Abstract 16594: Clinical Outcomes in Digital Electrocardiography: Evaluation of Mortality in Atrial Fibrillation (Code Study)
Bibliographic record
Abstract
Introduction: Telehealth system is an important tool to improve access and quality to health assistance.Large electrocardiogram (ECG) databases, linked to mortality or hospitalization data, can be useful in determining the prognostic value of ECG markers. Atrial fibrillation (AF) is a public health problem with increasing prevalence as the population ages, associated with cardiovascular mortality and morbidity. Hypothesis: Evaluate the association between the presence of AF with overall and cardiovascular mortality in a large electronic cohort of primary care patients of Minas Gerais. Methods: This is an observational retrospective study. Patients over 16 years old who performed digital electrocardiograms by Telehealth Network of Minas Gerais from 2013 to 2016 were assessed. A probabilistic linkage between data from the national mortality information system and our ECG database was made. Clinical data were self-reported, and ECGs were interpreted by a team of trained cardiologists and automatic software (Glasgow and Minnesota).The diagnosis of AF was considered if there was concordance between the cardiologist′s report and one of the automatic systems. In cases of disagreement, ECGs were reviewed manually.Only the first ECG made was analysed. To assess the relation between AF and mortality, Cox regression was used, adjusted by age, sex and clinical conditions. Results: From a dataset of 1,773,689 patients, 1,075,531 were included. The mean age was 51.4 years, 40.5% male.The prevalence of AF was 1.15%. There were 2.9% deaths for all causes in 2.69 years of mean follow up. In univariate analysis, AF was a risk factor for death from all causes (HR 6.98, 95%CI 6.68-7.28). After adjustment for age, sex and comorbidities, AF remained an independent risk factor for all-cause mortality (HR 2.49; 95% CI 2.39 - 2.61). AF was also a predictor of risk for cardiovascular mortality after adjustment for age, sex and clinical conditions (HR 2.35, 95% CI 2.01-2.73). In multivariate analysis by sex, adjusted for age and comorbidities, AF women had higher risk of death for all causes (HR 3.06; 95% CI 2.86-3.26) than men (HR 2.18; 95% CI 2.06-2.32). There were no difference between sex in cardiovascular mortality (HR 2.34; 95% CI 2.01-2.73 for male sex e HR 2.49; 95% CI 2.14-2.90 for female). Conclusions: AF was a strong predictor of mortality for all causes and cardiovascular mortality in primary care population with increased risk in women for deaths for all cause.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".