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Record W2014013247 · doi:10.3113/fai.2011.1155

Validation and Precision of Model-Based Radiostereometric Analysis (MBRSA) for Total Ankle Arthroplasty

2011· article· en· W2014013247 on OpenAlexaff
Jason Fong, Andrea Veljkovic, Michael Dunbar, David Wilson, Allan Hennigar, Mark Glazebrook

Bibliographic record

VenueFoot & Ankle International · 2011
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineProsthesisTibiaProtocol (science)ImplantBiomedical engineeringOrthodonticsNuclear medicineSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The goal of this study was to design a RSA marker insertion protocol to evaluate the stability of the bone-implant interface of a TAA prosthesis, and to validate that this marker insertion protocol can be combined with MBRSA technology to provide clinically adequate precision in assessing the micromotion of the TAA prosthesis. METHODS: The Mobility™ Total Ankle System was used in this study. A marker placement protocol was developed with a Phantom Protocol. The Improved Marker Placement Protocol was used in 20 patients. Postoperative RSA double exams were taken. Condition Numbers (CN) were used to assess the marker distribution. The system precision was defined as the standard deviation of the double exams (MTE, MRE). MBRSA software was used to evaluate the double exams. RESULTS: The RSA marker insertion technique for the 20 {\it in vivo} cases provided satisfactory results. CNs in all subjects but one were below 50 mm(-1) and implied a desirable marker configuration. The tibial sphere MTE was 0.07 mm and the talar was 0.09 mm. The talar MRE was 0.51 degrees. CONCLUSION: The system precision for these {\it in vivo} TAA implants was within the normal range identified by RSA studies, and comparable to the existing TAA RSA studies. This study demonstrated a reliable RSA marker insertion technique in both the tibia and talus. The study confirms that the insertion and MBRSA technique allows the typical high precision demonstrated in other RSA studies (standard deviation less than or equal to 0.25 mm or 0.6 degrees). CLINICAL RELEVANCE: This method may allow more accurate assessment of prosthetic subsidence clinically.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.507
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.291
Teacher spread0.243 · 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 teacher head, 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

Citations19
Published2011
Admission routes1
Has abstractyes

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