Cluster Analysis of the Risk of Metabolic Syndrome in Women for Reproductive Age

Cluster Analysis of the Risk of Metabolic Syndrome in Women for Reproductive Age.

Status

UNKNOWN

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT01826357

Enrollment

700

Registered

2013-04-08

Start date

2013-03-31

Completion date

2014-02-28

Last updated

2013-11-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Metabolic Cardiovascular Syndrome

Keywords

metabolic syndrome, cluster analysis, PCOS

Brief summary

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.

Detailed description

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.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

FEMALE

Age

13 Years to 48 Years

Healthy volunteers

Yes

Inclusion criteria

Women had been fulfilled with whole anthropometric measurements, clinic and biochemical survey about cardiovascular study.

Exclusion criteria

1. women who had been diagnosed with malignant tumor, Asherman's syndrome, Mullerian agenesis, and chromosomal anomalies; 2. women who had had menarche less than 1 years before evaluation or who were older than 49; 3. women who received hormones or drugs for major medical diseases within three months of blood sampling.

Design outcomes

Primary

Measure	Time frame	Description
metabolic syndrome	Retrospectively reviewed the patients who visited Reproductive Endocrinology Clinic from Jan. 1, 2009 to Jun. 31, 2012.	We conduct this retrospective study by using cluster analysis, to investigate the relationship between metabolic complications and biochemical/clinical characteristics of endocrinologic dysfunction in women with reproductive age.

Countries

Taiwan

Outcome results