Evaluation of aortic <sup>18</sup> F-NaF tracer uptake using PET/CT as a predictor of aortic calcification in postmenopausal women: A longitudinal study
Bibliographic record
Abstract
Introduction Aortic calcification as detected by computed tomography is associated with arterial stiffening and is an important predictor of cardiovascular morbidity and mortality. Uptake of 18 F-sodium fluoride ( 18 F-NaF) in the aortic wall reflects metabolically active areas of calcification. The aim of this study was to determine if 18 F-NaF uptake in the aorta is associated with calcification and progression of calcification as detected by computed tomography. Methods Twenty-one postmenopausal women (mean age 62 ± 6 years) underwent assessment of aortic 18 F-NaF uptake using positron emission tomography/computer tomography at baseline and a repeat computed tomography scan after a mean follow-up of 3.8 ± 1.3 years. Tracer uptake was quantified by calculating the target-to-background (TBR) ratios at baseline and follow-up. Calcification was assessed at baseline and follow-up using computed tomography. Results Over the follow-up period, aortic calcium volume increased from 0.46 ± 0.62 to 0.71 ± 0.93 cm 3 ( P < 0.05). However, the change in calcium volume did not correlate with baseline TBR either unadjusted ( r = 0.00, P = 1.00) or adjusted for age and baseline calcium volume (beta coefficient = −0.18, P = 0.42). TBR at baseline did not differ between participants with ( n = 16) compared to those without ( n = 5) progression in calcium volume (2.43 ± 0.46 vs. 2.31 ± 0.38, P = 0.58). In aortic segments identified to have the highest tracer uptake at baseline, calcium volume did not significantly change over the follow-up period ( P = 0.41). Conclusion In a cohort of postmenopausal women, 18 F-NaF uptake as measured by TBR in the lumbar aorta did not predict progression of aortic calcification as detected by computed tomography over a four-year follow-up.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.000 | 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".