Neutrosophic multicriteria method to determine the prevalence of polycystic ovary syndrome and associated risk factors in women attended at the Santa Rosa Health Center

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Adisnay Rodríguez Plasencia
Riber Fabián Donoso Noroña
Belkis Sánchez Martínez

Abstract

Polycystic ovary syndrome is an endocrinological condition that causes disorders of the menstrual cycle, secondary to ovarian dysfunction or hormonal physiological variation. Therefore, it seems important to determine the prevalence of polycystic ovarian syndrome and associated risk factors in women treated at the Santa Rosa health center. This research proposes a multicriteria neurosophic method to determine the prevalence of polycystic ovary syndrome and associated risk factors in women treated at the Santa Rosa Health Center. A descriptive, observational, cross-sectional methodology is applied, developed through a survey of 132 patients. As a result, 58% are between the ages of 20 and 39, 43% of them had hypertension, 74% diabetes mellitus type 2, 76% hyperandrogenism, another 67% obesity or overweight, and in relation to menstrual disorders, 96% of them manifested amenorrhea. Concluding that menstrual and endocrinological disorders made up a large part of the clinic and both contraceptives and metformin are the therapeutic pathways that provided the best results.

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Neutrosophic multicriteria method to determine the prevalence of polycystic ovary syndrome and associated risk factors in women attended at the Santa Rosa Health Center . (2022). Neutrosophic Computing and Machine Learning. ISSN 2574-1101, 20, 41-52. https://fs.unm.edu/NCML2/index.php/112/article/view/189
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How to Cite

Neutrosophic multicriteria method to determine the prevalence of polycystic ovary syndrome and associated risk factors in women attended at the Santa Rosa Health Center . (2022). Neutrosophic Computing and Machine Learning. ISSN 2574-1101, 20, 41-52. https://fs.unm.edu/NCML2/index.php/112/article/view/189