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Record W2414157279

[Treatment of Knee Osteoarthritis by Tendons of Minimally Invasive Therapy Combined Drug Ther- apy: a Clinical Observation of Sixty Cases].

2015· article· en· W2414157279 on OpenAlexaboutno aff
Chun-fu Hou, Wei Song, Zhi-huang Chen, Xiao-hao Li, Shuting Wang, Jing Guo

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisVisual analogue scaleCelecoxibCapsuleSurgeryJoint stiffnessInternal medicineStiffness
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the efficacy of tendons of minimally invasive therapy (TMIT) combined drug therapy by comparing it with treatment by drug therapy alone on patients with knee osteoarthritis (KOA). METHODS: Totally 60 KOA patients were assigned to the treatment group and the control group according to random digit table, 30 in each group. Patients in the control group took Hydrochloric Acid Glucosamine Capsule and Celecoxib Capsule. Patients in the treatment group additionally received TMIT. The treatment course for all was 4 weeks. Scores for visual analogue scale (VAS) and the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index were observed and recorded at week 1 and 4 after treatment by acupotomology mirror. RESULTS: Compared with before treatment, improvement was shown in VAS score, pain and stiffness degrees, activities and functions, and WOMAC scores at week 1 and 4 after treatment in all patients with statistical difference (P < 0.05). Besides, better effect was shown in the treatment group (P < 0.05). CONCLUSIONS: TMIT combined drug therapy could relieve KOA patients' pain, stiffness and joint activities, elevate the overall efficacy. TMIT was easily operated with less injury.

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 score0.474
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.083
GPT teacher head0.300
Teacher spread0.217 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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