Risk of Thromboembolism, Recurrent Hemorrhage, and Death After Warfarin Therapy Interruption for Gastrointestinal Tract Bleeding
Bibliographic record
Abstract
BACKGROUND: Patients who not only survive a warfarin-associated gastrointestinal tract bleeding (GIB) event but also have an ongoing risk for thromboembolism present 2 clinical dilemmas: whether and when to resume anticoagulation. The objective of this study was to determine the incidence of thrombosis, recurrent GIB, and death, as well as the time to resumption of anticoagulant therapy, during the 90 days following a GIB event. METHODS: In this retrospective, cohort study using administrative and clinical databases, patients experiencing GIB during warfarin therapy were categorized according to whether they resumed warfarin therapy after GIB and followed up for 90 days. Variables describing the management and severity of the index GIB were also collected. Kaplan-Meier curves were constructed to estimate the survival function of thrombosis, recurrent GIB, and death between the "resumed warfarin therapy" and "did not resume warfarin therapy" groups, with Cox proportional hazards modeling to adjust for potentially confounding factors. RESULTS: There were 442 patients with warfarin-associated index GIB included in the analyses. Following the index GIB, 260 patients (58.8%) resumed warfarin therapy. Warfarin therapy resumption after the index GIB was associated with a lower adjusted risk for thrombosis (hazard ratio [HR], 0.05; 95% CI, 0.01-0.58) and death (HR, 0.31; 95% CI, 0.15-0.62), without significantly increasing the risk for recurrent GIB (HR, 1.32; 95% CI, 0.50-3.57). CONCLUSIONS: The decision to not resume warfarin therapy in the 90 days following a GIB event is associated with increased risk for thrombosis and death. For many patients who have experienced warfarin-associated GIB, the benefits of resuming anticoagulant therapy will outweigh the risks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".