Use of the Free Endometriosis Risk Advisor App as a Non-Invasive Screening Test for Endometriosis in Patients with Chronic Pelvic Pain and/or Unexplained Infertility
Open accessAbstract
Endometriosis is a prevalent condition that affects millions of individuals globally, leading to various symptoms and significant disruptions to their quality of life. However, the diagnosis of endometriosis often encounters delays, emphasizing the pressing need for non-invasive screening. This retrospective cross-sectional study aimed to evaluate the utility of the Endometriosis Risk Advisor (EndoRA) mobile application in screening for endometriosis in patients with chronic pelvic pain and/or unexplained infertility. The study consisted of 293 patients who met specific criteria: they were English-speaking individuals with chronic pelvic pain and/or unexplained infertility, owned smartphones, and had no prior diagnosis of endometriosis. The results demonstrated that the EndoRA score exhibited a high sensitivity of 93.1% but a low specificity of 5.9% in detecting endometriosis. The positive predictive value was 94.1%, while the negative predictive value was 5.0%. Although the study had limitations and potential selection bias, its findings suggest that EndoRA can serve as a valuable screening tool for high-risk individuals, enabling them to identify themselves as being at an increased risk for endometriosis. EndoRA’s non-invasive nature, free access, and easy accessibility have the potential to streamline evaluation and treatment processes, thereby empowering individuals to seek timely care and ultimately improving patient outcomes and overall well-being.
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The Nezhat Endometriosis Risk Advisor application is a validated digital tool reported to have over 90% accuracy in identifying suspected endometriosis based on patient history and symptom profile.
“All patients were initially screened using the Nezhat Endometriosis Risk Advisor application, a validated digital tool reported to have over 90% accuracy in identifying suspected endometriosis based on patient history and symptom profile [13].”
From Selective Appendectomy in Patients Undergoing Minimally Invasive Surgery for Endometriosis: A Retrospective Cohort Study (2025) · cites this paper as [13]
Section 2.3 (page unavailable) describes EndoRA as a validated application that assesses risk from symptoms and patient history. The Results (page unavailable) report 93.1% sensitivity and 94.1% positive predictive value in the studied high-risk patients, but only 5.9% specificity; they do not establish the claimed over-90% overall accuracy. The app’s >90% high-risk category is a risk label, not a measured accuracy rate. (LLM, conf=0.90)
Experimental — accuracy not yet measuredThe use of the free endometriosis risk advisor app as a non-invasive screening test may be a helpful adjunct to diagnosis.
“The use of the free endometriosis risk advisor app as a non-invasive screening test may be a helpful adjunct to diagnosis [ 60 ].”
From Thoracic Endometriosis Syndrome: A Comprehensive Review and Multidisciplinary Approach to Management (2024) · cites this paper as [60]
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- Authors
- Nezhat, C., Armani, E., Chen, H.-C. C., Najmi, Z., Lindheim, S. R., & Nezhat, C.
- Affiliations
- University of California, San Francisco (US)
- Center for Special Minimally Invasive and Robotic Surgery (US)
- Stanford Medicine (US)
- University of Central Florida (US)
- Corresponding author
- Nezhat, Camran
- Venue
- Journal of Clinical Medicine
- Publisher
- MDPI AG
- Published
- 2023-08-11
- Volume
- 12
- Issue
- 16
- Pages
- 5234
- ISSN
- 2077-0383 (ISSN-L)
- PMC
- PMC10455338
- OpenAlex
- W4385758410
- Cited by
- 15
- References
- 41
- Citations by year
- 2026: 6 · 2025: 6 · 2024: 3
- FWCI
- 3.60
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Clinical Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- University of Central Florida
- Weill Cornell Medical College
- University of California, San Francisco
- Topics
- Health Sciences › Medicine › Reproductive Medicine › Endometriosis Research and Treatment
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ectopic Pregnancy Diagnosis and Management
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- endometriosis, mobile health apps, non-invasive screening, chronic pelvic pain, unexplained infertility, sensitivity and specificity
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