: We identified 10,541 participants with incident cancer and 3,696 deaths during follow-up. Compared to maintaining inactivity in both periods, remaining active pre- and post-diagnosis observed lower all-cause (Hazard Ratio [95% confidence interval]: WHS: 0.55 [0.47-0.64]; PHS-I: 0.77 [0.67-0.88]), cancer (WHS: 0.55 [0.45-0.67]; PHS-I: 0.75; [0.61-0.92]) and non-cancer/cardiovascular disease (CVD) mortality risks (WHS: 0.49 [0.38-0.65]). Similarly, becoming active post-diagnosis was associated with lower all-cause (WHS: 0.60 (0.48-0.75]; PHS-I: 0.72 [0.61-0.88]), cancer (WHS: 0.65 [0.49-0.86]; PHS-I: 0.64 [0.49-0.84]), and non-cancer/CVD mortality risk (WHS: 0.49 [0.33-0.75]). Being active pre- and post-diagnosis was associated with lower mortality risks in separate analyses, although significance differed by cohort and outcome. CONCLUSIONS: Remaining active pre- and post-diagnosis and becoming active post-diagnosis may be associated with improvements in cancer survival, however, research is needed across diverse cancer populations.

Case Report: Pazopanib-induced acute coronary syndrome.

Introduction: Pazopanib is a tyrosine kinase inhibitor approved for the treatment of metastatic renal cell carcinoma and advanced soft-tissue sarcoma that functions by inhibiting vascular endothelial growth factor receptors. Although the package insert and current cardio-oncology guidelines indicate a risk of acute coronary syndrome (ACS) associated with pazopanib, the causative role of pazopanib in arterial thrombosis is unclear due to a lack of focused coronary disease evaluation in oncological clinical trials prior to pazopanib initiation. Herein we present an antecedent ischemic evaluation of a patient who was prescribed pazopanib to demonstrate the first reported case of ACS directly attributable to pazopanib. Case description: A 65-year-old woman with metastatic leiomyosarcoma presented to the hospital with ACS. Pazopanib had been initiated 8 months prior, and an ischemic evaluation 6 weeks prior to hospitalization indicated mild coronary artery disease (CAD). Emergent cardiac catheterization revealed a large thrombotic occlusion of the mid-left anterior descending coronary artery involving the secondary diagonal artery, which was treated with manual aspiration thrombectomy. Pazopanib was discontinued, and the patient was discharged from the hospital 12 days later. Discussion: Although pazopanib is associated with ACS, there is a lack of definitive data supporting this association. This case-based demonstration of pazopanib-induced ACS provides a discrete clinical example of this phenomenon. The patient's minimal atherosclerotic burden 6 weeks prior to her presentation for ACS strongly suggests causality attributable to pazopanib. Given the increased risk for ischemic heart disease, careful attention and an individualized risk assessment for CAD should be provided to patients who are prescribed pazopanib.

Radiculomegaly as a key clinical feature in oculo-facio-cardio-dental (OFCD) syndrome: a case report with a novel truncating variant in BCOR gene.

Radiculomegaly is a rare dental anomaly characterised by the enlargement of the root canals of teeth. It is usually associated with oculo-facio-cardio-dental (OFCD) syndrome due to truncating variants in BCL-6 transcriptional corepressor (BCOR) (MIM*300485). We present the case of a 21-year-old female patient who was referred to genetics for a polymalformative syndrome including bilateral glaucoma and dental anomalies, especially radiculomegaly. Some others dysmorphic features were right superior lip notch, ogival palate, long philtrum, difficulty in pronation, café-au-lait spots, II-III toe bilateral syndactyly, and macrocephaly. Cone-beam CT confirmed radiculomegaly. The genetic analysis identified a heterozygous pathogenic variant NM_001123385.1:c.2093del (p.Pro698Glnfs*17) in the BCOR gene. After genetic diagnosis of OFCD syndrome, cardiac CT-scan revealed a large asymptomatic atrial septal defect that was subsequently surgically closed. Reviews of the literature have previously highlighted the prevalence of radiculomegaly in OFCD syndrome with a positive predictive value of 88.23% and a sensitivity of 75.94%. This case report highlights the importance of radiculomegaly as a clinical sign of OFCD syndrome, emphasising the rarity of non-syndromic radiculomegaly and the benefits of its diagnosis in clinical management, especially in cardiac screening.

Cardiovascular adverse events associated with targeted therapies for multiple myeloma: a pharmacovigilance study.

Introduction: Multiple myeloma (MM) is a leading cause of hematopoietic cancer-related mortality, accounting for 20% of deaths. MM-targeted therapies have demonstrated efficacy, and since 2015, the United States Food and Drug Administration (FDA) has approved five targeted drugs. However, their cardiovascular safety has not been comprehensively evaluated. Objective: This study aimed to investigate the association between MM-targeted therapy and cardiovascular adverse events (AEs). Methods: Disproportionality analysis was conducted on reports from the FDA AE Reporting System database from 2014 to the second quarter of 2023. Cardiovascular AEs were grouped into nine narrow categories using the Standardized Medical Dictionary for Regulatory Activities Queries (SMQs). Results: A total of 3,228 cardiovascular AE cases involving MM-targeted therapy were extracted and analyzed. Significant disproportionality was identified for daratumumab, elotuzumab, and isatuximab. Among the nine narrow SMQ categories, the three most reported cardiovascular AEs were cardiomyopathy, cardiac arrhythmias, and embolic and thrombotic events. Noninfectious myocarditis/pericarditis, cardiac arrhythmias, and embolic and thrombotic events exhibited the strongest signal strengths. The cardiovascular AE risk was higher within the first month and gradually decreased thereafter; however, it increased rapidly again after 1 year. This trend was observed for all cardiovascular AEs. The Kaplan-Meier curve and the log-rank test revealed that isatuximab and elotuzumab exhibited a significantly lower probability of cardiovascular AEs than daratumumab (p < 0.001). Conclusions: MM-targeted therapy is significantly associated with an increased risk of previously unknown cardiovascular AE profiles, with the range and onset differing among various drugs, thereby warranting specific monitoring and appropriate management.

Dynamics of cardio-muscular networks in exercise and fatigue.

A fundamental question in cardiovascular and muscle physiology is how the heart operates in synchrony with distinct muscles to regulate homeostasis, enable movement and adapt to exercise demands and fatigue. Here we investigate how autonomic regulation of cardiac function synchronizes and integrates as a network with the activity of distinct muscles during exercise. Further, we establish how the network of cardio-muscular interactions reorganizes with fatigue. Thirty healthy young adults performed two body weight squat tests until exhaustion. Simultaneous recordings were taken of a 3-lead electrocardiogram (EKG) along with electromyography (EMG) signals from the left and right vastus lateralis, and left and right erector spinae. We first obtained instantaneous heart rate (HR) derived from the EKG signal and decomposed the EMG recordings in 10 frequency bands (F1-F10). We next quantified pair-wise coupling (cross-correlation) between the time series for HR and all EMG spectral power frequency bands in each leg and back muscle. We uncovered the first profiles of cardio-muscular network interactions, which depend on the role muscles play during exercise and muscle fibre histochemical characteristics. Additionally, we observed a significant decline in the degree of cardio-muscular coupling with fatigue, characterized by complex transitions from synchronous to asynchronous behaviour across a range of timescales. The network approach we utilized introduces new avenues for the development of novel network-based markers, with the potential to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes. KEY POINTS: The heart operates in synchrony with muscles to regulate homeostasis, enable movement, and adapt to exercise demands and fatigue. However, the precise mechanisms regulating cardio-muscular coupling remain unknown. This study introduces a pioneering approach to assess cardio-muscular network interactions by examining the synchronization of cardiac function with muscle activity during exercise and fatigue. We uncover the first profiles of cardio-muscular interactions characterized by specific hierarchical organization of link strength. We observe a significant decline in the degree of cardio-muscular coupling with fatigue, marked by complex transitions from synchronous to asynchronous behaviour. This network approach offers new network-based markers to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes.

Impact of vascular biomarkers and supine hypertension on cardiovascular outcomes in hypertensive patients: first results from the Cardiovascular Prognostic COUPLING Study in Japan.

The prognostic impact of vascular biomarkers and supine blood pressure (BP) is not well understood. The multicenter, prospective Coupling study determined the prognostic impact of vascular biomarkers and supine BP in outpatients aged ≥30 years with ≥1 cardiovascular risk factor. Occurrence of major cardiovascular events during follow-up was recorded. The primary outcome was time to onset of a major cardiovascular event. Office and supine BP, the cardio-ankle vascular index (CAVI), and the ankle-brachial index (ABI) were determined annually. Of the 5109 participants in the Coupling study, 4716 were analyzed (51.9% male, mean age 68.5 ± 11.4 years); participants mostly had hypertension treated based on seated office/home BP according to relevant guidelines. During a median follow-up of 5.0 years (interquartile range 3.6-5.2), 231 major cardiovascular events occurred. After adjustment for age, sitting office systolic BP, and other covariates, a 1-unit increase in CAVI (hazard ratio [HR] 1.12, 95% confidence interval [CI] 1.01-1.24) and a 0.1-unit decrease in ABI (HR 1.41, 95% CI 1.18-1.68) were significantly associated with cardiovascular event risk; risk was greatest when CAVI was ≥8.0 and ABI was ≤1.10. Uncontrolled supine hypertension (≥140/90 mmHg) was also significantly associated with adjusted cardiovascular event risk (HR 1.36, 95% CI 1.02-1.81); seated office BP control was not significantly associated with cardiovascular event risk. Increased arterial stiffness, mildly lower ABI, and supine hypertension are risk factors for cardiovascular events during standard clinical practice. Supine evaluation of BP and vascular biomarkers has highlighted a blind spot in current hypertension management (Clinical trial registration: University Hospital Medical Information Network Clinical Trials Registry, UMIN000018474).

Practical Aspects of Using Large Language Models to Screen Abstracts for Cardiovascular Drug Development: Cross-Sectional Study.

Unlabelled: Cardiovascular drug development requires synthesizing relevant literature about indications, mechanisms, biomarkers, and outcomes. This short study investigates the performance, cost, and prompt engineering trade-offs of 3 large language models accelerating the literature screening process for cardiovascular drug development applications.

Detection and Classification of electrocardiography using hybrid deep learning models.

BACKGROUND: Electrocardiography (ECGs) has been a vital tool for cardiovascular disease (CVD) diagnosis, which visually depicts the heart's electrical activity. To enhance automatic classification between normal and diseased ECG, it is essential to extract consistent and qualitative features. METHODS: Precision of ECG classification through hybrid Deep Learning (DL) approach leverages both Convolutional Neural Network (CNN) architecture and Variational Autoencoder (VAE) techniques. By combining these methods, we aim to achieve more accurate and robust ECG interpretation. The method is trained and tested over PTB-XL dataset, which contains 21,799 with 12-lead ECGs from 18,869 patients, each spanning 10 seconds. The classification evaluation of 5 super-classes and 23 sub-classes of CVD, with the proposed CNN-VAE model is compared. RESULTS: The classification of various CVD had resulted with the highest accuracy of 98.51%, specificity of 98.12%, sensitivity 97.9% and F1-score 97.95%. We have also achieved the minimum false positive and false negative rates as 2.07 and 1.87 respectively during validation. The results are validated upon the annotations given by individual cardiologists, who assigned potentially multiple ECG statements to each record. CONCLUSION: When compared to other deep learning methods, our suggested CNN-VAE model performs significantly better in testing phase. This study proposes a new architecture of combining CNN-VAE for CVD classification from ECG data, this can help the clinicians to identify the disease earlier and carry further treatment. The CNN-VAE model can better characterize input signals due to its hybrid architecture.

Biomarker-enhanced cardiovascular risk prediction in patients with cancer: a prospective cohort study.

BACKGROUND: Continuously improving cancer-specific survival puts a growing proportion of cancer patients at risk of major adverse cardiovascular events (MACE), but tailored tools for cardiovascular risk prediction remain unavailable. OBJECTIVES: To assess a broad panel of cardiovascular biomarkers and risk factors for the prediction of MACE and cardiovascular death in cancer patients. METHODS: In total, 2192 patients with newly diagnosed or recurrent cancer were followed prospectively for the occurrence of 2-year MACE and 5-year cardiovascular death. Univariable and multivariable risk models were fit to assess independent associations of cardiovascular risk factors and biomarkers with adverse outcomes, and a risk score was developed. RESULTS: Traditional cardiovascular risk factors and selected cancer types were linked to higher MACE risk. While levels of Lp(a), CRP, and GDF-15 did not associate with MACE, levels of ICAM-1, P-/E-/L-selectins, and NT-proBNP were independently linked to 2-year MACE risk. A clinical risk score was derived, assigning +1 point for male sex, smoking, and age of ≥60 years and +2 points for atherosclerotic disease, yielding a bootstrapped C-statistic of 0.76 (95% CI: 0.71-0.81) for the prediction of 2-year MACE. Implementation of biomarker data conferred improved performance (0.83, 95% CI: 0.78-0.88), with a simplified model showing similar performance (0.80, 95% CI: 0.74-0.86). The biomarker-enhanced and simplified prediction models achieved a C-statistic of 0.82 (95% CI: 0.71-0.93) and 0.74 (95% CI: 0.64-0.83) for the prediction of 5-year cardiovascular death. CONCLUSION: Biomarker-enhanced risk prediction strategies allow the identification of cancer patients at high risk of MACE and cardiovascular death. While external validation studies are ongoing, this first-of-its-kind risk score may provide the basis for personalized cardiovascular risk assessment across cancer entities.

Obstetric anesthesia management of dilated cardiomyopathies and heart failure: a narrative review.

Pregnancy in patients with dilated cardiomyopathy carries a significantly increased risk of maternal mortality or severe morbidity, and pregnancy is typically considered contraindicated for patients with severely reduced ventricular function. Nonetheless, anesthesiologists will still encounter patients with cardiomyopathy requiring delivery or termination care. This review describes how NT-ProBNP testing and echocardiography can help with early recognition of heart failure in pregnancy, and describes a suggested approach to anesthetic management of patients with cardiomyopathies or acute heart failure, including hemodynamic goals, use of vasoactive medications and mechanical support. Vaginal delivery, with effective neuraxial anesthesia is the preferred mode of delivery in most patients with cardiomyopathy, with cesarean delivery reserved for maternal or fetal indications. The Pregnancy Heart Team is vital in coordinating the multidisciplinary care necessary to safely support these patients through pregnancy.

Blood Pressure and Cardiovascular Risk in Women With Breast Cancer: The Pathways Heart Study.

Background: Hypertension is an important contributor to cardiovascular disease (CVD) in breast cancer (BC) survivors; however, research on blood pressure (BP) and CVD outcomes in BC survivors is limited. Objectives: The purpose of this study was to better characterize the association between BP and CVD in a large, longitudinal cohort of BC patients. Methods: Women with invasive BC diagnosed from 2005 to 2013 at Kaiser Permanente Northern California were matched 1:5 to women without BC. Patient data were obtained from electronic health records. Multivariable Cox regression and penalized spline models were used to explore the linear and nonlinear relationship of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on CVD outcomes. Results: BC cases (n = 12,713) and controls (n = 55,886) had median follow-up of 9.6 years (IQR: 5.0-11.9 years). Women with BC had a mean age of 60.6 years; 64.8% were non-Hispanic White. For ischemic heart disease (IHD), every 10 mmHg increase in SBP and DBP was associated with 1.23 (95% CI: 1.14-1.33) and 1.10 (95% CI: 0.98-1.24) risk, respectively, in women with BC. For stroke, every 10 mmHg increase in SBP and DBP was associated with a 1.45 (95% CI: 1.34-1.58) and 1.91 (95% CI: 1.68-2.18) risk, respectively. A U-shaped relationship was observed between heart failure/cardiomyopathy and BP. The associations between BP and risk of IHD, stroke, and any primary CVD were not statistically different comparing women with BC to controls, but risks varied by BC status for heart failure/cardiomyopathy (P for interaction = 0.01). Conclusions: Women with and without BC showed similar risks for IHD, stroke, and any primary CVD suggesting similar BP targets should be pursued regardless of BC survivorship status.

Impact of Cardio-Ankle Vascular Index on Future Cancer in Patients With Coronary Artery Disease.

Background: Cardiovascular risk factors are associated with increased risk of future cancer. However, the relationship between quantitative parameters of atherosclerosis and future cancer risk is unclear. Methods and Results: A total of 1,057 consecutive patients with coronary artery disease was divided into 2 groups according to the cutoff value of the cardio-ankle vascular index (CAVI) derived by receiver operating characteristic curve analysis: low CAVI group (CAVI <8.82; n=487), and high CAVI group (CAVI ≥8.82; n=570). Patients in the high CAVI group were older and had a higher prevalence of diabetes, chronic kidney disease, anemia and history of stroke compared with patients in the low CAVI group. There were 141 new cancers during the follow-up period. The cumulative incidence of new cancer was significantly higher in the high CAVI group than in the low CAVI group (P=0.001). In a multivariate Cox proportional hazard analysis, high CAVI was found to be an independent predictor of new cancer diagnosis (hazard ratio 1.62; 95% confidence interval 1.11-2.36; P=0.012). In the analysis of individual cancer types, high CAVI was associated with lung cancer (hazard ratio 2.85; 95% confidence interval 1.01-8.07; P=0.049). Conclusions: High CAVI was associated with the risk of future cancer in patients with coronary artery disease.

Cardiovascular disease detection from cardiac arrhythmia ECG signals using artificial intelligence models with hyperparameters tuning methodologies.

Cardiovascular disease (CVD) is connected with irregular cardiac electrical activity, which can be seen in ECG alterations. Due to its convenience and non-invasive aspect, the ECG is routinely exploited to identify different arrhythmias and automatic ECG recognition is needed immediately. In this paper, enhancement for the detection of CVDs such as Ventricular Tachycardia (VT), Premature Ventricular Contraction (PVC) and ST Change (ST) arrhythmia using different dimensionality reduction techniques and multiple classifiers are presented. Three-dimensionality reduction methods, such as Local Linear Embedding (LLE), Diffusion Maps (DM), and Laplacian Eigen (LE), are employed. The dimensionally reduced ECG samples are further feature selected with Cuckoo Search (CS) and Harmonic Search Optimization (HSO) algorithms. A publicly available MIT-BIH (Physionet) - VT database, PVC database, ST Change database and NSR database were used in this work. The cardiac vascular disturbances are classified by using seven classifiers such as Gaussian Mixture Model (GMM), Expectation Maximization (EM), Non-linear Regression (NLR), Logistic Regression (LR), Bayesian Linear Discriminant Analysis (BDLC), Detrended Fluctuation Analysis (Detrended FA), and Firefly. For different classes, the average overall accuracy of the classification techniques is 55.65 % when without CS and HSO feature selection, 64.36 % when CS feature selection is used, and 75.39 % when HSO feature selection is used. Also, to improve the performance of classifiers, the hyperparameters of four classifiers (GMM, EM, BDLC and Firefly) are tuned with the Adam and Grid Search Optimization (GSO) approaches. The average accuracy of classification for the CS feature-based classifiers that used GSO and Adam hyperparameter tuning was 79.92 % and 85.78 %, respectively. The average accuracy of classification for the HSO feature-based classifiers that used GSO and Adam hyperparameter tuning was 86.87 % and 93.77 %, respectively. The performance of the classifier is analyzed based on the accuracy parameter for both with and without feature selection methods and with hyperparameter tuning techniques. In the case of ST vs. NSR, a higher accuracy of 98.92 % is achieved for the LLE dimensionality reduction with HSO feature selection for the GMM classifier with Adam's hyperparameter tuning approach. The GMM classifier with the Adam hyperparameter tuning approach with 98.92 % accuracy in detecting ST vs. NSR cardiac disease is outperforming all other classifiers and methodologies.