Association between the severity of acute renal colic episodes and clinical, laboratory, and imaging parameters

Kai Dang^1,2,#, Teng Cui^1,2,#, Yongan Zhou^1,2, Jiayuan Ji^1,2, Yang Yang^1,2, Xiangyu Wang^1,2, Jing Xiao^1,2,*
1 Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
2 Institute of Urology, Beijing Municipal Health Commission, Beijing, China
* Corresponding Author: Jing Xiao. Email: email
# These authors contributed equally to this work

Canadian Journal of Urology https://doi.org/10.32604/cju.2026.068291

Received 24 May 2025; Accepted 05 February 2026; Published online 04 March 2026

Abstract

Objectives: Although renal colic is a well-known acute manifestation of urolithiasis, the relationship between its pain severity and a range of clinical parameters has not been clearly established by comprehensive studies. This study aimed to construct and validate a simple and accurate clinical nomogram for predicting the occurrence of more intense acute renal colic (ARC) in patients with urolithiasis. Methods: The development and validation of the prediction model followed the reporting standards outlined in the TRIPOD checklist. A retrospective analysis was conducted on 285 patients who visited the Department of Urology at Beijing Friendship Hospital, Capital Medical University, from March 2024 to November 2024. Propensity score matching (PSM) of the raw observational data was conducted. This study utilized univariate, multivariate logistic, and linear regression analysis to screen and evaluate the risk factors for ARC pain intensity and constructed a predictive model. An evaluation was performed using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). Results: Univariate analysis after PSM and linear logistic regression analysis identified independent risk factors for higher Visual Analog Scale (VAS) scores: serum creatinine (β-Coefficient = 0.364, 95% CI: 0.117–0.610, p = 0.005), pyuria (β-Coefficient = 0.273, 95% CI: 0.006–0.548, p = 0.042), hydronephrosis (β-Coefficient = 0.128, 95% CI: 0.073–0.254, p = 0.007), CRP levels (β-Coefficient = 0.311, 95% CI: 0.113–0.582, p = 0.018), and urinary bacteriuria ≥5/HPF (β-Coefficient = 0.324, 95% CI: 0.074–0.641, p = 0.018). The nomogram model demonstrated good accuracy with an AUC value of 0.964, and in the validation cohort, the AUC value was 0.969. The calibration curve indicated a better consistency between the predictive model and the actual occurrence of more intense ARC in patients with urolithiasis. The decision curve analysis showed favorable clinical utility. Conclusion: Serum creatinine, pyuria, hydronephrosis, CRP levels, and urinary bacteriuria ≥5/HPF are independent risk factors for higher VAS scores. The constructed predictive model based on these factors effectively assesses the risk of more intense ARC in patients with urolithiasis.