Risk factors for coexistence of cervical elongation in uterine prolapse

Objective: To identify factors predicting cervical elongation in women with uterine prolapse. Study design: The medical records of women with uterine prolapse who underwent vaginal hysterectomy were reviewed. Multivariable logistic regression analysis was performed to identify predictors of cervical elongation. Results: Of 295 women with uterine prolapse, 136 (46.1%) patients had cervical elongation, according to Berger et al. Classification (i.e., cervical length >3.38 cm and/or cervix-to-corpus lengths ratio >0.79). Multivariable analysis revealed that lower parity (odds ratio = 0.85, 95% confidence interval [CI] = 0.73 to 0.99, P = 0.04) and advanced stage of uterine prolapse (odds ratio = 1.97, 95% CI = 1.35–2.88, P < 0.001) were predictors for cervical elongation. Based on a receiver operating characteristic curve (ROC) analysis, the following optimum cut-off values were determined for cervical elongation: (1) parity ?3, ROC area = 0.60 (95% CI = 0.53 to 0.66); (2) stage of uterine prolapse ?3, ROC area = 0.63 (95% CI = 0.56 to 0.69). Thus, the predicted logit(p) for a given parity (a) and stage of uterine prolapse (b) can be denoted by logit(p) = -1.26 - 0.16 x a + 0.68 x b. The optimum cut-off values of logit(p) ?-0.18 to predict cervical elongation were determined using ROC analysis (area = 0.66, 95% CI = 0.59 to 0.73). For women with parity ?6, we can use either (1) stage 2 uterine prolapse and parity ?1, or (2) ? stage 3 uterine prolapse as criteria to predict cervical elongation. Conclusions: Lower parity and advanced stage of uterine prolapse are predictors of cervical elongation in women with uterine prolapse. Thus, stage of uterine prolapse ?3 or logit(p) ?-0.18 may be useful for predicting cervical elongation. ? 2018 Elsevier B.V.