Quantitative and Qualitative Comparison of Thiel and Phenol‐Based Soft‐Embalmed skin for Surgical Training
Bibliographic record
Abstract
BACKGROUND Surgical training requires high‐fidelity models to in vivo. Embalmed cadaveric material has long been used as the standard. However, conventional formalin embalming is known to affect the quality of the tissue, compromising the tissue quality for optimal realistic surgical training. The aim of our study was to qualitatively compare Thiel and phenol‐based soft‐embalming techniques in a surgical training setup and to quantitatively compare the mechanical properties of embalmed skin to fresh tissue state. METHODS Twenty‐eight participants (4 experienced ENT and 6 residents; 8 Orthopaedic residents; 4 experienced OTL; 5 experienced Trauma and 1 resident) were involved in surgical workshops comparing Thiel and phenol‐based embalmed bodies. Participants were asked to evaluate pre‐defined aspects pertaining to their appreciation of the skin quality as the usability for skin dissection and suturing. In parallel, mechanical testing of skin flaps was conducted. Skin flaps were harvested from 6 fresh‐frozen thawed cadaveric upper limbs. Skin flaps from each specimen were divided in 3 equal in size sections; one subsection was refrozen, one was Thiel embalmed and the other one was phenol‐based embalmed. The three tissue states were compared together for each specimen, one month of embalming (n=3) or one year after embalming (n=3). Specimens were preloaded and pre‐conditioned before displacement‐controlled cycles were applied using an axial tensile testing machine (MTS, Eden Prairie, MN, USA). The tensile elasticity (Young's modulus) was calculated between loading and unloading state. Statistical analysis was performed using a two‐ way mixed ANOVA with a Holm‐Sidak correction for multiple comparisons. RESULTS Qualitatively, 18% of participants rated Thiel as more realistic and preferred this model for skin dissection and suturing; 64% preferred Phenol‐based soft‐embalmed; and 18% rated that both embalming states were comparable. Quantitatively, there were significant differences between the embalming techniques (p < 0.05), but no significant difference were made between embalming time (p = 0.47). Thiel embalmed skin had a significantly lower Young's modulus values compared to fresh state (p < 0.0001). There were no significant differences between phenol‐based embalmed skin and fresh state (p = 0.30). CONCLUSION Although there was variability in the relationship between tissue states, fresh and phenol‐based embalmed state were not consistently stiffer than the other, but both were stiffer than the Thiel embalmed samples; Thiel solution caused the samples to be less stiff than the fresh state. Based on our results, phenol‐based soft‐ embalming preserves the integrity of the skin tensile elasticity better, which could explain the better rating of this embalming technique for the practice of surgical exposures, simulated reconstructions and wound closure. Moreover, phenol‐based embalmed specimens can be prepared for a third of the cost and with none of the elaborate setup required for Thiel embalming. This abstract is from the Experimental Biology 2018 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 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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".