“I Didn't Know I Had a Choice” - Patient Values and Preferences Regarding Resumption of Oral Anticoagulants after Gastrointestinal Bleeding
Bibliographic record
Abstract
Introduction: Gastrointestinal (GI) bleeding is the most common complication of oral anticoagulant (OAC) treatment, which is often discontinued permanently after bleed cessation despite evidence of benefit to prevent future thromboembolic events. High-quality data to inform the management of OACs after GI bleeding are lacking, including when and how they should be resumed. Furthermore, patient/caregiver perspectives on this clinical situation and the factors influencing their decisions about OACs are poorly understood. Understanding patient/caregiver values and preferences is crucial for effective shared decision-making, particularly in situations of clinical uncertainty. This study aims to explore patient/caregiver perspectives to improve patient-centered care in the management of OACs after GI bleeding. Methods: We conducted a descriptive qualitative study using semi-structured interviews and focus groups. Adults who experienced GI bleeding within the previous two years while on OACs for any indication were recruited from outpatient clinics and inpatient wards at three tertiary care hospitals in Hamilton and Ottawa, Canada. Interviews were audio-recorded and transcribed verbatim. Two study investigators coded the first 15 transcripts inductively and the remainder of the transcripts were coded by one study investigator. Data analysis followed Braun and Clarke's reflexive thematic analysis. Results: Thirty-one participants were enrolled (29 individual interviews and 1 focus group). The most common indications for OACs were venous thromboembolism (55%) and atrial fibrillation (29%). Warfarin (35%), apixaban (29%), and rivaroxaban (26%) were the most prescribed OACs. Participants reported that physicians rarely solicited their preferences regarding whether and how OACs should be resumed following a GI bleed. Many were unaware that a decision needed to be made, assuming resumption was necessary to prevent thromboembolism. Despite this, participants did not perceive their lack of involvement in decision-making negatively. Participants experienced tension between the risks of bleeding and thromboembolic events after having a GI bleed while on OACs. Concerns about recurrent GI bleeding were often overshadowed by the fear of thromboembolism. Participants frequently perceived that not taking OACs would definitively result in a stroke or other thromboembolic events, with some equating discontinuation with death. In contrast, bleeding while on OACs was seen as a more transient and acceptable risk. Despite the prevailing fear of thromboembolic events, participants' trust in their physicians helped mitigate their fear of bleeding and thromboembolism. Participants felt their physicians had the expertise to balance these competing risks and had their best interest when determining the optimal management plan. As a result, they expressed strong reliance on their physicians' recommendations regarding OAC management. There was also a frequent desire for improved communication and education about their diagnoses and treatment options. Communication challenges were often experienced when multiple physicians were involved in their care, leading to confusion and uncertainty. However, participants felt that better understanding their diagnoses and the harms and benefits of OACs could help them navigate the tension between risk of bleeding and thromboembolism and make more informed decisions. Conclusions: Participants were often unaware of the need for decision-making regarding the resumption of OACs after a GI bleed. Although they experienced tension between the risks of bleeding and thromboembolism, the fear of thromboembolic events strongly influenced their desire to resume OACs. This underscores the need for physicians to address patient concerns and misconceptions about the risks and consequences of bleeding and thromboembolism. This study also highlights the importance of clear communication and patient education to mitigate the tension between bleeding and thromboembolism. These findings suggest that interventions targeting patient-physician communication and education about the harms and benefits of resuming OACs may help empower patients. Future research should focus on developing and testing such interventions to better support patients in making informed decisions about resuming OACs after a GI bleed.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".