1466 INCIDENCE OF HEMATURIA FOLLOWING TUR-BT AMONG 1315 PATIENTS RECEIVING ANTI-PLATELET THERAPY
Bibliographic record
Abstract
You have accessJournal of UrologyBladder Cancer: Superficial II1 Apr 20101466 INCIDENCE OF HEMATURIA FOLLOWING TUR-BT AMONG 1315 PATIENTS RECEIVING ANTI-PLATELET THERAPY Blair Egerdie, Shanta Chawla, Chris Nardo, and Bela Denes Blair EgerdieBlair Egerdie Kitchener, Canada More articles by this author , Shanta ChawlaShanta Chawla Irvine, CA More articles by this author , Chris NardoChris Nardo Irvine, CA More articles by this author , and Bela DenesBela Denes Irvine, CA More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.1181AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Currently, there are no clear compelling data that describe the risk of post TUR-BT hematuria for patients on anti-platelet therapy (APT). The present analysis examines the impact of APT on hematuria reported in 1315 patients randomized to either apaziquone or placebo, across 2 ongoing Phase 3 studies. METHODS We surveyed the databases from two ongoing studies (SPI 611/612) of low risk NMIBC patients receiving an immediate post TURBT instillation of apaziquone or placebo followed for 2 years. Use of anti-platelet medication was collected and categorized as taking Aspirin (ASA), clopidogrel, or both at study entry. Incidence and severity of physician reported post randomization hematuria was compared between patients who were and who were not taking APT using Pearson¡¦s Chi-Square statistic. A 2-tailed Fisher¡¦s Exact test was used to confirm the results when the sample size was small (<20) for any of the categories. The relative risk (RR), and corresponding 95% confidence interval (CI), of hematuria for patients on APT is reported. RESULTS The median patient age was 68 years (range 22-94). 414 patients (31%) reported ASA and/or clopidogrel use at the time of randomization. 347 of these patients (84%) were on ASA alone, while 67 (16%) were on clopidogrel +/- ASA. 134 incident cases of hematuria were reported after randomization. 57 were among patients on ASA+/-clopidogrel (13.8%) compared to 77 (8.5%) for patients not on either drug (fÓ2 = 8.45, p=0.004). The RR of hematuria for patients on APT was 1.61 (1.17-2.22)., The incidence of hematuria for 43 patients on ASA therapy alone was 12.4% (fÓ2 = 1.93, p=0.165) with a RR of 1.27 (0.91-1.79) compared to patients not on APT. For patients on clopidogrel or clopidogrel containing regimens the incidence was 20.9% (14/67; fÓ2 = 8.84, p=0.003) with a RR of 2.17 (1.32-3.57). Hematuria was reported as a serious adverse event (SAE) in 13 of 901 (1.4%) patients not on anti-platelet therapy, 4 of 347 (1%) patients on ASA alone and 5 of 67 (7%) on Plavix or combination therapy. CONCLUSIONS Anti-platelet therapy, specifically regimens with clopidogrel, may more than double the risk of hematuria in patients with NMIBC post TUR-BT however the overall risk of hematuria related SAEs remains low (9/414; 2.1%). For patients on ASA alone it is similar to those not on APT (1.4%vs. 1%; p =0.82) but is higher with the addition of clopidogrel alone or in combination. With the increasing use of APT in aging populations, Urologists should be aware of these additional risks. © 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e564-e565 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Blair Egerdie Kitchener, Canada More articles by this author Shanta Chawla Irvine, CA More articles by this author Chris Nardo Irvine, CA More articles by this author Bela Denes Irvine, CA 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".