SARS-CoV-2 infection and acute ischemic stroke in Lombardy, Italy

The influence of COVID-19 on short-term mortality in acute ischemic stroke: A systematic review and meta-analysis

OBJECTIVE

To evaluate the differences in short-term mortality risk between acute ischemic stroke (AIS) patients with and without SARS-CoV-2 infection.

METHODS

PubMed, EMBASE, Scopus, and Cochrane Databases were systematically searched from December 1, 2019 to May 20, 2022 using the keywords coronavirus disease 2019 (COVID-19), COVID-19, SARS-CoV-2, and ischemic stroke. A random-effects model was estimated, and subgroup analysis and meta-regressions were performed. The quality of eligible studies was assessed using the Newcastle-Ottawa Scale.

RESULTS

A total of 26 eligible studies with 307,800 patients were included in this meta-analysis. The overall results show that in-hospital and 90-day mortality was 3.31-fold higher in AIS with SARS-CoV-2 patients compared with those without SARS-CoV-2. When matched for age and National Institutes of Health Stroke Scale score at admission, the risk ratio of in-hospital mortality from AIS among patients with SARS-CoV-2 versus without decreased to 2.83. Reperfusion therapy and endovascular thrombectomy may further reduce the risk of death in patients to some extent but do not increase the incidence of symptomatic intracerebral hemorrhage. Meta-regression showed that in-hospital mortality decreased with increasing National Institutes of Health Stroke Scale score in AIS with SARS-CoV-2 compared to those without SARS-CoV-2 and that the difference in mortality risk between the 2 was independent of age and sex.

CONCLUSIONS

The results of this study suggest that AIS patients with SARS-CoV-2 have higher short-term mortality compared to AIS patients without SARS-CoV-2, and reperfusion and endovascular thrombectomy therapy may reduce the risk of short-term mortality to some extent. The differences in in-hospital mortality risk were similar across ages and sexes. Focused attention is therefore needed on AIS patients with SARS-CoV-2 to control mortality.

Incidence and Features of Acute Ischemic Stroke in Patients Hospitalized with COVID-19: A Multi-center Study in Turkey

Introduction

Acute ischemic stroke (AIS) is a devastating complication of COVID-19 with high morbidity and mortality. In this study, we reported the frequency, characteristics, and outcome of AIS in patients with COVID-19.

Methods

This multicenter and cross-sectional study was conducted between April 2020 and February 2021. Among the hospitalized patients with COVID-19, the detailed characteristics of those with and without AIS were recorded and compared.

Results

Six hundred ninety-three patients were included in the study. Acute ischemic stroke was detected in 16 (2.31%) patients, the median age was 77 (range, 48-91) years, and 10 (62.5%) were female. The median NIHSS score at admission was 9 (range, 3-17). Total anterior circulation infarction (TACI) was the most common (37.5%) type and cardioembolism was the most common etiology (37.5%). Nine patients (56.25%) developed AIS within 24 hours of having COVID-19. COVID-19 severity was severe or critical in seven patients (43.75%). Eight patients died, and eight were discharged. Patients with AIS had a higher rate of hypertension, coronary artery disease, heart failure, a history of myocardial infarction, a history of cerebrovascular disease, severe and critical COVID-19, a higher mean age, and a longer ICU stay compared with those without AIS (p<0.001 for each).

Conclusions

AIS can occur in patients with COVID-19 and is associated with mortality. Acute ischemic stroke is encountered at any stage of COVID-19, especially within the first 72 hours of the diagnosis, in older patients with comorbidities and severe COVID-19. There is an increased risk of AIS in patients with COVID-19 with a history of stroke.

Sex differences in ischemic stroke during COVID-19 first outbreak in northern Italy

INTRODUCTION

COVID-19 pandemic had a great impact on outcome in SARS-CoV-2 positive patients with ischemic stroke during the first wave in Italy. Few data are available on outcome stratified by sex.

METHODS

The Italian Society of Hospital Neuroscience conducted a multi-center, retrospective, observational study on neurological complications in COVID-19 patients with ischemic stroke. All the patients admitted from March 1st to April 30th, 2020 in 20 Neurology Units in Northern Italy were recruited. Demographical and clinical features, treatment and outcome data were compared focusing on sex differences.

RESULTS

812 patients with ischemic stroke were enrolled, of whom 129 with COVID-19; males were 53.8%. In-hospital mortality in COVID-19 patients was 35.3% in males and 27.9% in females while 8.5% in male and 5.8% in female patients without COVID-19. SARS-CoV-2 positive patients had a higher frequency of stroke of undetermined etiology, than negative ones (32.8% vs 22.5%; p = 0.02), especially in females compared to males (36.1% vs 27.9%), albeit without statistical significance. Male patients with SARS-CoV-2 were more likely to require cPAP (30.9% vs 14.8%; p = 0.03), endotracheal tube (14.9% vs 3.3%; p = 0.02) and reperfusion strategies (29.4% vs 11.5%; p = 0.01) than females, as well as to have a higher CRP and D-dimer. These elements together with older age, a total anterior circulation stroke and lymphopenia were predictors of a worse outcome.

DISCUSSION

Our study detected some differences due to sex in ischemic stroke with and without COVID-19, supporting the possibility to perform sex analyses for SARS-CoV-2 positive patients for a better clinical management.

Incidence and Long-term Functional Outcome of Neurologic Disorders in Hospitalized Patients With COVID-19 Infected With Pre-Omicron Variants

BACKGROUND AND OBJECTIVES

A variety of neurologic disorders have been reported as presentations or complications of coronavirus disease 2019 (COVID-19) infection. The objective of this study was to determine their incidence dynamics and long-term functional outcome.

METHODS

The Neuro-COVID Italy study was a multicenter, observational, cohort study with ambispective recruitment and prospective follow-up. Consecutive hospitalized patients presenting new neurologic disorders associated with COVID-19 infection (neuro-COVID), independently from respiratory severity, were systematically screened and actively recruited by neurology specialists in 38 centers in Italy and the Republic of San Marino. The primary outcomes were incidence of neuro-COVID cases during the first 70 weeks of the pandemic (March 2020-June 2021) and long-term functional outcome at 6 months, categorized as full recovery, mild symptoms, disabling symptoms, or death.

RESULTS

Among 52,759 hospitalized patients with COVID-19, 1,865 patients presenting 2,881 new neurologic disorders associated with COVID-19 infection (neuro-COVID) were recruited. The incidence of neuro-COVID cases significantly declined over time, comparing the first 3 pandemic waves (8.4%, 95% CI 7.9-8.9; 5.0%, 95% CI 4.7-5.3; 3.3%, 95% CI 3.0-3.6, respectively; p = 0.027). The most frequent neurologic disorders were acute encephalopathy (25.2%), hyposmia-hypogeusia (20.2%), acute ischemic stroke (18.4%), and cognitive impairment (13.7%). The onset of neurologic disorders was more common in the prodromic phase (44.3%) or during the acute respiratory illness (40.9%), except for cognitive impairment whose onset prevailed during recovery (48.4%). A good functional outcome was achieved by most patients with neuro-COVID (64.6%) during follow-up (median 6.7 months), and the proportion of good outcome increased throughout the study period (r = 0.29, 95% CI 0.05-0.50; p = 0.019). Mild residual symptoms were frequently reported (28.1%) while disabling symptoms were common only in stroke survivors (47.6%).

DISCUSSION

Incidence of COVID-associated neurologic disorders decreased during the prevaccination phase of the pandemic. Long-term functional outcome was favorable in most neuro-COVID disorders, although mild symptoms commonly lasted more than 6 months after infection.

The evolving epidemiology of monkeypox virus

Monkeypox, caused by the monkeypox virus (MPXV), is a zoonotic disease endemic mainly in West and Central Africa. As of 27 September 2022, human monkeypox has occurred in more than 100 countries (mostly in non-endemic regions) and caused over 66,000 confirmed cases, which differs from previous epidemics that mainly affected African countries. Due to the increasing number of confirmed cases worldwide, the World Health Organization (WHO) has declared the monkeypox outbreak as a Public Health Emergency of International Concern on July 23, 2022. The international outbreak of human monkeypox represents a novel route of transmission for MPXV, with genital lesions as the primary infection, and the emergence of monkeypox in the current outbreak is also new, as novel variants emerge. Clinical physicians and scientists should be aware of this emerging situation, which presents a different scenario from previous outbreaks. In this review, we will discuss the molecular virology, evasion of antiviral immunity, epidemiology, evolution, and detection of MPXV, as well as prophylaxis and treatment strategies for monkeypox. This review also emphasizes the integration of relevant epidemiological data with genomic surveillance data to obtain real-time data, which could formulate prevention and control measures to curb this outbreak.

Autologous Hematopoietic Stem-Cell Transplantation in Multiple Sclerosis: A Systematic Review and Meta-Analysis

INTRODUCTION

In 1995, the use of autologous hematopoietic stem-cell transplantation (AHSCT), which was previously used to treat hematological tumors, was introduced for severe autoimmune diseases such as multiple sclerosis (MS). AHSCT has proven its safety over the past few years due to technical advances and careful patient selection in transplant centers. While most studies have reported that AHSCT led to decreased Expanded Disability Status Scale (EDSS) scores, some patients reported increased EDSS scores following the procedure. Given the contradictory results, we aimed to conduct a comprehensive systematic review and meta-analysis to investigate the efficacy and safety of AHSCT.

METHODS

PubMed, Web of Science, and Scopus were searched in March 2022 using a predefined search strategy. We included cohort studies, clinical trials, case-control studies, and case series that investigated the efficacy or safety of AHSCT in patients with MS. PICO in the present study was defined as follows: problem or study population (P): patients with MS; intervention (I): AHSCT; comparison (C): none; outcome (O): efficacy and safety.

RESULTS

After a two-step review process, 50 studies with a total of 4831 patients with MS were included in our study. Our analysis showed a significant decrease in EDSS score after treatment (standardized mean difference [SMD]: -0.48, 95% CI -0.75, -0.22). Moreover, the annualized relapse rate was also significantly reduced after AHSCT compared to the pretreatment period (SMD: -1.58, 95% CI -2.34, -0.78). The pooled estimate of progression-free survival after treatment was 73% (95% CI 69%, 77). Furthermore, 81% of patients with MS who received AHSCT remained relapse-free (95% CI 76%, 86%). Investigating event-free survival, which reflects the absence of any disease-related event, showed a pooled estimate of 63% (95% CI 54%, 73%). Also, the MRI activity-free survival was 89% (95% CI 84%) among included studies with low heterogeneity. New MRI lesions seem to appear in nearly 8% of patients who underwent AHSCT (95% CI 4%, 12%). Our meta-analysis showed that 68% of patients with MS experience no evidence of disease activity (NEDA) after AHSCT (95% CI 59%, 77). The overall survival after transplantation was 94% (95% CI 91%, 96%). In addition, 4% of patients died from transplant-related causes (95% CI 2%, 6%).

CONCLUSION

Current data encourages a broader application of AHSCT for treating patients with MS while still considering proper patient selection and transplant methods. In addition, with increasing knowledge and expertise in the field of stem-cell therapy, AHSCT has become a safer treatment approach for MS.

Detecting accelerometer non-wear periods using change in acceleration combined with rate-of-change in temperature

Background

Accelerometery is commonly used to estimate physical activity, sleep, and sedentary behavior. In free-living conditions, periods of device removal (non-wear) can lead to misclassification of behavior with consequences for research outcomes and clinical decision making. Common methods for non-wear detection are limited by data transformations (e.g., activity counts) or algorithm parameters such as minimum durations or absolute temperature thresholds that risk over- or under-estimating non-wear time. This study aimed to advance non-wear detection methods by integrating a ‘rate-of-change’ criterion for temperature into a combined temperature-acceleration algorithm.

Methods

Data were from 39 participants with neurodegenerative disease (36% female; age: 45–83 years) who wore a tri-axial accelerometer (GENEActiv) on their wrist 24-h per day for 7-days as part of a multi-sensor protocol. The reference dataset was derived from visual inspection conducted by two expert analysts. Linear regression was used to establish temperature rate-of-change as a criterion for non-wear detection. A classification and regression tree (CART) decision tree classifier determined optimal parameters separately for non-wear start and end detection. Classifiers were trained using data from 15 participants (38.5%). Outputs from the CART analysis were supplemented based on edge cases and published parameters.

Results

The dataset included 186 non-wear periods (85.5% < 60 min). Temperature rate-of-change over the first five minutes of non-wear was − 0.40 ± 0.17 °C/minute and 0.36 ± 0.21 °C/minute for the first five minutes following device donning. Performance of the DETACH (DEvice Temperature and Accelerometer CHange) algorithm was improved compared to existing algorithms with recall of 0.942 (95% CI 0.883 to 1.0), precision of 0.942 (95% CI 0.844 to 1.0), F1-Score of 0.942 (95% CI 0.880 to 1.0) and accuracy of 0.996 (0.994–1.000).

Conclusion

The DETACH algorithm accurately detected non-wear intervals as short as five minutes; improving non-wear classification relative to current interval-based methods. Using temperature rate-of-change combined with acceleration results in a robust algorithm appropriate for use across different temperature ranges and settings. The ability to detect short non-wear periods is particularly relevant to free-living scenarios where brief but frequent removals occur, and for clinical application where misclassification of behavior may have important implications for healthcare decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01633-6.