A survey of healthcare professionals and oncology patients at the McGill University Health Centre reveals enthusiasm towards establishing a post-mortem rapid tissue donation program.
Bibliographic record
Abstract
e23005 Background: In the early developmental phase of a post-mortem Rapid Tissue Donation (RTD) program for metastatic cancer patients, we surveyed health care professionals (HCPs) and oncology patients at the McGill University Health Centre (MUHC) to assess their knowledge and attitudes pertaining to RTD from metastatic cancer patients for research purposes. Methods: A 23-item survey was developed and distributed to HCPs at tumour board meetings, and a related 26-item survey was developed and distributed to oncology patients at the MUHC Cedars Cancer Centre. Results: 73 HCPs, including 37 attending physicians, and 102 oncology patients participated in the study. Despite the fact that 88% of HCPs rated their knowledge of RTD as none or limited, 42% indicated that they would feel comfortable discussing RTD with their cancer patients. 67% of HCPs indicated that their current knowledge of RTD would impact their decision to discuss such a program with patients, implying the importance of educating HCPs to facilitate enrolment of patients into an RTD program. 78% of patients indicated that they would not be uncomfortable if their doctor discussed RTD with them, and 61% indicated that they would like for their doctor to discuss RTD with them. HCPs and patients felt that the best time for patients to be approached about consenting to an RTD program is in the transition to palliative care when there are no treatment options remaining. Conclusions: HCPs and patients at the MUHC are generally enthusiastic about adopting an RTD program for metastatic cancer patients. Education of HCPs and patients will be an important determinant of the program’s success.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".