Diagnostic accuracy of qPCR and microscopy for cutaneous leishmaniasis in rural Ecuador: A Bayesian latent class analysis.

BACKGROUND: Clinical and laboratory diagnosis of cutaneous leishmaniasis (CL) is hampered by under-ascertainment of direct microscopy. METHODS: This study compared the diagnostic accuracy of qPCR on DNA extracted from filter paper to the accuracy of direct smear slide microscopy in participants presenting with a cutaneous lesion suspected of leishmaniasis to 16 rural healthcare centers in the Ecuadorian Amazon and Pacific regions, from January 2019 to June 2021. We used Bayesian latent class analysis to estimate test sensitivity, specificity, likelihood ratios (LR), and predictive values (PV) with their 95% credible intervals (95%CrI). The impact of sociodemographic and clinical characteristics on predictive values was assessed as a secondary objective. RESULTS: Of 320 initially included participants, paired valid test results were available and included in the diagnostic accuracy analysis for 129 from the Amazon and 185 from the Pacific region. We estimated sensitivity of 68% (95%CrI 49% to 82%) and 73% (95%CrI 73% to 83%) for qPCR, and 51% (95%CrI 36% to 66%) and 76% (95%CrI 65% to 86%) for microscopy in the Amazon and Pacific region, respectively. In the Amazon, with an estimated disease prevalence among participants of 73%, negative PV for qPCR was 54% (95%CrI 5% to 77%) and 44% (95%CrI 4% to 65%) for microscopy. In the Pacific, (prevalence 88%) the negative PV was 34% (95%CrI 3% to 58%) and 37% (95%CrI 3% to 63%). The addition of qPCR parallel to microscopy in the Amazon increases the observed prevalence from 38% to 64% (+26 (95%CrI 19 to 34) percentage points). CONCLUSION: The accuracy of either qPCR on DNA extracted from filter paper or microscopy for CL diagnosis as a stand-alone test seems to be unsatisfactory and region-dependent. We recommend further studies to confirm the clinically relevant increment found in the diagnostic yield due to the addition of qPCR.

Clinical criteria for Mucosal Leishmaniasis diagnosis in rural South America: A systematic literature review.

BACKGROUND: Mucosal Leishmaniasis (ML), a neglected tropical disease caused by Leishmania parasites, impairs the quality of life of under-resourced populations in South America. If not treated promptly, this disease progresses to facial deformities and death. The low sensitivity of microscopy results and the unavailability of other accurate tests hamper the diagnosis. As clinical criteria are readily available in any setting, these may be combined in a syndromic algorithm, which in turn can be used as a diagnostic tool. We explore potential clinical criteria for a syndromic diagnostic algorithm for ML in rural healthcare settings in South America. METHODOLOGY/PRINCIPAL FINDINGS: The protocol for this systematic review was pre-registered in PROSPERO with the number: CRD42017074148. In patients with ML, described in case series identified through a systematic retrieval process, we explored the cumulative ML detection rates of clinical criteria. Participants: all patients with active mucosal disease from an endemic area in South America. Any original, non-treatment study was eligible, and case reports were excluded. PUBMED, EMBASE, Web of Science, SCIELO, and LILACS databases were searched without restrictions. The risk of bias was assessed with the JBI checklist for case series. We included 10 full texts describing 192 ML patients. Male gender had the highest detection rate (88%), followed by ulcer of the nasal mucosa (77%), age >15 (69%), and symptom duration >4 months (63%). SIGNIFICANCE: Within this selection of patients, we found that the male gender, ulcer of the nasal mucosa, age >15, and symptom duration >4 months lead to the highest detection rates. However, higher detection comes -naturally- with a higher rate of false positives as well. As we only included ML patients, this could not be verified. Therefore, the criteria that we found to be most promising should be validated in a well-designed prospective study.

Validation of search filters for identifying pediatric studies in PubMed.

OBJECTIVE: To identify and validate PubMed search filters for retrieving studies including children and to develop a new pediatric search filter for PubMed. STUDY DESIGN: We developed 2 different datasets of studies to evaluate the performance of the identified pediatric search filters, expressed in terms of sensitivity, precision, specificity, accuracy, and number needed to read (NNR). An optimal search filter will have a high sensitivity and high precision with a low NNR. RESULTS: In addition to the PubMed Limits: All Child: 0-18 years filter (in May 2012 renamed to PubMed Filter Child: 0-18 years), 6 search filters for identifying studies including children were identified: 3 developed by Kastner et al, 1 developed by BestBets, one by the Child Health Field, and 1 by the Cochrane Childhood Cancer Group. Three search filters (Cochrane Childhood Cancer Group, Child Health Field, and BestBets) had the highest sensitivity (99.3%, 99.5%, and 99.3%, respectively) but a lower precision (64.5%, 68.4%, and 66.6% respectively) compared with the other search filters. Two Kastner search filters had a high precision (93.0% and 93.7%, respectively) but a low sensitivity (58.5% and 44.8%, respectively). They failed to identify many pediatric studies in our datasets. The search terms responsible for false-positive results in the reference dataset were determined. With these data, we developed a new search filter for identifying studies with children in PubMed with an optimal sensitivity (99.5%) and precision (69.0%). CONCLUSION: Search filters to identify studies including children either have a low sensitivity or a low precision with a high NNR. A new pediatric search filter with a high sensitivity and a low NNR has been developed.