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  • Has COVID-19 played an unexpected "stroke" on the chain of survival? #MMPMID32416370
  • Naccarato M; Scali I; Olivo S; Ajcevic M; Buoite Stella A; Furlanis G; Lugnan C; Caruso P; Peratoner A; Cominotto F; Manganotti P
  • J Neurol Sci 2020[Jul]; 414 (ä): 116889 PMID32416370show ga
  • BACKGROUND: The COVID-19 pandemics required several changes in stroke management and it may have influenced some clinical or functional characteristics. We aimed to evaluate the effects of the COVID-19 pandemics on stroke management during the first month of Italy lockdown. In addition, we described the emergency structured pathway adopted by an Italian University Hub Stroke Unit in the cross-border Italy-Slovenia area. METHODS: We analyzed admitted patients' clinical features and outcomes between 9th March 2020 and 9th April 2020 (first month of lockdown), and compared them with patients admitted during the same period in 2019. RESULTS: Total admissions experienced a reduction of 45% during the lockdown compared to the same period in 2019 (16 vs 29, respectively), as well as a higher prevalence of severe stroke (NIHSS>10) at admission (n = 8, 50% vs n = 8, 28%). A dramatic prevalence of stroke of unknown symptom onset was observed in 2020 (n = 8, 50% vs n = 3, 10%). During lockdown, worse functional and independence outcomes were found, despite the similar proportion of reperfused patients. Similar 'symptoms alert-to-admission' and 'door-to-treatment' times were observed. During lockdown hospitalization was shorter and fewer patients completed the stroke work-up. CONCLUSION: In conclusion, the adopted strategies for stroke management during the COVID-19 emergency have suggested being effective, while suffering a reduced and delayed reporting of symptoms. Therefore, we recommend raising awareness among the population against possible stroke symptoms onset. Thus, think F.A.S.T. and do not stay-at-home at all costs.
  • |*Betacoronavirus[MESH]
  • |*Coronavirus Infections/complications/epidemiology[MESH]
  • |*Delivery of Health Care/statistics & numerical data[MESH]
  • |*Disease Management[MESH]
  • |*Health Services Accessibility/statistics & numerical data[MESH]
  • |*Pandemics[MESH]
  • |*Pneumonia, Viral/complications/epidemiology[MESH]
  • |Aged[MESH]
  • |Aged, 80 and over[MESH]
  • |Clinical Protocols[MESH]
  • |Comorbidity[MESH]
  • |Delayed Diagnosis[MESH]
  • |Emergency Service, Hospital/statistics & numerical data[MESH]
  • |Fear[MESH]
  • |Female[MESH]
  • |Hospital Units[MESH]
  • |Hospitalization/statistics & numerical data[MESH]
  • |Hospitals, University/organization & administration/statistics & numerical data[MESH]
  • |Humans[MESH]
  • |Italy[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Patient Admission/statistics & numerical data[MESH]
  • |Quarantine[MESH]
  • |Retrospective Studies[MESH]
  • |Risk Factors[MESH]
  • |Stroke/epidemiology/etiology/mortality/*therapy[MESH]
  • |Time-to-Treatment/statistics & numerical data[MESH]

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  • suck abstract from ncbi

    116889 ä.414 2020