Chronobiological Patterns of Acute Aortic Dissection
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Chronobiological rhythms have been shown to influence the occurrence of a variety of cardiovascular disorders. However, the effects of the time of the day, the day of the week, or monthly/seasonal changes on acute aortic dissection (AAD) have not been well studied. METHODS AND RESULTS: Accordingly, we evaluated 957 patients enrolled in the International Registry of Acute Aortic Dissection (IRAD) between 1996 and 2000 (mean age 62+/-14 years, type A 61%). A chi2 test for goodness of fit and partial Fourier analysis were used to evaluate nonuniformity and rhythmicity of AAD during circadian, weekly, and monthly periods. A significantly higher frequency of AAD occurred from 6:00 AM to 12:00 noon compared with other time periods (12:00 noon to 6:00 PM, 6:00 PM to 12:00 midnight, and 12:00 midnight to 6:00 AM; P<0.001 by chi2 test). Fourier analysis showed a highly significant circadian variation (P<0.001) with a peak between 8:00 AM and 9:00 AM. Although no significant variation was found for the day of the week, the frequency of AAD was significantly higher during winter (P=0.008 versus other seasons by chi2 test). Fourier analysis confirmed this monthly variation with a peak in January (P<0.001). Subgroup analysis identified a significant association for all subgroups with circadian rhythmicity. However, seasonal/monthly variations were observed only among patients aged <70 years, those with type B AAD, and those without hypertension or diabetes. CONCLUSIONS: Similar to other cardiovascular conditions, AAD exhibits significant circadian and seasonal/monthly variations. Our findings may have important implications for the prevention of AAD by tailoring treatment strategies to ensure maximal benefits during the vulnerable periods.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 it