Treatment response of cutaneous leishmaniasis due to Leishmania aethiopica to cryotherapy and generic sodium stibogluconate from patients in Silti, Ethiopia
Bibliographic record
Abstract
Cutaneous leishmaniasis in Ethiopia is caused mainly by Leishmania aethiopica. In this study, the response of L. aethiopica to sodium stibogluconate (SSG) and liquid nitrogen in Silti has been investigated. Patients were divided into two groups by the treating physician and were treated with either liquid nitrogen or SSG. Punch biopsy samples were collected from 54 patients with mean age of 20.61 (± 9.87 SD) years for histological characterization. The histological spectrum found to be type-1, type-2, type-3 and type-4 were 37.0%, 3.7%, 37.0% and 22.2% respectively. One hundred and three patients with a mean age of 18.4 (± 11.7 SD) years were treated with liquid nitrogen. The mean duration of the lesions before the onset of treatment was 8.5 months (± 6.7 SD). Of the 103 patients 80.6% (83/103) were cured, 13.6% (14/103) were dropouts and 5.8% (6/103) did not respond. Twenty patients with a mean age of 19.55 (+1.64 SD) years were treated with Pentostam on conventional dose. Of the 20 patients 85.0% (17/20) were cured, 10.0% (2/20) were unresponsive and 5.0% (1/20) were dropouts. The per protocol cure rate for cryotherapy and Pentostam was 93.3% and 89.5% respectively. Hence, liquid nitrogen can be used as one of the treatment options especially in resource poor settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".