Evidence map›Paper›PMID 39653015›Full record

ArticleThe Journal of urology2025

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.

Gregory E Tasian, Jonathan D Harper, Hussein R Al-Khalidi, Hongqiu Yang, Naim M Maalouf, Michele Curatolo, H Henry Lai, Alana Desai, Jodi A Antonelli, Jing Huang and 5 more

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in The Journal of urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Stent is a bane for urologists.World journal of urology · 2026
    Review
  2. Review
  3. Reply by Authors.The Journal of urology · 2025
    Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Gregory E TasianDepartment of Surgery, Division of Urology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Jonathan D HarperDepartment of Urology, University of Washington, Seattle, Washington.
Hussein R Al-KhalidiDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.
Hongqiu YangDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.
Naim M MaaloufDepartment of Internal Medicine and Charles and Jane Pak Center for Mineral Metabolism and Clinical Research, University of Texas Southwestern Medical Center, Dallas, Texas.
Michele CuratoloDepartment of Anesthesiology & Pain Medicine, University of Washington, Seattle, Washington.
H Henry LaiDepartment of Surgery (Urology), Washington University in St Louis, St Louis, Missouri.
Alana DesaiDepartment of Surgery (Urology), Washington University in St Louis, St Louis, Missouri.
Jodi A AntonelliDepartment of Urology, Duke University School of Medicine, Durham, North Carolina.
Jing HuangDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
Justin B ZiembaDepartment of Urology, University of Pennsylvania, Philadelphia, Pennsylvania.
Hunter WessellsDepartment of Urology, University of Washington, Seattle, Washington.
Ziya KirkaliNational Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland.
Charles D ScalesDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.ORCID 0000-0002-7887-0204
Peter P ReeseDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.

Funding

Urinary Stone Disease Research Network: Scientific Data Research CenterU01DK110988 · NIDDK · DUKE UNIVERSITY · PI AL-KHALIDI, HUSSEIN, SCALES, CHARLES D · 2016 to 2020
$6.9M
Optimizing Fluid Therapy and Stent Management in Children and Adults with NephrolithiasisU01DK110994 · NIDDK · UT SOUTHWESTERN MEDICAL CENTER · PI MAALOUF, NAIM M · 2016 to 2024
$5.3M
Harnessing Behavior to Decrease Urinary Stone Disease Morbidity Research ProjectU01DK110961 · NIDDK · CHILDREN'S HOSP OF PHILADELPHIA · PI REESE, PETER PHILIP, TASIAN, GREGORY EDWARD · 2016 to 2024
$5.3M
Extension of Urinary Stone Disease Research Network (USDRN) at Washington UniversityU01DK110986 · NIDDK · WASHINGTON UNIVERSITY · PI LAI, HING HUNG HENRY · 2016 to 2024
$5.2M
UW USDRN Clinical CenterU01DK110954 · NIDDK · UNIVERSITY OF WASHINGTON · PI HARPER, JONATHAN D., WESSELLS, HUNTER · 2016 to 2024
$4.9M
Urinary Stone Disease Research Network: Scientific Data Research CenterU24DK110988 · NIDDK · DUKE UNIVERSITY · PI AL-KHALIDI, HUSSEIN, SCALES, CHARLES D · 2022 to 2024
$4.1M
NIDDK NIH HHS U01 DK110954NIDDK NIH HHS U01 DK110961NIDDK NIH HHS U01 DK110986NIDDK NIH HHS U01 DK110988NIDDK NIH HHS U01 DK110994NIDDK NIH HHS U24 DK110988
6 · The paper itself

Abstract

purposeWe developed prediction models for severe pain and urinary symptoms after ureteroscopy with ureteral stent placement. MATERIALS AND

methodsThe 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.

resultsFemale 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).

conclusionsPreoperative 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.

Indexed as

Postoperative PainStentsUreteroscopyAdolescentAdultAgedFemaleHumansMaleMiddle AgedPain MeasurementProspective StudiesSeverity of Illness IndexUreterYoung Adultpainpredictionureteral stentsureteroscopy

Identifiers

PMID39653015
PMCPMC11888894

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.