Protocol for a multicentre and prospective follow-up cohort study of early detection of atrial fibrillation, silent stroke and cognitive impairment in high-risk primary care patients: the PREFA-TE study
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Future estimations suggest an increase in global burden of AF greater than 60% by 2050. Numerous studies provide growing evidence that AF is not only associated with stroke but also with cognitive impairment and dementia. AIM: The main goal is to assess the impact of the combined use of cardiac rhythm monitoring devices, echocardiography, biomarkers and neuroimaging on the early diagnosis of AF, silent strokes and cognitive decline, in subjects at high risk of AF. METHODS AND ANALYSIS: Two-year follow-up of a cohort of individuals aged 65-85 years at high risk for AF, with no prior diagnosis of either stroke or dementia. The study involves baseline echocardiography, biomarkers, and neuroimaging, yearly cardiac monitoring, and semiannual clinical assessments. Different parameters from these tests will be analysed as independent variables. Throughout the study period, primary outcomes: new diagnoses of AF, stroke and cognitive impairment, along with any clinical and therapeutic changes, will be registered. A first descriptive and bivariate statistical analysis, appropriate to the types of variables, will be done. The information obtained from the data analysis will encompass adjusted risk estimates along with 95% confidence intervals. Event risk predictions will rely on multivariate Cox proportional hazards regression models. The predictive value of the model will be evaluated through the utilisation of receiver operating characteristic curves for area under the curve calculation. Additionally, time-to-event analysis will be performed using Kaplan-Meier curves. ETHICS AND DISSEMINATION: This study protocol has been reviewed and approved by the Independent Ethics Committee of the Foundation University Institute for Primary Health Care Research-IDIAP Jordi Gol (expedient file 22/090-P). The authors plan to disseminate the study results to the general public through various scientific events. Publication in open-access journals and presentations at scientific congresses, seminars and meetings is also foreseen. TRIAL REGISTRATION NUMBER: NCT05772806.
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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 | 0.025 | 0.023 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.012 |
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".