MétaCan
Menu
Back to cohort
Record W2736464944 · doi:10.1186/s13013-017-0128-9

3D correction of AIS in braces designed using CAD/CAM and FEM: a randomized controlled trial

2017· article· en· W2736464944 on OpenAlexafffund
Nikita Cobetto, Carl‐Éric Aubin, Stefan Parent, Soraya Barchi, Isabelle Turgeon, Hubert Labelle

Bibliographic record

VenueScoliosis and Spinal Disorders · 2017
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMedicineRandomized controlled trialCADOrthopedic surgeryFinite element methodMedical physicsOrthodonticsInternal medicineSurgeryEngineeringStructural engineeringEngineering drawing

Abstract

fetched live from OpenAlex

BACKGROUND: Recent studies showed that finite element model (FEM) combined to CAD/CAM improves the design of braces for the conservative treatment of adolescent idiopathic scoliosis (AIS), using 2D measurements from in-brace radiographs. We aim to assess the immediate effectiveness on curve correction in all three planes of braces designed using CAD/CAM and numerical simulation compared to braces designed with CAD/CAM only. METHODS: SRS standardized criteria for bracing were followed to recruit 48 AIS patients who were randomized into two groups. For both groups, 3D reconstructions of the spine and patient's torso, respectively built from bi-planar radiographs and surface topography, were obtained and braces were designed using the CAD/CAM approach. For the test group, 3D reconstructions of the spine and patient's torso were additionally used to generate a personalized FEM to simulate and iteratively improve the brace design with the objective of curve correction maximization in three planes and brace material minimization. RESULTS: For the control group (CtrlBraces), average Cobb angle prior to bracing was 29° (thoracic, T) and 25° (lumbar, L) with the planes of maximal curvature (PMC) respectively oriented at 63° and 57° on average with respect to the sagittal plane. Average apical axial rotation prior to bracing was 7° (T) and 9° (L). For the test group (FEMBraces), initial Cobb angles were 33° (T) and 28° (L) with the PMC at 68° (T) and 56° (L) and average apical axial rotation prior to bracing at 9° (T and L). On average, FEMBraces were 50% thinner and had 20% less covering surface than CtrlBraces while reducing T and L curves by 47 and 48%, respectively, compared to 25 and 26% for CtrlBraces. FEMBraces corrected apical axial rotation by 46% compared to 30% for CtrlBraces. CONCLUSION: The combination of numerical simulation and CAD/CAM approach allowed designing more efficient braces in all three planes, with the advantages of being lighter than standard CAD/CAM braces. Bracing in AIS may be improved in 3D by the use of this simulation platform. This study is ongoing to recruit more cases and to analyze the long-term effect of bracing. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02285621.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.026
GPT teacher head0.330
Teacher spread0.304 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations55
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueScoliosis and Spinal DisordersSame topicScoliosis diagnosis and treatmentFrench-language works237,207