Cargando…

Stroke patterns and outcomes during the second wave of COVID-19 pandemic: a cross-sectional study

The coronavirus disease 2019 (COVID-19) pandemic has affected the number of stroke activations, admission of patients with various types of strokes, the rate and timely administration of reperfusion therapy, and all types of time-based stroke-related quality assessment metrics. In this study, we des...

Descripción completa

Detalles Bibliográficos
Autores principales: Gajurel, Bikram P., Giri, Subarna, Tamrakar, Parishma, Pandeya, Anupama, Gautam, Niraj, Shrestha, Aashish, Karn, Ragesh, Rajbhandari, Reema, Ojha, Rajeev
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289718/
https://www.ncbi.nlm.nih.gov/pubmed/37363610
http://dx.doi.org/10.1097/MS9.0000000000000722
Descripción
Sumario:The coronavirus disease 2019 (COVID-19) pandemic has affected the number of stroke activations, admission of patients with various types of strokes, the rate and timely administration of reperfusion therapy, and all types of time-based stroke-related quality assessment metrics. In this study, we describe the different types of strokes, different delays in seeking and completing treatment occurring during the second wave of the COVID-19 pandemic, and predictors of outcome at 3 months follow-up. MATERIALS AND METHODS: This is a single-centered prospective cross-sectional study carried out from May 2021 to November 2021, enrolling patients with stroke. Data collected were demographic characteristics, stroke types and their outcomes, and different types of prehospital delays. RESULTS: A total of 64 participants were included in the study with a mean age of 60.25±15.31 years. Ischemic stroke was more common than hemorrhagic stroke. The median time of arrival to the emergency room of our center was 24 h. The most common cause of prehospital delay was found to be delays in arranging vehicles. The median duration of hospital stays [odds ratio (OR)=0.72, P<0.05] and baseline NIHSS (National Institute of Health Stroke Scale) score (OR=0.72, P<0.05) were found to be a predictor of good outcomes at 3 months follow-up on binary logistic regression. CONCLUSION: The factors that cause the delayed transfer to the hospital and onset of treatment should be addressed. Patient counseling about the likely prognosis can be done after evaluating the probable outcome based on the NIHSS score and median duration of hospital stay. Nevertheless, mechanisms should be developed to reduce the prehospital delay at the ground level as well as at the policy level.