Clinical profile and prognostic factors of alcoholic cardiomyopathy in tribal and non-tribal population

natural history and prognostic factors in alcoholic cardiomyopathy

It is therefore possible that most of these studies may have also consistently marijuana addiction omitted most alcohol abusers in whom alcohol had already caused significant ventricular dysfunction. To our knowledge, our study determined prognostic factors for ACM outcome in the largest cohort of ACM patients described to date. Our data show that the variables most closely predicting a poor outcome in ACM are QRS duration, SBP and NYHA classification at admission. All 299 patients underwent a routine evaluation including a physical examination, 12-lead electrocardiography, 2-dimensional echocardiography, and a complete biochemical evaluation.

Alcoholic consumption and heart failure

Furthermore, WHO cardiovascular risk charts have been shown to misclassify high-risk South Asians as low-risk with higher prevalence13. These findings highlight the need for more accurate tools tailored to the unique risk profile of South Asian patients. Many studies were conducted on using CTP Score as a prognostic marker in cirrhotic cardiomyopathy. In our study, patients assessed as having https://ecosoberhouse.com/article/how-to-stop-alcohol-shakes-tremors/ CTP Score B, C had a higher mortality as compared with the patients having CTP Score A, and CTP Score was found to be one of the independent prognostic predictors in the multivariate Cox regression analysis. Plots of Kaplan-Meier displaying the estimated survival probability according to three factors (A–C). (A) Kaplan-Meier plots displaying the estimated survival probability in groups categorised according to QRS duration.

  • From January 2013 to December 2016, we collected data of 290 patients with ACM referred for evaluation to the Department of Internal Medicine and Department of Cardiology in our institute RIMS, Ranchi.
  • Unfortunately, all the available reports were completed at a time when a majority of the current heart failure therapies were not available (Table 1).
  • In summary, ML could significantly enhance MI diagnosis in the South Asian population by improving diagnostic accuracy, integrating multimodal data, and identifying atypical presentations94.
  • In the second study, Gavazzi led a multicentre study in which, from 1986 to 1995, 79 patients with ACM and 259 patients with DCM were recruited10.
  • Cohort studies in rural South India identify tobacco use, alcohol consumption, hypertension, diabetes mellitus, and obesity as significant risk factors9,20.

Study population

Additional studies included 24-hour ECG monitoring and cardiac magnetic resonance imaging. Coronary angiography, coronary artery computed tomography (CT), or nuclear medicine testing was performed to rule out coronary heart diseases. More specifically, atrial fibrillation with rapid ventricular response is a cause of arrhythmia-induced cardiomyopathy,61 which can potentially worsen LVEF in alcoholic cardiomyopathy AC patients, on top of the direct toxic effect of ethanol, acetaldehyde damage, or the aforementioned genetic factors. Stratified according to DM status and malnutrition, with a comparative analysis of all-cause death (a) or cardiac mortality (b).

1. Clinical features

natural history and prognostic factors in alcoholic cardiomyopathy

Generative artificial intelligence (AI) powered tools, such as virtual co-pilots, can support clinicians by offering real-time, personalized health recommendations that account for individual genetic, lifestyle, and environmental factors. Furthermore, AI platforms can deliver culturally tailored health education, improving patient understanding and engagement. Integrating these advanced AI technologies into clinical practice has the potential to significantly improve secondary cardiovascular prevention strategies, particularly in high-risk populations. Regarding ICD and CRT implantation, the same criteria as in DCM are used in ACM, although it is known that excessive alcohol intake is specifically linked to ventricular arrhythmia and sudden cardiac death71.

  • From the data provided in the available ACM studies, it appears that patients who received an ACEI globally showed improved prognosis.
  • Even investigations revealed higher incidences of AF, AVB, increased QRS duration, reduced LVEF, increased LVESD and LVEDD in tribal group.
  • Myocardial infarction (MI) is a leading cause of death globally, contributing to nearly 17.9 million annual deaths, significantly impacting healthcare systems and economic productivity1.
  • The suspicion that there may be an individual susceptibility to this disease is underscored by the finding that only a small group of alcoholics develop ACM, and that a proportional relationship between myocardial damage and alcohol intake has not been proven.

Incremental value of malnutrition in predicting adverse prognosis

It should be noted that a moderate drinker included in this latter group showed an improvement of his ejection fraction. In spite of the high prevalence of excessive alcohol consumption and of its consideration as one of the main causes of DCM, only a small number of studies have analysed the long-term natural history of ACM. Unfortunately, all the available reports were completed at a time when a majority of the current heart failure therapies were not available (Table 1). Unfortunately Lazarević et al23, as in most of these studies, systematically excluded patients with a history of heart disease or with HF symptoms.

Among patients who continued drinking heavily, transplant-free survival was significantly worse than in non-drinkers (27% vs 45%). Finally, it is worth stressing that a large majority of studies on the physiopathology and prognosis of ACM were conducted some years ago, prior to the development of our current understanding regarding the role of genetics in DCM67. According to recent data, a genetic form of DCM could be present in up to 50% of idiopathic DCM cases, and other specific forms of DCM such as peripartum cardiomyopathy have been shown to have a genetic basis in a significant number of cases68. It is therefore possible that patients with ACM could also harbour a genetic substrate that predisposes them to this form of cardiomyopathy. In this review, we evaluate the available evidence linking alcohol consumption with HF and DCM.

TREATMENT

natural history and prognostic factors in alcoholic cardiomyopathy

Architecturally, CNNs consist of convolutional filters, pooling modules, and fully connected layers. Convolutional layers perform the convolution of each sub-region of the input with a filter kernel, extracting features from the input provided by previous layers103. Pooling layers reduce the dimensions of feature maps, retaining essential information while lowering computational complexity.

natural history and prognostic factors in alcoholic cardiomyopathy

Prognostic factors assessment in ACM

natural history and prognostic factors in alcoholic cardiomyopathy

Moreover, ranolazine prevents ethanol-induced atrial arrhythmias both in vitro and in vivo by blocking the late sodium current, which is activated by CaMKII.112 Its effect on preventing the decrease of LVEF in AC is currently unknown. Several advanced CNN architectures, like AlexNet and VGG-Net, improve performance by using deeper networks and smaller convolutional filters103,104. A deep CNN developed by Acharya et al.94 for detecting MI achieved an accuracy of 93.53% using ECG94.

natural history and prognostic factors in alcoholic cardiomyopathy

All authors commented on prior manuscript versions and agreed to the final version for submission. Attention mechanisms overcame this limitation, enhancing translation performance by allowing a joint soft search of the source sentence without facing bottlenecks of a fixed vector, thereby improving translation accuracy. Transformers, introduced by Vaswani et al.112, are solely based on the attention mechanism, dispensing with recurrence and convolution entirely, achieving state-of-the-art results in machine translation112. Subsequently, Transformers have been applied to computer vision113,115 and speech recognition, achieving advanced performance across numerous ML tasks111,116,117. DL algorithms are trained using backpropagation through gradient descent, where backpropagation computes the gradient of the loss function concerning weights and biases, and gradient descent iteratively updates these parameters to improve feature extraction and prediction accuracy.

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