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Record W2737223780

CONTROLLING INFLAMMATION WITH DEXAMETHASONE AFTER ANTERIOR CRUCIATE LIGAMENT INJURY

2014· article· en· W2737223780 on OpenAlexvenueno aff
J M Reynolds, Kristen I. Barton, Bryan J. Heard, May Chung, Nigel G. Shrive, David Hart, Yamini Achari

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2014
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAnterior cruciate ligamentMedicineArthrotomyOsteoarthritisACL injurySurgeryStifle jointPatellaCruciate ligamentKnee JointDexamethasoneCondyleAnterior cruciate ligament reconstructionArthroscopyInternal medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION Anterior Cruciate Ligament (ACL) injuries are increasingly common, with about 250 000 ACL ruptures occurring per year in the US [1]. The current treatment for ACL rupture is ACL reconstructive surgery (ACL-R), which aims to successfully restore the biomechanical function of the knee. However, individuals who suffer from ACL injuries, including those who undergo ACL reconstruction, have a 50% chance of developing osteoarthritis (OA) within 10-20 years [2]. Inflammation of the knee joint has been hypothesized to be a factor [3]. Dexamethasone (DEX) is a type of corticosteroid used to control inflammation [4]. The purpose of this study was to determine if DEX treatment following anterior cruciate ligament reconstruction was an effective mechanism of long-term joint protection against the progression of osteoarthritis. METHODS Six female Suffolk cross sheep were allocated into one of three groups: sham surgery, idealized ACL-R surgery, and control. Surgeries were previously accomplished by arthrotomy to the right stifle joint. Animals that underwent idealized ACL reconstructive surgery received a single injection of DEX at the time of the surgery. At 2 weeks post surgery animals were sacrificed and cartilage samples were harvested from both standard as well as visibly damaged locations on the patella (PAT), femoral groove (FG), lateral femoral condyle (LFC), medial femoral condyle (MFC), lateral tibial condyle (LTC), and medial tibial condyle (MTC). These samples were then blinded and graded by three experienced observers on the modified Mankin scale. This scale gives a grade out of 24 based on four categories: safranin-O staining, structure, cell density, and cluster formation. ANOVA with Bonferroni post-hoc analysis was used to determine differences in histological scores between groups, using SPSS 19.0. RESULTS The average histological grades (and standard deviations) for the PAT, FG, LTP, MTP, LFC, and MFC are displayed in Figure 1. No significant differences were observed between the sham (n=2), ACL-R + DEX (n=2), and control groups in all locations. DISCUSSION AND CONCLUSIONS The similarity between the ACL-R+DEX and control groups indicates that DEX treatment has the potential to have a protective effect against the progression of OA, however further studies must be conducted to ensure long-term efficacy. Increasing the sample size as well as looking at longer time points is recommended to better understand the effect of dexamethasone on the progression of osteoarthritis

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.339
Teacher spread0.320 · 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".

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Citations0
Published2014
Admission routes1
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