Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
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...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Medicine
2019
|
| Tags: |
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|