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Record W4304944114 · doi:10.2196/36111

A Medical-Grade Polycaprolactone and Tricalcium Phosphate Scaffold System With Corticoperiosteal Tissue Transfer for the Reconstruction of Acquired Calvarial Defects in Adults: Protocol for a Single-Arm Feasibility Trial

2022· article· en· W4304944114 on OpenAlexvenueno aff
Isabel Gonzalez Matheus, Dietmar W. Hutmacher, Sarah Olson, Michael Redmond, Allison Sutherland, Michael Wagels

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research CouncilMetro South Health
KeywordsScaffoldBiomedical engineeringRegeneration (biology)SkullImplantCranioplastyMedicineMaterials scienceSurgeryBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Large skull defects present a reconstructive challenge. Conventional cranioplasty options include autologous bone grafts, vascularized bone, metals, synthetic ceramics, and polymers. Autologous options are affected by resorption and residual contour deformities. Synthetic materials may be customized via digital planning and 3D printing, but they all carry a risk of implant exposure, failure, and infection, which increases when the defect is large. These complications can be a threat to life. Without reconstruction, patients with cranial defects may experience headaches and stigmatization. The protection of the brain necessitates lifelong helmet use, which is also stigmatizing. OBJECTIVE: Our clinical trial will formally study a hybridized technique's capacity to reconstruct large calvarial defects. METHODS: A hybridized technique that draws on the benefits of autologous and synthetic materials has been developed by the research team. This involves wrapping a biodegradable, ultrastructured, 3D-printed scaffold made of medical-grade polycaprolactone and tricalcium phosphate in a vascularized, autotransplanted periosteum to exploit the capacity of vascularized periostea to regenerate bone. In vitro, the scaffold system supports cell attachment, migration, and proliferation with slow but sustained degradation to permit host tissue regeneration and the replacement of the scaffold. The in vivo compatibility of this scaffold system is robust-the base material has been used clinically as a resorbable suture material for decades. The importance of scaffold vascularization, which is inextricably linked to bone regeneration, is underappreciated. A variety of methods have been described to address this, including scaffold prelamination and axial vascularization via arteriovenous loops and autotransplanted flaps. However, none of these directly promote bone regeneration. RESULTS: We expect to have results before the end of 2023. As of December 2020, we have enrolled 3 participants for the study. CONCLUSIONS: The regenerative matching axial vascularization technique may be an alternative method of reconstruction for large calvarial defects. It involves performing a vascularized free tissue transfer and using a bioresorbable, 3D-printed scaffold to promote and support bone regeneration (termed the regenerative matching axial vascularization technique). This technique may be used to reconstruct skull bone defects that were previously thought to be unreconstructable, reduce the risk of implant-related complications, and achieve consistent outcomes in cranioplasty. This must now be tested in prospective clinical trials. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12620001171909; https://tinyurl.com/4rakccb3. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36111.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.006
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0220.005

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.

Opus teacher head0.157
GPT teacher head0.452
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreProtocol

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".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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