Ofloxacin-Containing Multidrug Therapy in Ambulatory Leprosy Patients: A Case Series
Bibliographic record
Abstract
Background Standard dapsone and clofazimine-containing multidrug therapy (MDT) for leprosy is limited by drug tolerability, which poses treatment adherence barriers. Although ofloxacin-based regimens are promising alternatives, current efficacy and safety data are limited, particularly outside of endemic areas. We evaluated treatment outcomes in patients with leprosy receiving ofloxacin-containing MDT (OMDT) at our center. Methods We performed a retrospective chart review of patients treated for leprosy at our center over an 8-year period (2011-2019). Primary outcomes evaluated were clinical cure rate, occurrence of leprosy reactions, antibiotic-related adverse events, and treatment adherence. Analyses were descriptive; however, data were stratified by age, sex, spectrum of disease, region of origin, and treatment regimen, and odds ratios were reported to assess associations with adverse outcomes. Results Over the enrolment period, 26 patients were treated with OMDT ( n = 19 multibacillary, n = 7 paucibacillary), and none were treated with clofazimine-based standard MDT. At the time of analysis, 23 patients (88%) had completed their course of treatment, and all were clinically cured, while 3 (12%) were still on treatment. Eighteen patients (69%) experienced either ENL ( n = 7, 27%), type 1 reactions ( n = 7, 27%), or both ( n = 4, 15%). No patients stopped ofloxacin due to adverse drug effects, and there were no cases of allergic hypersensitivity, tendinopathy or rupture, or C. difficile colitis. Conclusions We demonstrate a high cure rate and tolerability of OMDT in this small case series over an 8-year period, suggesting its viability as an alternative to standard clofazimine-containing MDT.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".