Validity of DMIST for monitoring healing of diabetic foot ulcers.

A new diabetic foot evaluation scale was proposed, using the seven domains of depth, maceration, inflammation/infection, size, tissue type of the wound bed, type of wound edge, and tunneling/undermining. This scale was named "DMIST" as an acronym from the initials of the domains. The purpose of this study was to evaluate the validity of DMIST. Secondary analysis was conducted in three investigations performed using the diabetic foot ulcer assessment scale (DFUAS) in Japan and Indonesia. Secondary analysis was assessed using DMIST, PUSH, and DESIGN for 4 weeks based on DFUAS score and photographs of diabetic foot ulcers by researchers. Concurrent validity was determined from the correlation of total DMIST scores with PUSH and DESIGN scores. Construct validity was determined by comparisons between total DMIST score and grade of the Wagner classification. Predictive validity was determined by receiver operating characteristic curve analysis for wound non-healing 4 weeks later. Subjects comprised 35 Japanese patients and 118 Indonesian patients. Correlations of total DMIST score with PUSH and DESIGN scores were 0.831 and 0.822, respectively. Comparison of total DMIST scores with grade of the Wagner classification (Grade I vs. Grade II/III vs. Grade IV/V) was p < 0.001. Based on an area under the curve of 0.872, a DMIST score of 9 was selected as a cut-off, offering sensitivity of 0.855 and specificity of 0.786 for wound non-healing 4 weeks later. Our findings suggest that DMIST offers high validity.

Global Epidemiology of Buruli Ulcer, 2010-2017, and Analysis of 2014 WHO Programmatic Targets.

Buruli ulcer is a neglected tropical disease caused by Myocobacterium ulcerans; it manifests as a skin lesion, nodule, or ulcer that can be extensive and disabling. To assess the global burden and the progress on disease control, we analyzed epidemiologic data reported by countries to the World Health Organization during 2010-2017. During this period, 23,206 cases of Buruli ulcer were reported. Globally, cases declined to 2,217 in 2017, but local epidemics seem to arise, such as in Australia and Liberia. In 2013, the World Health Organization formulated 4 programmatic targets for Buruli ulcer that addressed PCR confirmation, occurrence of category III (extensive) lesions and ulcerative lesions, and movement limitation caused by the disease. In 2014, only the movement limitation goal was met, and in 2019, none are met, on a global average. Our findings support discussion on future Buruli ulcer policy and post-2020 programmatic targets.

Drugs for treating Buruli ulcer (Mycobacterium ulcerans disease).

BACKGROUND: Buruli ulcer is a necrotizing cutaneous infection caused by infection with Mycobacterium ulcerans bacteria that occurs mainly in tropical and subtropical regions. The infection progresses from nodules under the skin to deep ulcers, often on the upper and lower limbs or on the face. If left undiagnosed and untreated, it can lead to lifelong disfigurement and disabilities. It is often treated with drugs and surgery. OBJECTIVES: To summarize the evidence of drug treatments for treating Buruli ulcer. SEARCH METHODS: We searched the Cochrane Infectious Diseases Group Specialized Register; the Cochrane Central Register of Controlled Trials (CENTRAL), published in the Cochrane Library; MEDLINE (PubMed); Embase (Ovid); and LILACS (Latin American and Caribbean Health Sciences Literature; BIREME). We also searched the US National Institutes of Health Ongoing Trials Register (clinicaltrials.gov) and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) (www.who.int/ictrp/search/en/). All searches were run up to 19 December 2017. We also checked the reference lists of articles identified by the literature search, and contacted leading researchers in this topic area to identify any unpublished data. SELECTION CRITERIA: We included randomized controlled trials (RCTs) that compared antibiotic therapy to placebo or alternative therapy such as surgery, or that compared different antibiotic regimens. We also included prospective observational studies that evaluated different antibiotic regimens with or without surgery. DATA COLLECTION AND ANALYSIS: Two review authors independently applied the inclusion criteria, extracted the data, and assessed methodological quality. We calculated the risk ratio (RR) for dichotomous data with 95% confidence intervals (CI). We assessed the certainty of the evidence using the GRADE approach. MAIN RESULTS: We included a total of 18 studies: five RCTs involving a total of 319 participants, ranging from 12 participants to 151 participants, and 13 prospective observational studies, with 1665 participants. Studies evaluated various drugs usually in addition to surgery, and were carried out across eight countries in areas with high Buruli ulcer endemicity in West Africa and Australia. Only one RCT reported adequate methods to minimize bias. Regarding monotherapy, one RCT and one observational study evaluated clofazimine, and one RCT evaluated sulfamethoxazole/trimethoprim. All three studies had small sample sizes, and no treatment effect was demonstrated. The remaining studies examined combination therapy.Rifampicin combined with streptomycinWe found one RCT and six observational studies which evaluated rifampicin combined with streptomycin for different lengths of treatment (2, 4, 8, or 12 weeks) (941 participants). The RCT did not demonstrate a difference between the drugs added to surgery compared with surgery alone for recurrence at 12 months, but was underpowered (RR 0.12, 95% CI 0.01 to 2.51; 21 participants; very low-certainty evidence).An additional five single-arm observational studies with 828 participants using this regimen for eight weeks with surgery (given to either all participants or to a select group) reported healing rates ranging from 84.5% to 100%, assessed between six weeks and one year. Four observational studies reported healing rates for participants who received the regimen alone without surgery, reporting healing rates ranging from 48% to 95% assessed between eight weeks and one year.Rifampicin combined with clarithromycinTwo observational studies administered combined rifampicin and clarithromycin. One study evaluated the regimen alone (no surgery) for eight weeks and reported a healing rate of 50% at 12 months (30 participants). Another study evaluated the regimen administered for various durations (as determined by the clinicians, durations unspecified) with surgery and reported a healing rate of 100% at 12 months (21 participants).Rifampicin with streptomycin initially, changing to rifampicin with clarithromycin in consolidation phaseOne RCT evaluated this regimen (four weeks in each phase) against continuing with rifampicin and streptomycin in the consolidation phase (total eight weeks). All included participants had small lesions, and healing rates were above 90% in both groups without surgery (healing rate at 12 months RR 0.94, 95% CI 0.87 to 1.03; 151 participants; low-certainty evidence). One single-arm observational study evaluating the substitution of streptomycin with clarithromycin in the consolidation phase (6 weeks, total 8 weeks) without surgery given to a select group showed a healing rate of 98% at 12 months (41 participants).Novel combination therapyTwo large prospective studies in Australia evaluated some novel regimens. One study evaluating rifampicin combined with either ciprofloxacin, clarithromycin, or moxifloxacin without surgery reported a healing rate of 76.5% at 12 months (132 participants). Another study evaluating combinations of two to three drugs from rifampicin, ciprofloxacin, clarithromycin, ethambutol, moxifloxacin, or amikacin with surgery reported a healing rate of 100% (90 participants).Adverse effects were reported in only three RCTs (158 participants) and eight prospective observational studies (878 participants), and were consistent with what is already known about the adverse effect profile of these drugs. Paradoxical reactions (clinical deterioration after treatment caused by enhanced immune response to M ulcerans) were evaluated in six prospective observational studies (822 participants), and the incidence of paradoxical reactions ranged from 1.9% to 26%. AUTHORS' CONCLUSIONS: While the antibiotic combination treatments evaluated appear to be effective, we found insufficient evidence showing that any particular drug is more effective than another. How different sizes, lesions, and stages of the disease may contribute to healing and which kind of lesions are in need of surgery are unclear based on the included studies. Guideline development needs to consider these factors in designing practical treatment regimens. Forthcoming trials using clarithromycin with rifampicin and other trials of new regimens that also address these factors will help to identify the best regimens.

Evaluation of validity of the new diabetic foot ulcer assessment scale in Indonesia.

We developed a new assessment tool for diabetic foot ulcers because no such tool specifically for diabetic foot ulcer exists. The diabetic foot ulcer assessment scale (DFUAS) has 11 domain items. The minimum and maximum scores on this scale are 0 and 98, respectively; higher scores indicate more severe wounds. The aim of this study was to evaluate the concurrent validity, construct validity and predictive validity of DFUAS in Indonesia. A prospective cohort study was conducted on patients with diabetic foot ulcer at Kitamura wound clinic in Indonesia. A total of 62 patients with 70 diabetic foot ulcers were assessed with DFUAS tool, Bates-Jensen wound assessment tool (BWAT), and pressure ulcer scale for healing (PUSH). Concurrent validity was determined by correlation of the DFUAS total score with the external criterion (BWAT, PUSH, and wound surface area). A comparison between the total DFUAS score and chronic wound status was made to determine construct validity. We also analyzed 41 wounds that were followed for 4 weeks to evaluate predictive validity. The correlation coefficient total scores of the DFUAS against the BWAT, PUSH, and wound surface area were 0.92, 0.87, and 0.82, respectively. The comparison of the total DFUAS score with chronic wound status was p < 0.001. The predictive validity test indicated that a DFUAS cutoff score of 12 produced the best balance of sensitivity, specificity, positive predictive value, and negative predictive value (89%, 71%, 86%, and 77%, respectively). In conclusion, the newly developed DFUAS is a valid tool for assessing diabetic foot ulcers.

[Leprosy awareness-raising summer seminar: results of participant survey during 2012 and 2015].

In order to assess the effectiveness of this leprosy awareness-raising program, we surveyed 123 participants between 2012 and 2015. They were asked about their satisfaction with the program and what impact it had on them. In the past four years 80% to 100% have reported being "very satisfied" with the seminar. Many participants were grateful for the opportunity to be able to learn about leprosy from multiple perspectives and interact with people affected by leprosy. Interaction and sharing of opinions between participants were also regarded as important. These findings elucidated the importance of this seminar to provide opportunities for knowing the right information about leprosy, interacting with people affected by leprosy, coming to know of their experience and thoughts, and gaining exposure to other participants' opinions.

The current status of neglected tropical diseases in Japan: A scoping review.

Little attention has been paid to neglected tropical diseases (NTDs) in high-income countries and no literature provides an overview of NTDs in Japan. This scoping review aims to synthesize the latest evidence and information to understand epidemiology of and public health response to NTDs in Japan. Using three academic databases, we retrieved articles that mentioned NTDs in Japan, written in English or Japanese, and published between 2010 and 2020. Websites of key public health institutions and medical societies were also explored. From these sources of information, we extracted data that were relevant to answering our research questions. Our findings revealed the transmission of alveolar echinococcosis, Buruli ulcer, Chagas disease, dengue, foodborne trematodiases, mycetoma, scabies, and soil-transmitted helminthiasis as well as occurrence of snakebites within Japan. Other NTDs, such as chikungunya, cystic echinococcosis, cysticercosis, leishmaniasis, leprosy, lymphatic filariasis, rabies, and schistosomiasis, have been imported into the country. Government agencies tend to organize surveillance and control programs only for the NTDs targeted by the Infectious Disease Control Law, namely, echinococcosis, rabies, dengue, and chikungunya. At least one laboratory offers diagnostic testing for each NTD except for dracunculiasis, human African trypanosomiasis, onchocerciasis, and yaws. No medicine is approved for treatment of Chagas disease and fascioliasis and only off-label use drugs are available for cysticercosis, opisthorchiasis, human African trypanosomiasis, onchocerciasis, schistosomiasis, and yaws. Based on these findings, we developed disease-specific recommendations. In addition, three policy issues are discussed, such as lack of legal frameworks to organize responses to some NTDs, overreliance on researchers to procure some NTD products, and unaffordability of unapproved NTD medicines. Japan should recognize the presence of NTDs within the country and need to address them as a national effort. The implications of our findings extend beyond Japan, emphasizing the need to study, recognize, and address NTDs even in high-income countries.

The potential role of artificial intelligence in the clinical management of Hansen's disease (leprosy).

Missed and delayed diagnoses of Hansen's disease (HD) are making the battle against it even more complex, increasing its transmission and significantly impacting those affected and their families. This strains public health systems and raises the risk of lifelong impairments and disabilities. Worryingly, the three countries most affected by HD witnessed a growth in new cases in 2022, jeopardizing the World Health Organization's targets to interrupt transmission. Artificial intelligence (AI) can help address these challenges by offering the potential for rapid case detection, customized treatment, and solutions for accessibility challenges-especially in regions with a shortage of trained healthcare professionals. This perspective article explores how AI can significantly impact the clinical management of HD, focusing on therapeutic strategies. AI can help classify cases, ensure multidrug therapy compliance, monitor geographical treatment coverage, and detect adverse drug reactions and antimicrobial resistance. In addition, AI can assist in the early detection of nerve damage, which aids in disability prevention and planning rehabilitation. Incorporating AI into mental health counseling is also a promising contribution to combating the stigma associated with HD. By revolutionizing therapeutic approaches, AI offers a holistic solution to reduce the burden of HD and improve patient outcomes.

[Present leprosy situation in the world in 2012].

The epidemiological situation of leprosy is reported by the health division of each country to WHO. The reported data is collected by WHO and is immediately run on the Weekly Epidemiological Record. On this latest edition, data from the beginning of 2012 was reported. The Enhanced global strategy for further reducing the disease burden due to leprosy (plan period: 2011-2015) emphasizes reducing grade-2 disabilities among new cases. The sustained and committed efforts by the national programmes along with the continued support from national and international partners have led to a decline in the global burden of leprosy. It is important that all endemic countries continue to provide innovative solutions to address barriers to timely case detection and treatment completion, to ensure that the current declining trend is sustained.

[Guidelines for the treatment of Hansen's disease in Japan (third edition)].

ad hoc committee of Japanese Leprosy Association recommends revised standard treatment protocol of leprosy in Japan, which is a modification of World Health Organization's multidrug therapy (WHO/MDT, 2010). For paucibacillary (PB) leprosy, 6 months treatment by rifampicin and dapsone (MDT/PB) is enough. However, for high bacterial load multibacillary (MB) leprosy, 12 months treatment seems insufficient. Thus, (A) For MB with bacterial index (BI) > 3 before treatment, 2 years treatment by rifampicin, dapsone and clofazimine (MDT/MB) is necessary. When BI becomes negative and active lesion is lost within 2 years, no maintenance therapy is necessary. When BI is still positive, one year of MDT/MB is added (3 years in total), followed by maintenance therapy by dapsone and clofazimine until BI negativity and loss of active lesions. (B) For MB with BI < 3 or fresh MB (less than 6 months after the onset of the disease) with BI > 3, 1 year treatment by MDT/MB is necessary. When BI becomes negative and active lesion is lost within one year, no maintenance therapy is necessary. When BI is still positive or active lesion is remaining, additional therapy with MDT/MB for one more year is recommended. Brief summary of diagnosis, purpose of therapy, character of drugs, and prevention of deformity is also described.

Deep learning for AI-based diagnosis of skin-related neglected tropical diseases: a pilot study.

Background: Deep learning, which is a part of a broader concept of artificial intelligence (AI) and/or machine learning has achieved remarkable success in vision tasks. While there is growing interest in the use of this technology in diagnostic support for skin-related neglected tropical diseases (skin NTDs), there have been limited studies in this area and fewer focused on dark skin. In this study, we aimed to develop deep learning based AI models with clinical images we collected for five skin NTDs, namely, Buruli ulcer, leprosy, mycetoma, scabies, and yaws, to understand how diagnostic accuracy can or cannot be improved using different models and training patterns. Methodology: This study used photographs collected prospectively in Côte d'Ivoire and Ghana through our ongoing studies with use of digital health tools for clinical data documentation and for teledermatology. Our dataset included a total of 1,709 images from 506 patients. Two convolutional neural networks, ResNet-50 and VGG-16 models were adopted to examine the performance of different deep learning architectures and validate their feasibility in diagnosis of the targeted skin NTDs. Principal findings: The two models were able to correctly predict over 70% of the diagnoses, and there was a consistent performance improvement with more training samples. The ResNet-50 model performed better than the VGG-16 model. Model trained with PCR confirmed cases of Buruli ulcer yielded 1-3% increase in prediction accuracy over training sets including unconfirmed cases. Conclusions: Our approach was to have the deep learning model distinguish between multiple pathologies simultaneously - which is close to real-world practice. The more images used for training, the more accurate the diagnosis became. The percentages of correct diagnosis increased with PCR-positive cases of Buruli ulcer. This demonstrated that it may be better to input images from the more accurately diagnosed cases in the training models also for achieving better accuracy in the generated AI models. However, the increase was marginal which may be an indication that the accuracy of clinical diagnosis alone is reliable to an extent for Buruli ulcer. Diagnostic tests also have its flaws, and they are not always reliable. One hope for AI is that it will objectively resolve this gap between diagnostic tests and clinical diagnoses with addition of another tool. While there are still challenges to be overcome, there is a potential for AI to address the unmet needs where access to medical care is limited, like for those affected by skin NTDs. AUTHOR SUMMARY: The diagnosis of skin diseases depends in large part, though not exclusively on visual inspection. The diagnosis and management of these diseases is thus particularly amenable to teledermatology approaches. The widespread availability of cell phone technology and electronic information transfer provides new potential for access to health care in low-income countries, yet there are limited efforts targeting these neglected populations with dark skin and consequently limited availability of tools. In this study, we leveraged a collection of skin images gathered through a system of teledermatology in the West African countries of Côte d'Ivoire and Ghana, and applied deep learning, a form of artificial intelligence (AI) - to see if deep learning models can distinguish between different diseases and support their diagnosis. Skin-related neglected tropical diseases, or skin NTDs, prevail in these regions and were our target conditions: Buruli ulcer, leprosy, mycetoma, scabies, and yaws. The accuracy of prediction depended on the number of images that were fed into the model for training with marginal improvement using laboratory confirmed cases in training. Using more images and greater efforts in this area, it is possible that AI can help address the unmet needs where access to medical care is limited.

Deep learning for AI-based diagnosis of skin-related neglected tropical diseases: A pilot study.

BACKGROUND: Deep learning, which is a part of a broader concept of artificial intelligence (AI) and/or machine learning has achieved remarkable success in vision tasks. While there is growing interest in the use of this technology in diagnostic support for skin-related neglected tropical diseases (skin NTDs), there have been limited studies in this area and fewer focused on dark skin. In this study, we aimed to develop deep learning based AI models with clinical images we collected for five skin NTDs, namely, Buruli ulcer, leprosy, mycetoma, scabies, and yaws, to understand how diagnostic accuracy can or cannot be improved using different models and training patterns. METHODOLOGY: This study used photographs collected prospectively in Côte d'Ivoire and Ghana through our ongoing studies with use of digital health tools for clinical data documentation and for teledermatology. Our dataset included a total of 1,709 images from 506 patients. Two convolutional neural networks, ResNet-50 and VGG-16 models were adopted to examine the performance of different deep learning architectures and validate their feasibility in diagnosis of the targeted skin NTDs. PRINCIPAL FINDINGS: The two models were able to correctly predict over 70% of the diagnoses, and there was a consistent performance improvement with more training samples. The ResNet-50 model performed better than the VGG-16 model. A model trained with PCR confirmed cases of Buruli ulcer yielded 1-3% increase in prediction accuracy across all diseases, except, for mycetoma, over a model which training sets included unconfirmed cases. CONCLUSIONS: Our approach was to have the deep learning model distinguish between multiple pathologies simultaneously-which is close to real-world practice. The more images used for training, the more accurate the diagnosis became. The percentages of correct diagnosis increased with PCR-positive cases of Buruli ulcer. This demonstrated that it may be better to input images from the more accurately diagnosed cases in the training models also for achieving better accuracy in the generated AI models. However, the increase was marginal which may be an indication that the accuracy of clinical diagnosis alone is reliable to an extent for Buruli ulcer. Diagnostic tests also have their flaws, and they are not always reliable. One hope for AI is that it will objectively resolve this gap between diagnostic tests and clinical diagnoses with the addition of another tool. While there are still challenges to be overcome, there is a potential for AI to address the unmet needs where access to medical care is limited, like for those affected by skin NTDs.

An mHealth App (eSkinHealth) for Detecting and Managing Skin Diseases in Resource-Limited Settings: Mixed Methods Pilot Study.

BACKGROUND: In sub-Saharan Africa, the disease burden from skin diseases, including skin-related neglected tropical diseases (skin NTDs), is extremely high. These diseases often are overlooked due to limited access to health care stemming from, for example, remote geographical locations and a lack of experts. To address these gaps, we developed a mobile health app, eSkinHealth, which is a field-adapted platform to serve as a portable electronic patient chart and for teledermatology. OBJECTIVE: The purpose of the study is to evaluate the usability and effectiveness of the app in rural Côte d'Ivoire for diagnosing and managing skin NTDs and other skin diseases. METHODS: A 2-arm trial with local health care providers and patients with skin diseases was implemented over a 3-month period. The providers were assigned to an intervention receiving the eSkinHealth app or control with usual care. Four nurses and 8 community health care workers participated in each arm. The training was provided on the use of the app to the intervention arm only, while both arms were trained on skin diseases. For the usability study, we evaluated our approach with the System Usability Scale (SUS) and in-depth interviews. For the effectiveness study, our primary outcome was to evaluate the detection and management of 5 skin NTDs as our targeted diseases, namely, Buruli ulcer, leprosy, lymphatic filariasis, scabies, and yaws, using the eSkinHealth app. Procedures of our methods were reviewed and approved by the institutional review board of the Ministry of Health and by Tulane University. RESULTS: The mean age of our participants (providers) was 40.5 and 42.5 years for the intervention and control arms, respectively, and all were male (n=24). The average SUS scores taken from the intervention arm at baseline, the midpoint (6 weeks), and the end of study (12 weeks) were 72.3 (SD 11.5), 72.3 (SD 12.4), and 86.3 (SD 10.8), respectively. All participants interviewed, including 4 dermatologists and program managers, were satisfied with the app. Especially community health care workers felt empowered by being equipped with the tool. A total of 79 cases of skin NTDs were reported in the intervention arm as compared to 17 cases in the control arm (P=.002). Besides the skin NTDs, more skin diseases and conditions were reported from the control than from the intervention arm (P<.001). However, 100 cases (66%) were not given any particular diagnosis in the control arm and were documented only as a "dermatosis." In the intervention arm, 151 cases (72.9%) were diagnosed within the eSkinHealth platform, and the remaining were diagnosed on-site by dermatologists. CONCLUSIONS: The study provided evidence for the usability and effectiveness of the eSkinHealth app embedded into our surveillance approach to improve the detection and management of skin NTDs and other skin diseases in Côte d'Ivoire and, furthermore, is expected to contribute to knowledge on mobile health approaches in the control of skin diseases in resource-limited settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT05300399; https://clinicaltrials.gov/ct2/show/NCT05300399.

A global call for action to tackle skin-related neglected tropical diseases (skin NTDs) through integration: An ambitious step change.

On 8 June 2022, the World Health Organization (WHO) released pivotal guidance, "Ending the neglect to attain the Sustainable Development Goals: A strategic framework for integrated control and management of skin-related neglected tropical diseases." Skin-related neglected tropical diseases, or skin NTDs, comprise a group of NTDs that produce signs and symptoms on the skin and include at least 9 diseases or disease groups. Moving away from disease-specific approaches, it is anticipated that synergies will be identified and integrated building on this shared feature, where possible, to achieve a greater health impact. This paper intends to draw attention to the prospects created by this scheme. The framework is a key basis for a proposal produced by WHO dedicated to skin NTD integration and describes the practical opportunities for this evolving strategy. It underlines the wider health benefits that will follow, thus working towards Universal Health Coverage and skin health for all.