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The Incidence and Associated Factors of Early Neurological Deterioration After Thrombolysis Results From SITS Registry

Publikace na Lékařská fakulta v Plzni |
2020

Tento text není v aktuálním jazyce dostupný. Zobrazuje se verze "en".Abstrakt

Background and purpose: Early neurological deterioration (END) after stroke onset may predict severe outcomes. Estimated rates of END after intravenous thrombolysis among small patient samples have been reported up to 29.8%.

We studied the incidence and factors associated with END among patients following intravenous thrombolysis. Methods: We analyzed SITS-International Stroke Thrombolysis registry patients with known outcomes enrolled in 2010 to 2017.

END was defined as an increase in National Institutes of Health Stroke Scale score >= 4 or death within 24 hours from baseline National Institutes of Health Stroke Scale. We determined the incidence of END and used logistic regression models to inspect its associated factors.

We adjusted for variables found significant in univariate analyses (P<0.05). Main outcomes were incidence of END, associated predictors of END, ordinal day-90 mRS, and day-90 mortality.

Results: We excluded 53 539 patients and included 50 726 patients. The incidence of END was 3415/50 726 (6.7% [95% CI, 6.5%-7.0%]).

Factors independently associated with END on multivariate analysis were intracerebral hemorrhage (OR, 3.23 [95% CI, 2.96-3.54],P<0.001), large vessel disease (LVD) with carotid stenosis (OR, 2.97 [95% CI, 2.45-3.61],P<0.001), other LVD (OR, 2.41 [95% CI, 2.03-2.88],P<0.001), and ischemic stroke versus transient ischemic attack (TIA)/stroke mimics (OR, 16.14 [95% CI, 3.99-65.3],P<0.001). END was associated with worse outcome on ordinal mRS: adjusted OR 2.48 (95% CI, 2.39-2.57,P<0.001) by day-90 compared with no END.

The adjusted OR for day-90 mortality was 9.70 (95% CI, 8.36-11.26,P<0.001). Conclusions: The routinely observed rate of END reflected by real-world data is low, but END greatly increases risk of disability and mortality.

Readily identifiable factors predict END and may help with understanding causal mechanisms to assist prevention of END.