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Record W3110481602 · doi:10.3390/app10238605

Manual Therapy Versus Closed Kinematic Exercises—The Influence on the Range of Movement in Patients with Knee Osteoarthritis: A Pilot Study

2020· article· en· W3110481602 on OpenAlexaboutno aff
Krystyna Hejdysz, Jagoda Goślińska, Agnieszka Wareńczak, Joanna Dudzińska, Ewa Adamczyk, Paweł Sip, Jarosław Gośliński, Piotr Owczarek, Adam Woźniak, Przemysław Lisiński

Bibliographic record

VenueApplied Sciences · 2020
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACOsteoarthritisRange of motionPhysical therapyMedicinePhysical medicine and rehabilitationVisual analogue scaleRehabilitationKinematicsKnee JointSurgery

Abstract

fetched live from OpenAlex

Reduced range of motion is one of the main symptoms of knee osteoarthritis. These deficits are believed to have a negative impact on activities of daily living. The aim of the study was to examine how manual therapy and closed-chain kinematic exercises affect the range of motion in patients with knee osteoarthritis. Sixty-six patients with knee osteoarthritis were recruited and divided into three groups: manual therapy group, exercise group, and control group. The following parameters were evaluated before and after 10 days of rehabilitation: the range of motion in the open and closed kinematic chain using Orthyo sensors, pain intensity using Visual Analogue Scale (VAS), and the subjective functional assessment in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). The results indicate an increase in the range of motion after manual therapy in the open chain test and an increase in the possible range of motion in the closed chain test in the exercise group. Both study groups showed significant improvement of WOMAC-assessed function and a significant decrease of VAS-assessed pain following rehabilitation. Manual therapy and exercise affect the range of motion in patients with knee osteoarthritis. When examining the range of motion, it is worth taking into account various biomechanical conditions.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.292
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.031
GPT teacher head0.257
Teacher spread0.226 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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