Continuous Perioperative use of Aspirin as Single Therapy during Percutaneous Nephrolithotomy
Bibliographic record
Abstract
Introduction: The rates of heart disease and nephrolithiasis continue to increase in the United States, and aspirin is increasingly prescribed for varying indications. Current recommendations in the urologic literature are to stop aspirin before percutaneous nephrolithotomy (PCNL); however, this is based on expert opinion. This study aims to determine the safety of PCNL performed on patients who took aspirin in the perioperative period. Methods: This study was a retrospective review of 27 consecutive PCNLs for patients who took aspirin in the perioperative period (January 2013-September 2016). Pre- and postoperative hemoglobin was recorded, as were age, sex, BMI, operative duration, skin-to-stone distance, stone size, aspirin dose, aspirin indication, number of blood transfusions, and Clavien-Dindo complication classification. Correlations between hemoglobin and explanatory variables were then explored with linear regression and the Wilcoxon rank-sum test. Results: Of the 199 PCNLs performed, 27 procedures on 23 patients were conducted without discontinuing aspirin perioperatively. Coronary artery disease was the most common indication for aspirin use (81%). Patients experienced a median hemoglobin decline of 1.4 g/dl perioperatively. No significant associations were found between hemoglobin decline and age, sex, BMI, operative duration, skin-to-stone distance, or stone size. There were no Clavien-Dindo grade III or higher complications, and no patients required a blood transfusion or angio-embolization. There were no thrombo-embolic or cardiac events in our series. Conclusions: In our single-center experience, PCNLs performed on patients taking aspirin perioperatively were not associated with the need for blood transfusion nor the occurrence of high-grade complications.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".