| Literature DB >> 33789760 |
Robin Jansen1, John-Ih Lee2, Bernd Turowski3, Marius Kaschner3, Julian Caspers3, Michael Bernhard4, Hans-Peter Hartung1,5,6, Sebastian Jander1, Tobias Ruck1, Sven G Meuth1, Michael Gliem1.
Abstract
BACKGROUND: COVID-19 pandemic caused a decline in stroke care in several countries. The objective was to describe lockdown stroke care in a tertiary stroke center in Düsseldorf, Germany near Heinsberg, a German hot spot for COVID-19 in spring 2020.Entities:
Keywords: COVID-19; Lockdown; Pandemic; Stroke
Year: 2021 PMID: 33789760 PMCID: PMC8011045 DOI: 10.1186/s42466-021-00118-z
Source DB: PubMed Journal: Neurol Res Pract ISSN: 2524-3489
Fig. 1Flowchart of analyzed patients during COVID-19 spring lockdown (16 March – 12 April 2020) comparative time period one year ago (16 March – 12 April 2019) and lockdown light (2 November 2020–29 November 2020)
Fig. 2Comparison of mean patient numbers per day in control vs lockdown and lockdown light period (a) treated in the ED (mean 117.8 vs 73.8, n = 3299 vs n = 2067 reduction 37.4% and vs lockdown light with mean 90.18 and n = 2525, reduction 23.45%, p < 0.0001), (b) seen by a neurologist in the ED (mean 17.1 vs 11, n = 478 vs n = 308, reduction 35.6%, p < 0.0001 and vs lockdown light with mean 13.46 and n = 377, reduction 21.2%, p < 0.01), (c) with diagnosis of ischemic or hemorrhagic stroke or TIA in the ED (mean 3.2 vs 2.6, n = 89 vs n = 72, reduction 19.1%, and vs lockdown light with mean 3.2 and n = 90, non-significant increase by 1.1%) (d) with diagnosis of ischemic or hemorrhagic stroke or TIA admitted to our stroke unit (2.5 vs 2.3, reduction 10% and vs lockdown light with mean 2.4 by 2.9%. Daily admissions were tested by one-way ANOVA with Bonferroni correction. Results were assumed statistically significant with * = p < 0.05. ** = p < 0.01.*** = p < 0.0001. Ns indicates non-statistical significance
Baseline and outcome parameters of patients admitted to the stroke unit
| Time interval | A | B | C | ||||
|---|---|---|---|---|---|---|---|
| n= | 70 | 63 | 68 | ||||
| Median age (IQR) | 79 (69–85) | 77 (64–82) | 80 (62–85) | ns, ANOVA | |||
| Male gender | 32 (45.7%) | 30 (47.6%) | 32 (47.1%) | ns, Kruskal-Wallis-Test | |||
| Vascular risk factors | |||||||
| Arterial hypertension | 55 (78.6%) | 44 (69.8%) | 49 (72.1%) | ns, Kruskal-Wallis-Test | |||
| Diabetes Mellitus | 14 (20%) | 18 (28.6%) | 17 (25.0%) | ns, Kruskal-Wallis-Test | |||
| Hyperlipidemia | 27 (38.6%) | 18 (28.6%) | 23 (33.8%) | ns, Kruskal-Wallis-Test | |||
| Coronary heart disease | 14 (20%) | 9 (14.3%) | 13 (19.1%) | ns, Kruskal-Wallis-Test | |||
| Smoking | 5 (7.1%) | 10 (15.9%) | 8 (11.9%) | ns, Kruskal-Wallis-Test | |||
| Peripheral artery disease | 3 (4.3%) | 5 (7.9%) | 3 (4.4%) | ns, Kruskal-Wallis-Test | |||
| No vascular risk factors | 6 (8.6%) | 4 (6.3%) | 0 (0%) | ns, Kruskal-Wallis-Test | |||
| Type of stroke | |||||||
| Cerebral infarction | 53 (75.7%) | 47 (74.6%) | 53 (77.9%) | ns, Kruskal-Wallis-Test | |||
| TIA | 11 (15.7%) | 10 (15.9%) | 11 (16.2%) | ns, Kruskal-Wallis-Test | |||
| Intracerebral hemorrhage | 6 (8.6%) | 6 (9.5%) | 4 (5.9%) | ns, Kruskal-Wallis-Test | |||
| Ischemic stroke etiology | |||||||
| Cardioembolic | 23 (32.9%) | 21 (33.3%) | 13 (19.1%) | ns, Kruskal-Wallis-Test | |||
| Embolic stroke of undetermined source | 6 (8.6%) | 10 (15.9%) | 19 (27.9%) | ns, Kruskal-Wallis-Test | |||
| Microangiopathic | 12 (17.1%) | 13 (20.6%) | 6 (8.8%) | ns, Kruskal-Wallis-Test | |||
| Macroangiopathic/Large artery arteriosclerosis | 10 (14.3%) | Kruskal-Wallis-Test | |||||
| Patent foramen ovale associated | 5 (7.1%) | 3 (4.8%) | 3 (4.4%) | ns, Kruskal-Wallis-Test | |||
| Unknown ischemic stroke etiology | 8 (11.4%) | 6 (9.5%) | 12 (17.6%) | ns, Kruskal-Wallis-Test | |||
| Large vessel occlusion (ICA, carotid T, M1, M2, basilar artery) | 25 (36%) | 11 (17%) | 15 (22%) | ns, Kruskal-Wallis-Test | |||
| Clinical and intrahospital management characteristics | |||||||
| I.v. thrombolysis | 17 (24.3%) | 15 (23.8%) | 14 (20.6%) | ns, Kruskal-Wallis-Test | |||
| Endovascular therapy | 10 (14.7%) | ||||||
| Admission within 4.5 h after stroke onset | 21 (30%) | 21 (33.3%) | 32 (47.1%) | ns, Kruskal-Wallis-Test | |||
| Median onset to door time in minutes (IQR) | 99.0 (57.0–445.25) | 120.5 (55.5–300.5) | 120 (59–684) | ns, Kruskal-Wallis-Test | |||
| Median door to needle time in minutes (IQR) | 47 (37.3–57.3) | 42 (20–62.5) | 40 (28.25–78.75) | ns, ANOVA | |||
| Median door to groin puncture time in minutes (IQR) | 77 (32–116) | 85 (36–85) | 121.50 (26.25–176.25) | ns, ANOVA | |||
| Median NIHSS at admission (IQR) | 4 (1–11) | 4 (1.8–10) | 5 (1.5–8) | ns, Kruskal-Wallis-Test | |||
| Median NIHSS at discharge (IQR) | 1 (0–4) | 1 (0–5) | 1 (0–5.5) | ns, Kruskal-Wallis-Test | |||
| Median mRS at admission (IQR) | 3 (1–5) | 3 (2–4) | 3 (2–4) | ns, Kruskal-Wallis-Test | |||
| Median mRS at discharge (IQR) | 2 (0–4) | 2 (1–4) | 2 (1–4) | ns, Kruskal-Wallis-Test | |||
| Median In-hospital days (IQR) | 6 (4–9) | 6 (4–9) | 7.5 (5–11) | ns, Kruskal-Wallis-Test | |||
| In-hospital deaths | 9 (12.9%) | 8 (12.7%) | 7 (10.3%) | ns, Kruskal-Wallis-Test | |||
Continuous variables are reported as medians with interquartile range (IQR), categorial variables are reported as absolute numbers and as proportion. Between-group comparisons for categorical data were analyzed using Kruskal-Wallis-test and post-hoc Mann Whitney U test with Bonferroni correction. Group comparisons for continuous data were performed with ANOVA and post-hoc Bonferroni correction (normally distributed) or Kruskal-Wallis-test and post-hoc Mann Whitney U test with Bonferroni correction (non-normally distributed). All tests were two tailed and results were assumed statistically significant with p < 0.05. Ns indicates non-statistical significance