Dataset Information

Stroke and Novel Coronavirus Infection in Humans: A Systematic Review and Meta-Analysis.

ABSTRACT: Background: As the world witnessed the devastation caused by the coronavirus disease 2019 (COVID-19) outbreak, a growing body of literature on COVID-19 is also becoming increasingly available. Stroke has increasingly been reported as a complication of COVID-19 infection. However, a systematic synthesis of the available data has not been conducted. Therefore, we performed a systematic review and meta-analysis of currently available epidemiological, clinical, and laboratory data related to both stroke and COVID-19 infection. Methods: We systematically searched Medline, Cinahl, and PubMed for studies related to stroke and COVID-19 from inception up to June 4, 2020. We selected cohort studies, case series, and case reports that reported the occurrence of stroke in COVID-19 patients. A fixed-effects model was used to estimate the pooled frequency of stroke in COVID-19 patients with a 95% confidence interval (CI). Results: Twenty-eight studies were included in the systematic review and seven studies for the meta-analysis. The pooled frequency of stroke in COVID-19 patients was 1.1% (95% CI: 0.8, 1.3). The heterogeneity was low (I 2 = 0.0%). Even though the frequency of stroke among patients having COVID-19 infection was low, those with concomitant COVID-19 infection and stroke suffered from a more severe infection and eventually had a poorer prognosis with a higher mortality rate (46.7%) than COVID-19 alone. Many COVID-19 patients shared the common traditional risk factors for stroke. We noted that ischemic stroke involving the anterior circulation with large vessels occlusion is the most common type of stroke with more strokes seen in multi-territorial regions, suggesting systemic thromboembolism. An elevated level of D-dimers, C-reactive protein, ferritin, lactic acid dehydrogenase, troponin, ESR, fibrinogen, and a positive antiphospholipid antibody were also noted in this review. Conclusions: The occurrence of stroke in patients with COVID-19 infection is uncommon, but it may pose as an important prognostic marker and indicator of severity of infection, by causing large vessels occlusion and exhibiting a thrombo-inflammatory vascular picture. Physicians should be made aware and remain vigilant on the possible two-way relationship between stroke and COVID-19 infection. The rate of stroke among patients with COVID-19 infection may increase in the future as they share the common risk factors.

SUBMITTER: Lee KW

PROVIDER: S-EPMC7573135 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Stroke and Novel Coronavirus Infection in Humans: A Systematic Review and Meta-Analysis.

Lee Kai Wei KW Yusof Khan Abdul Hanif Khan AHK Ching Siew Mooi SM Chia Peck Kee PK Loh Wei Chao WC Abdul Rashid Anna Misya'il AM Baharin Janudin J Inche Mat Liyana Najwa LN Wan Sulaiman Wan Aliaa WA Devaraj Navin Kumar NK Sivaratnam Dhashani D Basri Hamidon H Hoo Fan Kee FK

Frontiers in neurology 20201006

<b>Background:</b> As the world witnessed the devastation caused by the coronavirus disease 2019 (COVID-19) outbreak, a growing body of literature on COVID-19 is also becoming increasingly available. Stroke has increasingly been reported as a complication of COVID-19 infection. However, a systematic synthesis of the available data has not been conducted. Therefore, we performed a systematic review and meta-analysis of currently available epidemiological, clinical, and laboratory data related to ...[more]

PMID: 33123082

Similar Datasets

Project description:New evidence on the COVID-19 pandemic is being published daily. Ongoing high-quality assessment of this literature is therefore needed to enable clinical practice to be evidence-based. This review builds on a previous scoping review and aimed to identify associations between disease severity and various clinical, laboratory and radiological characteristics. We searched MEDLINE, CENTRAL, EMBASE, Scopus and LILACS for studies published between January 1, 2019 and March 22, 2020. Clinical studies including ?10 patients with confirmed COVID-19 of any study design were eligible. Two investigators independently extracted data and assessed risk of bias. A quality effects model was used for the meta-analyses. Subgroup analysis and meta-regression identified sources of heterogeneity. For hospitalized patients, studies were ordered by overall disease severity of each population and this order was used as the modifier variable in meta-regression. Overall, 86 studies (n = 91,621) contributed data to the meta-analyses. Severe disease was strongly associated with fever, cough, dyspnea, pneumonia, any computed tomography findings, any ground glass opacity, lymphocytopenia, elevated C-reactive protein, elevated alanine aminotransferase, elevated aspartate aminotransferase, older age and male sex. These variables typically increased in prevalence by 30-73% from mild/early disease through to moderate/severe disease. Among hospitalized patients, 30-78% of heterogeneity was explained by severity of disease. Elevated white blood cell count was strongly associated with more severe disease among moderate/severe hospitalized patients. Elevated lymphocytes, low platelets, interleukin-6, erythrocyte sedimentation rate and D-dimers showed potential associations, while fatigue, gastrointestinal symptoms, consolidation and septal thickening showed non-linear association patterns. Headache and sore throat were associated with the presence of disease, but not with more severe disease. In COVID-19, more severe disease is strongly associated with several clinical, laboratory and radiological characteristics. Symptoms and other variables in early/mild disease appear non-specific and highly heterogeneous. Clinical Trial Registration: PROSPERO CRD42020170623.

Project description:BackgroundCancer patients with COVID-19 disease have been reported to have double the case fatality rate of the general population.Materials and methodsA systematic search of PubMed/MEDLINE, Embase, Cochrane Central, Google Scholar, and MedRxiv was done for studies on cancer patients with COVID-19. Pooled proportions were calculated for categorical variables. Odds ratio and forest plots were constructed for both primary and secondary outcomes. The random-effects model was used to account for heterogeneity between studies.ResultsThis systematic review of 31 studies and meta-analysis of 181,323 patients from 26 studies involving 23,736 cancer patients is the largest meta-analysis to the best of our knowledge assessing outcomes in cancer patients affected by COVID-19. Our meta-analysis shows that cancer patients with COVID-19 have a higher likelihood of death (odds ratio, OR 2.54), which was largely driven by mortality among patients in China. Cancer patients were more likely to be intubated, although ICU admission rates were not statistically significant. Among cancer subtypes, the mortality was highest in hematological malignancies (OR 2.43) followed by lung cancer (OR 1.8). There was no association between receipt of a particular type of oncologic therapy and mortality. Our study showed that cancer patients affected by COVID-19 are a decade older than the normal population and have a higher proportion of co-morbidities. There was insufficient data to assess the association of COVID-directed therapy and survival outcomes in cancer patients. Despite the heterogeneity of studies and inconsistencies in reported variables and outcomes, these data could guide clinical practice and oncologic care during this unprecedented global health pandemic.ConclusionCancer patients with COVID-19 disease are at increased risk of mortality and morbidity. A more nuanced understanding of the interaction between cancer-directed therapies and COVID-19-directed therapies is needed. This will require uniform prospective recording of data, possibly in multi-institutional registry databases.

Dataset Information

Stroke and Novel Coronavirus Infection in Humans: A Systematic Review and Meta-Analysis.

Publications

Stroke and Novel Coronavirus Infection in Humans: A Systematic Review and Meta-Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets