Repository of Research and Investigative Information

Repository of Research and Investigative Information

Ilam University of Medical Sciences

Predictive Factors For Pelvic Organ Prolapse In Iranian Women's, An Ordinal Logistic Approc

Sat Jul 20 23:28:47 2024

(2014) Predictive Factors For Pelvic Organ Prolapse In Iranian Women's, An Ordinal Logistic Approc. Journal of Clinical and Diagnostic Research. pp. 96-99. ISSN 2249782X (ISSN)

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Introduction: To investigate the predictors factors of Pelvic Organ Prolapse (POP) in Iranian women by using ordinal logistic regression. Materials and Methods: The role of risk factors of POP was evaluated among 365 patients attending in two public centres in Ilam province, Iran. Exclusion criteria were of single, pregnant and lactate women receiving hormone replacement therapy. Both the unvaried and multi-variate ordinal logistic regression were used to find the predictive factors of POP and computing sensitivity and specificity of models. R esults: In multi-variate ordinal logistic regression the variables of Body Mass Index(BMI) Maximum Birth Weight (MBW) and delivery mode were the most important factors for prediction of prolapse stage. The sensitivity and specificity of multi-variate ordinal logistic, as a screening test, were 95.7 and 48.7 respectively. C onclusion: BMI, MBW and delivery mode can use for prediction of POP stage. Stage of prolapse is an ordinal variable, therefore to show relationship between stage of prolapse and other variables ordinal logistic regression is an appropriate model.

Item Type: Article
Direkvand-Moghadam, A.UNSPECIFIED
Keywords: Dorsal lithotomy position Ordinal logistic regression Pelvic organ prolapse adult article birth weight body mass constipation cross-sectional study female hormone substitution human information processing Iran major clinical study medical record pelvis surgery prevalence risk factor screening test tissue injury vaginal delivery
Page Range: pp. 96-99
Journal or Publication Title: Journal of Clinical and Diagnostic Research
Journal Index: Scopus
Volume: 8
Number: 1
Identification Number:
ISSN: 2249782X (ISSN)
Depositing User: مهندس مهدی شریفی

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