Sitafloxacin-Containing Regimen for the Treatment of Refractory Mycobacterium avium Complex Lung Disease
Bibliographic record
Abstract
BACKGROUND: complex (MAC) in both in vitro and in vivo experiments. However, limited data are available for the clinical efficacy and adverse effects of STFX and the susceptibility of refractory MAC lung disease (MAC-LD) to the drug. Therefore, this study was aimed at evaluating the clinical efficacy and safety of an STFX-containing regimen for the treatment of refractory MAC-LD. METHODS: We retrospectively evaluated treatment outcomes of 31 patients with refractory MAC-LD, who received an STFX-containing regimen for ≥4 weeks between January 2010 and July 2017. Refractory MAC-LD was defined as persistent positive sputum cultures for >6 months of macrolide-based standard therapy. RESULTS: Clarithromycin resistance (minimum inhibitory concentration [MIC] ≥32 μg/mL) was identified in 15 patients (48%). Twelve months after receiving the STFX-containing regimen, 26% and 19% of patients showed symptomatic and radiological responses, respectively. Although STFX-associated adverse effects were noted in 9 patients, their severity was grade 1 (National Cancer Institute Common Terminology Criteria); only 1 patient discontinued STFX because of suspected gastrointestinal disturbance. Negative sputum culture conversion was achieved in 7 patients (23%). Both univariate and multivariate logistic regression analyses revealed that surgery, low STFX MIC (≤1 μg/mL), and macrolide resistance were significant predictors of negative sputum culture conversion. CONCLUSIONS: Our results demonstrate that STFX may be effective in one-fourth of patients with refractory MAC-LD. Prospective larger studies that include the analyses of MAC are needed to determine the clinical efficacy of STFX against refractory MAC-LD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".