European Journal of Molecular & Clinical Medicine

In medical practise, an electrocardiogram (ECG) is a crucial indicator tool for assessing cardiovascular arrhythmias. In this study, a machine learning system is used to compare patient ECGs and perform programmed ECG arrhythmia identification. The system was previously tuned based on an overall image informational index. Arrhythmias are more prevalent in those over the age of 60. A convolutional neural network (particularly, Alex Net) is utilised to extract features, and the highlights are then passed via a basic back spread neural network to finish the classification. The fundamental purpose of this research is to provide a simple, effective, and relevant learning strategy for categorising the three types of heart conditions (cardiac defects) so that a diagnosis may be made. The findings showed that when a moving deep learning highlight extractor was combined with a standard back proliferation neural architecture, very elite rates could be achieved. In a comparative analysis, validation accuracy was shown to be 100 percent in Google Net, 94 percent in Squeeze Net, and about 97.33 percent in Alex Net.

Aim: To evaluate cardiac co-morbidities in patients with newly diagnosed type 2 diabetes mellitus using 2d echocardiography.
Method and material: This research comprised 100 newly diagnosed type 2 diabetes mellites individuals who were clinically asymptomatic, had blood pressure of 130/80mmHg, and had a normal ECG. All patients underwent FBS, PPBS, Renal function tests, including electrolytes, Glycosylated haemoglobin (HbA1c), urine routine and microscopy, ECG, Fundoscopy, Chest x-ray, and Echocardiography.
Results: In the current research, 100 asymptomatic type 2 diabetes mellitus patients received 2-D echocardiography, with men (75%) outnumbering women (25%). The most prevalent age groups were 45-55 years and 55-65 years (30% apiece), with under 45 years (22%). Diastolic dysfunction was detected on 2-D echocardiography in 22 individuals (22%). Diastolic dysfunction of grades I, II, and III was seen in 12%, 7%, and 3% of patients, respectively. In present study, reduced early mitral inflow velocity was noted in 10 cases (10%) and mitral annular early diastolic velocity was noted in 19 cases (19%). We discovered that when HbA1c levels rise, so does the degree of left ventricular diastolic dysfunction; this difference was statistically significant (Chi-square test, p value 0.001). Three cases with grade 3 diastolic dysfunction had HbA1c >9.5, two cases with HbA1c >9.5 had grade 2 diastolic dysfunction, and six cases with HbA1c >9.5 had grade 1 diastolic dysfunction, all of which had LVDD.
Conclusion: Screening for cardiovascular abnormalities by 2D Echo is indicated in all newly diagnosed type 2 diabetes melites patients, with or without cardiovascular symptoms, so that early measures may be done to avoid further development of symptomatic cardiovascular abnormalities.

Background: The present study was conducted for evaluating the role of serum magnesium levels in chronic heart failure.
Materials & methods: A total of 100 patients with chronic heart failurenormal sinus rhythm were included in the present study. Blood samples were obtained and serum magnesium levels were assessed in all the patients. On the basis of magnesium levels, all the patients were divided into two study groups; 41 patients with normal magnesium levels (>2mEq/L) and 59 patients with low magnesium levels (≤ 2 mEq/L). Profile was compared among the two study groups. All the results were recorded in Microsoft excel sheet and were analysed by SPSS software.
Results: Significant higher proportion of subjects were diabetic among low magnesium level group. Age and diabetic status were found to be significantly correlated with low magnesium levels.  Blood pressure was significantly higher among subjects with low magnesium levels. Non-significant results were obtained while correlating serum potassium levels and Left ventricular ejection fraction with magnesium status.
Conclusion: Low serum magnesium levels were predictor of deranged cardiac and biochemical profile in chronic heart failure patients.

Background: For many ailments, exercise has become a popular therapeutic choice. Rehab through exercise is frequently utilised to improve respiratory and cardiovascular conditions. Despite the numerous benefits of regular exercise, persons with sedentary lifestyles, particularly students, do not include exercise into their daily routines. Exercise has different effects on the cardiovascular and respiratory systems depending on health and disease. Its effects vary depending on the physical fitness of the individuals, even in healthy individuals.
Aim and Objectives: The purpose of this study was to determine the effect that short-term exercise has on cardiorespiratory parameters in young healthy people who have and have not been exercising regularly.
Methods: For the purpose of the study, there were collected fifty medical students between the ages of 18 and 25 who had never participated in regular physical activity. Group I consisted of 25 students who engaged in activities such as cycling, aerobics, and yoga for a total of three months, each day for a duration of twenty-five minutes. Group II consisted of 25 students who did not take part in any form of physical activity or exercise. Before and immediately after a short-term exercise consisting of cycling for six minutes, the heart rate and blood pressure of the participants were recorded. Tests of the pulmonary function were performed in a comparable fashion both before and two minutes after the exercise.
Results: There was no discernible difference between persons who had exercise training and those who had not in terms of their HR, SBP, DBP, PP, MAP, or RPP. In trained people, the PFT metrics SVC, PEF and MVV were considerably higher (p=0.01, 0.03 and 0.03 respectively). When the effects of short-term exercise were compared, it was found that HR, SBP, PP, MAP and RPP all increased considerably after exercise in both groups (p value 0.05). This was the case regardless of whether the exercise was aerobic or anaerobic. Untrained participants showed a substantial drop in their PEF following exercise (p=0.05), whereas trained persons did not demonstrate the same trend (p=0.05).
Conclusion: Exercise performed for a shorter period of time does not have a substantial impact on the respiratory parameters of those who are not exercise trained. A training programme consisting of three months' worth of exercise can improve respiratory function with almost little effect on cardiovascular function.