Literature DB >> 23419796

How to recognize PCOS: results of a web-based survey at IVF-worldwide.com.

Ning Ning1, Adam Balen, Paul R Brezina, Milton Leong, Zeev Shoham, Edward E Wallach, Yulian Zhao.   

Abstract

This retrospective evaluation of a web-based survey posted from 1 to 30 September 2010 was to determine which diagnostic tools physicians are currently utilizing to diagnose polycystic ovary syndrome (PCOS). Responses from 262 IVF centres in 68 countries are included in the study. Providers used various diagnostic criteria to diagnose PCOS, including the Rotterdam criteria (82%), National Institutes of Health criteria (8%), Androgen Excess Society 2006 criteria (3%) and other classification systems (7%). Many providers utilized diagnostic tools not necessarily included in traditional classification systems: 58% of respondents evaluated LH/FSH ratio in addition to androgen concentrations to define patients with PCOS; physicians also commonly obtain measurement of anti-Müllerian hormone (22%) and impaired glucose tolerance (74%) in diagnosing PCOS. Many respondents (64%) felt that polycystic-appearing ovaries on ultrasound with anovulation and a normal serum prolactin should be adequate criteria to diagnose PCOS. In conclusion, while the majority of centres (82%) uses the Rotterdam criteria to diagnose PCOS, other criteria and diagnostic tools are commonly used in evaluating patients with suspected PCOS. This study highlights the need for continual re-evaluation of PCOS diagnostic criteria with an ultimate goal of developing a consensus definition for the disorder in the future.
Copyright © 2013 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23419796     DOI: 10.1016/j.rbmo.2013.01.009

Source DB:  PubMed          Journal:  Reprod Biomed Online        ISSN: 1472-6483            Impact factor:   3.828


  2 in total

Review 1.  Polycystic ovary syndrome throughout a woman's life.

Authors:  José Bellver; Luis Rodríguez-Tabernero; Ana Robles; Elkin Muñoz; Francisca Martínez; José Landeras; Juan García-Velasco; Juan Fontes; Mónica Álvarez; Claudio Álvarez; Belén Acevedo
Journal:  J Assist Reprod Genet       Date:  2017-09-27       Impact factor: 3.412

2.  A Rat Model of Polycystic Ovary Syndrome with Insulin Resistance Induced by Letrozole Combined with High Fat Diet.

Authors:  Ming-Xing Wang; Qian Yin; Xin Xu
Journal:  Med Sci Monit       Date:  2020-05-25
  2 in total

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