Patient-acceptable Symptom State as an Outcome Measure in the Daily Care of Patients with Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: We assessed the prevalence of patients with ankylosing spondylitis (AS), rating their state as acceptable (patient-acceptable symptom state; PASS), among 190 patients with AS seen in daily practice. Factors associated with PASS status and PASS thresholds for outcome measures were also analyzed. METHODS: The characteristics of patients with affirmative and negative assignment to PASS were compared. Associated factors were estimated by logistic regression models and PASS thresholds by the 75th percentile and receiver-operating characteristic curve methods. RESULTS: A total of 77% of patients rated their state as acceptable (95% CI 62-91). These patients were taking fewer nonsteroidal antiinflammatory drugs and corticosteroids, practiced more exercise, had less anxiety and depression, and had lower values of all patient-reported outcome measures, physicians' assessment, AS Disease Activity Score (ASDAS) and C-reactive protein. Lower values of Bath AS Disease Activity Index and physician's global assessment were independent factors associated with acceptable symptom state. High rates of anxiety and depression were found in patients not in PASS. The thresholds with the 75th percentile approach were 4.55 for the BASDAI and 2.84 for the ASDAS. Fifty-three percent of patients in PASS had a high or very high disease activity state according to ASDAS cutoff values. CONCLUSION: A high percentage of patients with AS in daily practice declared that their symptom state was acceptable. PASS status correlated with physician global assessment and BASDAI. PASS thresholds for common recommended outcome measures were relatively high and many patients in PASS had unacceptably high disease activity states according to ASDAS. Other factors such as psychological problems may influence a negative PASS state.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".