Validation of a Formaldehyde‐Free Embalming Method for Preparing High Fidelity Cadavers for Teaching Surgical and Procedural Skills
Bibliographic record
Abstract
Cadavers embalmed using traditional formaldehyde‐based solutions are considered low‐fidelity in terms of representing the flexibility and texture of patients. Further, many current ‘soft’ embalming solutions are expensive, involve complicated procedures, and/or result in short‐term preservation periods. The objective of this study was to develop a low‐cost, formaldehyde‐free embalming solution that would produce high fidelity cadaveric models for teaching procedural or surgical skills in postgraduate medical education. The novel embalming formula was based on replacing formaldehyde with saturating levels of sodium chloride (357 grams/L) in combination with other conventionally used, low cost chemicals. Formaldehyde‐free cadavers (FFC) were compared with cadavers embalmed using a traditional formaldehyde‐based formula in terms of microbiological profiles, and in terms of feedback from residents and faculty who participated in cadaveric‐based workshops. Swabs from oral, nasal, and rectal cavities over a 100 day time course in formaldehyde‐free donors demonstrated a nearly complete reduction of microbes that was generally comparable to that observed in formaldehyde‐preserved cadavers. In terms of feedback, qualitative commentary was obtained from separate workshops for anesthesiologists, orthopaedic surgeons, plastics surgeons, ophthalmologists and neurosurgeons over a two year period (2016–2018). Across these different groups, clinicians generally perceived that FFC donors featured enhanced fidelity in terms of flexibility and texture, and produced more realistic and higher quality ultrasound images, relative to formaldehyde‐preserved donors. In particular, anaesthesiologists noted the potential utility of FFC specimens for practicing needle insertion techniques, while neurosurgeons and ophthalmologists had strong positive feedback regarding the texture and quality of brain specimens and eye musculature, respectively. FFC tissue remained viable at least two years post‐embalming for use in postgraduate workshops. In conclusion, the FFC model has the potential to generate low‐cost, high‐fidelity anatomical resources, with long‐term viability, for the purposes of surgical and procedural skills training. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".