Multinational Prevalence of Neurological Phenotypes in Patients Hospitalized with COVID-19

Abstract

Objective: Neurological complications can worsen outcomes in COVID-19. We defined the prevalence of a wide range of neurological conditions among patients hospitalized with COVID-19 in geographically diverse multinational populations.

Methods: Using electronic health record (EHR) data from 348 participating hospitals across 6 countries and 3 continents between January and September 2020, we performed a cross-sectional study of hospitalized adult and pediatric patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test, both with and without severe COVID-19. We assessed the frequency of each disease category and 3-character International Classification of Disease (ICD) code of neurological diseases by countries, sites, time before and after admission for COVID-19, and COVID-19 severity.

Results: Among the 35,177 hospitalized patients with SARS-CoV-2 infection, there was increased prevalence of disorders of consciousness (5.8%, 95% confidence interval [CI]: 3.7%-7.8%, p _FDR <.001) and unspecified disorders of the brain (8.1%, 95%CI: 5.7%-10.5%, p _FDR <.001), compared to pre-admission prevalence. During hospitalization, patients who experienced severe COVID-19 status had 22% (95%CI: 19%-25%) increase in the relative risk (RR) of disorders of consciousness, 24% (95%CI: 13%-35%) increase in other cerebrovascular diseases, 34% (95%CI: 20%-50%) increase in nontraumatic intracranial hemorrhage, 37% (95%CI: 17%-60%) increase in encephalitis and/or myelitis, and 72% (95%CI: 67%-77%) increase in myopathy compared to those who never experienced severe disease.

Interpretation: Using an international network and common EHR data elements, we highlight an increase in the prevalence of central and peripheral neurological phenotypes in patients hospitalized with SARS-CoV-2 infection, particularly among those with severe disease.

Figure 1.. Schematic diagram of the cohort and data generation workflow for each site.

Figure 2.. Characteristics of the study population across sites and countries.

(A) Total number of male (left) and female (right) patients grouped by country shown in square-root scale. (B) Proportion of ever-severe cases by median age estimate at each site, grouped by country. Node size corresponds to the total number of patients per site. (C) Distribution of self-identified race among patients at sites in Singapore and the United States. The Other/Unknown category includes patients who did not identify with any of the predefined race categories and/or whose data were not reported. Most European sites did not report race. (D) Average proportion of patients in each age group within each country. FR, France; DE, Germany; ES, Spain; IT, Italy; SG, Singapore; US(A), United States of America.

Figure 3.. Prevalence of neurological phenotypes among all patients.

(A) Difference in prevalence of each neurological ICD-10 code by site and country, calculated as after admission - before admission date (eEq. 2). Pink color on the heat map indicates increased prevalence, while green color indicates decreased prevalence. Please see eFig. 1 for the absolute values of prevalence. (B) Total counts of patients with a given neurological ICD-10 code (left) and the mean proportion of patients (right) before and after admission date across all sites. The mean proportion estimates are shown as circles and the 95% confidence intervals are shown as bars.

Figure 4.. Analysis of enrichment or depletion of neurological conditions after admission in patients with severe disease.

For each neurological ICD-10 code, we show the log₂ enrichment (LOE) and its 95% confidence interval (left), and the absolute difference between the observed ( ) and expected (·) number of patients experiencing severe COVID-19 in square-root scale (right). A purple positive LOE value for an ICD-10 code indicates a statistically significantly higher proportion of severe cases having a given neurological ICD-10 code when compared to the never-severe cases. Conversely, a green negative LOE value indicates a statistically significantly lower proportion of severe cases having a given neurological ICD-10 code when compared to the never-severe cases. Neurological ICD-10 codes are ordered by the expected number of severe cases after admission.