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Neurol Sci ; 2022 Jan 31.
Article in English | MEDLINE | ID: covidwho-2244052


INTRODUCTION: During the first wave of the COVID-19 pandemic in spring 2020, our stroke network shifted from a drip-and-ship strategy (transport of acute ischemic stroke patients to the nearest primary stroke centers) toward a mothership model (direct transportation to the Comprehensive Stroke Center). We retrospectively analyzed stroke network performances comparing the two models. PATIENTS AND METHODS: All spoke-district patients treated with endovascular thrombectomy (EVT) between 15th March-15th June 2019 (drip-and-ship) and 2020 (mothership) were considered. We compared onset-to-groin time (OGT) and onset-to-needle time (ONT) between the two periods. Secondarily, we investigated other performances parameters (percentage of IV thrombolysis, timing of diagnostic and treatment) and clinical outcome (3-month modified Rankin Scale). RESULTS: Twenty-four spoke-district patients in 2019 (drip-and-ship) and 26 in 2020 (mothership) underwent EVT. The groups did not differ for age, sex, risk factors, pre-stroke mRS 0-1, NIHSS, and ASPECTS distribution. The MS model showed a significant decrease of the OGT (162.5 min vs 269 min, p = 0.001) without significantly affecting the ONT (140.5 min vs 136 min, p = 0.853), ensuring a higher number of IV thrombolysis in combination with EVT (p = 0.030). The mothership model showed longer call-to-door time (median + 23 min, p < 0.005), but shorter door-to-needle (median - 31 min, p = 0.001), and door-to-groin time (- 82.5 min, p < 0.001). We found no effects of the stroke network model on the 3-month mRS (ordinal shift analysis, p = 0.753). CONCLUSIONS: The shift to the mothership model during the COVID-19 pandemic guaranteed quicker EVT without significantly delaying IVT.

Int J Stroke ; 16(7): 771-783, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1374086


BACKGROUND: The effect of the COVID pandemic on stroke network performance is unclear, particularly with consideration of drip&ship vs. mothership models. AIMS: We systematically reviewed and meta-analyzed variations in stroke admissions, rate and timing of reperfusion treatments during the first wave COVID pandemic vs. the pre-pandemic timeframe depending on stroke network model adopted. SUMMARY OF FINDINGS: The systematic review followed registered protocol (PROSPERO-CRD42020211535), PRISMA and MOOSE guidelines. We searched MEDLINE, EMBASE, and CENTRAL until 9 October 2020 for studies reporting variations in ischemic stroke admissions, treatment rates, and timing in COVID (first wave) vs. control-period. Primary outcome was the weekly admission incidence rate ratio (IRR = admissions during COVID-period/admissions during control-period). Secondary outcomes were (i) changes in rate of reperfusion treatments and (ii) time metrics for pre- and in-hospital phase. Data were pooled using random-effects models, comparing mothership vs. drip&ship model. Overall, 29 studies were included in quantitative synthesis (n = 212,960). COVID-period was associated with a significant reduction in stroke admission rates (IRR = 0.69, 95%CI = 0.61-0.79), with higher relative presentation of large vessel occlusion (risk ratio (RR) = 1.62, 95% confidence interval (CI) = 1.24-2.12). Proportions of patients treated with endovascular treatment increased (RR = 1.14, 95%CI = 1.02-1.28). Intravenous thrombolysis decreased overall (IRR = 0.72, 95%CI = 0.54-0.96) but not in the mothership model (IRR = 0.81, 95%CI = 0.43-1.52). Onset-to-door time was longer for the drip&ship in COVID-period compared to the control-period (+32 min, 95%CI = 0-64). Door-to-scan was longer in COVID-period (+5 min, 95%CI = 2-7). Door-to-needle and door-to-groin were similar in COVID-period and control-period. CONCLUSIONS: Despite a 35% drop in stroke admissions during the first pandemic wave, proportions of patients receiving reperfusion and time-metrics were not inferior to control-period. Mothership preserved the weekly rate of intravenous thrombolysis and the onset-to-door timing to pre-pandemic standards.

COVID-19 , Hospitalization/statistics & numerical data , Stroke/therapy , Thrombolytic Therapy , Humans , Incidence , Pandemics , Reperfusion , Time-to-Treatment
Neurol Sci ; 42(2): 399-406, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-938581


BACKGROUND: During the coronavirus disease 2019 (COVID-19) outbreak, a decrease of stroke's hospital admissions and reperfusion therapy has been reported worldwide. This retrospective observational study assessed the volume of stroke cases managed in the Emergency Department (ED) and reperfusion therapies in an Italian stroke network with a high incidence of COVID-19, particularly to evaluate if the in-hospital rerouting and the switch from a drip-and-ship to a mothership model could assure an adequate volume of acute treatments. METHODS: We compared data from March 2020 with those from previous years and formulated five PICO questions regarding (1) incidence of stroke cases in the ED; (2) relation between stroke cases and COVID-19; (3) differences in the number of reperfusion therapies, (4) in the call-to-needle and door-to-needle times for intravenous thrombolysis, and (5) in the call-to-groin and door-to-groin times for thrombectomy. RESULTS: We found (1) a 28% decreased of confirmed stroke cases managed in the ED, (2) a negative correlation between stroke cases in ED and COVID-19 progression (rs = - .390, p = .030), and (3) a similar number of treatments in March 2020 and March 2019. The adoption of the mothership model (4) did not delay alteplase infusion (median call-to-needle p = .126, median door-to-needle p = .142) but led to (5) a significant reduction in median call-to-groin (p = .018) and door-to-groin times (p = .010). CONCLUSION: The "hospital avoidance" of stroke patients during the "stay-at-home" appeals needs to be considered for future public health campaigns. A prompt reorganization of the stroke network can guarantee optimal performances at times of crisis.

COVID-19 , Emergency Service, Hospital/statistics & numerical data , Physical Distancing , Reperfusion/statistics & numerical data , Stroke/therapy , Thrombectomy/statistics & numerical data , Thrombolytic Therapy/statistics & numerical data , COVID-19/prevention & control , Humans , Italy , Models, Organizational , Outcome Assessment, Health Care , Retrospective Studies , Time Factors