Is Early Tuberculosis Death Associated with Increased Tuberculosis Transmission?
Bibliographic record
Abstract
INTRODUCTION: Tuberculosis (TB) is now a relatively uncommon disease in high income countries. As such, its diagnosis may be missed or delayed resulting in death before or shortly after the introduction of treatment. Whether early TB death is associated with increased TB transmission is unknown. To determine the transmission risk attributable to early TB death we undertook a case-control study. METHODS: All adults who were: (1) diagnosed with culture-positive pulmonary TB in the Province of Alberta, Canada between 1996 and 2012, and (2) died a TB-related death before or within the first 60 days of treatment, were identified. For each of these "cases" two sets of "controls" were randomly selected from among culture-positive pulmonary TB cases that survived beyond 60 days of treatment. "Controls" were matched by age, sex, population group, +/- smear status. Secondary cases of "cases" and "controls" were identified using conventional and molecular epidemiologic tools and compared. In addition, new infections were identified and compared in contacts of "cases" that died before treatment and contacts of their smear-matched "controls". Conditional logistic regression was used to find associations in both univariate and multivariate analysis. RESULTS: "Cases" were as, but not more, likely than "controls" to transmit. This was so whether transmission was measured in terms of the number of "cases" and smear-unmatched or -matched "controls" that had a secondary case, the number of secondary cases that they had or the number of new infections found in contacts of "cases" that died before treatment and their smear-matched "controls". CONCLUSION: In a low TB incidence/low HIV prevalence country, pulmonary TB patients that die a TB-related death before or in the initial phase of treatment and pulmonary TB patients that survive beyond the initial phase of treatment are equally likely to transmit.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".