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Data and code for "Influence of setting and diagnostic algorithm on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa"

Domain:

healthcare

Record type:

dataset
Creator:
McC
Editor:
GovSitWonBut
Publisher:
Lon
Host:avatar
Data and code to replicate the analyses in the paper "Influence of setting and diagnostic algorithm on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa". Dataset variables cover participant demographics, CD4TB score, TB diagnosis and symptoms, Xpert Ultra result, past instances of TB, HIV/ART status, and cavitation on chest X-ray. R code is used to generate table 1 and figure 1-2.

Visit

doi.orgdatacompass.lshtm.ac.uk

Licenses

Data Sharing Agreementhttps://datacompass.lshtm.ac.uk/id/eprint/5244Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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Influence of setting and diagnostic algorithm on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa

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Influence of setting and diagnostic algorithm on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa: Dataset and code