AIS patients with different TOAST subtypes show distinct onset rhythms across circadian, seasonal, and weekday/holiday distributions, with LAA peaking in early morning, CE clustering at night, and SAO peaking in Quarter 3.
Key Findings
Results
Large-artery atherosclerosis (LAA) stroke patients had higher incidence of onset in the early morning hours.
A total of 722 AIS patients were enrolled from the Emergency Stroke Center of the 960th Hospital of PLA between January 4, 2019 and December 30, 2024.
Patients were classified into LAA, SAO, and CE subgroups based on TOAST criteria using medical history and examination results.
LAA subtype showed a clustered onset pattern during early morning, consistent with circadian physiological changes such as increased platelet aggregability and blood pressure surges in the morning.
Results
Cardioembolism (CE) stroke patients showed clustered onset at night, distinguishing them from other TOAST subtypes.
CE patients exhibited a nocturnal onset pattern, differing markedly from the early morning peak seen in LAA patients.
This nighttime clustering in CE may reflect the arrhythmic or cardiac-related mechanisms underlying cardioembolic stroke.
The distinct nocturnal pattern of CE was identified across the 722-patient cohort enrolled over approximately five years.
Results
Small-artery occlusion (SAO) stroke patients had higher incidence in the third quarter (July–September), while LAA and CE patients had higher incidence in the first quarter (January–March).
Seasonal analysis revealed that LAA and CE subtypes both showed higher incidence in Quarter 1 (winter/early spring).
SAO patients, by contrast, showed higher incidence in Quarter 3 (summer), indicating a divergent seasonal pattern compared to the other two subtypes.
These seasonal differences suggest subtype-specific environmental or physiological triggers influencing stroke onset across seasons.
Results
Acute ischemic stroke onset showed a significant morning peak on weekdays but an irregular onset rhythm on holidays.
On weekdays, stroke onset was concentrated in the morning hours, reflecting the influence of routine daily activity schedules on stroke timing.
On holidays, this morning peak was absent, and onset patterns were irregular, suggesting that behavioral and social factors modulate stroke onset rhythms.
This weekday versus holiday difference was observed across the full 722-patient cohort and represents a notable behavioral influence on stroke epidemiology.
Methods
The study enrolled 722 acute ischemic stroke patients admitted to the Emergency Stroke Center over approximately five years, classifying them into three TOAST subtypes for rhythmic analysis.
Patients were admitted between January 4, 2019 and December 30, 2024 from the 960th Hospital of PLA.
The three subgroups analyzed were large-artery atherosclerosis (LAA), small-artery occlusion (SAO), and cardioembolism (CE).
Comparisons among groups included onset time, laboratory test results, and clinical symptoms.
The study investigated rhythmic variations across circadian, seasonal, and weekday/holiday dimensions for each subtype.
What This Means
This research suggests that strokes do not occur randomly throughout the day, year, or week — rather, different types of stroke tend to strike at predictable times depending on their underlying cause. The study followed 722 stroke patients over five years and grouped them by stroke subtype: those caused by large artery disease, small vessel disease, or blood clots traveling from the heart. The researchers found that large-artery strokes tended to happen in the early morning, heart-related strokes clustered at night, and small-vessel strokes were more common in summer, while the other two types were more common in winter.
The study also found that on regular weekdays, strokes peaked in the morning — likely because people wake up and resume physical and mental activity — but on holidays, this pattern disappeared and stroke timing became more unpredictable. This points to the role that daily routines and behavioral patterns play in triggering stroke events.
This research suggests that hospitals and health systems could use these timing patterns to develop more targeted prevention strategies — for example, scheduling preventive medications or monitoring more intensively during high-risk time windows specific to each stroke subtype. Understanding when different types of strokes are most likely to occur could help both clinicians and patients take precautionary measures at the right times.
Li W, Zang L, Zhang Y, Gao Y, Ni N, Liu H, et al.. (2026). Difference of onset rhythm in acute ischemic stroke patients with different TOAST subtypes.. PloS one. https://doi.org/10.1371/journal.pone.0357414