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Record W7010986759

Klinik Ve Radyolojik Olarak Diz Osteoartriti Tanısı Almış Olan Hastalarda Serum Comp ve Mmp-3 Düzeylerinin Hastalık Evresi ve Günlük Yaşam Aktiviteleri ile İlişkisi

2020· dissertation· en· W7010986759 on OpenAlexaboutno aff

Bibliographic record

VenueHacettepe University Institutional Repository (hacettepe.edu.tr) · 2020
Typedissertation
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisWOMACQuality of life (healthcare)Incidence (geometry)Stage (stratigraphy)DiseaseArthropathyJoint disease
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Osteoarthritis is the most common joint disease affecting the knee joints mostly. The incidence is increasing and it significantly affects the quality of life by causing significant morbidity especially in the second half of life. In recent years, a multifactorial disease with low-grade chronic inflammation is considered to play a role in the pathogenesis of osteoarthritis. The aim of this study is to investigate the relationship between serum COMP (Cartilage Oligomeric Matrix Protein) and MMP-3 (Matrix Metalloproteinase-3) levels and disease stage and daily life activities in patients diagnosed with knee osteoarthritis. \n \nMaterials and Methods: A total of 85 patients who were diagnosed with knee osteoarthritis according to ACR (American College of Rheumatology) criteria and had been admitted to Hacettepe University Faculty of Medicine, Department of Physical Medicine and Rehabilitation, were included to the study. Patients' age, gender, weight, height, educational background, occupation, additional diseases and medications were recorded. Knee osteoarthritis was evaluated by performing a detailed physical examination. In addition, blood samples were taken from patients for serum COMP and MMP-3 measurements. The severity of pain in patients and functional status in daily life activities were evaluated with VAS (Visual Analog Scale), WOMAC (The Western Ontario and McMaster Universities Osteoarthritis Index), Lequesne and KOOS-PS (Knee Injury and Osteoarthritis Outcome Score Short Form) scales. \n \nResults: Seventy-five (88.2%) of the patients were female and ten (11.8%) were male. 85 patients were divided into 3 groups according to the Kellgren-Lewrence radiological staging system (K-L). K-L stage I patients were included in group 1, patients with K-L stage II and III were included in group 2, and patients with K-L stage IV were included in group 3. The mean age was 57.17 ± 9.37 in group 1, 64.73 ± 9.48 in group 2, and 68.17 ± 10.27 years in group 3. In our study, serum COMP and MMP-3 levels were found to be similar in all three patient groups. When these biomarkers and functional test scores were compared, moderate correlation between serum COMP level and VAS score, moderately negative correlation with WOMAC, and low-moderately negative correlation with KOOS-PS was found. There was no correlation between serum MMP-3 level and VAS, WOMAC, KOOS-PS scores, but a low correlation with Lequesne score was observed. \nConclusion: In our study, there was no significant differences in serum COMP and MMP-3 levels between different stage of knee osteoarthritis groups. Further studies are needed in larger sample groups of these biomarkers to predict the diagnosis and prognosis of osteoartritis.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.013
GPT teacher head0.224
Teacher spread0.212 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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