Safety of transrectal ultrasound-guided prostate biopsy in patients receiving aspirin
Bibliographic record
Abstract
BACKGROUND: The management of aspirin before transrectal prostate puncture-guided biopsy continues to be controversial. The conclusions in newly published studies differ from the published guideline. Therefore, an updated meta-analysis was performed to assess the safety of continuing to take aspirin when undergoing a transrectal ultrasound-guided prostate biopsy (TRUS-PB). METHODS: We searched the following databases for relevant literature from their inception to October 30, 2020: PubMed, EMBASE, Cochrane Central Register of Controlled Trials, Medline, Web of Science, Sinomed, Chinese National Knowledge Internet, and WANGFANG. Studies that compared the bleeding rates between aspirin that took aspirin and non-aspirin groups were included. The quality of all included studies was evaluated using the Newcastle-Ottawa Scale. Revman Manger version 5.2 software was employed to complete the meta-analysis to assess the risk of hematuria, hematospermia, and rectal bleeding. RESULTS: Six articles involving 3373 patients were included in this meta-analysis. Our study revealed that compared with the non-aspirin group, those taking aspirin exhibited a higher risk of rectal bleeding after TRUS-PB (risk ratio [RR] = 1.27, 95% confidence interval [CI] [1.09-1.49], P = .002). Also, the meta-analysis results did not reveal any significant difference between the 2 groups for the risk of hematuria (RR = 1.02, 95%CI [0.91-1.16], P = .71) and hematospermia (RR = 0.93, 95%CI [0.82-1.06], P = .29). CONCLUSION: Taking aspirin does not increase the risk of hematuria and hematospermia after TRUS-PB. However, the risk of rectal bleeding, which was slight and self-limiting, did increase. We concluded that it was not necessary to stop taking aspirin before undergoing TRUS-PB.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.018 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".