Evidence map›Paper›PMID 42430219›Full record

ArticleJMIR research protocols2026

Novel Multiplex Near-Point-of-Care PCR Assay for Detecting Sexually Transmitted Infections Among PrEP Users in Western Kenya: Protocol for a Cross-Sectional Pilot Study With an Epidemiological Assessment.

Aarman Sohaili, Felix Mogaka, Zoïe Alexiou, Victor Ocholla Omollo, Servaas A Morre, Elizabeth Anne Bukusi, Pierre P M Thomas

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Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Aarman Sohaili *Microbe & Lab BV, Matrix SIX, 1st Floor Sciencepark 408, Amsterdam, 1098 XH, The Netherlands, 31 616089665.ORCID 0009-0004-2633-804X
Felix Mogaka *Centre for Microbiology Research, Kenya Medical Research Institute, Kisumu, Kenya.ORCID 0000-0002-7750-0404
Zoïe AlexiouDepartment of Social Medicine, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands.ORCID 0000-0002-8828-8904
Victor Ocholla OmolloCentre for Microbiology Research, Kenya Medical Research Institute, Kisumu, Kenya.ORCID 0009-0007-9655-7821
Servaas A MorreDepartment of Genetics and Cell Biology, Faculty of Health, Medicine and Life Sciences, Research Institute for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands.ORCID 0000-0002-9953-0495
Elizabeth Anne BukusiCentre for Microbiology Research, Kenya Medical Research Institute, Kisumu, Kenya.ORCID 0000-0002-2031-2808
Pierre P M ThomasDepartment of Genetics and Cell Biology, Faculty of Health, Medicine and Life Sciences, Research Institute for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands.ORCID 0000-0001-8426-6217

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The global impact of sexually transmitted infections (STIs) significantly affects low- and middle-income countries (LMIC). Iin Kenya, where access to STI diagnostics is limited, effective diagnostic solutions are critically needed. Nucleic acid amplification tests are considered the laboratory gold standard for detecting pathogens such as Chlamydia trachomatis and Neisseria gonorrhoeae due to their high sensitivity and specificity. However, these methods typically require centralized laboratories, trained personnel, and longer turnaround times. FlashDx is a near-point-of-care molecular diagnostic platform designed to address these challenges by integrating automated sample processing and multiplex pathogen detection within a compact system suitable for decentralized use. Objective: The primary aim of this study is to validate the performance of the FlashDx STI multiplex assay for detecting STIs including Chlamydia trachomatis, Neisseria gonorrhoeae, Trichomonas vaginalis, Mycoplasma genitalium, Mycoplasma hominis, and Ureaplasma species compared with the reference Conformité Européenne In-Vitro Diagnostic (CE-IVD)-D dual real-time polymerase chain reaction (rtPCR) from Mikrogen. Methods: We propose a comparative cross-sectional study conducted with up to 400 young pre-exposure prophylaxis (PrEP) users aged between 15 years and 55 years at the Kenya Medical Research Institute Center for Microbiology Research Care and Training Program research site in Kisumu, Kenya. Urine samples were collected and analyzed using the FlashDx STI multiplex chip-based assay to detect 6 STIs, with results confirmed by the CE-IVD-D certified Mikrogen assay in the Netherlands. Participants were recruited in Kisumu, Kenya, from existing HIV prevention programs and sexual health services. Diagnostic performance will be assessed by calculating sensitivity, specificity, positive predictive value, and negative predictive value with 95% CIs. Descriptive and epidemiological analyses will summarize participant characteristics, behavioral risk factors, and the prevalence of STI infections within the cohort. Epidemiological data generated will include prevalence rates for all 6 STIs, providing an overview of STI prevalence with external validation to ensure accuracy and reliability. Results: The study was funded by Microbe & Lab, with in-kind contributions from the Kenya Medical Research Institute (KEMRI) Centre for Microbiology Research (CMR) Research Care and Training Program (RCTP). Data collection was conducted between April 2025 and June 2025 at the KEMRI research site in Kisumu, Kenya. A total of 400 participants were recruited for the study. The study is currently in the data analysis phase. Statistical evaluation of the diagnostic performance of the FlashDx STI multiplex assay is being carried out. In parallel, epidemiological analyses are being conducted. Final results and associated epidemiological findings are expected to be completed and prepared for publication in the summer of 2026. Conclusions: The findings from this study are expected to show the FlashDx STI multiplex assay as an effective point-of-care system for diagnosing 6 common STIs in settings such as Kenya. By demonstrating its usability, accuracy, and reliability, the FlashDx assay could be considered for broader implementation in clinical settings across Kenya and other LMIC.

Indexed as

Multiplex Polymerase Chain ReactionPre-Exposure ProphylaxisSexually Transmitted DiseasesAdultCross-Sectional StudiesFemaleHumansKenyaPilot ProjectsPoint-of-Care SystemsRapid Diagnostic TestsSensitivity and SpecificitychlamydiadiagnosticsgonorrheaKenyapoint of careSTI

Identifiers

PMID42430219
PMCPMC13353406

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.