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Record W3187189475 · doi:10.2147/jpr.s312418

Long-Term Outcomes of Single versus Multiple Courses of Viscosupplementation for Osteoarthritic Knee Pain: Real-World, Multi-Practice Experience Over a Six-Year Period

2021· article· en· W3187189475 on OpenAlexaffabout
Janice Johnston, Karen E. Brown, Jeffrey M. Muir, Michael J. Sloniewsky

Bibliographic record

VenueJournal of Pain Research · 2021
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsBlackberry (Canada)
Fundersnot available
KeywordsViscosupplementationMedicineWOMACOsteoarthritisVisual analogue scalePhysical therapyRehabilitationKnee painCohortInternal medicineAlternative medicineIntra articular

Abstract

fetched live from OpenAlex

INTRODUCTION: Viscosupplementation (VS) is a safe and effective local treatment for osteoarthritis (OA) of the knee. While much research has been completed evaluating its efficacy, comparatively little research has been completed examining the effects of multiple, repeat courses of treatment versus a single course of treatment. METHODS: We retrospectively reviewed real-world data from a large cohort of patients receiving treatment for OA of the knee at 16 rehabilitation clinics. Patients were grouped based on whether they received a single course of treatment or multiple courses. Outcomes for this study included pain (measured via the visual analog scale, VAS) and functional ability (measured via the Western Ontario and McMaster Universities Arthritis Index (WOMAC)). Pain and function scores were collected at baseline (prior to treatment administration) and one week following each course of treatment. RESULTS: Patients receiving multiple courses of treatment saw greater improvements than those receiving a single course. For VAS, maximal improvement occurred after the fourth course (66% improvement: 1.7±1.2 vs 5.0±2.4 at baseline, p<0.0001). WOMAC scores saw maximal improvement up to the fourth course for all domains (pain: 74%: 2.5±3.3 vs 9.5±5.3, p<0.0001; stiffness: 61%: 1.3±1.0 vs 3.3±2.0, p<0.0001; function: 66%: 9.5±7.2 vs 28.3±14.1, p<0.0001). When scores from multiple courses were averaged, improvements were maintained through the fourth course for VAS (3.4±2.8) and all WOMAC domains (pain: 6.1±5.0; stiffness: 3.0±2.2; function: 23.4±17.3). DISCUSSION: Our results indicate that multiple courses of treatment are associated with greater improvements than a single course of VS, and that these improvements continue through four courses of treatment.

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)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.129
GPT teacher head0.450
Teacher spread0.321 · 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.

Study designBench or experimental
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
Published2021
Admission routes2
Has abstractyes

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