Effects of the cardiac cycle on carotid intima-media thickness measurements in a large Brazilian cohort (ELSA-Brasil)
Bibliographic record
Abstract
Abstract Background/Introduction It is unclear to what extent the cardiac cycle influences carotid intima-media thickness (CIMT) values, especially in individuals with major cardiovascular risk factors (CVRF). Purpose To analyze CIMT variability throughout the cardiac cycle using baseline data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) and its association with major CVRFs (hypertension, diabetes, dyslipidemia, smoking and family history of premature cardiovascular disease). Methods Our sample consisted of 9,546 participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) with valid left and right CIMT values. ELSA-Brasil is a cohort study of individuals aged 35 to 74 years in six Brazilian cities. CIMT image acquisition was performed using ECG-gated video recording of common carotid arteries during three cardiac cycles (70 to 90 frames each exam). CIMT reading was computer-assisted (MIA software), upon discretization of a 1-cm long region of interest to assess minimal, mean and maximum CIMT in each frame. In this analysis, we analyzed frame-by-frame data to calculate the coefficient of variation (CV), range, and interquartile range of CIMT measurements within each exam. Furthermore, we classified the sample according to the presence of major CVRFs. Results Our sample had a mean age of the sample was 51.5 years and 56% were women. CIMT variability was higher in individuals with major CVRFs, except for family history of premature cardiovascular disease As shown in Table 1, CIMT variability was relatively higher in proximal wall measurements (CV: 5.8% and 4.9% for left and right common carotid artery (CCA), respectively) than in far wall measurements (CV: 2.1% for both CCAs). For all measurements, a higher number of CVRFs were significantly associated with higher variability across the cardiac cycle (Table 2). Conclusion(s) There is a significant CIMT variability across the cardiac cycle, especially in individuals with established CVRFs. Study protocols and technicians must be aware of this phenomenon during image acquisition to ensure variability does not interfere with the study results.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".