Alt Ekstremite A?rısı Olan Hastalarda Venöz Yetmezlik Birlikteli?i, A?rı ve Fonksiyonel Kapasite Üzerine Etkisi
Bibliographic record
Abstract
ABSTRACTVenous insufficiency in patients with lower extre-mity pain and its efficacy on pain and functional capacity The aim of this study is to evaluate the frequency of venous insufficiency in patients with knee osteoarthritis and the effect of venous insufficiency on pain and functional capacity. 49 patients who were admitted to the out-patient clinic of Physical Medicine and Rehabilitation Department with knee osteoarthritis (Group 1) and 30 patients with lower extremity pain without clinical knee osteoarthritis in physical examination as control group were included in the study (Group 2). The age, disease duration, body mass index of the patients were recorded. The pain in motion and at rest were evaluated with visual analogue scale. Radiologic grading were assessed by Kellgren Lawrence Classification with anteroposterior knee radiographies. Functional capacity was assessed by Western Ontario McMaster University Osteoarthrit Index (WOMAC). The venous insufficiency was diagnosed with venous doppler ultrasonography. The venous insufficiency was identified in 33% of patients (16 patients) with knee osteoartritis and 23% of patients (7 patients) in control group. Between the groups, WOMAC function (p=0.001), WOMAC stifness (p=0.021), WOMAC pain scores (p=0.005) and visual analogue scale scores (p=0.005) were statistically more affected in group 1. When the patients with venous insufficiency were compared with patients without insufficiency, there was no significant difference in WOMAC function and pain scores (p>0.05). Venous insufficiency and knee osteoarthritis may cause pain and functional limitation in lower extremity. The incidence of these conditions increase with age and they can be seen together. However, the treatment of these conditions are different. Thereby, the patients with knee osteoarthritis should be evaluated in terms of venous insufficiency.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".