MP57-13 AGE-STRATIFIED POTENCY OUTCOMES OF BILATERAL NERVE SPARING ROBOTIC-ASSISTED RADICAL PROSTATECTOMY
Bibliographic record
Abstract
advancements have led to decreased rates of infectious complications.The AUA best practice statement recommends administering perioperative aminoglycoside with either vancomycin or a first or second generation cephalosporin.There is a lack of evidence to show which antibiotic combinations correlate to decreased rates of post-operative infection.This study aims to determine adherence to AUA guidelines and which antibiotics combinations are associated with decreased rates of infection.METHODS: The Truven MarketScan (MS) database of commercial claims encounters was used to identify men over age 18 who underwent penile prosthetic surgery between 2012 and 2017.Antibiotic combinations were generated to stratify patients and determine risk of post-operative infection (Table 1).A cox proportional hazards model was performed from time of penile prosthetic surgery to date of infection.Binary cofactors were used for each antibiotic combination.Men were considered censored at the time they dropped out of MS.RESULTS: 17,067 men underwent penile prosthetic surgery.Of those, 6889 had documented antibiotics administered on the day of surgery.Those who did not have an antibiotic record were excluded.49% of patients were administered antibiotics according to AUA guidelines.The remainder of patients received either a single antibiotic or another combination.There was no difference in post-operative infection rates between patients who received an AUA recommended antibiotic combination and other antibiotics (Table 2).CONCLUSIONS: Approximately half of men undergoing penile prosthetic surgery were administered antibiotics according to AUA guidelines.There was no difference in infection rates post-operatively, regardless of which antibiotic combination administered.Perioperative antibiotic use varies widely and surgeons should tailor their antibiotics regiment based on local antibiogram.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".