ABSTRACT
Context: A total of 350 million individuals are affected by chronic hepatitis B virus infection world-wide. Historically, liver biopsy has been instrumental in adequately assessing patients with chronic liver disease. A number of non-invasive models have been studied world-wide. Aim: The aim of this study is to assess the utility of non-invasive mathematical models of liver fi brosis in chronic hepatitis B (CHB). Indian patients in a resource limited setting using routinely performed non-invasive laboratory investigations. Settings and Design: A cross-sectional study carried out at a tertiary care center. Subjects and Methods: A total of 52 consecutive chronic liver disease patients who underwent percutaneous liver biopsy and 25 healthy controls were enrolled in the study. Routine laboratory investigations included serum aspartate aminotransferase (AST), Alanine aminotransferase (ALT), Gama glutamyl transpeptidase (GGT), total bilirubin, total cholesterol, prothrombin time and platelet count. Three non-invasive models for namely aspartate aminotransferase to platelet ratio index (APRI), Fibrosis 4 (FIB-4) and Forn’s index were calculated. Outcomes were compared for the assessment of best predictor of fi brosis by calculating the sensitivity, specifi city, positive predictive value (PPV) and negative predictive value (NPV) of each index. Statistical Analysis Used: Medcalc online software and by Microsoft Excel Worksheet. Chi-square test was used for signifi cance. P value < 0.05 was taken as signifi cant. Results: While the serum levels of AST, ALT and GGT were signifi cantly higher in patients group as compare with the healthy controls (P < 0.01), the platelet counts were signifi cantly lower in patient group as compared to the control group (P < 0.01). Mean value of all 3 indices were signifi cantly higher in patients group as compare with the controls (P < 0.01). Conclusions: Out of the three indices, APRI index with a NPV of 95% appeared to be a better model for excluding signifi cant liver fi brosis while FIB-4 with a PPV of 61% showed fair correlation with signifi cant fi brosis. Thus, these two non-invasive models for predicting of liver fi brosis, namely APRI and FIB-4, can be utilized in combination as screening tools in monitoring of CHB patients, especially in resource limiting settings.
ABSTRACT
BACKGROUND AND AIM: While the effect of age, gender, body mass index and renal failure on B-type natriuretic peptide (BNP) has been studied individually in different trials, the influence of all these co-morbidities in patients with dyspnea needs to be evaluated. The objective of our study was to examine the effect of age, gender, obesity and co-morbid conditions on the evaluation of higher BNP levels in patients presenting with dyspnea. METHODS: A total of 382 patients admitted with shortness of breath and suspected to have congestive heart failure were included in the study. The co-morbid conditions studied were pulmonary hypertension, pleural effusion, obesity, renal failure and chronic obstructive pulmonary disease. RESULTS: The mean BNP levels significantly increased with age. Women tended to have slightly higher mean BNP levels than men, but the differences were not statistically significant. The body mass index had an inverse correlation with the BNP level. Regression analysis demonstrated that the most significant predictors of a higher BNP were the lower left ventricular ejection fraction (OR 6.2: 95% CI 2.74-14.02), renal failure (OR 3.88: 95% CI 1.9-7.91) and pulmonary hypertension (OR 2.28: 95% CI 1.14-4.54). CONCLUSION: A lower left ventricular ejection fraction, renal failure and pulmonary hypertension were the most significant predictors of an increased BNP level. Age, gender, obesity and pleural effusion minimally influenced the BNP level and were not significantly predictive of congestive heart failure.