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Record W2566589478

COMPUTER-ASSISTED DISTRACTION OSTEOGENESIS USING THE TAYLOR FRAME: INITIAL CLINICAL EXPERIENCES

2008· article· en· W2566589478 on OpenAlexaboutno aff
Amber L. Simpson, Benard Ma, B. Slagel, Dan Borschneck, R.E. Ellis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDeformityDistraction osteogenesisOrthodonticsTibiaRadiographyFrame (networking)SurgeryDistractionComputer science
DOInot available

Abstract

fetched live from OpenAlex

Our research group has recent clinical experience with our novel computer-assisted method of bone deformity correction using the Taylor spatial frame (Smith & Nephew, Memphis, TN). Practitioners of the Taylor spatial frame admit that there is a steep learning curve in using the frame. This is in large part due to the difficulty in accurately measuring 13 frame parameters and mounting the frame to the patient without inducing residual rotational and translational errors. Our technique aims to reduce complications due to these factors by preoperatively planning the desired correction and calculating the correction based on the actual three-dimensional location of the frame with respect to the anatomy, rather than from traditional radiographs. The surgeon has greater flexibility in choosing the position of the rings since this technique does not depend on placing the rings in a particular configuration. Four clinical procedures have been performed at Kingston General Hospital (Kingston, ON, Canada) to date. The first patient presented with a proximal tibial growth-plate arrest that was secondary to a fracture. The result was a recurvatum deformity secondary to an eccentric growth arrest anteriorly. This deformity caused a stretch of the posterior capsule and posterior cruciate ligament that produced an unstable knee. The achieved correction, measured radiographically, was from an initial; − 14 degrees to a final +7 degrees of posterior slope. The second patient presented with a proximal tibial soft tissue imbalance that was thought would eventually lead to a recurvatum deformity. An increase in the posterior slope of the tibia was induced to compensate for the soft tissue deformity. The radiographic correction was an increase in posterior slope from +7 degrees to +14 degrees and from 5 degrees varus to 8 degrees varus. The third patient patient presented with a partially-healed malunited tibial fracture with 14 degrees of proximal tibial varus and 16 degrees of posterior slope. In spite of an uncomplicated frame application, the patient was not compliant with post-operative care and the frame was removed before correction could be achieved. The fourth patient underwent a limb lengthening. At the time of writing, the adjustment schedule had not been completed. Our computer-assisted procedure appears to be an effective method of improving Taylor spatial frame use. The senior surgeon (DPB) noted that the procedure is easy to perform, he no longer needs to measure the 13 frame parameters, and he can plan the correction in three dimensions. We also have the ability to modify the pace of the correction schedule to accommodate the rate of bone growth for each individual patient. Drawbacks of the technique include the requirements for a preoperative CT scan and a segmentation of the scan to produce the three-dimensional computer models.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.130
GPT teacher head0.406
Teacher spread0.277 · 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 designObservational
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

Citations1
Published2008
Admission routes1
Has abstractyes

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