Evidence of Cyclic Changes in the Metabolism of Abdominal Aortic Aneurysms During Growth Phases: <sup>18</sup>F-FDG PET Sequential Observational Study
Bibliographic record
Abstract
UNLABELLED: The rates of growth of medically treated abdominal aortic aneurysms (AAA) are difficult to determine, and relationships with parietal inflammation and with metabolic parameters from (18)F-FDG PET remain unclear. This (18)F-FDG PET sequential observational study was aimed at analyzing the metabolic changes accompanying the growth phases of medically treated AAA. METHODS: Thirty-nine patients (37 men; age [mean ± SD], 71 ± 12 y) exhibiting small and medically treated AAA (maximal diameter, 46 ± 3 mm) underwent (18)F-FDG PET and CT angiography at baseline and 9 mo later. Clinical and imaging parameter correlates of the 9-mo increase in maximal diameter were investigated; these included (18)F-FDG maximal standardized uptake values (SUVmax) averaged for slices encompassing the AAA volume. RESULTS: Of the 39 patients, 9 (23%) had a significant (≥2.5 mm) increase in maximal diameter at 9 mo, whereas the remaining 30 did not. The patients with an increase in maximal diameter at 9 mo exhibited lower SUVmax within the AAA at baseline than patients who did not have such an increase (1.80 ± 0.45 vs. 2.21 ± 0.52; P = 0.04); they also displayed a trend toward greater changes in SUVmax at 9 mo (difference between 9 mo and baseline: +0.40 ± 0.85 vs. -0.06 ± 0.57; P = 0.07). Similar levels were ultimately reached in both groups at 9 mo (2.20 ± 0.83 and 2.15 ± 0.66). SUVmax was a significant, yet modest, baseline predictor of the absolute change in maximal diameter during follow-up (P = 0.049). CONCLUSION: The enhancement in the maximal diameter of small AAA was preceded by a stage with a low level of (18)F-FDG uptake, but this low level of uptake was no longer documented after the growth phases, suggesting a pattern of cyclic metabolic changes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".