MP16-03 THE IMPACT OF TIMING OF DEFINITIVE INTERVENTION FOR PATIENTS WITH ACUTE RENAL COLIC: A POPULATION-BASED STUDY
Bibliographic record
Abstract
You have accessJournal of UrologyCME1 Apr 2023MP16-03 THE IMPACT OF TIMING OF DEFINITIVE INTERVENTION FOR PATIENTS WITH ACUTE RENAL COLIC: A POPULATION-BASED STUDY Michael Ordon, Sarah Bota, Yuguang Kang, and Blayne Welk Michael OrdonMichael Ordon More articles by this author , Sarah BotaSarah Bota More articles by this author , Yuguang KangYuguang Kang More articles by this author , and Blayne WelkBlayne Welk More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003236.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Little data exists on the optimal timing for intervention for symptomatic kidney stones, as such, our objective was to determine the impact of early intervention versus delayed intervention/expectant management for patients presenting to the emergency department (ED) with renal colic. METHODS: We conducted a population-based cohort study in the province of Ontario, utilizing linked administrative health data. Patients who presented to an ED with renal colic between April 1, 2010 to June 30, 2020 were included. Patients were divided into two groups. The early intervention (EI) group underwent shockwave lithotripsy (SWL), ureteroscopy (URS) or percutaneous nephrolithotomy (PCNL) within 2-weeks of presentation. The delayed intervention/expectant management (non-EI) group represented all other patients. Patients were followed forward in time for 3 months in the EI group and for 4 weeks post-intervention or 3 months (whichever was longer) in the non-EI group to assess for our outcomes. The outcomes included additional ED visits, hospitalizations or imaging studies, stent or nephrostomy insertion and urologist/primary care visits. These outcomes were compared across the two groups using matched propensity score modelling. RESULTS: There were 397,185 index renal colic events (EI=28,910, non-EI=368,275). The EI group was slightly older and more likely to have a history for stones, hypertension and diabetes (Table 1). The EI group had a lower risk for additional ED visits (RR 0.70 95% CI 0.68-0.72, p<0.001) and hospital admissions (RR 0.52, 95% CI 0.50-0.55, p<0.001) compared to the non-EI group. Similarly, the EI group had a lower risk for stent (RR 0.62, 95% CI 0.54-0.71, p<0.001) or nephrostomy insertion (RR 0.49, 95% CI 0.42-0.57, p<0.001), however there was no difference for additional imaging. The EI group had a slightly increased risk for urologist/primary care visit (RR 1.02, 95% CI 1.02-1.03, p<0.001). In the non-EI group, 17% underwent eventual intervention. CONCLUSIONS: Our population-based study suggests a benefit to EI for those presenting with renal colic to the ED, but potentially with the risk of exposing some patients to unneeded treatment. These findings could influence practice patterns and guideline recommendations moving forward. Source of Funding: Northeastern Section of the AUA © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e202 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Michael Ordon More articles by this author Sarah Bota More articles by this author Yuguang Kang More articles by this author Blayne Welk More articles by this author Expand All Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".