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)
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,003 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,045 | 0,021 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».