Efficacy and safety of non-vitamin K antagonist oral anticoagulants post-kidney transplantation
Bibliographic record
Abstract
BACKGROUND: Novel oral anticoagulants (NOACs) were developed as alternatives to vitamin K antagonists, primarily warfarin, as they do not require routine monitoring and have limited drug-drug and drug-food interactions. However, the efficacy and safety of these agents in kidney transplantation are not well studied. AIM: To assess the profile and safety of NOACs for patients who had kidney transplantation, and to provide recommendations and guidelines on therapeutic strategies in these patients. METHODS: This was a retrospective study carried out among adult patients who were actively on the following NOACs (apixaban, rivaroxaban or dabigatran) in our renal transplantation program from December 2015 to December 2016. The patients were identified primarily through electronic medical record system (patient data linkage). Data on the clinical and laboratory profile of the patients were retrieved and analyzed with SPSS 22.0. RESULTS: = 0.232). CONCLUSION: No thromboembolic events or significant changes in renal profile were observed in our cohort of kidney transplant recipients who were treated with NOACs for at least a year. However, a few bleeding events were observed. This calls for further well-planned randomized controlled trials to assess the efficacy and safety of NOACs among renal transplant recipients.
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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 | 0.003 | 0.008 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".