Diabetes is associated with atrial fibrillation phenotype, cardiac and neurological comorbidities: insights from the Swiss-AF study
Bibliographic record
Abstract
Abstract Background Diabetes mellitus is a major risk factor for atrial fibrillation (AF). However, it remains unclear whether individual AF phenotype and related comorbidities differ between AF patients with and without diabetes. Purpose To investigate the association of diabetes with AF phenotype, cardiac and neurological comorbidities in patients with documented AF. Methods Participants of the multicenter Swiss-AF study with available data on diabetes and AF phenotype were eligible. The primary outcomes were parameters of AF phenotype, including AF type (paroxysmal vs non-paroxysmal), AF symptoms (yes vs no), and quality of life (assessed by EQ-5D score). The secondary outcomes were cardiac (ie, history of hypertension, myocardial infarction, heart failure) and neurological comorbidities (ie, history of stroke, cognitive impairment). The cross-sectional association of diabetes with these outcomes was assessed using logistic and linear regression. Results were adjusted for age, sex, and cardiovascular risk factors. Results We included 2411 AF patients (27.4% women; median age, 73.6 years). Diabetes was not associated with non-paroxysmal AF (odds ratio [OR]=1.01; 95% confidence interval [CI]=0.81 to 1.27). Patients with diabetes less often perceived AF symptoms (OR=0.73; CI=0.59 to 0.91), but had worse quality of life (predicted mean difference in EQ-5D score: β=−4.54; CI=−6.40 to −2.68) than those without diabetes. Patients with diabetes were more likely to have cardiac comorbidities [history of hypertension (OR=3.04; CI=2.19 to 4.22), myocardial infarction (OR=1.55; CI=1.18 to 2.03), heart failure (OR=1.99; CI=1.57 to 2.51)] and neurological comorbidities [history of stroke (OR=1.39; CI=1.03 to 1.87), cognitive impairment (OR=1.75; CI=1.39 to 2.21)]. Conclusions In the Swiss-AF cohort population, patients with diabetes less often perceived AF symptoms, but had worse quality of life, more cardiac and neurological comorbidities than those without diabetes. These findings have significant clinical implications. The reduced perception of AF symptoms in patients with diabetes might result in a delayed AF diagnosis and consequently more adverse events, especially cardioembolic stroke. This raises the question whether patients with diabetes should be systematically screened for silent AF. Moreover, patients with concomitant AF and diabetes have increased likelihood of comorbidities and therefore deserve more attentive care. Funding Acknowledgement Type of funding sources: None.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".