Fluoroquinolone resistance in renal isolates of Mycobacterium tuberculosis.
Bibliographic record
Abstract
SETTING: Alberta, Canada, 1990-2003. OBJECTIVE: Monotherapy of active tuberculosis (TB) promotes drug resistance. Given the common practice of empiric fluoroquinolone (FQ) therapy for urinary tract infections (UTI) and frequent delayed diagnosis of renal TB, we assessed urine Mycobacterium tuberculosis isolates for FQ resistance. DESIGN: Retrospective study. Urine M. tuberculosis isolates underwent FQ susceptibility testing. Records were reviewed for evidence of FQ exposure and diagnostic delay. RESULTS: Among 78 culture-positive renal TB patients between 1990 and 2003, initial isolates of M. tuberculosis were available from 74 (94.9%). Three (4.1%) were FQ-resistant. Previous FQ use was confirmed in nine cases (12.2%). FQ-exposed isolates were more likely than non-exposed isolates to be FQ-resistant (2/9, 22.2% vs. 1/65, 1.5%, P = 0.037). Among 41 cases (55.4%) with signs or symptoms of UTI, eight (19.5%) had previous FQ exposure, of which seven (87.5%) had delayed diagnosis. Only 15/33 (45.5%) UTI symptomatic cases without prior FQ exposure had delayed diagnosis (P = 0.050). In 2/8 (25%) UTI symptomatic cases with prior FQ exposure, the M. tuberculosis isolate was FQ-resistant. CONCLUSION: FQ monotherapy of unsuspected renal TB may delay diagnosis and lead to FQ resistance.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".