Embalming Procedures and Laboratory Practices for Cadaver‐Based Learning
Bibliographic record
Abstract
Introduction The use of embalming chemicals, techniques, and laboratory practices for educational purposes is not well documented in Canada. While there is a preference for the use of hard‐fixation techniques, soft‐preservation techniques and unembalmed tissue for undergraduate learning, clinical training and research, the choice of tissue state in Canadian institutions remains unknown. Little has been reported on the effects of the introduction of clinical training programs on the choice of tissue state and on the effects that these choices have on human body donation programs. It is hypothesized that embalming procedures and laboratory practices will be highly variable across Canadian institutions, that a higher percentage of donors will be allocated to non‐hard‐fixation methods in institutions with a clinical training program, and that this shift in practices will require an increase in the number of donors needed from human body donation programs. This study aims to assess the use of embalming techniques and laboratory practices for education in Canada and to assess the impact of the integration of clinical training on human body donation programs. Methods An online questionnaire was distributed to 25 institutions in Canada that list an anatomy laboratory on their department website. A descriptive analysis was completed. Results A total of 23 embalming solutions were identified, and laboratory practices like sanitization, mold management, and health and safety measures were highly variable. This study confirmed that in Canadian institutions hard‐fixed donors are preferred for teaching, prosection and dissection, while soft‐preserved donors are preferred for clinical training, and unembalmed donors are preferred for research. Institutions with a clinical training program allocate a higher percentage of their donors to non‐hard‐fixed methods and require a higher number of donors from human body donation programs. Conclusion This study confirms that the embalming procedures and laboratory practices used for cadaver‐based learning in Canadian institutions are highly variable. Furthermore, the introduction of a clinical training program leads to an increased need for soft‐preserved and unembalmed donors. This shift in practices requires a higher number of donors from human body donation programs. Implication This study identifies 23 embalming solutions that can be tested for their efficacy and use in cadaver‐based learning to establish a best practice in embalming. Furthermore, this study sheds a light on the need to investigate the direct effects of clinical training sessions on human body donation programs and provides a perspective on the implementation of creative approaches to maximize the use of each donor received. This study opens a door to collaboration amongst the community of anatomists to establish the best embalming and safety practices to satisfy the need for donors in cadaver‐based learning, while minimizing the strain on human body donation programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".