Impact of tuberculosis on mortality among HIV-infected patients receiving antiretroviral therapy in Uganda: a prospective cohort analysis
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) disease affects survival among HIV co-infected patients on antiretroviral therapy (ART). Yet, the magnitude of TB disease on mortality is poorly understood. METHODS: Using a prospective cohort of 22,477 adult patients who initiated ART between August 2000 and June 2009 in Uganda, we assessed the effect of active pulmonary TB disease at the initiation of ART on all-cause mortality using a Cox proportional hazards model. Propensity score (PS) matching was used to control for potential confounding. Stratification and covariate adjustment for PS and not PS-based multivariable Cox models were also performed. RESULTS: A total of 1,609 (7.52%) patients had active pulmonary TB at the start of ART. TB patients had higher proportions of being male, suffering from AIDS-defining illnesses, having World Health Organization (WHO) disease stage III or IV, and having lower CD4 cell counts at baseline (p < 0.001). The percentages of death during follow-up were 10.47% and 6.38% for patients with and without TB, respectively. The hazard ratio (HR) for mortality comparing TB to non-TB patients using 1,686 PS-matched pairs was 1.37 (95% confidence interval [CI]: 1.08 - 1.75), less marked than the crude estimate (HR = 1.74, 95% CI: 1.49 - 2.04). The other PS-based methods and not PS-based multivariable Cox model produced similar results. CONCLUSIONS: After controlling for important confounding variables, HIV patients who had TB at the initiation of ART in Uganda had an approximate 37% increased hazard of overall mortality relative to non-TB patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".