Dataset Information

High risk for latent tuberculosis infection among medical residents and nursing students in India.

ABSTRACT: Defining occupational latent tuberculosis infection (LTBI) risk among healthcare workers is needed to support implementation of prevention guidelines. Prospective cohort study of 200 medical residents and nursing students in India was conducted May 2016-December 2017. Tuberculin skin test (TST) and QuantiFERON TB Gold Test-in-tube (QFT-GIT) were performed at study entry and 12 months. Primary outcome was incident LTBI (?10mm TST induration and/or ?0.35IU/mL QFT-GIT) at 12 months; secondary outcomes included baseline LTBI prevalence and risk factors for incident and prevalent LTBI using Poisson regression. Among 200, [90 nursing students and 110 medical residents], LTBI prevalence was 30% (95% CI, 24-37); LTBI incidence was 26.8 (95% CI, 18.6-37.2) cases per 100 person-years and differed by testing method (28.7 [95% CI, 20.6-38.9] vs 17.4 [95% CI, 11.5-25.4] cases per 100 person-years using TST and QFT-GIT, respectively). Medical residents had two-fold greater risk of incident LTBI than nursing students (Relative Risk, 2.16; 95% CI, 1.05-4.42). During study period 6 (3%) HCWs were diagnosed with active TB disease. Overall, median number of self-reported TB exposures was 5 (Interquartile Range, 1-15). Of 60 participants with prevalent and incident LTBI who were offered free isoniazid preventive therapy (IPT), only 2 participants initiated and completed IPT. High risk for LTBI was noted among medical residents compared to nursing students. Self-reported TB exposure is underreported, and uptake of LTBI prevention therapy remains low. New approaches are needed to identify HCWs at highest risk for LTBI.

SUBMITTER: Kinikar A

PROVIDER: S-EPMC6613683 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High risk for latent tuberculosis infection among medical residents and nursing students in India.

Kinikar Aarti A Chandanwale Ajay A Kadam Dileep D Joshi Samir S Basavaraj Anita A Pardeshi Geeta G Girish Sunita S Shelke Sangeeta S DeLuca Andrea A Dhumal Gauri G Golub Jonathan J Lokhande Nilima N Gupte Nikhil N Gupta Amita A Bollinger Robert R Mave Vidya V

PloS one 20190708 7

Defining occupational latent tuberculosis infection (LTBI) risk among healthcare workers is needed to support implementation of prevention guidelines. Prospective cohort study of 200 medical residents and nursing students in India was conducted May 2016-December 2017. Tuberculin skin test (TST) and QuantiFERON TB Gold Test-in-tube (QFT-GIT) were performed at study entry and 12 months. Primary outcome was incident LTBI (≥10mm TST induration and/or ≥0.35IU/mL QFT-GIT) at 12 months; secondary outco ...[more]

PMID: 31283794

Similar Datasets

Project description:BackgroundMeaning in life, defined by an individual's understanding and appreciation of life, is a vital aspect of a positive psychological state, that has a significant influence on physical and mental health. Therefore, improving the sense of meaning in life among nursing students has emerged as a crucial concern in nursing education. This study aimed to clarify the profiles and influencing factors of meaning in life among nursing students.MethodsA descriptive cross-sectional online survey was conducted among nursing students in China from November 16, 2022, to January 17, 2023. The demographic information questionnaire and the meaning in life questionnaire (MLQ) were used to collect data. Latent profile analysis (LPA) was used to identify groups exhibiting distinct levels of meaning in life. Additionally, univariate analysis and multinominal logistic regression analysis were used to investigate the factors influencing each group. The reporting of this study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist.ResultsA total of 10,583 valid responses were received, and the analysis revealed four distinct profiles. The profiles identified were the medium meaning group (C1, 41.4%), medium fluctuation meaning-no motivation group (C2, 8.7%), lower meaning group (C3, 9.7%), and higher meaning group (C4, 40.2%). The univariate analysis revealed that age, gender, ethnicity, marital status, educational level, grade, university classification, student leadership experience, and political affiliation were factors that influenced the four latent profiles (P < 0.05). The multinomial logistic regression analysis showed that age, gender, ethnicity, education level, and student leadership experience were significant predictors of the various profiles (P < 0.05).ConclusionThere is heterogeneous in meaning in life among nursing students in China. Nursing educators need to provide tailored guidance based on the latent classification characteristics of meaning in life among nursing students, aiming at improving their meaning in life and promoting the development of the nursing workforce.

Project description:ImportanceTesting for and treating latent tuberculosis infection (LTBI) is among the main strategies to achieve TB elimination in the United States. The best approach to testing among non-US born residents, particularly those with comorbid conditions, is uncertain.ObjectiveTo estimate health outcomes, costs, and cost-effectiveness of LTBI testing and treatment among non-US born residents with and without medical comorbidities.Design, setting, and participantsDecision analytic tree and Markov cohort simulation model among non-US born residents with no comorbidities, with diabetes, with HIV infection, or with end-stage renal disease (ESRD) using a health care sector perspective with 3% annual discounting. Strategies compared included no testing, tuberculin skin test (TST), interferon gamma release assay (IGRA), confirm positive (initial TST, IGRA only for TST-positive results; both tests positive indicates LTBI), and confirm negative (initial IGRA, then TST for IGRA-negative; any test positive indicates LTBI). All strategies were coupled to treatment with 3 months of self-administered rifapentine and isoniazid.Main outcomes and measuresNumber needed to test and treat to prevent 1 case of TB reactivation, discounted quality-adjusted life-years (QALYs), discounted lifetime medical costs, and incremental cost-effectiveness ratios (ICERs).ResultsImproving health outcomes increased costs, with choice of test dependent on willingness to pay. Strategies ranked by ascending costs and benefits: no testing, confirm positive, TST, IGRA, and confirm negative. The ICERs varied by non-US born patient risk group: patients with no comorbidities, IGRA was likely cost-effective at $83 000/QALY; patients with diabetes, both confirm positive ($53 000/QALY) and IGRA ($120 000/QALY) were likely cost-effective; patients with HIV, confirm negative was clearly preferred ($63 000/QALY); and patients with ESRD, no testing was cost-effective. Increased LTBI prevalence and reduced return for TST reading improved IGRA's relative performance. In 10 000 probabilistic simulations among non-US born patients with no comorbidities, with diabetes, and with HIV, some form of testing was virtually always cost-effective. These simulations highlight the uncertainty of test choice for non-US born patients with no comorbidities and non-US born patients with diabetes, but strategies including IGRA were preferred in over 60% of simulations for all non-US born populations except those with ESRD.Conclusions and relevanceTesting for and treating LTBI among non-US born residents with and without selected comorbidities is likely cost-effective except among those with ESRD in whom competing risks of death limit benefits. Strategies including IGRA fell below a $100 000/QALY willingness-to-pay threshold for non-US born patients with no comorbidities, patients with diabetes, and patients with HIV.

Dataset Information

High risk for latent tuberculosis infection among medical residents and nursing students in India.

Publications

High risk for latent tuberculosis infection among medical residents and nursing students in India.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets