Role of 3D Printing in Post-op Rehabilitation of Palatal Bone Loss by Mucormycosis: A Survey
Bibliographic record
Abstract
BACKGROUND: Three dimensions (3D) modeling, printing, and manufacturing can help in personalized and customized surgical reconstruction of complex defects in the craniofacial region with precision by manipulating tissues based on the preoperative assessment, planning the shape of metal and alloplastic materials, and reduction in the total cost and time of the surgery. AIM: The present survey study aimed to assess the approach of treating surgeons towards the role of 3D printing in post-op rehabilitation of palatal bone loss by mucormycosis. METHODS: One thousand eyes nose and throat (ENT) and maxillofacial surgeons were given a pre-formed structured survey questionnaire to be filled by subjects themselves for their view on the role of 3D printing for rehabilitation and reconstruction of palatal bone loss due to mucormycosis. RESULTS: Efficacy of 3D printing to print the pneumatic sinus design and palatal contour helping to design accurate support with a lightweight prosthesis, 67.2% (n=672) subjects whereas, exact duplication of the excised tissue, 85.4% (n=854) subjects, to detect and duplicate undercuts, 58.4% (n=584) subjects, 3D printing can be helpful as the proper extension of impression 73.2% (n=732) subjects responded positively. For reconstruction of a lost palate by prosthesis 91.2% (n=912) of study participants, in making obturators using Titanium framework and Polyetheretherketone (PEEK) was given a positive response by 82.2% (n=822) subjects, to fabricate prosthesis obturator required in palatal perforation in case of mucormycosis was given a positive response by 88.1% (n=881) subjects, the role of 3D printing to overlay zygomatic implant prosthesis was responded positively by 68.9% (n=689) study subjects. CONCLUSION: The present survey study concludes that 3D printing is a reliable and accurate method for palatal reconstruction following bone destruction by mucormycosis as reported by the majority of ENT and maxillofacial surgeons.
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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 | 0.000 | 0.000 |
| 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".