1538 SHOCKWAVE LITHOTRIPSY INDUCED PERINEPHRIC HEMATOMA: A MATCHED CASE-CONTROL ANALYSIS OF RISK FACTORS
Bibliographic record
Abstract
You have accessJournal of UrologyStone Disease: New Technology/SWL, Ureteroscopic or Percutaneous Stone Removal I1 Apr 20121538 SHOCKWAVE LITHOTRIPSY INDUCED PERINEPHRIC HEMATOMA: A MATCHED CASE-CONTROL ANALYSIS OF RISK FACTORS Andrew Fuller, Kirsten Foell, Carlos Mendez-Probst, Rasmus Leistner, Sumit Dave, and Hassan Razvi Andrew FullerAndrew Fuller London, Canada More articles by this author , Kirsten FoellKirsten Foell London, Canada More articles by this author , Carlos Mendez-ProbstCarlos Mendez-Probst London, Canada More articles by this author , Rasmus LeistnerRasmus Leistner London, Canada More articles by this author , Sumit DaveSumit Dave London, Canada More articles by this author , and Hassan RazviHassan Razvi London, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.1307AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES To determine the incidence of and evaluate potential risk factors for the development of symptomatic post-shock wave lithotripsy (SWL) perinephric hematoma (PNH) with the latest generation shock wave lithotripter. METHODS From April 2006 to August 2010, 6172 SWL treatments for proximal ureteral and renal stones were performed using the Storz Modulith SLX-F2 device. Data was collected prospectively for patient and treatment-related data. Hematomas were detected by imaging studies when patients developed suggestive signs or symptoms post-procedure. A matched case-control study was performed, with 4 controls matched for each hematoma case based on: sex, age (± 5 years), shock wave rate, energy and number, and no SWL within previous 6 months. Baseline characteristics were compared between the cases and controls using Student's t-test. A conditional logistic regression analysis was performed to assess the independent variables hypertension (intraoperative value ≥ 140/90), anticoagulant/antiplatelet drugs, obesity (BMI ≥ 30) and diabetes; the dependent variable was hematoma. RESULTS Following SWL, 21 patients (0.34%) developed clinically apparent PNH. The mean age was 55.2 years. Male sex was a risk factor for hematoma formation. Intraoperative hypertension (HR 3.302, 1.066 – 10.230, p = 0.0384), and anticoagulant/antiplatelet drugs (HR 4.198, 1.103 – 15.984, p = 0.0355) were significant risk factors. Obesity (p=0.1021) and diabetes (p=0.1043) were not. CONCLUSIONS The incidence of perinephric hematoma formation with the SLX-F2 was less than 1% and consistent with reports of earlier generation devices. Male gender, intraoperative hypertension, and the use of anticoagulant/antiplatelet drugs were identified as risk factors for hematoma formation. © 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 4SApril 2012Page: e622 Peer Review Report Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.MetricsAuthor Information Andrew Fuller London, Canada More articles by this author Kirsten Foell London, Canada More articles by this author Carlos Mendez-Probst London, Canada More articles by this author Rasmus Leistner London, Canada More articles by this author Sumit Dave London, Canada More articles by this author Hassan Razvi London, Canada More articles by this author Expand All Advertisement 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".