Is a differentiated care model needed for patients with TB? A cohort analysis of risk factors contributing to unfavourable outcomes among TB patients in two states in South India.

BACKGROUND: TB is a preventable and treatable disease. Yet, successful treatment outcomes at desired levels are elusive in many national TB programs, including India. We aim to identify risk factors for unfavourable outcomes to TB treatment, in order to subsequently design a care model that would improve treatment outcomes among these at-risk patients. METHODS: We conducted a cohort analysis among TB patients who had been recently initiated on treatment. The study was part of the internal program evaluation of a USAID-THALI project, implemented in select towns/cities of Karnataka and Telangana, south India. Community Health Workers (CHWs) under the project, used a pre-designed tool to assess TB patients for potential risks of an unfavourable outcome. CHWs followed up this cohort of patients until treatment outcomes were declared. We extracted treatment outcomes from patient's follow-up data and from the Nikshay portal. The specific cohort of patients included in our study were those whose risk was assessed during July and September, 2018, subsequent to conceptualisation, tool finalisation and CHW training. We used bivariate and multivariate logistic regression to assess each of the individual and combined risks against unfavourable outcomes; death alone, or death, lost to follow up and treatment failure, combined as 'unfavourable outcome'. RESULTS: A significantly higher likelihood of death and experiencing unfavourable outcome was observed for individuals having more than one risk (AOR: 4.19; 95% CI: 2.47-7.11 for death; AOR 2.21; 95% CI: 1.56-3.12 for unfavourable outcome) or only one risk (AOR: 3.28; 95% CI: 2.11-5.10 for death; AOR 1.71; 95% CI: 1.29-2.26 for unfavourable outcome) as compared to TB patients with no identified risk. Male, a lower education status, an initial weight below the national median weight, co-existing HIV, previous history of treatment, drug-resistant TB, and regular alcohol use had significantly higher odds of death and unfavourable outcome, while age > 60 was only associated with higher odds of death. CONCLUSION: A rapid risk assessment at treatment initiation can identify factors that are associated with unfavourable outcomes. TB programs could intensify care and support to these patients, in order to optimise treatment outcomes among TB patients.

A Study to Evaluate Lipid Profile in Treatment Naïve HIV Positive Patients.

HIV infection is associated with lipid abnormalities in treatment naïve patients. CD4 count is used for monitoring the HIV infection. Primary objective was to evaluate and correlate lipid profile and CD4 counts in HIV infection. Secondary objective was to evaluate the feasibility of using Lipid profile to monitor the HIV infected treatment naïve patients instead of CD4 counts. 112 patients were selected based on a criteria from ART center in tertiary care center. CD4 counts were assessed and Lipid profile was evaluated enzymatically. A correlation study was done between the lipid profile and the CD4 count and clinical stages of infection. Cholesterol showed no significant correlation in any stage. HDL-C showed significant correlation (p < 0.05) with stage 2 and 4 disease. LDL-C showed no significant correlation in any stage. TGL showed significant correlation (p < 0.05) at stage 4 disease. Hence, HDL-C and TGL can be used as indicators of lipid status and for infection progression in treatment naive HIV patients, while Cholesterol and LDL-C has no role to play.

Naturally occurring polymorphisms and primary drug resistance profile among antiretroviral-naive individuals in Bangalore, India.

Although India has a large burden of HIV infection, good access to first-line antiretroviral therapy is widely available. However, understanding HIV resistance-associated mutations and polymorphisms is critical for continued success. The RT region of the HIV-1 pol gene was studied among 21 ART-naive HIV-1-infected individuals from South India. In addition, 421 published Indian HIV-1 subtype C sequences were analyzed for time trends in polymorphism frequency. Among primary isolates, all HIV-1 isolates were subtype C, and drug-resistant mutations were identified among two (9.56%) subjects. Mutations included E138A (etravirine resistance associated) and L210LS (thymidine analog mutation). The overall frequency of specific polymorphisms was similar to frequencies reported from different regions of India. Novel mutations were observed at positions Q23P/H and A129AG among isolates from our clinical cohort. Over a span of 10 years, the median polymorphism frequency among ART-naive subjects has remained unchanged, suggesting the slow evolution of HIV-1 subtype C in India.