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Optimizing Tuberculosis Diagnosis in HIV-Infected Inpatients Meeting the Criteria of Seriously Ill in the WHO Algorithm
Background The WHO algorithm for the diagnosis of tuberculosis in seriously ill HIV-infected patients lacks a firm evidence base. We aimed to develop a clinical prediction rule for the diagnosis of tuberculosis and to determine the diagnostic utility of the Xpert MTB/RIF assay in seriously ill HIV...
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| Format: | Thesis |
| Language: | English |
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Department of Medicine
2019
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| _version_ | 1867613198609285120 |
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| access_status_str | Open Access |
| author | Griesel, Rulan |
| author2 | Maartens, Gary |
| author_browse | Griesel, Rulan Maartens, Gary |
| author_facet | Maartens, Gary Griesel, Rulan |
| author_sort | Griesel, Rulan |
| collection | Thesis |
| description | Background
The WHO algorithm for the diagnosis of tuberculosis in seriously ill HIV-infected patients lacks a firm evidence base. We aimed to develop a clinical prediction rule for the diagnosis of tuberculosis and to determine the diagnostic utility of the Xpert MTB/RIF assay in seriously ill HIV-infected patients.
Methods
We conducted a prospective study among HIV-infected inpatients with any cough duration and WHO-defined danger signs. Culture-positive tuberculosis from any site was the reference standard. A priori selected variables were assessed for univariate associations with tuberculosis. The most predictive variables were assessed in a multivariate logistic regression model and used to establish a clinical prediction rule for diagnosing tuberculosis.
Results
We enrolled 484 participants: median age 36 years, 65·5% female, median CD4 count 89 cells/μL, and 35·3% on antiretroviral therapy. Tuberculosis was diagnosed in 52·7% of participants. The c-statistic of our clinical prediction rule (variables: cough ≥14 days, unable to walk unaided, temperature >39oC, chest radiograph assessment, haemoglobin, and white cell count) was 0·811 (95%CI 0·802, 0·819). The classic tuberculosis symptoms (fever, night sweats, weight loss) added no discriminatory value in diagnosing tuberculosis. Xpert MTB/RIF assay sensitivity was 86·3% and specificity was 96·1%.
Conclusion
Our clinical prediction rule had good diagnostic utility for tuberculosis among seriously ill HIV-infected inpatients. Xpert MTB/RIF assay, incorporated into the updated 2016 WHO algorithm, had high sensitivity and specificity in this population. Our findings could facilitate improved diagnosis of tuberculosis among seriously ill HIV-infected inpatients in resource-constrained settings. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/30006 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:20.328Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Department of Medicine |
| publisherStr | Department of Medicine |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/30006 Optimizing Tuberculosis Diagnosis in HIV-Infected Inpatients Meeting the Criteria of Seriously Ill in the WHO Algorithm Griesel, Rulan Maartens, Gary Sinxadi Phumla Background The WHO algorithm for the diagnosis of tuberculosis in seriously ill HIV-infected patients lacks a firm evidence base. We aimed to develop a clinical prediction rule for the diagnosis of tuberculosis and to determine the diagnostic utility of the Xpert MTB/RIF assay in seriously ill HIV-infected patients. Methods We conducted a prospective study among HIV-infected inpatients with any cough duration and WHO-defined danger signs. Culture-positive tuberculosis from any site was the reference standard. A priori selected variables were assessed for univariate associations with tuberculosis. The most predictive variables were assessed in a multivariate logistic regression model and used to establish a clinical prediction rule for diagnosing tuberculosis. Results We enrolled 484 participants: median age 36 years, 65·5% female, median CD4 count 89 cells/μL, and 35·3% on antiretroviral therapy. Tuberculosis was diagnosed in 52·7% of participants. The c-statistic of our clinical prediction rule (variables: cough ≥14 days, unable to walk unaided, temperature >39oC, chest radiograph assessment, haemoglobin, and white cell count) was 0·811 (95%CI 0·802, 0·819). The classic tuberculosis symptoms (fever, night sweats, weight loss) added no discriminatory value in diagnosing tuberculosis. Xpert MTB/RIF assay sensitivity was 86·3% and specificity was 96·1%. Conclusion Our clinical prediction rule had good diagnostic utility for tuberculosis among seriously ill HIV-infected inpatients. Xpert MTB/RIF assay, incorporated into the updated 2016 WHO algorithm, had high sensitivity and specificity in this population. Our findings could facilitate improved diagnosis of tuberculosis among seriously ill HIV-infected inpatients in resource-constrained settings. 2019-05-10T11:00:46Z 2019-05-10T11:00:46Z 2018 2019-05-09T13:21:48Z Master Thesis Masters MMed. (Clinical Pharmacology) http://hdl.handle.net/11427/30006 eng application/pdf Department of Medicine Faculty of Health Sciences |
| spellingShingle | Griesel, Rulan Optimizing Tuberculosis Diagnosis in HIV-Infected Inpatients Meeting the Criteria of Seriously Ill in the WHO Algorithm |
| thesis_degree_str | Master's |
| title | Optimizing Tuberculosis Diagnosis in HIV-Infected Inpatients Meeting the Criteria of Seriously Ill in the WHO Algorithm |
| title_full | Optimizing Tuberculosis Diagnosis in HIV-Infected Inpatients Meeting the Criteria of Seriously Ill in the WHO Algorithm |
| title_fullStr | Optimizing Tuberculosis Diagnosis in HIV-Infected Inpatients Meeting the Criteria of Seriously Ill in the WHO Algorithm |
| title_full_unstemmed | Optimizing Tuberculosis Diagnosis in HIV-Infected Inpatients Meeting the Criteria of Seriously Ill in the WHO Algorithm |
| title_short | Optimizing Tuberculosis Diagnosis in HIV-Infected Inpatients Meeting the Criteria of Seriously Ill in the WHO Algorithm |
| title_sort | optimizing tuberculosis diagnosis in hiv infected inpatients meeting the criteria of seriously ill in the who algorithm |
| url | http://hdl.handle.net/11427/30006 |
| work_keys_str_mv | AT grieselrulan optimizingtuberculosisdiagnosisinhivinfectedinpatientsmeetingthecriteriaofseriouslyillinthewhoalgorithm |