Feasibility of blinding in a randomized controlled trial comparing preoperative autologous blood donation and acute normovolemic hemodilution in adult cardiac surgery
Bibliographic record
Abstract
BACKGROUND: Acute normovolemic hemodilution and preoperative autologous donation have been shown to be effective techniques for decreasing the exposure of patients to allogeneic blood during cardiac surgery. They have not, however, been compared to each other, because of perceived difficulties in blinding in such a clinical study. The feasibility of blinding was tested in a pilot trial. STUDY DESIGN AND METHODS: Ten patients were randomly assigned to undergo preoperative autologous blood donation or acute normovolemic hemodilution during cardiac surgery. Patients were blinded during this process by shielding of the arm and by insertion of an intravenous line in each patient. Every attempt was made to blind the clinical staff during and after surgery. The effectiveness of this blinding was determined by using a questionnaire. RESULTS: In the 10 cases, six patients, four surgeons, and one anesthetist answered, "I do not know," with respect to whether preoperative autologous blood donation had occurred. The remaining people interviewed believed the blinding was unsuccessful. However, correct answers were given by 75 percent of the patients (95% CI, 19-99%), 83 percent of the surgeons (95% CI, 36-99.6%), and 66 percent of the anesthetists (95% CI, 29.9-92.5%). The frequency of correct answers did not differ significantly from the 50 percent expected by chance, but the CIs are wide. CONCLUSIONS: Blinding of patients and all members of the surgical team during both the preoperative donation process and acute normovolemic hemodilution in the operating theater was successful most of the time, as the frequency of correct answers did not differ significantly from the 50 percent expected by chance. However, more accurate estimates of the success of blinding require a study with a larger sample. It is possible that, with a larger series, the physician's ability to determine patient assignment would be significantly better than that by chance alone.
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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 | 0.074 | 0.132 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".