Blood Pressure and Brain Lesions in Patients With Atrial Fibrillation
Bibliographic record
Abstract
The association of blood pressure (BP) and hypertension with the presence of different types of brain lesions in patients with atrial fibrillation is unclear. BP values were obtained in a multicenter cohort of patients with atrial fibrillation. Systolic and diastolic BP was categorized in predefined groups. All patients underwent brain magnetic resonance imaging and neurocognitive testing. Brain lesions were classified as large noncortical or cortical infarcts, small noncortical infarcts, microbleeds, or white matter lesions. White matter lesions were graded according to the Fazekas scale. Overall, 1738 patients with atrial fibrillation were enrolled in this cross-sectional analysis (mean age, 73 years, 73% males). Mean BP was 135/79 mm Hg, and 67% of participants were taking BP-lowering treatment. White matter lesions Fazekas ≥2 were found in 54%, large noncortical or cortical infarcts in 22%, small noncortical infarcts in 21%, and microbleeds in 22% of patients, respectively. Compared with patients with systolic BP <120 mm Hg, the adjusted odds ratios (95% CI) for Fazekas≥2 was 1.25 (0.94–1.66), 1.41 (1.03–1.93), and 2.54 (1.65–3.95) among patients with systolic BP of 120 to 140, 140 to 160, and ≥160 mm Hg ( P for linear trend<0.001). Per 5 mm Hg increase in systolic and diastolic BP, the adjusted β-coefficient (95% CI) for log-transformed white matter lesions was 0.04 (0.02–0.05), P <0.001 and 0.04 (0.01–0.06), P =0.004. Systolic BP was associated with small noncortical infarcts (odds ratios [95% CI] per 5 mm Hg 1.05 [1.01–1.08], P =0.006), microbleeds were associated with hypertension, but large noncortical or cortical infarcts were not associated with BP or hypertension. After multivariable adjustment, BP and hypertension were not associated with neurocognitive function. Among patients with atrial fibrillation, BP is strongly associated with the presence and extent of white matter lesions, but there is no association with large noncortical or cortical infarcts. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02105844.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".