Prediction of polycystic ovarian syndrome based on ultrasound findings and clinical parameters

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To determine the accuracy of sonographic-diagnosed polycystic ovaries and clinical parameters in predicting polycystic ovarian syndrome. Methods: Medical records and ultrasounds of 151 women with sonographically diagnosed polycystic ovaries were reviewed. Sonographic criteria for polycystic ovaries were based on 2003 Rotterdam European Society of Human Reproduction and Embryology/American Society for Reproductive Medicine guidelines: at least one ovary with 12 or more follicles measuring 2-9 mm and/or increased ovarian volume >10 cm3. Clinical variables of age, gravidity, ethnicity, body mass index, and sonographic indication were collected. One hundred thirty-five patients had final outcomes (presence/absence of polycystic ovarian syndrome). Polycystic ovarian syndrome was diagnosed if a patient had at least one other of the following two criteria: oligo/chronic anovulation and/or clinical/biochemical hyperandrogenism. A logistic regression model was constructed using stepwise selection to identify variables significantly associated with polycystic ovarian syndrome (p<.05). The validity of the model was assessed using receiver operating characteristics and Hosmer-Lemeshow χ2 analyses. Results: One hundred twenty-eight patients met official sonographic criteria for polycystic ovaries and 115 (89.8%) had polycystic ovarian syndrome (p=009). Lower gravidity, abnormal bleeding, and body mass index >33 were significant in predicting polycystic ovarian syndrome (receiver operating characteristics curve, c=0.86). Pain decreased the likelihood of polycystic ovarian syndrome. Conclusions: Polycystic ovaries on ultrasound were sensitive in predicting polycystic ovarian syndrome. Ultrasound, combined with clinical parameters, can be used to generate a predictive index for polycystic ovarian syndrome.

Original languageEnglish (US)
Pages (from-to)157-163
Number of pages7
JournalJournal of Clinical Ultrasound
Volume43
Issue number3
DOIs
StatePublished - Mar 1 2015

Keywords

  • Gynecology
  • Polycystic ovarian syndrome
  • Polycystic ovaries
  • Ultrasound

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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