Systolic Blood Pressure and Effects of Screening for Atrial Fibrillation With Long-Term Continuous Monitoring (a LOOP Substudy)
Bibliographic record
Abstract
Background: Hypertension is a well-known risk factor for atrial fibrillation (AF) and stoke, but data on the interaction between systolic blood pressure (SBP) and effects of AF screening are lacking. Methods: The LOOP Study randomized AF-naïve individuals aged 70 to 90 years with additional stroke risk factors to either screening with implantable loop recorder (ILR) and anticoagulation initiation upon detection of AF episodes ≥6 minutes, or usual care. In total, 5997 participants with available baseline SBP measurements were included in this substudy. Outcomes were analyzed according to the time-to-first-event principle using cause-specific Cox models. Results: The hazard ratio of stroke or systemic arterial embolism for ILR versus control decreased with increasing SBP. ILR screening yielded a 44% risk reduction of stroke or systemic arterial embolism among participants with SBP ≥150 mm Hg (adjusted hazard ratio, 0.56 [0.37–0.83]). Within the ILR group, SBP≥150 mm Hg was associated with a higher incidence of AF episodes ≥24 hours than lower SBP (adjusted hazard ratio, 1.70 [1.08–2.69]) but not with the overall occurrence of AF (adjusted P >0.05). Conclusions: The impact of AF screening on thromboembolic events increased with increasing blood pressure. SBP≥150 mm Hg was associated with a >1.5-fold increased risk of AF episodes ≥24 hours, along with an almost 50% risk reduction of stroke or systemic arterial embolism by ILR screening compared to lower blood pressure. These findings should be considered hypothesis-generating and warrant further study. Registration: URL: https://www.clinicaltrials.gov ; Unique Identifier: NCT02036450.
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".