http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/242 Assistant Professor, College Veng, Aizawl 2025-10-30T07:48:42Z http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/739 Title: Prevalence and predictors of tobacco use among currently married pregnant women in India Authors: Pasupuleti, Samba Siva Rao Abstract: Tobacco use during pregnancy has harmful consequences both to the women and their fetuses. There is a lack of national-level information on the prevalence and predictors of tobacco use among pregnant women in India. This study fills this gap by investigating the prevalence and predictors of tobacco use among currently married pregnant women in India. METHODS Unit level data from the fourth National Family Health Survey, conducted in India during 2015–2016, were used in this study. Logistic regression analyses were performed to identify independent factors associated with tobacco use. RESULTS Our results suggest the prevalence of tobacco use among currently married pregnant women in India is 4.6% (95% CI: 4.3–5.1), and more than 80% of pregnant tobacco users use tobacco in the smokeless form only. Age of woman, region of residence, education level, religion, caste, wealth quintile, frequency of watching television were the independent predictors of tobacco use among currently married pregnant women in India. In general, lower socioeconomic status is positively associated with tobacco use among them. CONCLUSIONS Around 4.6% of pregnant women in India use tobacco, and the smokeless form of tobacco use is predominant among pregnant tobacco users. Socioeconomic disadvantage is positively associated with tobacco use among pregnant women in India. The findings of the present study need to be used to reduce tobacco use among pregnant women in the country by identifying subpopulations at risk, and sensitizing them to the harmful consequences of tobacco use, by offering tobacco cessation services during prenatal checkups. 2021-03-22T00:00:00Z http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/738 Title: Comparison of Prognostic Models in Acute Liver Failure: Decision is to be Dynamic Authors: Pasupuleti, Samba Siva Rao Abstract: Background and aims: Acute liver failure (ALF) is a rare disease entity with a high mortality. Management is dependent on accurate prognostication. Materials and methods: One hundred consecutive patients presenting with ALF were prospectively evaluated. The King’s college criteria (KCC), ALF early dynamic model (ALFED), sequential organ failure assessment (SOFA) score, and acute physiology and health evaluation II (APACHE II) scores were compared to predict mortality. Results: There were significant differences in means of all the scores between survivors and nonsurvivors. The SOFA 48 hours had the highest area under receiver operating characteristic curve (AUC) (0.857) closely followed by the ALFED score (0.844). The optimal cutoff for the SOFA score at 48 hours to predict subsequent survival outcome is ≥10 and for the ALFED score is ≥5. Sequential organ failure assessment 48 hours had a good sensitivity of 87%, and the ALFED score showed a good specificity of 84%. The decision curve analysis showed that between a threshold probability of 0.13 and 0.6, use of the SOFA score provided the maximum net benefit and at threshold probabilities of >0.6, the use of ALFED score provided the maximum clinical benefit. Conclusion: Dynamic scoring results in better prognostication in ALF. The SOFA 48 hours and ALFED score have good prognostication value in nonacetaminophen-induced liver failure. 2019-01-01T00:00:00Z http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/737 Title: Degree of Portal and Systemic Hemodynamic Alterations Predict Recurrent AKI and Chronic Kidney Disease in Patients With Cirrhosis Authors: Pasupuleti, Samba Siva Rao Abstract: The relevance of hemodynamic derangements on the incidence of recurrent acute kidney injury (AKI) and chronic kidney disease (CKD) in patients with cirrhosis is largely unknown. Consecutive patients with cirrhosis with a complete record of baseline hemodynamics were followed for identifying risk factors for the development of recurrent AKI and CKD by using negative binomial regression and competing risk analysis, respectively. Consecutive patients with cirrhosis (n = 2013, age 50.1 ± 11.8 years, 80% male, Child A:B:C percentage 13.7:52.9:33.4, and mean Child- Turcotte-Pugh score 8.6 ± 1.8) were enrolled, 893 (44.3%) of whom received beta-blockers, with 44.2% responders. Prior AKI was noted in 12.4% at enrollment. At a median follow-up of 379 (interquartile range: 68-869) days, AKI developed at a rate of 0.37 episodes per person-year, and 26% patients developed CKD. A lower mean number of AKI episodes (0.05 ± 0.25 vs. 0.42 ± 0.868; P < 0.001), CKD (subdistribution hazard ratio 0.74 [0.54-1.02]), and mortality (hazard ratio 0.21 [0.06-0.73]) were observed in beta-blocker responders. Albuminuria was an independent risk factor for recurrent AKI, CKD, and mortality (P < 0.05). Lower systemic vascular resistance index predicted hemodynamic response (odds ratio 2.04 [1.29-3.22]), cumulative AKI episodes (ratio of means 0.10 [0.08-0.14]), and development of CKD (subdistribution hazard ratio 0.70 [0.58-0.83]). Higher hepatic venous pressure gradient (≥17 mm Hg) predicted AKI episodes (ratio of means 1.76 [1.32-2.35]) but not CKD. Conclusion: High portal pressure and severe vasodilatation predispose patients with cirrhosis to repeated AKI episodes and development of CKD. Response to beta-blockers and therapies targeting the vasodilatory state could prevent frequent AKI and the risk of CKD development. Albuminuria could serve as an early marker of renal dysfunction in patients with cirrhosis. (Hepatology Communications 2021;5:293-308). 2021-01-01T00:00:00Z http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/735 Title: A nonparametric regression-based linkage scan of rheumatoid factor-IgM using sib-pair squared sums and differences Authors: Pasupuleti, Samba Siva Rao Abstract: Parametric linkage methods for quantitative trait locus mapping require explicit specification of the probability model of the quantitative trait and hence can lead to misleading linkage inferences when the model assumptions are not valid. Ghosh and Majumder developed a nonparametric regression method based on kernel-smoothing for linkage mapping of quantitative trait locus using squared differences in trait values of independent sib pairs, which is relatively more robust than parametric methods with respect to violations in distributional assumptions. In this study, we modify the above mentioned nonparametric regression method by considering local linear polynomials instead of the Nadaraya-Watson estimator and squared sums of sib-pair trait values in addition to squared differences to perform a genome-wide scan of rheumatoid factor-IgM levels on sib pairs in the Genetic Analysis Workshop 15 simulated data set. We obtain significant evidence of linkage very close to the quantitative trait locus controlling for RF-IgM. We find that the simultaneous use of squared differences and squared sums increases the power to detect linkage compared to using only squared differences. However, because of all the sib pairs are selected for rheumatoid arthritis, there is reduced variance of RF-IgM values, and empirical power to detect linkage is not very high. We also compare the performance of our method with two linear regression approaches: the classical Haseman-Elston method using squared sib-pair trait differences and its extension proposed by Elston et al. using mean-corrected sib-pair cross-products. We find that the proposed nonparametric method yields more power than the linear regression approaches. 2017-12-18T00:00:00Z