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Record W3015360527 · doi:10.2106/jbjs.oa.19.00038

Individual Gait Features Are Associated with Clinical Improvement After Total Knee Arthroplasty

2020· article· en· W3015360527 on OpenAlexaffabout
Kathryn L. Young‐Shand, Michael Dunbar, Janie L. Astephen Wilson

Bibliographic record

VenueJBJS Open Access · 2020
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsMcMaster UniversityDalhousie University
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisDemographicsPhysical therapyGaitMann–Whitney U testArthroplastyTotal knee arthroplastyGait analysisPhysical medicine and rehabilitationRange of motionBiomechanicsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Over 20% of patients do not report clinically relevant pain relief or functional improvements after total knee arthroplasty (TKA). The aim of this study was to investigate the effect of demographics, pre-TKA knee-joint biomechanics, and postoperative changes in knee biomechanics on meaningful improvements in self-reported pain and function after TKA. METHODS: Forty-six patients underwent 3-dimensional gait analysis and completed the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire before and 1 year after TKA. Response to treatment in terms of pain relief and functional improvement ("pain and function responders") was defined as improvements in WOMAC scores that met minimal clinically important difference thresholds in the pain and function domains. Differences between responder and non-responder demographics, severity of the osteoarthritis as seen radiographically, and knee kinematics and kinetics before TKA were explored using the t test and Mann-Whitney U test. Correlations and regression models were used to examine demographics, baseline knee kinematics and kinetics, and post-TKA kinematic and kinetic improvements associated with being a pain responder and a function responder separately. Analyses were conducted using a hypothesis-driving approach. RESULTS: Of the 46 patients, 34 were pain responders and 36 were function responders. Preoperatively, both responder groups had a higher radiographic severity (Kellgren-Lawrence) grade (p = 0.03) and pain responders were more symptomatic according to their WOMAC score (p < 0.04). Less preoperative stance-phase flexion-extension angle range (p ≤ 0.03), lower preoperative stance-phase adduction (varus) angle magnitude (p = 0.01), and less postoperative reduction in the adduction angle magnitude (p ≤ 0.009) were independently associated with more self-reported improvement in pain and function. CONCLUSIONS: Patients with a higher radiographic severity grade, with specific frontal and sagittal knee kinematic patterns during gait before TKA, and who demonstrated less reduction in frontal plane angles during gait after TKA had greater self-reported pain and function score improvements after standard TKA. Gait analysis may aid preoperative identification of kinematic subgroups associated with self-reported improvements after TKA, and provide evidence that may inform triaging, surgical planning, and expectation management strategies. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.370
Teacher spread0.316 · 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

Citations24
Published2020
Admission routes2
Has abstractyes

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