ArticleJournal of clinical tuberculosis and other mycobacterial diseases2024
Clinical and microbiological predictors of healing in Buruli ulcer disease.
Article in Journal of clinical tuberculosis and other mycobacterial diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- High-dose rifampicin and clarithromycin for 4 weeks versus standard-dose rifampicin and clarithromycin for 8 weeks to treat Buruli ulcer: An open-label, individually randomized, controlled trial in Ghana.PLoS neglected tropical diseases · 2026Trial
- Biological, Environmental, and Social Determinants of Buruli Ulcer in Africa: Their Interplay Across Disease Severity and Patient Outcome.Public health challenges · 2026Review
- Assessing the acceptability of photographs and medical illustrations in Buruli ulcer health communication among health providers, community volunteers and community members in endemic districts of Ghana.PLoS neglected tropical diseases · 2026Article
- Improved protocols for isolation of Mycobacterium ulcerans from clinical samples.BMC microbiology · 2025Article
- Buruli ulcer: Current landscape, challenges, and future directions.Journal of clinical tuberculosis and other mycobacterial diseases · 2025Article
- Bacterial diversity in Buruli ulcer lesions in Ghana.Journal of clinical tuberculosis and other mycobacterial diseases · 2024Article
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Authors and funding
13 authors.
Funding
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Abstract
Introduction: Wound measurements are relevant in monitoring the rate of healing (RoH) and may predict time to healing. Predicting the time to healing can help improve the management of Buruli ulcer. We examine three methods for the determination of RoH and their use as predictors of time to healing. Methods: Lesion measurements of Buruli ulcer patients treated from 2007 to 2022 were obtained with acetate sheet tracings (2D) or Aranz software (3D) fortnightly. RoH was determined using the absolute area, percentage area reduction and linear methods at 4 weeks post onset of antibiotic treatment. Predicted time to healing was compared to the actual healing time. Baseline characteristics were assessed for associations with healing. Results: All three methods for calculating the RoH significantly distinguished between fast and slow healers (p < 0.0001). The predicted healing time using the linear method was comparable to the actual healing time for fast healers (p = 0.34). The RoH was influenced by the form of lesion, with plaques [OR 2.19 5 %CI (1.2-3.6), p = 0.009], and oedemas [OR 8.5; 95 %CI (1.9--36.9), p = 0.004] being associated with delayed healing. The proportion of patients with paradoxical reactions 16 % vs 3 %, p < 0.0001), higher baseline bacterial load (75/104;72 % vs 21/47;45 %, p = 0.001) and delayed clearance of viable organisms (71/104;68 % vs 9/47;19 %, p < 0.0001) was higher in the slow healers than the fast healers. Conclusion: Predicted healing rates were comparatively lower for slow healers than fast healers. Baseline characteristics associated with healing can be explored for an improved disease management plan to reduce patient and caregiver anxiety.
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