Abstract
BackgroundTo develop and validate a practical nomogram for predicting the probability of patients with impacted ureteral stone.MethodsBetween June 2020 to March 2021, 214 single ureteral stones received ureteroscopy lithotripsy (URSL) were selected in development group. While 82 single ureteral stones received URSL between April 2021 to May 2021 were included in validation group. Independent factors for predicting impacted ureteral stone were screened by univariate and multivariate logistic regression analysis. The relationship between preoperative factors and stone impaction was modeled according to the regression coefficients. Discrimination and calibration were estimated by area under the receiver operating characteristic (AUROC) curve and calibration curve respectively. Clinical usefulness of the nomogram was evaluated by decision curve analysis.ResultsAge, ipsilateral stone treatment history, hydronephrosis and maximum ureteral wall thickness (UWTmax) at the portion of stone were identified as independent predictors for impacted stone. The AUROC curve of development and validation group were 0.915 and 0.882 respectively. Calibration curve of two groups showed strong concordance between the predicted and actual probabilities. Decision curve analysis showed that the predictive nomogram had a superior net benefit than UWTmax for all examined probabilities.ConclusionsWe developed and validated an individualized model to predict impacted ureteral stone prior to surgery. Through this prediction model, urologists can select an optimal treatment method and decrease intraoperative and postoperative complications for patients with impacted ureteral calculus.
Highlights
To develop and validate a practical nomogram for predicting the probability of patients with impacted ureteral stone
Sarica et al [7] indicated that the serum acute phase reactants CRP (C-reactive protein) and Erythrocyte sedimentation rate (ESR) values as well as the UWT were helpful to estimate the presence of stone impaction
Significant differences between the impacted and non-impacted patients in the development group were viewed for the following parameters: age (P < 0.001), ipsilateral stone treatment history (P < 0.001), stone density (P = 0.008), hydronephrosis (P < 0.001), maximum stone diameter (P = 0.002), maximum cross-sectional area of the stone (P = 0.002), stone volume (P = 0.002), percussion tenderness over kidney region (P < 0.001) and Maximum ureteral wall thickness (UWTmax) (P < 0.001)
Summary
To develop and validate a practical nomogram for predicting the probability of patients with impacted ureteral stone. Stone impaction is common in clinical practice and often lead to obstructive hydronephrosis, which may cause urosepsis even renal failure. There is an urgent need for developing a tool to predict stone impaction prior to surgery. It was found that several preoperative factors, such as age, stone location and UWT, were strongly associated with the impacted ureteral stone [8]. Based on a review of previous studies, the present study aimed to evaluate the ability of preoperative factors for screening and identifying the stone impaction prior to surgery. Established models for predicting ureteral calculi associated with urosepsis exist but the model for predicting the ureteric stone impaction is still in development [9]. We subsequently developed and validated a preoperative model for predicting these stones
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