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Record W4317470475 · doi:10.1055/s-0042-1759790

Clinical Outcomes after Computed Tomography-Based Total Knee Arthroplasty: A Minimum 3-Year Analyses

2023· article· en· W4317470475 on OpenAlexaboutno aff
Robert Marchand, Laura Scholl, Kelly Taylor, Daniel J. Erwin, Manoshi Bhowmik-Stoker, Zhongming Chen, Hytham S. Salem, Michael A. Mont

Bibliographic record

VenueThe Journal of Knee Surgery · 2023
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACCohortOsteoarthritisRadiographySurvivorship curveCohort studyTotal knee arthroplastyComputed tomographyRange of motionArthroplastyNuclear medicinePhysical therapySurgeryRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Computed tomography (CT) scan–based three-dimensional (3D) modeling operative technology has been shown to improve upon results of manual total knee arthroplasties (TKAs). Although there are many reports on superior precision of this CT-based technology, there has been continuing interest regarding extended clinical outcomes. The purpose of this study was to compare their clinical outcomes with manual TKAs at approximately 3-year follow-up. Specifically, we analyzed: (1) survivorship, (2) functional outcomes, (3) complications, and (4) radiographic outcomes (i.e., alignment, progressive radiolucencies). A total of 210 patients receiving CT-based TKAs performed by a single surgeon at a single center between July 1, 2016, and February 16, 2018, were compared with 210 manual TKAs completed by the same surgeon immediately preceding implementation of the CT-based technology. Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) surveys were collected at ∼3 years postoperatively. Subgroup analyses of pain and physical function scores were performed. Follow-up radiographs were evaluated for alignment, loosening, and/or progressive radiolucencies. There was 100% survivorship at final follow-up. The postoperative mean pain scores for the CT-based cohort and manual cohort were 1 ± 2 (range, 0–14) and 2 ± 3 (range, 0–17), respectively (p < 0.05). The postoperative mean physical function scores for the CT-based cohort and manual cohort were 3 ± 4 (range, 0–18) and 5 ± 5 (range, 0–19), respectively (p < 0.05). The postoperative mean total WOMAC scores for the CT-based cohort and manual cohort were 5 ± 4 (range, 0–32) and 7 ± 8 (range, 0–35), respectively (p < 0.05). There were low numbers of postoperative complications at final follow-up in either cohort. None exhibited progressive radiolucencies by final follow-up. The 3-year postoperative clinical outcomes support excellent survivorship and radiographic outcomes, low complication rates, as well as improved pain, physical function, and total WOMAC scores for CT-based TKAs. Therefore, patients who undergo CT-based 3D modeling TKAs should expect to have superior long-term clinical outcomes.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.338
Teacher spread0.288 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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