Acute Ischemic Stroke and COVID-19: An Analysis of 27 676 Patients

Adnan I. Qureshi, MD; William I. Baskett, BS; Wei Huang, MA; Daniel Shyu, BS; Danny Myers, PhD; Murugesan Raju, PhD; Iryna Lobanova, MD; M. Fareed K. Suri, MD; S. Hasan Naqvi, MD; Brandi R. French, MD; Farhan Siddiq, MD; Camilo R. Gomez, MD; Chi-Ren Shyu, PhD

Disclosures

Stroke. 2021;52(3):905-912. 

In This Article

Methods

We performed this retrospective cohort study with short-term (in hospital) follow-up by analyzing the data from the Cerner deidentified COVID-19 dataset—a subset of Cerner Real-World Data extracted from the electronic medical records of health care facilities that have a data use agreement with Cerner Corporation.[17,18] The methodological aspects of the dataset are available in another publication.[19] The data are based on electronic medical encounters between December 2019 and April 2020. The dataset as part of deidentification procedure does not provide data on regions and hospitals. Institutional review board approval was not required as the data analyzed consisted of deidentified medical encounters. The dataset is available through Cerner Corporation and includes data for patients who qualified for inclusion based on the following criteria:

  1. Patient has a minimum of 1 emergency department or inpatient encounter with a discharge diagnosis code that could be associated with exposure to or clinical suspicion of COVID-19 or

  2. Patient has a minimum of 1 emergency department or inpatient encounter with a positive laboratory test for COVID-19.

The Cerner Real-World Data-COVID-2020Q2apr version of the data included data from 54 contributing Cerner Real-World Data health systems that had qualifying patients. The dataset included both patients in whom COVID-19 was confirmed and those in whom the diagnosis was suspected but excluded. In general, Cerner Real-World Data comprise >100 clinical and nonclinical variables associated with hospital stays, including primary and secondary diagnoses, primary and secondary procedures, patients' admission and discharge status, and patient demographic information. Race was coded into various categories (White, Black, Asian or Pacific Islander, or American Indian or Alaska Native), and ethnicity was coded as Hispanic or non-Hispanic as recorded in electronic medical records within the US population. The Cerner Corporation has established Health Insurance Portability and Accountability Act–compliant operating policies to establish deidentification for Cerner Real-World Data.

We used the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), primary discharge diagnosis codes I63, I65, and I66 to identify the patients admitted with acute ischemic stroke. The ICD-10-CM codes were used to identify patients with hypertension (I10, O10.0, O10.9, I16, and I67.4), diabetes (E08, E09, E10, E11, and E13), nicotine dependence (F17), hyperlipidemia (E78), atrial fibrillation (I48), and congestive heart failure (I09.81, I11.0, and I50). The ICD-10-CM secondary diagnosis codes were used to identify those with stroke-associated complications such as cerebral edema (G93.5 and G93.6), acute kidney injury (N17), hepatic failure (K72), cardiac arrest (I46), systemic inflammatory response syndrome (R65.1), respiratory failure (J96), pneumonia (J12–J18), urinary tract infection (N30.0, N30.9, N34.1, N34.2, and N39.0), septic shock (A41 and R65.21), deep venous thrombosis (I82), pulmonary embolism (I26), intracerebral (I61 and I62.9) or subarachnoid hemorrhage (I60), and acute myocardial infarction (I21). We also used ICD-10-CM procedure codes and current procedural terminology codes to estimate the proportion of acute ischemic stroke patients who underwent thrombolytic treatment identified by ICD-10 procedure codes 3E03317 and 3E06317 or current procedural terminology codes 37195 and mechanical thrombectomy or intraarterial thrombolytic administration by ICD-10 procedure codes (03CG3ZZ, 03CG3Z7, 03CH3Z7, 03CJ0ZZ, 03CJ3ZZ, 03CK3Z7, 03CK3ZZ, 03CL3Z7, 03CL3ZZ, 03CL0ZZ, 03CP3ZZ, 03CY3ZZ, 00C73ZZ or 3E03317, and 3E06317) or current procedural terminology codes 61654 or 37195. Intubation and mechanical ventilation were identified by ICD-10-CM codes 0BJ17EZ and Z9911 or current procedural terminology codes 31500, 94656, and 94657 (for intubation) or 94002 to 94005 (for mechanical ventilation).

The outcome was based on discharge destination without any postdischarge data. Discharge destination was categorized as home or discharge to destination other than home (acute rehabilitation, intermediate care or skilled nursing facility, or nursing home). Discharge destination to home has been shown to predict none-to-mild disability while discharge to destination other than home predicts moderate-to-severe disability at 3 months poststroke.[20,21] Our analysis included only patients with medical history to ensure completeness of the records of potential comorbidities that constituted ≈67% of patients within the dataset.

Statistical Analysis

We performed this analysis to identify any significant differences in demographic and clinical characteristics, in-hospital events, and outcomes between (1) COVID-19 patients with and without acute ischemic stroke and (2) acute ischemic stroke patients with and without COVID-19. We compared patients' age, sex, race/ethnicity, cardiovascular risk factors, length of stay, medical complications, procedures performed, and discharge status (categorized into discharge home, discharge to destination other than home, or death) for patients in strata based on the presence or absence of acute ischemic stroke among COVID-19 patients. We also analyzed the data from patients with acute ischemic stroke without COVID-19 to identify differences in abovementioned variables between ischemic stroke patients with or without COVID-19. We used the χ 2 test for categorical data and 2-sample t test for continuous data to detect any significant differences in variables among COVID-19 patients with and without ischemic stroke. We adjusted for multiple comparisons using Bonferroni correction. Any P<0.05 is considered significant.

We performed stepwise backward logistic regression analysis including all COVID-19 patients to identify the association between the presence of acute ischemic stroke and risk of discharge to destination other than home or death after adjusting for age (age strata, <35, 35–54, 55–70, and >70 years), sex, race/ethnicity, hypertension, diabetes, nicotine dependence, hyperlipidemia, atrial fibrillation, and congestive heart failure. We performed another stepwise backward logistic regression analysis including all ischemic stroke patients to identify the association between the presence of COVID-19 and risk of discharge to destination other than home or death after adjusting for age (age strata), sex, race/ethnicity, hypertension, diabetes, nicotine dependence, hyperlipidemia, atrial fibrillation, and congestive heart failure. All the analyses were done using R, version 3.6.3.

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