483Blood pressure and white matter lesions in patients with atrial fibrillation
Bibliographic record
Abstract
Abstract Background Hypertension (HTN) is one of the most common cardiovascular risk factors in patients with atrial fibrillation (AF). As a potential risk factor for cerebral white matter lesions (WML), HTN might explain the increased risk of cognitive dysfunction in AF patients. Methods In a multicenter cohort study of patients with documented AF in Switzerland, systolic and diastolic blood pressure (SBP, DBP) was measured up to three times in a supine position and the mean was calculated. HTN was defined as controlled, when SBP was <140 and DBP <90 mmHg with treatment, and uncontrolled when SBP was ≥140 or DBP ≥90 mmHg with treatment. All patients underwent brain magnetic resonance imaging. Volumes of WML were assessed and graded using the Fazekas scale. A Fazekas score of ≥2 was defined as moderate or severe WML. Multivariable adjusted regression models were used to assess the association between BP and WML. Results Overall, 1738 patients were enrolled in this cross-sectional analysis (mean age 73 years, 73% males). Mean BP was 135/79 mmHg, 69% had a history of HTN. Any WMLs were found in 99% of the patients and 54% had at least moderate WMLs. The prevalence of Fazekas ≥2 was 47%, 50% and 61% among AF patients with SBP <120, 120–140 and ≥140mmHg (p<0.001), respectively. Volumes of WMLs significantly increased across the same SBP categories (2943, 3512 and 4988 mm3, p<0.001). Among patients with normotension, controlled and uncontrolled HTN, moderate or severe WMLs were present in 173 (42.5%), 345 (55%) and 307 (61%), respectively. SBP was associated with Fazekas ≥2 and WML volume after multivariable adjustment (Table). Compared to normotension, both controlled and uncontrolled HTN were significantly associated with higher WML volume (Table). Association between blood pressure and white matter lesions Blood pressure Fazekas ≥2 OR (95% CI) Volume WML β-coefficient (95% CI) <120 mmHg Ref Ref 120–140 mmHg 1.17 (0.88; 1.55) 0.14 (−0.01; 0.30) ≥140 mmHg 1.49 (1.11; 2.00) 0.28 (0.12; 0.43) Continuous, per SD 1.20 (1.09; 1.36), p<0.001 0.12 (0.06; 0.18), p<0.001 Normotension Ref Ref Treated hypertension 1.26 (0.94; 1.68), p=0.12 0.22 (0.07; 0.38), p=0.005 Treated, uncontrolled hypertension 1.52 (1.13; 2.05), p=0.005 0.38 (0.21; 0.54), p<0.001 Regression analyses were adjusted for age, sex, BMI, smoking status, stroke, diabetes, coronary heart disease, AF type, and antihypertensive treatment. One standard Deviation (SD) of SBP = 18 mmHg. Volume of WML was log-transformed. Conclusion Moderate or severe cerebral WMLs are highly prevalent in AF patients and strongly associated with SBP. Our data suggests that optimal treatment of HTN might play an essential role in preventing WMLs. Acknowledgement/Funding Swiss National Science Foundation
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".