The development and preliminary validation of a scale measuring the impact of syncope on quality of life
Bibliographic record
Abstract
AIMS: To develop a brief syncope-specific measure of health-related quality of life. METHODS AND RESULTS: One hundred and fourteen patients with syncope completed a 48-item questionnaire derived from a generic measure of quality of life (the EQ-5D), the Syncope Functional Status Questionnaire, a depression scale (the CES-D) and historical symptoms. From these, clinical impact methodology was used to derive 12-item Impact of Syncope on Quality of Life (ISQL). The ISQL correlated with the number of syncopal spells in the previous year (r = 0.35), self-perceived health status (r = -0.55), the three scores from the SFSQ: [impairment (r = 0.77), fear and worry (r = 0.72), syncope dysfunction (r = 0.82), and depression (r = 0.62)], illustrating its convergent validity with these concepts. Known group differences were evident between patients who exhibited reduced quality of life on the EQ-5D and those who did not. There was no significant correlation between ISQL score and age or gender. ISQL score correlated better with the frequency of spells in the previous year than years prior to the previous year. CONCLUSION: The ISQL is a brief valid measure of the impact of syncope on quality of life. It measures impairment, fear, depression, and physical limitations, and correlates with recent syncope frequency.
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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 | 0.006 | 0.012 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".