Clinical characteristics and disability in patients with knee osteoarthritis: real world experience from Bulgaria
Bibliographic record
Abstract
Objectives Although knee osteoarthritis (KOA) is a leading cause of impaired functioning among older adults globally, little is still known about the complex mechanisms of disability accumulation in these patients. The aim of the study was to analyze the clinical parameters of patients with KOA in a Bulgarian population and to determine which of these clinical characteristics define disability to the greatest extent. Material and methods Patients aged 40–80 years with symptomatic KOA were included. The assessment tools for pain, clinical disease severity, and disability were the pain visual analogue scale (VAS) and disease-specific questionnaires: Algofunctional Index of Lequesne, Western Ontario and McMaster Universities OA Index (WOMAC), and the Health Assessment Questionnaire-Disability Index (HAQ-DI), respectively. Radiographs of the knees were obtained and graded according to the Kellgren-Lawrence (KL) system. Results One hundred and thirty-two patients (81% women) participated in the study. The median values of VAS (mm), WOMAC, Lequesne, and HAQ-DI scores were 52, 37.5, 11, 0.88, respectively. Men had milder disease, resulting in lower VAS, WOMAC, Lequesne, and HAQ-DI scores and less structural damage compared to women (p < 0.05). WOMAC index correlated positively with age of the patients but not with duration of the complaints. Patients with severe and very severe pain did not differ in their HAQ-DI, disease severity and KL grading. WOMAC physical function score and Lequesne index were independent predictors for the HAQ-DI in patients with KOA. Conclusions Bulgarian patients with KOA had moderate disability which showed a strong relationship with physical function of WOMAC and disease severity. Multiple layers of causality coexist to determine the knee pain in Bulgarian patients with KOA.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".