2026 American Academy of Neurology Abstract Website

Objective:

To assess seasonal and year-to-year variation in ischemic stroke severity and in-hospital mortality using the U.S. National Inpatient Sample (NIS) from 2016-2022.

Background:

Although seasonal variation in stroke incidence and outcomes has been reported, large-scale, nationally representative analyses remain limited with prior work conveyed from single-center or regional studies. We examined whether ischemic stroke severity and in-hospital mortality varied by admission month and year in the U.S. using the National Inpatient Sample (NIS).

Design/Methods:

We analyzed adult patients (≥18 years) admitted non-electively with ischemic stroke in the NIS from 2016–2022. Stroke severity was measured using the National Institutes of Health Stroke Scale (NIHSS), and in-hospital mortality was modeled using multivariable logistic regression adjusted for age, sex, race, comorbidities and hospital region. Adjusted predictive margins with 95% confidence intervals were generated by admission month and year to assess seasonal and annual trends.

Results:

A total of 326,938 ischemic stroke admissions were included. Mean NIHSS varied significantly by month (p < 0.01), with higher severity during winter months (January–March: mean ≈ 6.8) compared with summer (June–August: mean ≈ 6.4), as shown by adjusted predictive margins and observed means. Over time, stroke severity increased from 2016 to 2022, while adjusted mortality declined through 2019 and rose slightly during 2020–2022, coinciding with the COVID-19 period. These patterns persisted after adjustment for demographics, comorbidities, and hospital characteristics.

Conclusions:

In this large, nationally representative cohort, both stroke severity and in-hospital mortality illustrated distinct patterns. Severity peaked during winter months and mortality showed an increase in recent years. These findings suggest that environmental and system-level factors like infection burden, temperature variation and healthcare resource strain may underlie these differences. Understanding these cyclical patterns can help inform hospital preparedness, prevention efforts during high-risk periods, and support future work to identify predictors of seasonal variation in stroke outcomes.