The identification of pregnant women with renal colic who may need surgical intervention
Mao-mao He, Xiaoting Lin, Ming Lei, Xiaolan Xu, Zhihui He
Abstract
BACKGROUND: Renal colic is a surgical emergency in pregnancy that is caused by a range of non-obstetric factors and known to occur more frequently during the second and third trimesters. Several studies have reported that up to 70-80% of stones pass spontaneously during pregnancy. There are some patients will not pass their stones and will ultimately require surgical intervention. Through retrospective analysis of the clinical data of 212 pregnant women with renal colic, the predictive factors of pregnant women with renal colic in need of surgical intervention were determined. METHODS: We conducted a retrospective review of 212 pregnant women presenting with renal colic between 1st January 2009 and 31st December 2020. Univariate and multivariate analyses identified a range of predictive variables for surgical intervention. In addition, we used receiver operating characteristic curve analysis to evaluate the predictive power of our model and created a nomogram for clinical application. RESULTS: Of the 212 patients presenting with acute renal colic in pregnancy, 100 patients (47.2%) underwent surgical intervention and 112 patients (52.8%) were treated conservatively. Univariate analysis identified significant differences between the two groups with regards to fever, the duration of pain, white blood cells, C-reactive protein, ureteral stone size, hydronephrosis, and stone location. Multivariate analysis further identified a number of independent predictors for surgical intervention, including fever, a duration of pain ≥ 4 days, a ureteral stone size ≥ 8 mm, and moderate or severe hydronephrosis. CONCLUSIONS: We identified several independent predictors for surgical intervention for renal colic in pregnancy. Fever, a duration of pain ≥ 4 days, a ureteral stone size ≥ 8 mm, and moderate/severe hydronephrosis, play significant roles in predicting surgical intervention. Our nomogram can help to calculate the probability of surgical intervention in a simple and efficient manner. Prospective studies are now required to validate our model.