
Vaginal rugae: measurement and significance.
OBJECTIVE: To devise a validated measure of vaginal rugae and assess the relationships between vaginal rugae and important clinical parameters. METHODS: Two techniques of assessing vaginal rugae were developed and their inter-/intra-observer variability assessed. Examination variability was assessed using intraclass correlation and by way of an analysis of the absolute difference between the two rugal quantitations. After validating the assessment technique, the rugal quantitations of 88 women were compared to clinical parameters such as age, estrogen status, stage of prolapse, parity, history of anterior vaginal wall surgery, and body mass index. Linear regression analysis was used to assess the relationships between vaginal rugae score and these clinical parameters. RESULTS: The mean age and body mass index of the subjects were 56 years (standard deviation (SD) +/- 13.8 years) and 30.4 kg/m2 (SD +/- 7.5 kg/m2), respectively. The median parity was 2 (range 0-11). A history of anterior vaginal wall surgery was present in 29% of subjects and 46% were estrogen-deficient. Scores for the two techniques to quantitate vaginal rugae were normally distributed. Both techniques demonstrated satisfactory interexaminer reliability. Increasing age and deficient estrogen status were found to be independent predictors of less vaginal rugae. CONCLUSIONS: Vaginal rugae can be reliably quantitated. Loss of vaginal rugae is associated with estrogen deficiency and advancing age.
Duke Scholars
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Related Subject Headings
- Vagina
- Uterine Prolapse
- Reproducibility of Results
- Reference Values
- Prospective Studies
- Parity
- Obstetrics & Reproductive Medicine
- Observer Variation
- Middle Aged
- Humans
Citation

Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Vagina
- Uterine Prolapse
- Reproducibility of Results
- Reference Values
- Prospective Studies
- Parity
- Obstetrics & Reproductive Medicine
- Observer Variation
- Middle Aged
- Humans