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Record W3084449746 · doi:10.1097/md.0000000000021813

Viscossuplementation for the treatment of osteoarthritis of the knee

2020· article· en· W3084449746 on OpenAlexaboutno aff
Carlos Augusto Ferreira de Andrade, I Genov, Sara Regina Neto Pereira, Joao Mauricio Barreto, Max Rogério Freitas Ramos, Eduardo Costa Freitas da Silva, Liszt Palmeira de Oliveira

Bibliographic record

VenueMedicine · 2020
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCochrane LibraryOsteoarthritisMEDLINEViscosupplementationAdverse effectMeta-analysisRandomized controlled trialPlaceboClinical trialPsychological interventionPhysical therapyEvidence-based medicineIntensive care medicineAlternative medicineInternal medicineIntra articularPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Knee osteoarthritis (KOA) is a common chronic disease with worldwide prevalence of 10% to 79%, with costs ranging from $560 to $635 billion for year in United States of America. The main guidelines recommend interventions with undesirable adverse events (AE) or highly dependent on the patient's persistence. Thus, intra-articular (IA) therapies appear to be attractive in patients with KOA, as well as a valid therapy by maximizing effects locally in the joint and limiting systemic AE. Presently, the main available IA therapies are corticosteroids and hyaluronic acid.As several meta-analyses about the efficacy of intra-articular hyaluronic acid (IAHA) for treatment of KOA with discordant results were published, we decided to conduct an umbrella review to summarize this efficacy METHODS:: We will search MEDLINE/PubMed, EMBASE, Cochrane Library, and Virtual Health Library (BVS) from inception to February 2020 for systematic reviews with meta-analyses of randomized clinical trials that investigate IAHA for therapy of KOA. Grey literature will be searched in Opengray platform, Research Gate, and Google Scholar. The reference lists of eligible studies will be screened. The search will be performed without language restriction.We will include any type of IAHA as experimental intervention and different types of oral or intra-articular placebo or medications as controls. The primary outcome will be measures of efficacy as the Western Ontario and McMaster Universities Osteoarthritis Index.A synthesis of the evidence will be conducted and data will be presented in tables.Two reviewers will independently appraise the quality of included meta-analyses using the Assessment of Multiple Systematic Reviews 2 (AMSTAR 2) tool and will classify the included systematic reviews into high, moderate, low, or critically low levels of confidence. RESULTS: The results of this study will be published in a peer-reviewed journal. ETHICS AND DISSEMINATION: No ethical approval is required since this study data is based on published literature. PROTOCOL REGISTRATION NUMBER: PROSPERO CRD42019120269 (https://www.crd.york.ac.uk/PROSPERO/#joinuppage).

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.037
GPT teacher head0.296
Teacher spread0.259 · 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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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