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Record W4390864623 · doi:10.3724/sp.j.1329.2023.06009

Therapeutic Effect of Yijinjing Rehabilitation Training Combined with Interference Current Therapy on Patients with Knee Osteoarthritis

2023· article· en· W4390864623 on OpenAlexaboutno aff
Ming Xu, Ya Li, Shuang QIN, Xiaoye Lu, Kun Ai, Hong Zhang

Bibliographic record

VenueRehabilitation Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicMedical Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisRehabilitationMedicinePhysical therapyPhysical medicine and rehabilitationAlternative medicinePathology

Abstract

fetched live from OpenAlex

Objective To observe the effect of Yijinjing rehabilitation training combined with interference current therapy (ICT) on motor function and balance function of patients with knee osteoarthritis (KOA). Methods A total of 68 patients with KOA in the Rehabilitation Medicine Department of Changsha Central Hospital from April 2022 to January 2023 were randomly divided into control group and observation group, with 34 cases in each group. During the intervention, two cases discontinued the trial or dropped out respectively in the control group and observation group, and a total of 64 cases were finally included, 32 cases in each group. Both groups received routine rehabilitation treatment. The control group received ICT on treatment additionally, with the carrier frequency of 4 000 Hz and the beat frequency of 90-100 Hz based on the tolerance of patients, once a day, 20 minutes a time, six times a week, lasting for four weeks. The observation group received additional Yijinjing rehabilitation training on the basis of the control group to ensure that the patients could complete 50% or more rehabilitation training, without pain or with slight pain, once a day, 20 minutes a time, six times a week, lasting for four weeks. Before and after treatment, visual analogue score (VAS) was used to evaluate the severity of pain; universal goniometer was used to measure the active range of motion (AROM); timed "up and go" test (TUGT) was used to evaluate the functional walking ability; Western Ontario and McMaster University Arthritis Index (WOMAC) score was used to evaluate knee function; and Berg balance scale (BBS) and balance function test system were used to evaluate balance function (left and right swing index, center of gravity track length, track rectangular area, track peripheral area, and track length per unit area with eyes open or closed). Results Compared with that before treatment, TUGT, pain, stiffness and physical function scores and total score of WOMAC, left and right swing index, center of gravity track length, track rectangular area and track peripheral area with eyes open or closed in both groups after treatment decreased significantly, the proportion of low VAS score (0-2 points), the maximum AROM, the BBS score and track length per unit area with eyes open or closed increased significantly, and the differences were statistically significant (P<0.05). Compared with the control group, TUGT, pain, stiffness and physical function scores and total score of WOMAC, left and right swing index, center of gravity track length, track rectangular area and track peripheral area with eyes open or closed in the observation group after treatment decreased significantly, the proportion of low VAS score (0-2 points), the maximum AROM, the BBS score and track length per unit area with eyes open or closed increased significantly, and the diffe-rences were statistically significant (P<0.05). Conclusion Yijinjing rehabilitation training combined with ICT can improve pain, motor function and balance function of patients with KOA, which is recommended for clinical application.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.026
GPT teacher head0.337
Teacher spread0.311 · 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 designNon-randomized trial
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

Citations0
Published2023
Admission routes1
Has abstractyes

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