2 research outputs found
High risk for latent tuberculosis infection among medical residents and nursing students in India.
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
The Lung Image Database Consortium, (LIDC) and Image Database Resource Initiative (IDRI)::a completed reference database of lung nodules on CT scans
Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process