Endometriosis Application for a Quicker Diagnosis: Comparison
Please note this is a comparison between Version 4 by Elizabeth Williamson and Version 5 by Catherine Yang.

Endometriosis is a disease in which uterine tissue grows outside the uterus. It can cause chronic pain and infertility in patients. Mobile health (mHealth), the practice of medicine from mobile devices, is being utilized across the healthcare field for screening, diagnostics, and treatment. MHealth is widely used in the field of OB/GYN. 

  • Endometriosis
  • Gynecology
  • OB/GYN
  • Women's Health
  • mHealth
  • Mobile Healthcare
  • Infertility
  • Pelvic Pain
  • Menstruation

1. Introduction to EndometriosisEndometriosis Application for a Quicker Diagnosis

Introduction to Endometriosis

Endometriosis is a common whole-body condition that affects millions of patients worldwide. It is a disease in which uterine tissue anomalously grows outside of the uterine cavity. The abnormal tissue can cause an inflammatory reaction resulting in adhesions and fibrosis in the pelvic cavity as well as several other locations throughout the body. There are many factors thought to contribute to the development of endometriosis including but not limited to retrograde menstruation, cellular metaplasia (the differentiation of one cell type to another) and stem cell deposition. Retrograde menstruation is the process of menstrual blood containing endometrial cells flowing backward into the pelvic cavity during a patient’s menstrual cycle.

For many patients, endometriosis starts at the onset of their first menstrual cycle and can continue until menopause. The most common symptoms experienced by patients with endometriosis are pelvic pain, infertility, and organ dysfunction. Some patients with severe endometriosis may be asymptomatic and suffer silent organ dysfunction. Many patients suffer immense psychosocial consequences as a result of the chronic and regular pain, delayed diagnosis, sexual dysfunction, and infertility that endometriosis often causes.

2. History of the Long Road to Diagnosis

History of the Long Road to Diagnosis

While highly prevalent, the myriad of symptoms and variety in presentation result in extensive issues diagnosing and treating this condition. Several factors have been proposed to explain the delay in diagnosis including the normalization of menstrual pain, the diversity of symptoms, and the lack of non-invasive testing. The average time for a patient to obtain a diagnosis of endometriosis is estimated to be around 10-12 years [1](1). This results in prolonged suffering of symptoms, unexplained infertility, and decreased quality of life. Further, there is massive cost burden for both the health care system as well as the patient, as they search years for an explanation to their symptoms, resulting in thousands of dollars in direct cost [2](2). Endometrial biopsy function testing for B-cell lymphoma 6 (Bcl-6) and saliva sampling for salivary miRNAs via next generation sequencing and artificial intelligence (AI) are recently becoming promising options for more prompt diagnosis, but a non-invasive method is still needed.

3. The EndoApp – A Response to the Delay

The EndoApp – A Response to the delay

The technological capacity, availability, and increased smartphone ownership globally, including developing nations, promotes the smartphone as an attractive tool to deliver personalized healthcare solutions. It can empower patient self-management, encourage continuous symptoms and vital sign monitoring, and facilitate patient and physician communication. Smartphone technology, including mobile applications and app integrated wearable sensors have increasingly been applied to chronic disease management, and are being referred to as “mHealth” technology. Notably, mHealth applications for diabetes have been widely accepted as a tele-management service for Type 1 and Type 2 Diabetes Mellitus. mHealth applications are also being extensively used in the field of Women’s Health. Fertility tracking applications are used by both women and men for a variety of reasons including but not limited to: tracking fertility, following cycle, conceiving, and informing fertility treatment [3](3). These applications can also be utilized to spread awareness and obtain information regarding symptoms. There is excellent precedent for the use of mHealth technology to track, control, and diagnose clinical pathologies. It has proven to be a greatly beneficial resource across multiple health specialties, contributing to better patient outcomes, lower health costs, and higher levels of efficiency for health care providers. In the search for novel diagnostic measures of endometriosis, smartphone technology could provide a mechanism for detecting disease and a means of education for patients struggling to understand their symptoms thereby furthering patient autonomy. The Endometriosis Risk Advisor, or “EndoRA,” developed by Nezhat et. al. aims to streamline endometriosis diagnosis and treatment and empower individuals to seek care for their chronic pelvic pain and/or infertility [4](4).

4. Application of the Endometriosis Risk Advisor

Application of the Endometriosis Risk Advisor

EndoRA is designed to identify individuals with a high index of suspicion for endometriosis, allowing them and their physician team to seek expedited gold-standard diagnostic and therapeutic measures. The application was developed utilizing an artificial intelligence (AI)-based algorithm that first categorizes patients based on their chief complaint (pelvic pain or infertility). Patients are then asked to respond to a series of questions regarding symptomatology, family history, psychiatric history, past medical history, fertility issues, and prior fertility testing. The application will identify patients as low, moderate, or high risk of having endometriosis. EndoRA was validated through a study that consisted of 293 patients who had 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%. The positive predictive value was 94.1%, and the negative predictive value was 5.0%. The study found that EndoRA is most predictive of Stages III and IV endometriosis. While the application development team acknowledged some issues in the study design including potential selection bias and low specificity, they believe this application could serve as a valuable screening tool for high-risk individuals.

5. Steps Forward

Steps Forward

Endometriosis is a difficult condition that often goes undiagnosed in women with chronic pelvic pain and infertility. Gold-standard diagnosis for endometriosis includes surgical measures that are delayed on average 10-12 years from the time of initial presentation. The EndoRA mobile application is a new screening measure for women who have chronic pelvic pain and/or infertility. While the validation of the application has some concerns regarding low specificity and sample size, the device is still a promising option to assist patients in educating themselves and advocating for further diagnostic steps and therapeutic management. Increased knowledge and suspicion of endometriosis can expedite referral processes and guide preventive interventions for patients. For patients living in low resource areas, this tool can serve as a vital resource in recognizing their risk and seeking appropriate medical help. For medial practitioners, the high sensitivity of EndoRA can be especially valuable in guiding specialist referrals. For patients seeking help in the field of assisted reproduction, a deeper understanding into a potential cause of their infertility could be vital in upholding their autonomy and directing their treatment plans. mHealth and EndoRA’s non-invasive nature and free accessibility bring hope to patients with endometriosis for quicker answers and better solutions to their chronic symptoms.

1. Leyland N, Casper R, Laberge P, Singh SS, Allen L, Arendas K, et al. Endometriosis: Diagnosis and Management. Journal of Endometriosis. 2010;2(3):107-34.

2. Surrey E, Soliman AM, Trenz H, Blauer-Peterson C, Sluis A. Impact of Endometriosis Diagnostic Delays on Healthcare Resource Utilization and Costs. Adv Ther. 2020;37(3):1087-99.

3. Earle S, Marston HR, Hadley R, Banks D. Use of menstruation and fertility app trackers: a scoping review of the evidence. BMJ Sexual & Reproductive Health. 2021;47(2):90-101.

4. Nezhat C, Armani E, Chen HC, Najmi Z, Lindheim SR, Nezhat C. 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. J Clin Med. 2023;12(16).

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