Evaluation of a decision aid for patients considering autologous blood donation before open-heart surgery.
Bibliographic record
Abstract
BACKGROUND: Patients undergoing open-heart surgery frequently require one or more blood transfusions. Because of the risks of receiving blood from volunteer donors, some patients choose to donate their own blood before surgery. This reduces their risk of exposure to volunteer-donated blood, but it increases their chance of receiving any transfusion, either of self-donated or volunteer-donated blood. Also, preoperative hemoglobin levels tend to be lower in patients who donate their own blood, and surgeons may be more likely to give transfusions to patients with self-donated blood. To help patients decide whether to donate their blood before surgery, we designed a decision aid comprising a booklet and audiotape and assessed its effectiveness. METHODS: The 59 study subjects were a sample of consecutive patients referred to the Ottawa Heart Institute between Oct. 1, 1998, and Jan. 5, 1999, for future coronary artery bypass grafting, valve surgery or combined surgery. All were eligible to donate blood. Initial questionnaires were administered in the clinic by a physician or study nurse, and follow-up questionnaires were completed at home and mailed in after use of the decision aid. Outcome measures included patients' knowledge, values (importance ratings), preferences for transfusion methods, decisional conflict (the amount of uncertainty about the course of action to take), risk perception and acceptability of the decision aid. RESULTS: Mean knowledge scores on a 15-item test increased from 67% correct responses before the decision aid to 85% correct responses after use of the aid (p < 0.001); the effect was similar when the patients were divided into subgroups according to education level. The number of patients favouring donating their own blood increased from 41 (69%) before to 45 (76%) after use of the aid. Nine (64%) of 14 initially uncertain patients preferred autologous donation after use of the aid. The overall mean score for decisional conflict was unchanged, at 1.7, which indicated a low level of uncertainty. Risk perception improved, from 0%-14% correct responses on an 8-item test before the aid to 18%-60% correct responses after use of the aid. The decision aid was acceptable to the majority of patients, and 95% indicated that they would recommend it to others. INTERPRETATION: The decision aid improved knowledge and risk perceptions of blood donation and transfusion, and it helped uncertain patients to make choices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".