Assessment of psychometric characteristics and quality of life in adult and elderly patients with rheumatoid arthritis
Bibliographic record
Abstract
Introduction: Rheumatoid arthritis (RA) is characterised by persistent joint inflammation and cartilage and bone damage with significant activity limitation, reduction in the Quality of Life (QoL), and often systemic complications. In recent years, there have been many advances in diagnostic and treatment modalities available for RA with better access to tertiary care centres in our country. The study aimed to analyse the present-day clinical profile of patients of RA reporting to a tertiary care centre in this part of India. Material and methods: This prospective observational, hospital-based study was carried out in a tertiary care teaching Mahavir Institute of Medical Sciences, Vikarabad over a period of six months. All diagnosed consecutive cases of RA visiting our OPD or admitted inwards were examined. The patients were diagnosed for RA based on the American College of Rheumatology Criteria-201. Detailed clinical history and examination along with inflammatory markers were analysed. The following instruments were used: The tools include the Medical Outcomes Study Short Form-36 (SF-36), The Western Ontario and McMaster (WOMAC) index, a disease-specific measure, was used to assess functional disability. Mini-International Neuropsychiatric Interview (MINI): The Mini-International Neuropsychiatric Interview (MINI) is a short diagnostic structured interview as per the Diagnostic and Statistical Manual (DSM-IVTR) diagnostic criteria. Results: The results indicated that there was a statistical difference in the QoL between subjects with RA and healthy population according to SF-36 Croatian norms. Also, the results showed that severe pain experience was significantly associated with poorer social functioning assessment. The RA group had significantly lower QoL scores in the psychological and environmental domains of QoL; life satisfaction scores were also significantly lower in the RA group when compared to control subjects. Conclusion: QoL and functional capacity in RA were affected in adults and the elderly. However, the results showed a significant difference between groups. There were significant proportions of patients who presented with high disease activity.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".