Protocol: Cross-Sectional Pilot Study Evaluating a Novel Multiplex Near–Point-of-Care PCR Assay for Detecting Sexually Transmitted Infections Among PrEP Users in Western Kenya with an Epidemiological Assessment (Preprint)
Bibliographic record
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.045 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".