Polycystic ovary syndrome: computer program-assisted diagnosis based on clinical and anamnestic factors and hormonal and ultrasound markers
- Authors: Beglova A.Y.1, Elgina S.I.1
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Affiliations:
- Kemerovo State Medical University
- Issue: No 3 (2020)
- Pages: 133-140
- Section: Articles
- URL: https://journals.eco-vector.com/0300-9092/article/view/248900
- DOI: https://doi.org/10.18565/aig.2020.3.133-140
- ID: 248900
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Abstract
Objective. To develop a computer program for the diagnosis of polycystic ovary syndrome (PCOS) in reproductive-aged women. Subjects and methods. The investigation enrolled 200 women aged 18 to 35 years, who were examined using clinical, anamnestic, laboratory, ultrasound, and statistical studies: Group 1 consisted of100 women with PCOS; Group 2 included 100 women without PCOS. Results. Statistically significant differences were found between the main indicators characterizing the ovarian reserve in reproductive-aged women with PCOS and in healthy ones. Based on the obtained information base, a computer program was developed using the logistic regression method for the diagnosis of factors and the identification of diagnostic markers for PCOS; the program was tested using an independent sample. The sensitivity and specificity of this method to diagnose PCOS were 70.9% and 75.7%, respectively. The computer program “Clinical, anamnestic, laboratory, and ultrasound diagnosis of PCOS” was developed and registered (State Registration Certificate for Computer Program No. 2019662249; the state registration date in the Computer Programs Registry was September 9, 2019 in the Federal Service for Intellectual Property, Moscow). Conclusion. The program “Clinical, anamnestic, laboratory, and ultrasound diagnosis of PCOS”, which is based on the identification of clinical and anamnestic factors, laboratory and ultrasound markers, can be recommended for routine use for the diagnosis of PCOS and a more differentiated approach to implementing therapeutic measures.
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About the authors
Angelika Yu. Beglova
Kemerovo State Medical University
Email: angelik-i986@mail.ru
Svetlana I. Elgina
Kemerovo State Medical University
Email: elginas.i@mail.ru
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