MP43-08 VENOUS THROMBOEMBOLISM RISK IN TESTOSTERONE TREATED MEN WITH AND WITHOUT KLINEFELTER SYNDROME
Bibliographic record
Abstract
You have accessJournal of UrologyCME1 Apr 2023MP43-08 VENOUS THROMBOEMBOLISM RISK IN TESTOSTERONE TREATED MEN WITH AND WITHOUT KLINEFELTER SYNDROME Christopher Lau, Yunzhe Zhang, Bethany Gabriel, Jesufikunayomi Ifeoluwa, and Tet Yap Christopher LauChristopher Lau More articles by this author , Yunzhe ZhangYunzhe Zhang More articles by this author , Bethany GabrielBethany Gabriel More articles by this author , Jesufikunayomi IfeoluwaJesufikunayomi Ifeoluwa More articles by this author , and Tet YapTet Yap More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003289.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: There is a higher risk of VTE in Klinefelter syndrome (KS) (∼17%) compared to the general population (∼0.1%). The risk of venous thromboembolism (VTE) as an adverse effect of testosterone therapy (TT) has been hypothesised, however there is limited data on this. TT is a common treatment for symptom management in KS, and is potentially a factor in higher VTE rates seen in KS. This study aims to evaluate the association between TT in both men with and without KS and VTE. METHODS: A literature review was performed following PRISMA guidelines, using sites such as BMJ, PubMed and ScienceDirect. Study searches, selection, data collection and analysis were carried out by four researchers independently and cross reviewed. 27 studies were selected and results from 6, which were specific to TT and VTE, were included [Table 1]. Significance level was set at p≤0.05. To assess risk of bias, tools such as Newcastle-Ottawa scale were used, and heterogeneity was found. RESULTS: The incidence of VTE in non-KS on TT ranged from 0.6-5.6% (n=2224). The incidence of VTE in KS on TT ranged from 31.3-40.0% (n=135). The background risk was 0.12% and 17.0% for the non-KS and KS groups respectively. Overall, there was a statistically significant increase in incidence of VTE in men taking TT both in the KS [χ2 = 9.95, p<.05] and non-KS [χ2 = 545.66, p<.05] patient groups. However, no statistically significant difference in VTE between the different routes of administration of TT in both the KS [χ2 = 0.12, p=.729485] and non-KS [χ2 = 7.29, p=.06309] patient groups. CONCLUSIONS: Overall, a significant increase in incidence of VTE was observed in men taking TT both in the KS and non-KS patient groups. However, similar rates of VTE between the different routes of administration of TT. Owing to the highly variable follow up period of testosterone treated men, a transient increase in risk of VTE in the first 6 months of initiating treatment was observed by a case control study. It is possible that this change was also observed in the results and therefore more data would be required exploring the long term use of TT and VTE risk. Source of Funding: N/A © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e604 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Christopher Lau More articles by this author Yunzhe Zhang More articles by this author Bethany Gabriel More articles by this author Jesufikunayomi Ifeoluwa More articles by this author Tet Yap 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".