| Literature DB >> 32989032 |
Adam de Havenon1, Shadi Yaghi2, Eva A Mistry3, Alen Delic4, Samuel Hohmann5, Ernie Shippey5, Eric Stulberg4, David Tirschwell6, Jennifer A Frontera2, Nils H Petersen7, Mohammad Anadani8.
Abstract
BACKGROUND: We aimed to compare the outcome of acute ischemic stroke (AIS) patients who received endovascular thrombectomy (EVT) with confirmed COVID-19 to those without.Entities:
Keywords: infection; stroke; thrombectomy
Mesh:
Year: 2020 PMID: 32989032 PMCID: PMC7523171 DOI: 10.1136/neurintsurg-2020-016777
Source DB: PubMed Journal: J Neurointerv Surg ISSN: 1759-8478 Impact factor: 8.572
Baseline demographics and outcomes of patients discharged with acute ischemic stroke who had endovascular thrombectomy, with and without COVID-19.
| Variable | COVID - | COVID + | P-value* |
| Age category (years) | |||
| 18–50 (n, %) | 388 (12.7%) | 25 (24.0%) | |
| 51–64 | 770 (25.1%) | 38 (36.5%) | <0.001 |
| 65–74 | 771 (25.2%) | 19 (18.3%) | |
| ≥75 | 1132 (37.10%) | 22 (21.2%) | |
| Male sex | 1571 (51.3%) | 71 (68.3%) | 0.001 |
| Race | |||
| White | 2003 (65.4%) | 27 (26.0%) | |
| Black | 517 (16.9%) | 27 (26.0%) | <0.001 |
| Hispanic | 172 (5.6%) | 20 (19.2%) | |
| Asian | 86 (2.8%) | suppressed | |
| Other/unknown | 283 (9.3%) | 26 (25.0%) | |
| Elixhauser comorbidity score | |||
| Median (IQR) | 4, 3–5 | 4, 3–5 | 0.672 |
| Congestive heart failure | 883 (28.9%) | 32 (30.8%) | 0.671 |
| Obese | 620 (20.3%) | 26 (25.0%) | 0.238 |
| Smoker | 490 (16.0%) | suppressed | 0.011 |
| Atrial fibrillation | 1301 (42.5%) | 30 (28.9%) | 0.006 |
| Diabetes | 1038 (33.9%) | 49 (47.1%) | 0.005 |
| Dyslipidemia | 1961 (64.1%) | 58 (55.8%) | 0.083 |
| Hypertension | 2327 (76.0%) | 74 (71.2%) | 0.254 |
| Interfacility transfer | 1280 (41.8%) | 34 (32.7%) | 0.063 |
| Mechanical ventilation | 923 (30.2%) | 56 (53.9%) | <0.001 |
| Acute renal failure | 639 (20.9%) | 36 (34.6%) | 0.001 |
| Acute coronary syndrome | 274 (9.0%) | 18 (17.3%) | 0.004 |
| Pulmonary embolism | 87 (2.8%) | suppressed | 0.241 |
| Length of hospital stay (days) | 9.1 (10.6) | 14.2 (15.4) | <0.001 |
| Length of intensive care unit stay (days)* | 4.1 (6.0) | 6.2 (8.0) | 0.002 |
| Favorable discharge | 1893 (61.8%) | 49 (47.1%) | 0.002 |
| In-hospital death | 378 (12.4%) | 31 (29.8%) | <0.001 |
*Binary variables presented as n, %; ordinal variables as median, IQR; interval variables as mean (SD). P-values calculated with the chi-squared test for binary variables, the Wilcoxon rank-sum test for ordinal variables, and student’s t-test for interval variables. Length of intensive care unit stay restricted to patients with >24 hours spent in intensive care. Some values are suppressed for low count. White and black racial categories are non-Hispanic.
Mixed-effects logistic regression fit to in-hospital death and favorable discharge, showing ORs for patients with comorbid COVID-19
| OR for death | 95% CI* | SE* | P-value | OR for favorable discharge | 95% CI* | SE* | P-value | |
| Model 1† | 4.48 | 3.02 to 6.65 | 0.90 | <0.001 | 0.43 | 0.30 to 0.61 | 0.08 | <0.001 |
| Model 2† | 3.37 | 1.77 to 6.43 | 1.11 | <0.001 | 0.58 | 0.36 to 0.91 | 0.14 | 0.019 |
*CI: confidence interval, SE: standard error, calculated with 1000 cluster bootstrap replications.
†Model 1 adjusted for patient age, sex, race, ethnicity, and Elixhauser comorbidity score. Model 2 adjusted for patient age, sex, race, ethnicity, Elixhauser comorbidity score, acute respiratory failure requiring intubation, acute coronary syndrome, acute renal failure, pulmonary embolus, and hospital length of stay.
Mixed-effects logistic regression fit to in-hospital death and favorable discharge, showing ORs for AIS patients with COVID-19 who did not undergo EVT compared with those had EVT
| OR for death | 95% CI | SE | P-value | OR for favorable discharge | 95% CI | SE | P-value | |
| Model 1* | 1.14 | 0.73 to 1.79 | 0.24 | 0.564 | 0.68 | 0.44 to 1.06 | 0.15 | 0.091 |
| Model 2* | 1.52 | 0.87 to 2.66 | 0.44 | 0.140 | 0.55 | 0.34 to 0.89 | 0.14 | 0.015 |
*Model 1 adjusted for patient age, sex, race, ethnicity, and Elixhauser comorbidity score. Model 2 adjusted for patient age, sex, race, ethnicity, Elixhauser comorbidity score, acute respiratory failure requiring intubation, acute coronary syndrome, acute renal failure, pulmonary embolus, and hospital length of stay.