Health-related outcomes of importance to patients with Takayasu's arteritis.
Bibliographic record
Abstract
OBJECTIVES: The need to include patients' perspectives as key outcomes in clinical trials is widely accepted. No disease-specific patient-reported outcomes have been developed in Takayasu's arteritis. This project was designed to identify outcomes of importance to patients with Takayasu's arteritis during active disease and remission across 2 different cultures. METHODS: Patients with Takayasu's arteritis from the US and Turkey were recruited to participate in semi-structured, one-on-one interviews or focus groups. The interviews and group sessions were recorded, transcribed, and entered into an Nvivo database. A line-by-line review of narrative data was used to develop themes describing the impact of Takayasu's arteritis on patients' life. US Patients were invited to freelist terms that they associated with disease states (active disease and remission). The Smith's Salience Index (SSI) was used to identify the most salient terms. RESULTS: Results. A total of 31 patients with Takayasu's arteritis participated in this study. Interviews and focus groups identified pain, fatigue, and emotional impact as common themes. Outcomes did not differ between the 2 countries. The most salient terms identified through freelisting were pain/discomfort and fatigue/low energy levels (SSI=0.56 and 0.33, respectively) during active disease and pain/discomfort and emotional impact (SSI=0.51 and 0.37, respectively) during remission. CONCLUSIONS: Patients with Takayasu's arteritis report a range of disease-specific symptoms across different cultures and disease states that are generally not specifically captured by generic patient-reported outcome tools currently used in research. Identifying disease-specific outcomes would advance clinical trials methodology to best capture the full spectrum of disease activity in Takayasu's arteritis.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".