Measures and time points relevant for post-surgical follow-up in patients with inflammatory arthritis: a pilot study
Bibliographic record
Abstract
BACKGROUND: Rheumatic diseases commonly affect joints and other structures in the hand. Surgery is a traditional way to treat hand problems in inflammatory rheumatic diseases with the purposes of pain relief, restore function and prevent progression. There are numerous measures to choose from, and a combination of outcome measures is recommended. This study evaluated if instruments commonly used in rheumatologic clinical practice are suitable to measure outcome of hand surgery and to identify time points relevant for follow-up. METHODS: Thirty-one patients (median age 56 years, median disease duration 15 years) with inflammatory rheumatic disease and need for post-surgical occupational therapy intervention formed this pilot study group. Hand function was assessed regarding grip strength (Grippit), pain (VAS), range of motion (ROM) (Signals of Functional Impairment (SOFI)) and grip ability (Grip Ability Test (GAT)). Activities of daily life (ADL) were assessed by means of Disabilities of the Arm, Shoulder and Hand Outcome (DASH) and Canadian Occupational Performance Measure (COPM). The instruments were evaluated by responsiveness and feasibility; follow-up points were 0, 3, 6 and 12 months. RESULTS: All instruments showed significant change at one or more follow-up points. Satisfaction with activities (COPM) showed the best responsiveness (SMR>0.8), while ROM measured with SOFI had low responsiveness at most follow-up time points. The responsiveness of the instruments was stable between 6 and 12 month follow-up which imply that 6 month is an appropriate time for evaluating short-term effect of hand surgery in rheumatic diseases. CONCLUSION: We suggest a core set of instruments measuring pain, grip strength, grip ability, perceived symptoms and self-defined daily activities. This study has shown that VAS pain, the Grippit instrument, GAT, DASH symptom scale and COPM are suitable outcome instruments for hand surgery, while SOFI may be a more insensitive test. However, the feasibility of this protocol in clinical practice awaits prospective studies.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".