Assessment of sputum smear-positive but culture-negative results among newly diagnosed pulmonary tuberculosis patients in Tanzania
Bibliographic record
Abstract
Nicholaus Peter Mnyambwa,1,2 Esther S Ngadaya,2 Godfather Kimaro,2 Dong-Jin Kim,1 Rudovick Kazwala,3 Pammla Petrucka,1,4 Sayoki G Mfinanga2 1School of Life Sciences and Bioengineering, Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania; 2National Institute for Medical Research, Muhimbili Medical Research Center, Dar es Salaam, Tanzania; 3Department of Veterinary Medicine, Sokoine University of Agriculture, Morogoro, Tanzania; 4College of Nursing, University of Saskatchewan, Saskatoon, Canada Abstract: Diagnosis of pulmonary tuberculosis (TB) in technology-limited countries is widely achieved by smear microscopy, which has limited sensitivity and specificity. The frequency and clinical implication of smear-positive but culture-negative among presumptive TB patients remains unclear. A cross-sectional substudy was conducted which aimed to identify the proportion of nontuberculous mycobacteria (NTM) infections among 94 “smear-positive culture-negative” patients diagnosed between January 2013 and June 2016 in selected health facilities in Tanzania. Out of 94 sputa, 25 (26.60%) were GeneXpert® mycobacteria TB positive and 11/94 (11.70%) repeat-culture positive; 5 were Capilia TB-Neo positive and confirmed by GenoType MTBC to be Mycobacterium tuberculosis/Mycobacterium canettii. The remaining 6 Capilia TB-Neo negative samples were genotyped by GenoType® CM/AS, identifying 3 (3.19%) NTM, 2 Gram positive bacteria, and 1 isolate testing negative, together, making a total of 6/94 (6.38%) confirmed false smear-positives. Twenty-eight (29.79%) were confirmed TB cases, while 60 (63.83%) remained unconfirmed cases. Out of 6 (6.38%) patients who were HIV positive, 2 patients were possibly coinfected with mycobacteria. The isolation of NTM and other bacteria among smear-positive culture-negative samples and the presence of over two third of unconfirmed TB cases emphasize the need of both advanced differential TB diagnostic techniques and good clinical laboratory practices to avoid unnecessary administration of anti-TB drugs. Keywords: nontuberculous mycobacteria, pulmonary TB, smear-positive, culture-negative, tuberculosis diagnosis
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".