Introduction and objective We used AST to ALT ratio (AAR) and, liver stiffness measurement (LSM), splenic stiffness measurement (SSM) by transient elastography to develop a statistical model and present it as a user-friendly smartphone application to exclude the presence of oesophageal and cardio-fundal varices to avoid upper gastrointestinal endoscopy in selected patients. Methods A prospective study was carried out among patients with Child-Pugh Class A cirrhosis (non-viral and non-obese - BMI<30kg/m2). LSM and SSM were obtained using Fibroscan (EchoSens) by a single operator, blinded to the presence or absence of varices. The predictors used to develop the formula were AAR, LSM and SSM. Multiple logistic regression was used to create the algorithms in 70% of the sample and validated using 30% of the sample with Bootstrapping of 1000. Best algorithms with the highest area under the curve (AUC) were selected and identified as different cut-off levels to exclude or predict the presence of varices. Those values were included in a smartphone application on android and iOS web-based platforms. Results One hundred nine out of 211 had varices. After modelling different combinations, logistic regression formula (LRF)=5.577+(LSM*0.035)+(SSM*0.08)+(AAR*1.48) resulted AUCs 0.93. Cut-off value <-1.26 of LRF predicted the exclusion of varices with a negative predictive value of 90%. Cut-off value >0.829 of LRF predicted the presence of varices with a positive predictive value of 91%. Multiple values were used to develop a smartphone app on the Angular 2+ platform. (It can be downloaded for use @https://mediformula-65ef0.web.app/).
Objectives We estimated the prevalence and effect sizes of associations for NAFLD, the commonest chronic liver disease worldwide, among South-Asian adults. Design We searched the PubMed database, using search terms "Prevalence of NAFLD (Non-Alcoholic Fatty Liver Disease)" AND "South Asia" AND South Asian countries ("Afghanistan", "Bangladesh", "Bhutan", "India", "Maldives", "Nepal", "Pakistan" and "Sri Lanka"). We included descriptive, epidemiological studies with satisfactory methodology, reporting the prevalence of NAFLD with a valid diagnostic method (ultrasound/CT imaging, biochemistry, histology). The quality of the studies was assessed using Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. Two authors screened and extracted data independently. A random-effects meta-analysis of prevalence and effect sizes of associations of NAFLD was performed. Gender, urban/rural setting, general population and individuals with metabolic diseases (MetD) stratified the analysis. Results Thirty-two articles were included in the systematic review, and 21 publications were included in the meta-analysis after quality assurance. The pooled overall prevalence of NAFLD in the general population was 25.2% [95%CI 20.3-30.5%] with high heterogeneity (k=9; Q=251.6, DF=8, P<0.0001, I 2 =96.8%). The prevalence was similar among men and women (Q=0.10, DF=1, P=0.746). The NAFLD prevalence in the rural communities were 26.0% (95%CI: 18.2–34.5%) and it was 26.6% (95%CI: 20.5-33.1%) in urban communities without significant differences in the prevalence (Q=0.01, DF=1, P= 0.916). The pooled overall prevalence of NAFLD in patients with MetD was 55.1% [95%CI 47.4-62.8%] with high heterogeneity (k=8; Q=53.8, DF=7, P<0.0001, I 2 =85.2%). The pooled overall prevalence of NAFLD in the non-obese population was 11.7% [95%CI 7.0-17.3%] (k=6; Q=170.1, DF=5, P<0.0001; I2=97.1%). The pooled prevalence of non-obese NAFLD in the NAFLD population was 43.4% [95%CI 28.1-59.4%] [k=6; Q=181.1; P<0.0001; I2=97.2%]. Meta-analysis of binary outcomes showed presence of NAFLD in South Asian population was associated with diabetes mellitus [RR-2.03 (1.56-2.63)], hypertension [RR-1.37 (1.03-1.84)], dyslipidaemia [RR-1.68 (1.51-1.88)], general obesity [RR-2.56 (1.86-3.51)], central obesity [RR-2.51 (1.69-3.72)] and metabolic syndrome [RR-2.86 (1.79-4.57)]. Gender was not associated with NAFLD. Conclusions The overall prevalence of NAFLD among adults in South Asia is high, especially those with metabolic abnormalities, and a considerable proportion are non-obese. In the South Asian population, NAFLD was associated with MetD.
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