Usefulness of the Calgary Syncope Symptom Score for the diagnosis of vasovagal syncope in the elderly
Bibliographic record
Abstract
AIMS: The Calgary Syncope Symptom Score (CSSS) has been validated as a simple point score of historical features with high sensitivity and specificity for the diagnosis of vasovagal syncope (VVS) in younger populations without evidence of structural heart disease. Our purpose was to evaluate the performance of the CSSS in an elderly population with suspected VVS. METHODS AND RESULTS: Hundred and eighty patients of ≥60 years of age (mean 73.4 ± 7.8) with suspected clinical diagnosis of VVS were studied. The CSSS (VVS score ≥-2) was calculated in all patients prior to undergoing head-up tilt test (HUT). A standardized HUT protocol with active nitroglycerin phase was used to reproduce syncopal symptoms as gold standard for diagnosis of VVS. Hundred and forty patients had positive HUT response. Eighty-three patients (42.3%) had CSSS ≥-2 suggesting a diagnosis of VVS. The Calgary Syncope Symptom Score sensitivity was 0.51 [95% confidence interval (CI) 0.42-0.59] and specificity 0.73 (95% CI 0.52-0.85) with positive predictive value and negative predictive value of 0.87 (95% CI 0.77-0.93) and 0.30 (95% CI 0.21-0.40), respectively. One hundred (55.6%) patients had previous history of mild cardiovascular disease documented during assessment prior to HUT. In this population sensitivity and specificity was markedly reduced: 0.13 (95% CI 0.05-0.29) and 0.70 (95% CI 0.57-0.80), respectively. CONCLUSION: The CSSS has a lower sensitivity and specificity in an elderly population presenting with syncope compared to previously validated data in young adults, particularly in elderly patients with previous history of mild cardiovascular disease. A modified CSSS may be needed to improve specificity and sensitivity in this population.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".