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Record W4360807636 · doi:10.1097/md.0000000000033339

A comparative study of the efficacy of intra-articular injection of different drugs in the treatment of mild to moderate knee osteoarthritis: A network meta-analysis

2023· article· en· W4360807636 on OpenAlexaboutno aff
Yuan Xue, Xuan Wang, Xiuming Wang, Li Huang, Aina Yao, Yan Xue

Bibliographic record

VenueMedicine · 2023
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisCochrane LibraryMeta-analysisRandomized controlled trialPhysical therapyConfidence intervalMEDLINEVisual analogue scaleAdverse effectInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Knee osteoarthritis (KOA) has a high clinical prevalence and frequently interferes with patients normal lives. In KOA patients, evidence suggests that intra-articular (IA) injection improves joint function and decreases discomfort. Several IA injection treatments are used in daily practice to improve symptomatic control of knee osteoarthritis, but their efficacy is frequently disputed. METHODS: This network meta-analysis compares the efficacy of different IA injections for mild to moderate knee osteoarthritis. Seven databases (PubMed, EMBASE, Web of Science, Cochrane Library, China Biology Medicine disc, WanFang, and China National Knowledge Infrastructure) were searched for randomized controlled trials published up to and including December 20, 2021, and final follow up indicators were used. Visual analogue scale (VAS) score and The Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index (WOMAC) score change from baseline were the primary outcomes. We used the Cochrane risk of bias tool to assess the quality and risks of biases of papers. We calculated the weighted mean difference (WMD) and 95% confidence interval (CI) for each outcome. State (Version 15.1, Texas, USA) and SPSS (Version 20, Chicago, USA) was used in all statistical analyses, and Review Manager (version 5.4) was used in assessing the risks of biases. RESULTS: Our study included 16 randomized controlled trials with a total of 1652 patients. platelet-rich plasma (PRP) IA injection therapy had the highest likelihood of being the best intervention in reducing WOMAC pain (surface under the cumulative ranking area [SUCRA] 84.7%), stiffness (SUCRA 95.1%), and function (SUCRA 98.5%) scores, according to the SUCRA. The best measures for lowering the WOMAC total and VAS scores were IA injection platelet-rich plasma-derived growth factor (SUCRA 84.9%) and hyaluronic acid and platelet-rich plasma (SUCRA 84.9%). In the VAS score group, PRP outperformed hyaluronic acid (HA) (WMD 1.3, 95% CI 0.55-2.55) and corticosteroids (CS) (WMD 4.85, 95% CI 4.02-5.08), according to the forest map results. PRP also outperformed CS (WMD 14.76, 95% CI 12.11-17.41), ozone (WMD 9.16, 95% CI 6.89-11.43), and PRP + HA (WMD 2.18, 95% CI 0.55-3.81) in the WOMAC total score group. Furthermore, PRP outperforms other drugs in terms of reducing WOMAC function, stiffness, and function score. CONCLUSION: In patients with mild to moderate KOA, IA injection PRP outperformed IA injection ozone, HA, CS, platelet-rich plasma-derived growth factor, and hyaluronic acid and platelet-rich plasma in terms of pain, stiffness, and dysfunction.

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)0.028
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.049
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0240.051
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.069
GPT teacher head0.325
Teacher spread0.256 · 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 designMeta-analysis
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

Citations26
Published2023
Admission routes1
Has abstractyes

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