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Record W2316732736 · doi:10.1177/1071100714531232

Total Ankle Arthroplasty Accuracy and Reproducibility Using Preoperative CT Scan-Derived, Patient-Specific Guides

2014· article· en· W2316732736 on OpenAlex
Gregory C. Berlet, Murray J. Penner, Sarah L. Lancianese, Paul Stemniski, Richard Obert

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFoot & Ankle International · 2014
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineCadaveric spasmTibiaImplantValgusCadaverComputer-assisted surgeryAnkleOrthodonticsReduction (mathematics)ArthroplastySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Preoperative navigation has provided many potential benefits for total knee arthroplasty, including patient-specific alignment, repeatable implant placement, and decreased operative time. For the first time, this technology was applied to total ankle arthroplasty (TAA). This study evaluated repeatability of tibia and talus patient-specific guide placement and deviation between the preoperative plan and actual implant placement. METHODS: Routine ankle CT scans were acquired of 15 cadaveric lower extremity limbs, converted into 3D solid models, and imported into a computer-assisted design assembly. Anatomic landmarks defining tibia/talus alignment were established and used to perform a virtual TAA. Commercially available implant components were placed to mimic traditional cases. An operative guide referencing the cadaver-specific anatomy was engineered to define the resection planes necessary to re-create virtual placement of traditional tibia and talus implants in the postoperative position. Board-certified TAA orthopaedic surgeons with no prior preoperative navigation experience placed the operative guides onto the bones based on tactile and visual feedback. Guide placement was repeated 4 times to determine variability. Final implant position was recorded with an infrared probe, confirmed with CT scans, and compared to the preoperative plan. Average deviations between planned and actual guide placement were determined for all rotational and translational degrees of freedom (DOF). In addition, implant component location was measured radiographically. RESULTS: Intraobserver tibia and talus guide variation between all trials was 0.26 ± 0.18 degrees and 0.36 ± 0.25 degrees in flexion/extension, 0.61 ± 0.58 and 0.53 ± 0.53 in varus/valgus, and 0.79 ± 0.38 degrees and 1.15 ± 0.77 degrees in internal/external rotation, respectively. Average variation between preoperative and postoperative implant placement was less than 2 degrees and 1.4 mm in all specimens tested. CONCLUSION: Preliminary data suggest that preoperative navigation and custom operative guides result in reliable and reproducible placement of TAA implants and patient-specific ankle alignment. Deviation of final implant placement from the preoperative plan was less than 2 degrees in all angular DOF, providing greater accuracy than the ±3 degrees determined in other implant system studies using traditional instrumentation and computer navigation. CLINICAL RELEVANCE: We have further demonstrated that final implant position is successfully guided by these patient-specific guides, with reproducibility of tibial component placement falling within 2 degrees of the intended target. This level of reproducibility suggests a promise for this technology, and it is hoped this level of accuracy will become the benchmark for the next generation of total ankle arthroplasty.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.289
Teacher spread0.263 · 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