Sensitivity and Specificity of the Remote Evaluation of Therapeutic Response in Cutaneous Leishmaniasis Using Photographs from a Mobile Application.

Cutaneous leishmaniasis (CL) primarily affects people in remote settings with limited access to health services. mHealth tools offer an opportunity to overcome knowledge gaps about clinical response to treatment. We evaluated the validity of the Guaral+ST mobile application for the remote assessment of therapeutic response in patients with CL, through photographs of lesions captured with the app by community health volunteers. Patients with confirmed CL were followed at weeks 13 and 26 after completion of treatment to assess therapeutic response in two clinical settings in southwest Colombia. Direct evaluation of lesions performed by an experienced physician was considered the reference standard. Photographs of lesions taken by CHV or nurse assistants with the mobile app, were independently evaluated by three physicians to define clinical response. A summary measure of clinical outcome defined by the three physicians was considered the index test. Sensitivity, specificity, and positive and negative predictive values were estimated. Interrater reliability (kappa) was calculated. Among 53 participants with CL who had at least one follow-up visit, the sensitivity of therapeutic response evaluation through photographs taken with the Guaral+ST app, compared with direct evaluation by an expert physician, had high validity with sensitivity of 100% (95% confidence interval: 80.5-100%) and specificity of 97.2% (95% confidence interval: 85.5-99.9%). The chance-adjusted agreement (κ) was > 0.8, which is conventionally characterized as almost perfect. The high accuracy of the remote evaluation of photographs for the assessment of therapeutic response supports the use of mHealth tools for improving access to treatment follow-up for CL.

Diagnostic performance of a Recombinant Polymerase Amplification Test-Lateral Flow (RPA-LF) for cutaneous leishmaniasis in an endemic setting of Colombia.

BACKGROUND: Control of cutaneous leishmaniasis by public health systems in the Americas relies on case identification and treatment. Point-of-care diagnostics that can be performed by health workers within or near affected communities could effectively bring the health system to the resource-limited sites providing early diagnosis and treatment, reducing morbidity and the burden of disease. METHODOLOGY/PRINCIPAL FINDINGS: A cross-sectional study was undertaken to evaluate the diagnostic test performance of Isothermal Recombinase Polymerase Amplification (RPA) targeting Leishmania kinetoplast DNA, coupled with a lateral flow (LF) immunochromatographic strip, in a field setting and a laboratory reference center. Minimally invasive swab and FTA filter paper samples were obtained by community health workers and highly trained technicians from ulcerated lesions of > 2 weeks' evolution from 118 patients' ≥ 2 years of age in the municipality of Tumaco, Nariño. Extracted DNA was processed by RPA-LF at a reference center or in a primary health facility in the field. Evaluation was based on a composite "gold standard" that included microscopy, culture, biopsy and real-time polymerase chain reaction detection of Leishmania 18S rDNA. Standard of care routine diagnostic tests were explored as comparators. Sensitivity and specificity of RPA-LF in the reference lab scenario were 87% (95%CI 74-94) and 86% (95%CI 74-97), respectively. In the field scenario, the sensitivity was 75% (95%CI 65-84) and specificity 89% (95%CI 78-99). Positive likelihood ratios in both scenarios were higher than 6 while negative likelihood ratios ranged to 0.2-0.3 supporting the usefulness of RPA-LF to rule-in and potentially to rule-out infection. CONCLUSIONS/SIGNIFICANCE: The low complexity requirements of RPA-LF combined with non-invasive sampling support the feasibility of its utilization by community health workers with the goal of strengthening the diagnostic capacity for cutaneous leishmaniasis in Colombia. TRIAL REGISTRATION: ClinicalTrials.gov NCT04500873.

Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis.

BACKGROUND: Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce. METHODS: We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician. RESULTS: The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was >95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel. CONCLUSIONS: Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare.