Raw, Unadulterated African Honey for Ulcer Healing in Leprosy: Protocol for the Honey Experiment on Leprosy Ulcer (HELP) Randomized Controlled Trial
Bibliographic record
Abstract
Background: Leprosy leads to nerve damage and slow-healing ulcers, which are treatable with routine therapy. There has been a recent resurgence of interest in the use of honey for the treatment of different kinds of wounds. Objective: The aim of this study, Honey Experiment on Leprosy Ulcer (HELP), is to evaluate the healing properties of raw, unadulterated African honey in comparison with normal saline dressing for the treatment leprosy ulcers. Methods: This is a multicenter, comparative, prospective, single-blinded, parallel-group, and 1:1 individually randomized controlled trial to be conducted at The Leprosy Referral Hospital, Chanchaga in Minna, Niger State, North Central Nigeria, and St. Benedict Tuberculosis and Leprosy Rehabilitation Hospital in Ogoja, Cross River State, South-South Nigeria. Raw, unadulterated honey will be used in the ulcer dressing of eligible, consenting participants in the intervention group, whereas those in the control group will be treated by dressing with normal saline. The main outcomes will be the proportion of complete healing and the rate of healing up to 84 days after randomization. Follow-up will be conducted 6 months after randomization. We aim to enroll 90-130 participants into the study. Blinded observers will examine photographs of ulcers to determine the outcomes. Results: The recruitment of trial participants began on March 14, 2022, and has been continuing for approximately 24 months. Conclusions: Our study will provide an unbiased estimate of the effect of honey on the healing of neuropathic ulcers.
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 | 0.021 | 0.019 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.008 |
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".