Inaccuracy of Death Certificate Diagnosis of Tuberculosis and Potential Underdiagnosis of TB in a Region of High HIV Prevalence
Bibliographic record
Abstract
UNLABELLED: Despite the South African antiretroviral therapy rollout, which should reduce the incidence of HIV-associated tuberculosis (TB), the number of TB-attributable deaths in KwaZuluNatal (KZN) remains high. TB is often diagnosed clinically, without microbiologic confirmation, leading to inaccurate estimates of TB-attributed deaths. This may contribute to avoidable deaths, and impact population-based TB mortality estimates. OBJECTIVES: (1) To measure the number of cases with microbiologically confirmed TB in a retrospective cohort of deceased inpatients with TB-attributed hospital deaths. (2) To estimate the rates of multi-drug resistant (MDR) and extensively drug resistant (XDR) TB in this cohort. RESULTS: Of 2752 deaths at EDH between September 2006 and March 2007, 403 (15%) were attributed to TB on the death certificate. 176 of the TB-attributed deaths (44%) had a specimen sent for smear or culture; only 64 (36%) had a TB diagnosis confirmed by either test. Of the 39 culture-confirmed cases, 27/39 (69%) had fully susceptible TB and 27/39 (69%) had smear-negative culture-positive TB (SNTB). Two patients had drug monoresistance, three patients had MDR-TB, and one had XDR-TB. CONCLUSIONS: Most TB-attributed deaths in this cohort were not microbiologically confirmed. Of confirmed cases, most were smear-negative, culture positive and were susceptible to all first line drugs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".