CHADS<sub>2</sub> and CHA<sub>2</sub>DS<sub>2</sub>-VASc score to assess risk of stroke and death in patients paced for sick sinus syndrome
Bibliographic record
Abstract
OBJECTIVE: The risk of stroke in patients with atrial fibrillation (AF) can be assessed by use of the CHADS2 and the CHA2DS2-VASc score system. We hypothesised that these risk scores and their individual components could also be applied to patients paced for sick sinus syndrome (SSS) to evaluate risk of stroke and death. DESIGN: Prospective cohort study. SETTINGS: All Danish pacemaker centres and selected centres in the UK and Canada. PATIENTS: Risk factors were recorded prior to pacemaker implantation in 1415 patients with SSS participating in the Danish Multicenter Randomized Trial on Single Lead Atrial Pacing versus Dual Chamber Pacing in Sick Sinus Syndrome (Danpace) trial. Development of stroke was assessed at follow-up visits and by evaluation of patient charts. Mortality was assessed from the civil registration system. INTERVENTIONS: Patients were randomised to AAIR (N = 707) or DDDR pacing (N = 708). MAIN OUTCOME MEASURES: Stroke and death during follow-up. RESULTS: Mean follow-up was 4.3 ± 2.5 years. In the AAIR group 6.9% patients developed stroke versus 6.1% in the DDDR group (NS). There was a significant association between CHADS2 score and the development of stroke (HR 1.41; 95% CI 1.22 to 1.64, p < 0.001). CHA2DS2-VASc score was also significantly associated with stroke (HR 1.25; CI 1.12 to 1.40, p < 0.001). CHADS2 score (HR 1.46; CI 1.36 to 1.56, p < 0.001) and CHA2DS2-VASc score (HR 1.39; CI 1.31 to 1.46, p < 0.001) were associated with mortality. Results were still significant after adjusting for AF and anticoagulation therapy. CONCLUSIONS: CHADS2 and CHA2DS2-VASc score are associated with increased risk of stroke and death in patients paced for SSS irrespective of the presence of AF.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".