COVID-19 and Intracranial Hemorrhage: A Multicenter Case Series, Systematic Review and Pooled Analysis

Abstract

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) profoundly impacts hemostasis and microvasculature. In the light of the dilemma between thromboembolic and hemorrhagic complications, in the present paper, we systematically investigate the prevalence, mortality, radiological subtypes, and clinical characteristics of intracranial hemorrhage (ICH) in coronavirus disease (COVID-19) patients.

Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we performed a systematic review of the literature by screening the PubMed database and included patients diagnosed with COVID-19 and concomitant ICH. We performed a pooled analysis, including a prospectively collected cohort of critically ill COVID-19 patients with ICH, as part of the PANDEMIC registry (Pooled Analysis of Neurologic Disorders Manifesting in Intensive Care of COVID-19).

Results: Our literature review revealed a total of 217 citations. After the selection process, 79 studies and a total of 477 patients were included. The median age was 58.8 years. A total of 23.3% of patients experienced the critical stage of COVID-19, 62.7% of patients were on anticoagulation and 27.5% of the patients received ECMO. The prevalence of ICH was at 0.85% and the mortality at 52.18%, respectively.

Conclusion: ICH in COVID-19 patients is rare, but it has a very poor prognosis. Different subtypes of ICH seen in COVID-19, support the assumption of heterogeneous and multifaceted pathomechanisms contributing to ICH in COVID-19. Further clinical and pathophysiological investigations are warranted to resolve the conflict between thromboembolic and hemorrhagic complications in the future.

Keywords: COVID-19; anticoagulation; intracranial hemorrhage; prognosis.

Figure 1

Study selection diagram adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) group statement [17].

Figure 2

Prevalence of ICH in COVID-19 patients. The random and fixed effects model for the prevalence of ICH in COVID-19 patients. To account for the inconsistency in the measurements in the different studies, the effect estimates were calculated using the inverse variance method to allow for the weighing of the different variables according to their precision. The weight is illustrated by the size of the squares. Black and white lines indicate the respective 95% confidence intervals. The diamond shape indicates the average effect calculated by the fixed and random effects model, with the length of the shape representing the confidence interval.

Figure 3

Mortality of ICH in COVID-19 patients. The random and fixed effects model for mortality of ICH in COVID-19 patients.

Figure 4

Heterogeneity and bias of studies reporting the prevalence and mortality of ICH in COVID-19 patients. Standard error as an indicator of study precision are plotted against study results ((A): mortality; (B): prevalence), with the vertical line representing the value derived from the random effects model. The diagonal lines indicate the corresponding 95% confidence intervals (‘funnel plot’). Each dot represents a single study. The Egger’s test for funnel plot asymmetry is significant for mortality (p = 0.04), but not for prevalence (p = 0.80).