Incidence of Tuberculosis among HIV-infected patients receiving highly active antiretroviral therapy in Europe and North America: the Antiretroviral Therapy Cohort Collaboration
Bibliographic record
Abstract
a (See the editorial commentary by Lawn and Wood on pages 1783-6)Background.We obtained estimates of the incidence of tuberculosis (TB) among patients receiving HAART and identified determinants of the incidence. Methods.We analyzed the incidence of TB during the first 3 years after initiation of HAART among 17,142 treatment-naive, AIDS-free persons starting HAART who were enrolled in 12 cohorts from Europe and North America.We used univariable and multivariable Poisson regression models to identify factors associated with the incidence.Results.During the first 3 years (36,906 person-years), 173 patients developed TB (incidence, 4.69 cases per 1000 person-years).In multivariable analysis, the incidence rate was lower for men who have sex with men, compared with injection drug users (relative rate, 2.46; 95% confidence interval [CI], 1.51-4.01),heterosexuals (relative rate, 2.42; 95% CI, 1.64-3.59),those with other suspected modes of transmission (relative rate, 1.66; 95% CI, 0.91-3.06),and those with a higher CD4 + count at the time of HAART initiation (relative rate per log 2 cells/ mL, 0.87; 95% CI, 0.84-0.91).During 28,846 person-years of follow-up after the first 6 months of HAART, 88 patients developed TB (incidence, 3.1 cases per 1000 person-years of follow-up).In multivariable analyses, a low baseline CD4 + count (relative rate per log 2 cells/mL, 0.89; 95% CI, 0.83-0.96),6-month CD4 + count (relative rate per log 2 cells/mL, 0.90; 95% CI, 0.81-0.99),and a 6-month HIV RNA level 1400 copies/mL (relative rate, 2.21; 95% CI, 1.33-3.67)were significantly associated with the risk of acquiring TB after 6 months of HAART. Conclusion.The level of immunodeficiency at which HAART is initiated and the response to HAART are important determinants of the risk of TB.However, this risk remains appreciable even among those with a good response to HAART, suggesting that other interventions may be needed to control the TB epidemic in the HIVinfected population.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 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".