A Review on the Appropriate Dosage of Aspirin as a Prophylactic Agent Against Deep Vein Thrombosis Following Total Knee Arthroplasties
Bibliographic record
Abstract
Guidelines regarding Deep Vein Thrombosis prophylaxis following total knee arthroplasties have had conflicting information regarding the use of aspirin as a prophylactic agent in recent years. The National Institute for Clinical Excellence refrains from listing the drug in its guidelines while the American College of Chest Physicians advocates for the drug. Despite the conflicting guidelines, physicians have favored the drug in recent years, with more than 80% utilizing it as a prophylactic agent in total knee arthroplasties. Although a consensus may have been reached by physicians regarding the use of the drug, a consensus has not been reached regarding the preferred dosage. With this in mind, a search of the PubMed database was conducted which yielded six studies that discussed the efficacy of various dose ranges of aspirin. All studies corroborated that not only was aspirin an effective prophylactic agent, but that there was no significant difference between dosages regarding efficacies. Due to factors such as aspirin resistance and the potential of aspirin to cause gastrointestinal injuries, this literature review concludes that the dosage of aspirin given for the prophylaxis of DVT in TKAs should be considered on a patient to patient basis.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".