Feeling good rather than feeling better matters more to patients
Bibliographic record
Abstract
OBJECTIVE: To determine the most appropriate means to assess the response to treatment in terms of pain and functional impairment in a chronic rheumatic condition (knee osteoarthritis [OA]) and an acute rheumatic condition (rotator cuff syndrome [RCS]). METHODS: Two prospective studies were conducted consisting of 1,019 outpatients with knee OA and 271 patients with acute RCS. The minimal clinically important improvement and the patient acceptable symptom state were determined for knee OA pain using a visual analog scale, and for knee OA function using the Western Ontario and McMaster Universities Osteoarthritis Index function subscale; for acute RCS pain, a numeral rating scale was used, and the Neer function subscale was used for RCS function. RESULTS: The minimal clinically important improvement was shown to be the change required to achieve the patient acceptable symptom state, whatever the baseline level of symptom, the outcome (pain or function), or type of condition (chronic or acute). This acceptable state for pain was higher for chronic (27.0-36.4 across the baseline score) than acute (16.7-24.1) conditions. The level of functional impairment considered satisfactory by patients with knee OA was higher for more disabled patients (43.1) than for less disabled patients (20.4). CONCLUSION: Patients consider that they experienced an important improvement only if this improvement allowed them to achieve a state they consider satisfactory. The most appropriate means to assess the response to therapy seems to be to assess whether patients feel good (i.e., achieve the patient acceptable symptom state).
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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".