The metabolic syndrome (MetS) is a cluster of clinical indices that signals increased risk for cardiovascular disease and Type 2 diabetes. Women with polycystic ovary syndrome (PCOS) were associated with MetS and insulin resistance. Cluster analysis was a useful tool for identifying groups of women sharing similar metabolic risk factor patterns. Oligomenorrhea, hyperandrogenism and polycystic ovary morphology were the three major components of PCOS. Obesity is a main risk factor in metabolic syndrome. the investigators are interesting to evaluate the relationship between risk of metabolic syndrome and their clinical and/or biochemical characteristics in women with reproductive age.
Design: Retrospective study; medical records reviewed. Participants and setting: The investigators retrospectively reviewed the medical records of female patients who visited our Reproductive Endocrinology Clinic from Jan. 1, 2009 to Jun. 31, 2012.
Primary Outcome Measures:
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||February 2014 (Final data collection date for primary outcome measure)
Definitions of the metabolic syndrome based on arbitrary cutoff points for several quantitative variables, where each variable is related linearly to cardiovascular risk. Even consensual definitions differ between international authorities and continue to change. Moreover, such cutoff s should be gender and ethic difference. Cluster analysis is a statistical method base on algorithms, which seek to minimize within-group variation and maximize between-group variation for the clustering variables. This technique is suitable for defining groups, reflecting the natural structure of data without relying on inappropriate arbitrary cutoffs. We conduct this retrospective study to review the medical records of female patients who visited our Reproductive Endocrinology Clinic from Jan. 1, 2009 to Dec. 31, 2012. Cluster analysis was performed in our studied cases to evaluate the correlation between clinical/biochemical characteristic and risk of metabolic risk in women with reproductive age.