Abstract 237: Family History Of Premature Cardiovascular Events And Total Plaque Area
Bibliographic record
Abstract
Although the positive family history for premature cardiovascular events has been considered a putative risk factor for decades, it has not been incorporated along with other established risk factors such as hyperlipidemia, hypertension, and cigarette smoking in the daily clinical practice when physicians evaluates the cardiovascular risk of a patient. One of the reason may be the presence of multiple risk factors coexisting during these evaluations. The objective of this research was to investigate if patients with a family history of premature cardiovascular events have higher total plaque area than patients without it, in the absence of other classical risk factors. Design and method: Patients from the primary prevention database of Blossom DMO program were identified to have positive family history of premature cardiovascular events (FHPCVE). After apply excluding criteria (absence of any classical risk factor) 23 patients qualified. A control group was generated reaching same data in variables (blood pressure, age, body weight, LDL cholesterol), except carotid total plaque area which was reported at the end of groups formation, once both groups were formed. We used the same definition as the Framingham study (family history of <55 years in men and <65 years in women, first degree relatives) to consider a patient with FHPCVE. Results: The group with FHPCVE was similar to the control group. Age 59±2 sv 60±1 yo, blood pressure 126±2/75±1 mmHg vs 127±1/74±1 mmHg, body mass index, 23±1 vs 24±1 Kg/cm 2 and LDL cholesterol 116±15 vs 139±20 mg/dl. When total plaque area was determined by Doppler, patients with FHPCVE had a TPA of 49±8 mm 2 while control group 33±4 mm 2 (p<0.05). Framingham risk score were similar, while the post test for acute myocardial infarction was lower in control group (16±1% vs 20±3%, p<0.05). Conclusions: Our data indicates that patients with positive family history for premature cardiovascular events have larger total plaque area than patients without it, indicating enhanced risk to develop a cardiovascular event, even in the absence of other classical risk factor. Physicians should identify early and treat accordingly these patients to prevent arterial deterioration.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.012 | 0.001 |
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".