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Record W2191957104 · doi:10.1055/s-0035-1566736

Effect of Sodium Hyaluronate on Recovery after Arthroscopic Knee Surgery

2015· article· en· W2191957104 on OpenAlexaboutno aff
Sanjeev Anand, Koppa N. R. Srikanth, Cathy Bamforth, Theophilus Asumu, Keyur Buch, Kiran Singisetti

Bibliographic record

VenueThe Journal of Knee Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSodium hyaluronateWOMACArthroscopyRandomized controlled trialVisual analogue scaleSurgeryBupivacaineAnesthesiaProspective cohort studyOsteoarthritis

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate the effect of a single immediate postoperative instillation of 10 mL of sodium hyaluronate (Viscoseal) into the knee following arthroscopy. A single-center, prospective, randomized, controlled study was undertaken. Consenting knee arthroscopy patients were randomized into two groups following surgery: the study group received 10 mL of sodium hyaluronate intra-articularly, while the control group received an intra-articular instillation of 10 mL of Bupivacaine. Pre- and postoperative visual analogue scale scores for pain and Western Ontario and McMaster Universities (WOMAC) scores for knee function were obtained. Overall, 48 patients under the care of a single surgeon were randomized into two groups of 24. There were no statistically significant demographic differences at baseline. Three patients were lost to follow-up. There was a statistically significant difference in pain scores favoring the study group compared with the control group at 3 and 6 weeks postoperatively (p < 0.05), and a statistically significant difference in WOMAC scores favoring the study group compared with the control group at 3 and 6 weeks postoperatively (p = 0.01). Synovial fluid replacement with sodium hyaluronate following arthroscopic knee surgery conferred statistically significant improvements in pain and function scores compared with Bupivacaine in the short term (3-6 weeks).

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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)0.0000.000

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 head0.030
GPT teacher head0.295
Teacher spread0.265 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

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