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Effects of intra-articular hylan G-F 20 injections on clinical and biomechanical characteristics of the knee in osteoarthritis

2005· article· en· W1980114389 on OpenAlexaboutno aff
G. Yavuzer, Birkan Sonel, Nurben S ld r

Bibliographic record

VenueInternational Journal of Rehabilitation Research · 2005
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisMedicineArticular cartilagePhysical therapyPhysical medicine and rehabilitationKnee JointSurgeryAlternative medicinePathology

Abstract

fetched live from OpenAlex

The objectives of this study were to investigate the effects of Hylan G-F 20 (Synvisc; Genzyme Biosurgery, Ridgefield, New Jersey, USA) injections on clinical and biomechanical gait characteristics of patients with knee osteoarthritis. The design was a before-after trial, set in the gait laboratory of the rehabilitation unit of a university hospital. Twelve patients participated with an average age (+/-SD) of 63.2+/-4.4 years, and Kellgren and Lawrence grade II or III knee osteoarthritis. The main outcome measures were the Western Ontario McMaster Universities Osteoarthritis Index, and time-distance, kinematic and kinetic parameters of gait. The intervention used was a single course of three bilateral intra-articular injections of 2 ml Hylan G-F 20. One week after the treatment, the pain subscore and total score of WOMAC decreased from 9.2+/-2.7 to 4.8+/-3.1 and from 42.1+/-15.2 to 37.9+/-13.5, respectively. There was improvement in sagittal plane excursions of the knee (from 40.2+/-8.1 to 43.3+/-8.5), in extensor and adductor moments (from 0.26+/-0.2 to 0.14+/-0.1 and from 0.45+/-0.1 to 0.41+/-0.1, respectively), and in scaled vertical forces (from 85.8+/-4.5 to 88.4+/-5.4). All these differences were statistically significant. In conclusion, intra-articular Hylan G-F 20 injections not only decrease pain in patients with knee osteoarthritis, but can alter the natural history of the disease by decreasing excessive loads in the knees.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0000.000

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 head0.024
GPT teacher head0.385
Teacher spread0.361 · 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

Citations18
Published2005
Admission routes1
Has abstractyes

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