Evaluation of the Diagnostic Potential of Liver Aminotransferases and Alkaline Phosphatase in Patients with Cardiovascular Diseases.

Background Cardiovascular diseases (CVDs) are the major cause of morbidity and mortality, particularly in developing countries. Early diagnosis with the best diagnostic marker is highly desired for the prevention and timely treatment of CVDs. However, there is still a dearth of an ideal marker for the detection of CVDs. Objective To explore the diagnostic potential of liver aminotransferases (AST and ALT), and alkaline phosphatase for the diagnosis of CVDs without liver involvement. Method This was a cross-sectional study conducted among 200 adult patients with CVDs, who visited the cardiology and emergency units of Manipal Teaching Hospital, Pokhara, Nepal. The study was conducted from January 2018 to December 2020. The baseline data on family history, anthropometry, baseline biochemical parameters, liver enzymes, and cardiac biomarkers were collected using standard and validated methods. The data were analyzed using SPSS version 21 and MedCalc software 2021. Result The diagnostic sensitivity of aspartate aminotransferase, alanine aminotransferase and alkaline phosphatase were 53.7%, 52.6%, and 33.7% and specificity were 99%, 90%, and 90% respectively. The area under the curve (AUC) of AST, ALT, and ALP were 0.78, 0.73, and 0.52 respectively. ROC curve indicated that serum AST and ALT activity was a better reliable marker than the serum ALP activities. Conclusion Our study suggests that serum aspartate aminotransferase and alanine aminotransferase but not alkaline phosphatase could have some diagnostic potential to diagnose the risk of CVDs. However, they could not replace the currently adopted cardiac biomarkers such as cTnI and CK-MB.

Association of Anthropometric Parameters with Lipid Profile among Adult Population of Kaski District, Nepal.

Background Anthropometric parameters of individuals are good at predicting functional impairment, mortality, and future cardiometabolic diseases. The relationship between anthropometric parameters and lipid profiles have been studied in different parts of the world. But to date, no such studies have been conducted in Nepal. Objective To investigate the association between anthropometric parameters and lipid profile in the adult population of Kaski district, Nepal. Method This study was carried out at Manipal Teaching Hospital, Pokhara, Kaski, Nepal. The fasting lipid profiles were analyzed in a total of 400 subjects aged > 18 years with an automated OCD Vitros 350 dry chemistry analyzer. The Kolmogorov-Smirnov test was used to test the normality of the data. The mean values of fasting lipids were compared within the subjects with different body mass index groups using ANOVA and waist circumference, waist-hip ratios, waist-height ratios, and neck circumference using independent samples t-test. The anthropometric indices evaluated were body mass index, waist circumference, waist-hip ratio, waist-height ratio, head circumference, neck circumference, and mid-upper arm circumference. Pearson's correlation coefficients and multiple regression analysis were performed to identify the association between the lipid profile and anthropometric parameters. The difference was considered statistically significant when p values (two-tailed) were < 0.050. Result The mean values of the serum lipid parameters other than high-density lipoprotein cholesterol were found to be higher in the subjects with an above than normal BMI, waist circumference, waist-hip ratio, waist-height ratio, and neck circumference. Pearson's correlation coefficient and multiple regression analysis showed that waistheight ratio best predicts serum triglycerides (ß=0.622, p < 0.001) and high-density lipoprotein cholesterol (ß=-0.711, p < 0.001) among all measured anthropometric parameters. Conclusion Among all the studied anthropometric parameters, the WHtR was found to be the most powerful predictor of serum triglycerides and high-density lipoprotein cholesterol.