This clinical study aims to train the algorithm and assess the performance of the Ainos Flora Women's Vaginal Health Tester in identifying vaginal infections.
Ainos Flora Women's Vaginal Health Tester is an in vitro diagnostic device implementing electronic nose technology to detect vaginal infections by examining metabolized gases of vaginal bacteria. The electronic nose system mainly comprises the Micro-Electro-Mechanical Systems (MEMS) gas sensor array and the Artificial Neural Network algorithm. The primary purpose of this study is to train the algorithm and assess the performance of the Ainos Flora in identifying vaginal infections. In addition, the primary outcome measures of this study, including sensitivity and specificity, will be used as a reference for the feasibility and sample size assessment of the next phase of pivotal clinical trials.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
120
Screening for Bacterial vaginosis (BV) / Trichomonas / Chlamydia trachomatis / Candida albicans
Screening for Group B streptococcus / Neisseria gonorrhoeae / Escherichia coli
The participant operates the Ainos Flora to collect signatures of metabolic gases in the vagina by herself.
MacKay Memorial Hospital
Taipei, Taiwan
RECRUITINGTri-Service General Hospital
Taipei, Taiwan
RECRUITINGTo assess the sensitivity and specificity of Ainos Flora in subjects compared to RT-PCR and culture groups in identifying the types of vaginitis.
* Bacterial infection : Bacterial vaginosis (BV) / Escherichia coli / Trichomonas / Group B streptococcus / Chlamydia trachomatis / Neisseria gonorrhea * Fungal infection: Candida albicans * Mixed infection: Bacterial and fungal infections coexist * No infection: Healthy participant
Time frame: Up to 6 months.
Assess the change in sensitivity as the number of subjects is changed.
When the number of subjects reaches 30,60,90,120, input the collected gas data into the algorithm and calculate the sensitivity. We can then assess the change in sensitivity when the number of subjects changes from 30 to 60, 90, and 120.
Time frame: Up to 6 months.
Assess the change in specificity as the number of subjects is changed.
When the number of subjects reaches 30,60,90,120, input the collected gas data into the algorithm and calculate the specificity. We can then assess the change in specificity when the number of subjects changes from 30 to 60, 90, and 120.
Time frame: Up to 6 months.
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The medical staff operates the Ainos Flora to collect signatures of metabolic gases in the participant's vagina.