Longitudinal quantitative assessment of coronary atherosclerosis related to normal systolic blood pressure maintenance in the absence of established cardiovascular disease
Bibliographic record
Abstract
Abstract Background Atherosclerosis‐related adverse events are commonly observed even in conditions with low cardiovascular (CV) risk. Longitudinal data regarding the association of normal systolic blood pressure maintenance (SBPmaintain) with coronary plaque volume changes (PVC) has been limited in adults without traditional CV disease. Hypothesis Normal SBPmaintain is important to attenuate coronary atherosclerosis progression in adults without baseline CV disease. Methods We analyzed 95 adults (56.7 ± 8.5 years; 40.0% men) without baseline CV disease who underwent serial coronary computed tomographic angiography with mean 3.5 years of follow‐up. All participants were divided into two groups of normal SBPmaintain (follow‐up SBP < 120 mm Hg) and ≥elevated SBPmaintain (follow‐up SBP ≥ 120 mm Hg). Annualized PVC was defined as PVC divided by the interscan period. Results Compared to participants with normal SBPmaintain, those with ≥elevated SBPmaintain had higher annualized total PVC (mm3/year) (0.0 [0.0–2.2] vs. 4.1 [0.0–13.0]; p < .001). Baseline total plaque volume (β = .10) and the levels of SBPmaintain (β = .23) and follow‐up high‐density lipoprotein cholesterol (β = −0.28) were associated with annualized total PVC (all p < .05). The optimal cutoff of SBPmaintain for predicting plaque progression was 118.5 mm Hg (sensitivity: 78.2%, specificity: 62.5%; area under curve: 0.700; 95% confidence interval [CI]: 0.59–0.81; p < .05). SBPmaintain ≥ 118.5 mm Hg (odds ratio [OR]: 4.03; 95% CI: 1.51–10.75) and baseline total plaque volume (OR: 1.03; 95% CI: 1.01–1.06) independently influenced coronary plaque progression (all p < .05). Conclusion Normal SBPmaintain is substantial to attenuate coronary atherosclerosis progression in conditions without established CV disease.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".