Journal article
Development of Prediction Models for Severe Pain and Urinary Symptoms After Ureteroscopy With Ureteral Stent Placement: Results From the STENTS Study and Initial Validation of Pain Interference
The Journal of urology, Vol.213(4), pp.475-484
04/2025
DOI: 10.1097/JU.0000000000004370
PMID: 39653015
Abstract
Purpose:We developed prediction models for severe pain and urinary symptoms after ureteroscopy with ureteral stent placement.Materials and Methods:The development cohort included 424 adults and adolescents enrolled in the multicenter STENTS prospective cohort study who underwent ureteroscopy with stent placement for urinary stones. The validation cohort was an independent prospective cohort of 115 adults. The outcomes were severe pain intensity and pain interference, measured by the Patient-Reported Outcomes Measurement Information System, and severe urinary symptoms, measured by the Ureteral Stent Symptom Questionnaire. The top quartile of symptoms on postoperative days 1 and 3 was defined as severe. Generalized estimating equation models were used to predict severe symptoms on postoperative days 1, 3, 5, and 7 to 9 in the development cohort and severe pain interference on days 1 and 7 in the validation cohort.Results:Female sex, younger age, higher BMI, baseline pain interference, number of chronic pain conditions, renal stone location, and history of anxiety predicted severe pain. In the development cohort, the C statistics were 0.83 (95% CI 0.80-0.85) for severe pain interference and 0.82 (95% CI 0.79-0.84) for severe pain intensity. A model in which baseline urinary symptoms replaced pain interference had excellent discrimination for severe urinary symptoms (C statistic 0.83; 95% CI 0.81-0.85). In the validation cohort, the C statistic was 0.7 for severe pain interference (95% CI 0.54-0.78).Conclusions:Preoperative characteristics accurately predicted severe pain and urinary symptoms after ureteroscopy with stent placement. On further validation, these models could guide clinical decisions to improve surgical outcomes.
Details
- Title: Subtitle
- Development of Prediction Models for Severe Pain and Urinary Symptoms After Ureteroscopy With Ureteral Stent Placement: Results From the STENTS Study and Initial Validation of Pain Interference
- Creators
- Gregory E. Tasian - Children's Hospital of PhiladelphiaJonathan D. Harper - University of WashingtonHussein R. Al-Khalidi - Duke UniversityHongqiu Yang - Duke UniversityNaim M. Maalouf - The University of Texas Southwestern Medical CenterMichele Curatolo - University of WashingtonH. Henry Lai - Washington University in St. LouisAlana Desai - Washington University in St. LouisJodi A. Antonelli - Duke UniversityJing Huang - University of PennsylvaniaJustin B. Ziemba - University of PennsylvaniaHunter Wessells - University of WashingtonZiya Kirkali - Natl Inst Diabet & Digest & Kidney Dis, Bethesda, MD USACharles D Scales Jr - Duke UniversityPeter P. Reese - University of PennsylvaniaNIDDK Urinary Stone Dis Res Network
- Resource Type
- Journal article
- Publication Details
- The Journal of urology, Vol.213(4), pp.475-484
- DOI
- 10.1097/JU.0000000000004370
- PMID
- 39653015
- NLM abbreviation
- J Urol
- ISSN
- 0022-5347
- eISSN
- 1527-3792
- Publisher
- Lippincott Williams & Wilkins
- Number of pages
- 10
- Grant note
- Washington University in St Louis Robert Sweet, MD National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK); United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK) University of Texas Southwestern Medical Center, Dallas, Texas National Institute of Diabetes and Digestive and Kidney Diseases; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Diabetes & Digestive & Kidney Diseases (NIDDK) University of Washington, Seattle, Washington; University of Washington
- Language
- English
- Date published
- 04/2025
- Academic Unit
- Urology
- Record Identifier
- 9985244656202771
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