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Record W4407780707 · doi:10.1002/ksa.12623

Symptoms predict total knee arthroplasty more than osteoarthritis severity: A multivariable analysis of more than 7500 knees

2025· article· en· W4407780707 on OpenAlexaboutno aff
Luca Bianco Prevot, Alessandro Bensa, Giuseppe M. Peretti, Giuseppe Filardo

Bibliographic record

VenueKnee Surgery Sports Traumatology Arthroscopy · 2025
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisWOMACHazard ratioVisual analogue scaleArthroplastyPopulationProportional hazards modelOrthopedic surgeryTotal knee arthroplastyPhysical therapyConfidence intervalSurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: Multiple clinical factors may concur to determine the clinical trajectory leading towards total knee arthroplasty (TKA) in patients affected by knee osteoarthritis (OA). The aim of this study was to identify the main factors influencing progression to TKA in a large population of knee OA patients. METHODS: A total of 7552 knees were selected from the Osteoarthritis Initiative (OAI) multicentre database. The data collected included demographic data, Kellgren-Lawrence (KL) grade, the presence of knee swelling, the frequency of swelling, visual analogue scale (VAS) for pain, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Knee Injury and Osteoarthritis Outcome Score (KOOS) and the number of knees requiring TKA. The baseline data were collected as reported by the OAI database, and patients were followed up at 12, 24, 36, 48, 60, 72, 84 and 96 months, documenting whether they underwent TKA during this period. RESULTS: A multivariable analysis was performed to identify factors independently influencing progression to TKA. At 96 months, 7.1% of knees underwent TKA. The progression to TKA correlated with age (p < 0.001), KL grade (p < 0.001), swelling frequency (p < 0.001), knee swelling (p < 0.001), VAS (p = 0.003) and KOOS (p < 0.001). Knees with KL Grades 3 and 4 had the same risk of undergoing this procedure, while the need for TKA was able to be predicted based on WOMAC pain (p = 0.035, hazard ratio [HR] = 0.864), VAS (p = 0.008, HR = 1.131) and KOOS (p = 0.02, HR = 0.966). CONCLUSIONS: This study revealed that several factors influenced progression to TKA, including age, KL grade, knee swelling, VAS pain and KOOS. However, there was no statistically significant difference between KL 3 and KL 4 in predicting the disease trajectory, and patients' clinical symptoms, as quantified by WOMAC pain subscale, VAS and KOOS, had a greater influence on progression to TKA than knee KL OA severity. LEVEL OF EVIDENCE: Level IIb.

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)0.003
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.008
GPT teacher head0.257
Teacher spread0.249 · 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

Citations6
Published2025
Admission routes1
Has abstractyes

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