Cardiac Ailments Research Articles

OPTIMIZING HEART HEALTH THROUGH AYURVEDA: A DETAILED FOCUS ON THE PREVENTION AND TREATMENT OF HRIDROGA

Purpose(Introduction): Diseases associated with a person's lifestyle are known as lifestyle diseases. Condi-tions, including heart disease, stroke, obesity, and type II diabetes, mainly impact our way of life. This article focuses on the idea of Hridroga (Heart Diseases) and how to handle it from an Ayurvedic perspective, including current updates so that one might avoid certain illnesses or treat them with greater precision. Design/methodology/approach: The study is grounded in analysing ancient Ayurvedic texts, including the Charaka Samhita and Sushruta Samhita. It examines the concepts of Dosha Imbalances, dietary guidelines, and holistic practices prescribed for maintaining heart health. Discussion : Heart disease, or Hridroga , is one of the leading causes of death in India. In Ayurveda, heart disorders are re-ferred to as Hridroga. The heart is a Marma, or vital organ. Cardiovascular disease is one illness that is significantly on the rise in the modern day. Stress, alcohol consump-tion, smoking, and high-calorie intake are a few examples of lifestyle modifications that raise the risk of cardio-vascular disease. Nidan-Parivarjana (avoid causative factor) is the first line of treatment for all ailments since Nidan(Causative Factor) plays a significant role in how disorders emerge. Practical implications: The Ayurvedic scriptures provide in-depth explanations of the causes, signs, and treat-ment of Hridroga. Ayurveda describes in great detail how vitiated Pitta, Kapha, and Vata cause symptoms and how to treat them clinically to avoid these circumstances. Originality/value: This study, which focuses primarily on cardiac ailments, aids in managing lifestyle condi-tions.

Targeting Wnt Pathways with Small Molecules as New Approach in Cardiovascular Disease.

The increasing incidences of morbidity and mortality associated with cardiovascular diseases represent significant difficulties for clinical treatment and have a major impact on patient health. Wnt signaling pathways are highly conserved and are well known for their regulatory roles in embryonic development, tissue regeneration, and adult tissue homeostasis. Wnt signaling is classified into two distinct pathways: canonical Wnt/β-catenin signaling and noncanonical pathways, including planar cell polarity and Wnt/Ca2+ pathways. A growing body of experimental evidence suggests the involvement of both canonical and non-canonical Wnt signaling pathways in the development of cardiovascular diseases, including myocardial hypertrophy, arrhythmias, diabetic cardiomyopathy, arrhythmogenic cardiomyopathy, and myocardial infarction. Thus, to enhance patient quality of life, diagnosing and treating cardiac illnesses may require a thorough understanding of the molecular functions played by the Wnt pathway in these disorders. Many small-molecule inhibitors specifically target various components within the Wnt signaling pathways, such as Frizzled, Disheveled, Porcupine, and Tankyrase. This study aims to present an overview of the latest findings regarding the functions of Wnt signaling in human cardiac disorders and possible inhibitors of Wnt, which could lead to novel approaches for treating cardiac ailments.

Insights Of Cardiac Changes In Sudden Deaths In Kalaburagi District- An Autopsy Study.

Introduction: Sudden and unexpected death often arises as a complication of diverse cardiac ailments. The occurrence of sudden cardiac-related deaths is increasingly prevalent in both urban and rural settings. This surge presents a formidable challenge for forensic physicians tasked with conducting autopsies to ascertain the precise cause and manner of death, particularly in individuals previously considered healthy. Consequently, this study aims to shed light on infrequent lesions that may go unnoticed during the individual's lifetime, offering valuable insights into this phenomenon. Aims and Objectives of the study: 1) To study the demographic distribution of cardiac specimens of sudden death. 2) To study the histomorphology features in cardiac specimens in sudden death. 3) To grade the atherosclerotic lesions as per Modified American Heart Association Classification of Atherosclerotic Lesion. Materials and method: This is a retrospective study of 3 years from December 2020 to November 2023.The data of medicolegal autopsies was retrieved from the records of department of Pathology, Gulbarga Institute of Medical Sciences, Kalaburagi. A total of 371 medicolegal autopsy specimens were received in the department. Out of which 114 cardiac specimens (sent with other organs) of sudden death were studied. Results: Out of 114 cases of sudden death, 57% of the deaths occurred in outdoor location and remaining 43% occurred in hospitalized patients and homes. The commonest age group of sudden cardiac death was 31 to 40 years of age (27%). We found males were affected more commonly (84%) than females. The most common cause of sudden cardiac death is coronary artery disease (74.6%) followed by myocardial infarction (7.6%). Conclusion: The most common cause of sudden cardiac death is coronary artery disease, which is common in young males (age group 31-40 years).

HF-CMN: a medical report generation model for heart failure.

Heart failure represents the ultimate stage in the progression of diverse cardiac ailments. Throughout the management of heart failure, physicians require observation of medical imagery to formulate therapeutic regimens for patients. Automated report generation technology serves as a tool aiding physicians in patient management. However, previous studies failed to generate targeted reports for specific diseases. To produce high-quality medical reports with greater relevance across diverse conditions, we introduce an automatic report generation model HF-CMN, tailored to heart failure. Firstly, the generated report includes comprehensive information pertaining to heart failure gleaned from chest radiographs. Additionally, we construct a storage query matrix grouping based on a multi-label type, enhancing the accuracy of our model in aligning images with text. Experimental results demonstrate that our method can generate reports strongly correlated with heart failure and outperforms most other advanced methods on benchmark datasets MIMIC-CXR and IU X-Ray. Further analysis confirms that our method achieves superior alignment between images and texts, resulting in higher-quality reports.

Iron Deficiency and its Relationship with Chronic Heart Failure- A Review.

This review article discusses multifactorial pathophysiology, the relationship between clinical characteristics, functional and absolute ID, and the advantages of medicinal intervention in chronic heart failure (CHF). It also covers how iron shortage affects other body parts. The most recent publications that included substantial scientific data on the connection between CHF and ID, with or without anaemia, were selected. Complex physiopathological interactions, including higher hepcidin levels, systemic inflammation, and activation of the renin-angiotensin-aldosterone system, have been identified in these patients. These mechanisms exacerbate the outcomes for patients by amplifying the severity of anemia, chronic heart failure (CHF), and Chronic kidney disease (CKD). Research in this area has been limited and has shown inconsistent findings. Still, it has also examined evidence-based treatment approaches and diagnostic guidelines, especially in relation to iron supplements and erythropoietin-stimulating medications. Anemia is a frequent chronic heart failure consequence and a poor prognostic factor. We still don't completely understand the many complex causes of anemia. Iron deficiency screening is highly recommended for people with cardiac ailments because of its significance for their prognoses. Due to the paucity of research proving its effectiveness, the high incidence of unfavourable gastrointestinal side effects, and the prolonged length of time required for treatment to boost haemoglobin levels, an oral iron supplement is not advised for people with chronic heart failure. An insufficient amount of iron not only impacts the heart but also various other body components.

IoT-Driven Approaches for Early Detection and Monitoring of Heart Disease: Current Trends and Future Directions

Cardiovascular disease (CVD) is a serious disease having a widespread effect on individuals across the world. Early and accurate detection of cardiac disease is crucial in healthcare, especially in the domain of cardiology. Currently, a non-invasive ultrasound imaging method is used that evaluates the structure, performance, and blood, allowing for the precise identification of a number of cardiac ailments, such as valve problems, heart failure, and congenital anomalies. These traditional techniques have some limitations, including high cost, the need for medical expertise and equipment, and the fact that they often create incorrect results due to human involvement. Furthermore, the traditional method takes more time to predict heart disease. Electrocardiogram (ECG) signals play a critical role in reducing death rates caused by CVDs, and they provide details regarding the heart patient’s health to a medical expert by employing an automated heart failure detection system. Recent developments in deep learning-based health care systems, such as ECG signal analysis, include CNN, LSTM, and other neural networks. In this research, we provide a hybrid deep learning based approach for the timely and accurate diagnosis of cardiovascular disease. The proposed system uses a hybrid of convolutional neural networks (CNN) and long short-term memory (LSTM) and utilizes the MIT-BIH ECG signal dataset for heart disease diagnosis. This study uses two different approaches with MIT-BIH arrhythmia imbalanced and balanced datasets. The first approach uses CNN and CNN-LSTM with an imbalanced dataset, and the second approach uses CNN and CNN-LSTM with a balanced dataset. The performance of both approaches was analyzed. The experimental outcomes show that the overall performance of both CNN, CNN-LSTM was excellent on a balanced dataset compared to imbalanced dataset. The proposed system achieved a better result than the previous suggested methods. Additionally, it is easy to adopt the suggested technique in the field of healthcare in order to identify heart disease.

The impact of diabetes on tight junctions in cardiomyopathy dysfunction.

Diabetic cardiomyopathy is a condition characterized by ventricular dysfunction in diabetic patients that is not caused by other cardiac ailments. It is associated with factors such as left ventricular hypertrophy, metabolic disturbances, and oxidative stress. Tight junctions, which form a barrier between cells, play a role in the vascular complications of diabetes. Proteins such as claudins and occludens are important for the structure and function of tight junctions. Zona occludens (ZO) proteins are also involved in tight junctions and their expression may be affected by diabetes. The review discusses the impact of diabetes on the tight junctions and the role of ZO proteins in diabetic cardiovascular dysfunction.

The role of stem cell-derived tissues in novel treatments for cardiac ailments

The role of stem cell-derived tissues in novel treatments for cardiac ailments Curbs on animal testing mean human tissues derived from induced pluripotent stem cells offer a promising platform in discovering novel treatments for cardiac ailments. In the realm of research and development in novel treatments for cardiac ailments, the use of animal models, such as mice, presents inherent limitations due to physiological discrepancies between species, specifically between humans and experimental animals. For instance, the heart rate in mice can surpass 500 beats per minute, a rate considerably faster than that observed in humans.

Role of Specificity Protein 1 (SP1) in Cardiovascular Diseases: Pathological Mechanisms and Therapeutic Potentials.

In mammals, specificity protein 1 (SP1) was the first Cys2-His2 zinc finger transcription factor to be isolated within the specificity protein and Krüppel-like factor (Sp/KLF) gene family. SP1 regulates gene expression by binding to Guanine-Cytosine (GC)-rich sequences on promoter regions of target genes, affecting various cellular processes. Additionally, the activity of SP1 is markedly influenced by posttranslational modifications, such as phosphorylation, acetylation, glycosylation, and proteolysis. SP1 is implicated in the regulation of apoptosis, cell hypertrophy, inflammation, oxidative stress, lipid metabolism, plaque stabilization, endothelial dysfunction, fibrosis, calcification, and other pathological processes. These processes impact the onset and progression of numerous cardiovascular disorders, including coronary heart disease, ischemia-reperfusion injury, cardiomyopathy, arrhythmia, and vascular disease. SP1 emerges as a potential target for the prevention and therapeutic intervention of cardiac ailments. In this review, we delve into the biological functions, pathophysiological mechanisms, and potential clinical implications of SP1 in cardiac pathology to offer valuable insights into the regulatory functions of SP1 in heart diseases and unveil novel avenues for the prevention and treatment of cardiovascular conditions.

Advances in nanotechnological approaches for the detection of early markers associated with severe cardiac ailments.

Mortality from cardiovascular disease (CVD) accounts for over 30% of all deaths globally, necessitating reliable diagnostic tools. Prompt identification and precise diagnosis are critical for effective personalized treatment. Nanotechnology offers promising applications in diagnostics, biosensing and drug delivery for prevalent cardiovascular diseases. Its integration into cardiovascular care enhances diagnostic accuracy, enabling early intervention and tailored treatment plans. By leveraging nanoscale innovations, healthcare professionals can address the complexities of CVD progression and customize interventions based on individual patient needs. Ongoing advancements in nanotechnology continue to shape the landscape of cardiovascular medicine, offering potential for improved patient outcomes and reduced mortality rates from these pervasive diseases.

ECG Arrhythmia Classification using Deep Learning

An electrocardiogram (ECG) is a painless, noninvasive way to help diagnose numerous common heart problems. ECG plays an important role in diagnosing various Cardiac ailments. In recent years, Deep learning techniques have shown remarkable promise in achieving accurate and automated ECG arrhythmia classification. The primary goal of the system is to develop a robust and accurate system for the automated detection and classification of arrhythmias in electrocardiogram (ECG) data. By leveraging state-of-the-art techniques such as Convolutional Neural Networks (CNNs), we analyze pattern recognition within ECG signals to detect arrhythmias. Furthermore, we address the challenge of dataset scarcity by augmenting the data through nine different image cropping methods during the training phase. The implementation of techniques like Batch Normalization and data augmentation will further enhance the model's adaptability to diverse data sources, making it an invaluable tool for healthcare professionals. The CNN will be trained and tested using the ECG Dataset obtained from the MIT-BIH Database and from it, seven types of signals of arrhythmia will be classified. These seven signals are Premature Ventricular contractions (PVC), Paced beat (PAB), Right bundle branch block beat (RBB), Left bundle branch block beat (LBB), Atrial premature contraction (APC), Ventricular escape beat (VEB) and Normal beat. This system bridges the gap between advanced technology and healthcare, offering a transformative approach to ECG arrhythmia classification that has the potential to significantly improve patient outcomes and reduce the burden of manual diagnosis

Is Agri-residue Burning a Menace for Air Quality & Public Health in Delhi, India?

Skies over Delhi become blurred and visibility is significantly reduced and the air is hefty and causes a burning sensation in the eyes. As every year in November, a thick blanket of smog veils Delhi and its surrounding National Capital Region-NCR of India, which constitute the world’s most polluted megacity. According to a senior pulmonologist and member of the WHO commission on global air pollution and health, patients experiencing breathing problems increase by 30-40 percent every year during October-November. But Delhi’s smog wasn’t always this bad in early winter; it started only about 10-15 years ago. Satellite images show high Aerosol Optical Depth (AOD), as soon as farmers start burning paddy straw and stubble (agri-residue) in agricultural fields, and air quality severely deteriorates. The agri-residue smoke from agricultural areas surrounding Delhi, combined with urban pollution from vehicles, industry, and fireworks from the Diwali festival, increase pollutants to the severe category. Smoke from farm fires after harvest contributed about ⁓ 26-50% of the PM2.5 (tiny particles that damage lungs and can worsen cardiac ailments) to Delhi’s air in November 2023. The average resident of this megacity is on track to lose ⁓ 8 years of life expectancy if high pollution levels persist (EPIC, 2023). Authorities in this smog-ridden capital, even imposed emergency school closures of 7 to 15 days in 2016, 2017 and 2023 to mitigate health issues in the population, who flooded emergency wards at hospitals.

Emerging Roles of Cullin-RING Ubiquitin Ligases in Cardiac Development.

Heart development is a spatiotemporally regulated process that extends from the embryonic phase to postnatal stages. Disruption of this highly orchestrated process can lead to congenital heart disease or predispose the heart to cardiomyopathy or heart failure. Consequently, gaining an in-depth understanding of the molecular mechanisms governing cardiac development holds considerable promise for the development of innovative therapies for various cardiac ailments. While significant progress in uncovering novel transcriptional and epigenetic regulators of heart development has been made, the exploration of post-translational mechanisms that influence this process has lagged. Culling-RING E3 ubiquitin ligases (CRLs), the largest family of ubiquitin ligases, control the ubiquitination and degradation of ~20% of intracellular proteins. Emerging evidence has uncovered the critical roles of CRLs in the regulation of a wide range of cellular, physiological, and pathological processes. In this review, we summarize current findings on the versatile regulation of cardiac morphogenesis and maturation by CRLs and present future perspectives to advance our comprehensive understanding of how CRLs govern cardiac developmental processes.

In silico Study on Structural Inhibition of Bacterial DNA Gyrase by Major Secondary Metabolites Found in Grape Seed Extract

In the early 20th century, during the era of investigating and identifying essential “vitamins”, scientific research focused on grape seed extracts and their bioactive components, particularly polyphenols. Extensive studies have demonstrated that grape seed extract, rich in proanthocyanidins, offers protection against a wide spectrum of diseases, encompassing inflammation, cardiac ailments, peptic ulcers, hypertension, diabetes, cancer, and microbial infections. To explore potential secondary metabolites within grape seed extract that could serve as structural inhibitors of bacterial DNA Gyrase, molecular docking studies were performed. The docking results revealed that two phytochemicals, namely (-)-catechin and Procyanidin-B2, exhibited the highest potency in inhibiting DNA gyrase subunit B. Subsequent in silico physicochemical and pharmacokinetic parameter predictions were conducted using specialized web servers for the examined phytochemicals. Notably, (-)-catechin displayed superior inhibitory and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) characteristics, suggesting its potential for utilization in synthesizing novel antibacterial compounds.

Unveiling the Cardioprotective Power: Liquid Chromatography–Mass Spectrometry (LC–MS)-Analyzed Neolamarckia cadamba (Roxb.) Bosser Leaf Ethanolic Extract against Myocardial Infarction in Rats and In Silico Support Analysis

Neolamarckia cadamba (Roxb.) Bosser, a member of the Rubiaceae family, is a botanical species with recognized therapeutic properties. It is commonly used in traditional medicine to treat cardiac ailments and other disorders. However, the precise active constituents and the potential mechanisms by which they manage cardiovascular disorders remain unclear. Therefore, this study aimed to ascertain the bioactive components and investigate their underlying mechanisms of action. N. cadamba is used to treat cardiovascular disorders using the integrated metabolomic methodology. An HPLC-QTOF-MS/MS analysis determined the potential chemicals in the N. cadamba leaf ethanol extract (NCEE). A thorough investigation of the NCEE samples used in this study led to the identification of 32 phytoconstituents. Of the 32 compounds, 19 obeyed Lipinski’s rule of five (RO5). A molecular docking study directed towards HMG-CoA reductase used 19 molecules. The reference drug atorvastatin indicated a binding energy of −3.9 kcal/mol, while the other substances, Cinchonain Ib and Dukunolide B, revealed binding energies of −5.7 and −5.3 kcal/mol, respectively. Both phytocompounds showed no toxicity and exhibited favorable pharmacokinetic properties. In vivo study results concluded that treatment with NCEE significantly reduced the cardiac myocardial infarction (MI) marker CK-MB and atherogenic risk indices, such as the atherogenic index plasma (AIP), cardiac risk ratio (CRR), and atherogenic coefficient (AC) in isoproterenol-induced MI rats. In MI rats, NCEE therapy significantly improved the antioxidant system of the heart tissue, as evidenced by the increased levels of GSH and SOD, lower levels of the oxidative stress marker MDA, and significantly decreased HMG-CoA activity. Additionally, electrocardiogram (ECG) signals from rats treated with NCEE resembled those treated with traditional atorvastatin to treat myocardial infarction. This study used H&E staining to show that administering NCEE before treatment reduced cardiac myocyte degeneration in rats with myocardial infarction, increased the presence of intact nuclei, and increased myocardial fiber strength. The potential cardioprotective effect observed in myocardial infarction (MI) rats treated with NCEE can be extrapolated from computational data to be caused by Cinchonain Ib.

Congestive Heart Failure in the Light of Ancient Wisdom of Unani Medicine: A Review

Congestive heart failure is a complex clinical syndrome that causes functional impairment of ventricular filling and ejection of blood. It can cause dyspnea, fatigue, and fluid retention, affecting exercise tolerance and causing pulmonary and peripheral edema. Moreover, it is a burgeoning and life-threatening syndrome characterized by significant morbidity and mortality, poor functional capacity and quality of life, and high costs. Worldwide congestive heart failure affects more than 64 million people. Nowadays: congestive heart failure is correlated with Suqūṭ-e-Qalb Imtilāʼī, by modern Unani physicians. However, the disease is mentioned in classical Unani literature under the headings of Ikhtilāj-e-qalbi (arrhythmia), Rabw (cardiac asthma), Buhr (cardiac asthma), Khafaqān (palpitation), Istisqā’ Laḥmī (anasarca), Du‘f al-Qalb (weakness of heart), Intiṣāb al-Nafas (orthopnoea), Sudda-e-Urooq-e-Qalb (coronary artery obstruction), Ghashī (syncope), Tasallub-al- Sharāyīn (arteriosclerosis) and Imtilā’ bi Hasbil Aw’iya (congestion of blood vessels). Congestive heart failure and mortality are on the rise despite the significant advancements in contemporary medicine and guidelines directed medical therapy for congestive heart failure. Congestive heart failure hospitalizations make up 1-2% of Western hospital admissions, with the highest 30-day readmission rate (20-25%) in congestive heart failure patients reflecting due to high comorbidity burden. Unani drugs, despite advancements in modern medicine, still significantly impact patient health. They are traditionally used for cardiac ailments like palpitations, coronary artery disease, heart weakness, and cardiotonic. Unani medicine especially Khamīrajat (fermented confections) used in various cardiac diseases is cardio-protective and cardiotonic. According to reports, complementary and alternative medicine is used by up to 61% of cardiac patients with coronary artery disease and those at risk for arteriosclerosis. Therefore, a thorough evaluation of the Unani literature on cardiac illness and its treatment in the Unani system of medicine is needed to decrease congestive heart failure social and economic burdens have become a major global public health priority. This review is an effort to summarize the Unani classical literature on congestive heart failure.

Impact of Covid-19 on Respiratory and Cardiovascular Status in Covid Recovered Young Adults

Introduction: Corona viruses are a type of virus that can infect both humans as well as animals. they can impact both the pulmonary and extra-pulmonary systems, resulting in a high fatality rate. The purpose of this review article is to understand the impact of COVID-19 on cardiovascular and respiratory function in young adults who have recovered from Covid-19. Methodology: To construct a narrative review on this topic, we examined a number of databases, Google Scholar, Medline, PubMed, Researchgate and search approach was using a combination of the words impact of Covid- 19 on young adults, SARS-CoV-2, cardiovascular status, respiratory status. Discussion: It was found that even while the majority of mild and moderate instances of acute respiratory distress syndrome recover completely, a tiny percentage of severe cases of acute respiratory distress syndrome remain hypoxemic despite obtaining proper care and VO2 max is seen to be reduced in COVID-19 symptomatic patients compared to asymptomatic. There was a high prevalence of multi-organ failure and associated elevated d-dimer, fibrinogen, and delayed thrombin time in severe diseases, and their negative outcomes were linked to co-morbidities such as hypertension, cardiovascular, pulmonary illness and acute respiratory distress syndrome (ARDS). Conclusion: The long-term effect of Coronavirus on cardiopulmonary function is highly controversial. It is expected that some patients will have subclinical and possibly observable cardiovascular abnormalities. Patients with allegedly recovered cardiac function may still be at risk of CAD, atrial fibrillation or ventricular arrhythmias. Recovered patients with compromised respiratory status are more vulnerable to develop respiratory and cardiac ailments later in life.

Ensembled Feature based Multi-Label ECG Arrhythmia Classification.

Arrhythmia is one of the major contributors to sudden cardiac death. Compared to single-label arrhythmia classification, multi-label classification provides the advantage of simultaneous detection of different cardiac ailments. Existing multi-label approaches employ deep learning models, which have several limitations, e.g., data dependency, overfitting, complexity, and lack of interpretability. In this work, we propose a multi-label classification framework with ensembled hand-crafted features added with label powerset, which better preserves the correlation between classes. Experimentation with CPSC 2018 database shows that the proposed model provides accuracy and F1-score of 88.52% and 88.45% for single-label data and 88.11% and 86.32% for multi-label data, respectively. The proposed method improves individual class performance for some important diseases compared to the existing multi-label state-of-the-art methods.Clinical relevance- Early detection of life-threatening multi-label ECG patterns consisting of atrial fibrillation, atrioventricular block, and right bundle branch block with high accuracy can reduce the sudden cardiac death rate.

Classification of ECG signals using deep neural networks

The electrocardiogram (ECG) is an essential tool in the field of cardiology, as it enables the electrical activity of the heart to be measured. It involves placing electrodes on the patient's skin, facilitating the measurement and analysis of cardiac rhythms. This non-invasive and painless test provides essential information about the heart's function and helps in diagnosing various cardiac conditions. The classification of ECG signals using deep learning techniques has garnered substantial interest in recent years; ECG classification tasks have exhibited promising outcomes with the application of deep learning models, particularly convolutional neural networks (CNNs). The GoogleNet, AlexNet, and ResNet Deep-CNN models are proposed in this study as reliable methods for accurately diagnosing and classifying cardiac diseases using ECG data. The primary objective of these models is to predict and classify prevalent cardiac ailments, encompassing arrhythmia (ARR), congestive heart failure (CHF), and normal sinus rhythm (NSR). To achieve this classification, 2D Scalogram images obtained through the continuous wavelet transform (CWT) are utilized as input for the models. The study's findings demonstrate that the GoogleNet, AlexNet and Resnet models achieve an impressive accuracy rate of 96%, 95,33% and 92,66%, in accurately predicting and classifying ECG signals associated with these cardiac conditions, respectively. Overall, the integration of deep learning techniques, such as the GoogleNet, AlexNet, and ResNet models, in ECG analysis holds promise for enhancing the accuracy and efficiency of diagnosing and classifying cardiac diseases, potentially leading to improved patient care and outcomes.

A Study of Prognosis and Outcome of COVID-19-Infected Hypertensive Patients on Angiotensin-Converting Enzyme Inhibitors/Angiotensin Receptor Blockers

Abstract Background and Objective: COVID-19 is a pandemic caused by the virus severe acute respiratory syndrome coronavirus-2. The mortality in susceptible populations with chronic pulmonary disease, cardiac ailments, kidney disease, diabetes, and hypertension is high. While the role of angiotensin-converting enzyme inhibitors (ACEi)/angiotensin receptor blockers (ARBs) in contracting novel coronavirus has clearly been elucidated, there remains uncertainty in the prognosis and outcome of COVID-19-infected patients on ACE inhibitors and ARBs. The current study was conducted to find whether these medications bore any significance in the prognosis and outcome of hypertensive patients with COVID-19 infection. Materials and Methods: This is a retrospective cohort study. We studied 96-admitted hypertensive patients with pneumonia due to COVID-19 in Krishna Rajendra Hospital at Mysore during April 2021. Patients were categorized into two groups based on antihypertensive treatment: (1) Those on ACEi/ARBs (n = 33) and (2) Those on non-ACEi/ARBs (n = 66). We analyzed the parameters such as duration of hypertension, comorbidities, mode of oxygen/pressure support delivery, duration of hospital stay, and mortality among the two groups. Results: 65.6% of patients were on non-ACEi/ARBs, 10.4% on ACE inhibitors, and 24% on ARBs. Of the patients on non-ACEi/non-ARBs, 51% were on supplemental oxygen, 20.8% were on NIV, 6.3% were intubated, and 21.9% did not require oxygen. Of those on ACEi, 63.6% were on supplemental oxygen, 15.2% were on NIV, none were intubated, and 21.2% did not require oxygen. Of those on ARBs, 53.3% were on supplemental oxygen, 18.5% were on NIV, 5.4% were intubated, and 22.8% did not require oxygen. 62.5% of patients on non-ACEi/ARBs recovered, whereas 37.5% succumbed. 83.3% of patients on ACEi recovered, whereas 16.7% succumbed. 65.2% of patients on ARBs recovered, whereas 34.8% succumbed. There was no significant correlation between non-ACEi/ARBs, ACEi, and ARBs with duration of hypertension (P = 0.092), sex (P = 0.189), mode of oxygen/pressure support delivery (P = 0.313), ward/intensive care unit stay (P = 0.624), and the final outcome of the patient (P = 0.734). Conclusion: In the population studied, the use of ACEi/ARBs in COVID-positive hypertensives was not associated with adverse outcomes as compared to those on non-ACEi/non-ARBs.