The startup has developed a vaginal diagnostic device that utilizes a sensitive probe with silver electrodes and a wireless analytical system to detect sphincter injuries. This technology enhances postpartum diagnostic capabilities, enabling healthcare providers to deliver more accurate care for women experiencing related complications.
Funding
$3.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Approximately 26% of women who give vaginal childbirth experience perineal injuries affecting the anal sphincter complex, and up to 80% of these cases go undetected. Missed or delayed diagnosis of Obstetric Anal Sphincter Injuries (OASI) can lead to long-term complications such as fecal incontinence. Current methods for OASI detection may lack sensitivity, leading to underdiagnosis and delayed intervention.
Solution
OASIS Diagnostics offers ONIRY, a diagnostic system designed for the rapid and accurate detection of OASI immediately following delivery. The system utilizes a small, comfortable probe with silver electrodes to measure tissue impedance via impedance spectroscopy. Measurements are processed through machine learning algorithms to identify sphincter injuries, including occult injuries, with high sensitivity and specificity. The ONIRY system aims to improve detection rates, enabling timely intervention and reducing the risk of long-term complications for women who experience OASI.
Target Audience
The primary target audience includes obstetricians, gynecologists, midwives, and other healthcare professionals involved in postpartum care, as well as hospitals and clinics providing maternity services.
Features
- Impedance spectroscopy technology for objective assessment of anal sphincter integrity
- Small-diameter probe designed for patient comfort during postpartum examination
- Rapid, one-minute testing procedure for immediate results after delivery
- High sensitivity and specificity (approximately 90%) for accurate detection of OASI
- Machine learning algorithms for automated analysis and interpretation of impedance measurements
- Wireless analytical system for streamlined data acquisition and reporting
- Intended to improve early detection of OASI and reduce the risk of fecal incontinence