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Novel and Innovative Hybrid Technique for Type A Aortic Dissection
Published on: March 28, 2025
Chronobiological patterns of acute aortic dissection in central China
Liangtao Xia1, Lu Huang2, Xin Feng1
1Division of Cardiothoracic and Vascular Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Insights
Acute aortic dissection (AAD) shows distinct seasonal and circadian patterns, with higher incidence in colder months and specific daily peaks. Understanding these patterns may help in AAD prevention.
Area of Science:
- Cardiology
- Public Health
- Epidemiology
Background:
- Acute aortic dissection (AAD) is a critical medical emergency with high mortality rates.
- Identifying temporal patterns of AAD onset is crucial for understanding its triggers and improving prevention strategies.
Purpose of the Study:
- To investigate the seasonal, weekly, and circadian patterns of AAD onset.
- To explore potential differences in these patterns among patient subgroups.
Main Methods:
- Analysis of data from 2048 AAD patients diagnosed between 2011 and 2018.
- Utilized chi-squared tests for seasonal/weekly distribution analysis.
- Employed Fourier models to assess monthly and circadian rhythmicity.
Main Results:
- AAD incidence peaked in colder months (winter/December) and was lowest in warmer months (summer/June).
- Significant circadian variations were observed, with a nocturnal trough and two daily peaks (morning and afternoon).
- Circadian rhythmicity was noted in most subgroups, except for females and individuals under 55.
Conclusions:
- AAD onset demonstrates significant seasonal, monthly, and circadian patterns.
- Subgroup analyses reveal variations in circadian patterns based on dissection type, sex, age, and hypertension status.
- These findings offer new insights for AAD trigger identification and prevention.
Background:
Acute aortic dissection (AAD) is a life-threatening emergency with poor clinical outcomes. Understanding the chronological patterns of AAD onset would be helpful for identifying the triggers of AAD and preventing this catastrophic event.
Methods:
We collected data from 2048 patients diagnosed with AAD at Tongji Hospital (Wuhan, China) from 2011 to 2018. The χ2 test was used to determine whether a specific period had significantly different seasonal/weekly distributions from other periods. Fourier models were used to analyse the rhythmicity in monthly/circadian distribution.
Results:
The mean age was 53.4±10.9 years, and 1161 patients (56.7%) were under 55 years. One thousand six hundred fifty-seven patients (80.9%) were male, and 935 cases (45.7%) were type A dissections. The proportions of patients with comorbid hypertension/diabetes were 60.3% (1234 cases) and 1.8% (36 cases), respectively. A peak was identified in colder periods (winter/December) and a trough in warmer periods (summer/June). No significant variation was observed in weekly distribution. Fourier analysis showed a statistically significant circadian variation (p<0.001) with a nocturnal trough in 2:00-3:00, a morning peak in 9:00-10:00, and an afternoon peak in 16:00-17:00. Subgroup analyses identified circadian rhythmicity in all subgroups except for the female group and younger group (younger than 55 years).
Conclusion:
Our results confirmed that the onset of AAD exhibits significant seasonal, monthly and circadian patterns. Patients with AAD with different Stanford-type dissections, sexes, ages and hypertension statuses could present different circadian variations. These findings may provide novel perspectives for identifying the triggers of AAD and better preventing this catastrophic event.
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