Thoracic Aortic Calcification and Pre-Clinical Hypertension by New 2017 ACC/AHA Hypertension Guidelines
Bibliographic record
Abstract
The recently revised 2017 American College of Cardiology/American Heart Association (ACC/AHA) hypertension (HTN) guidelines employ a lower blood pressure threshold to define HTN, aiming for earlier prevention of HTN-related cardiovascular diseases (CVD). Thoracic aortic calcification (TAC), a new surrogate marker of aging and aortic medial layer degeneration, and different stages of HTN, according to the 2017 ACC/AHA HTN guidelines, remain unknown. We classified 3022 consecutive asymptomatic individuals enrolled into four HTN categories using the revised 2017 ACC/AHA guidelines: normal blood pressure (NBP), elevated blood pressure (EBP), and stage 1 (S1) and stage 2 (S2) HTN. The coronary artery calcification score and TAC metrics (total Agaston TAC score, total plaque volume (mm3), and mean density (Hounsfield units, HU)) were measured using multi-detector computed tomography. Compared to NBP, a graded and significant increase in the TAC metrics was observed starting from EBP and S1 and S2 HTN, using the new 2017 ACC/AHA guidelines (NBP as reference; all trends: p < 0.001). These differences remained consistent after being fully adjusted. Older age (>50 years), S1 and S2 HTN, prevalent diabetes, and chronic kidney disease (<60 mL/min/1.73 m2) are all independently contributing factors to higher TAC risk using multivariate stepwise logistic regressions (all p ≤ 0.001). The optimal cutoff values of systolic blood pressure, diastolic blood pressure, and pulse pressure were 121, 74, and 45 mmHg, respectively, for the presence of TAC after excluding subjects with known CVD and ongoing HTN medication treatment. Our data showed that the presence of TAC starts at a stage of elevated blood pressure not categorized as HTN from the updated 2017 ACC/AHA hypertension guidelines.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".