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Record W3145559190

Effects of 650 nm - 10.6 μm Combined Laser Acupuncture- Moxibustion on Knee Osteoarthritis: A Randomized,Double-blinded and Placebo-controlled Clinical Trial

2008· article· zh· W3145559190 on OpenAlexaboutno aff
沈雪勇, 丁光宏, Wu Fan, 王丽祯, 赵玲, W.-H. Yao L. Min, 劳力行

Bibliographic record

Venue针灸推拿医学:英文版 · 2008
Typearticle
Languagezh
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsDouble blindedOsteoarthritisMedicineMoxibustionAcupuncturePlaceboRandomized controlled trialPhysical therapyInternal medicineAlternative medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

目的:观察650nm-10.6μm复合激光治疗膝骨关节炎患者的有效性以及与红光照射相比,在减轻疼痛和改善关节功能方面是否具有更好疗效。方法:48名膝骨关节炎患者被随机分到两组(每组24人),分别接受650nm-10.6μm复合激光或红光照射犊鼻穴,每次治疗20min,第一疗程(共2星期)每星期治疗3次,第二疗程(共4星期)每星期治疗2次。主要结果采用McMaster大学关节炎量表(Western Ontario and McMaster Universities Osteoarthritis Index,WOMAC)进行打分。并对患者关于疗效的自评、治疗的副作用及盲法的有效性进行统计分析。结果:所有患者均完成了第一疗程,但有12名患者在第二疗程脱落。由于第二疗程的脱落率较高,故只对第一疗程的数据进行分析。治疗前,两组患者一般情况及WOMAC得分无显著性差异(P〉0.05)。治疗后,复合激光组及红光照射组患者WOMAC得分与基线期相比均有显著降低(P〈0.01)。两组患者WOMAC得分改善率比较无显著性差异(P〉0.05)。两组患者对疗效的自评及脱落率比较均无统计学差异(P〉0.05)。两组患者对自己所属分组的猜测无统计学差异(P〉0.05),且两组患者对自己所属分组的猜测未对其WOMAC得分改善率及对疗效的自评产生影响(P〉0.05).结论:复合激光和红光照射犊鼻穴对膝骨关节炎患者均有疗效,需扩大样本量,控制脱落率,以进一步观察两者的差异。

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.033
GPT teacher head0.333
Teacher spread0.300 · 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 designRandomized 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
Published2008
Admission routes1
Has abstractyes

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