Background Correct diagnosis of stroke and its subtypes is pivotal in early stages for optimum treatment. Aims The aim of this systematic review and meta-analysis is to summarize the published evidence on the potential of blood biomarkers in the diagnosis and differentiation of stroke subtypes. Methods A literature search was conducted for papers published until 20 April 2020 in PubMed, EMBASE, Cochrane Library, TRIP, and Google Scholar databases to search for eligible studies investigating the role of blood biomarkers in diagnosing stroke. Quality assessment was done using modified Quality Assessment of Diagnostic Accuracy Studies questionnaire. Pooled standardized mean difference and 95% confidence intervals were calculated. Presence of heterogeneity among the included studies was investigated using the Cochran's Q statistic and I2 metric tests. If I2 was < 50% then a fixed-effect model was applied else a random-effect model was applied. Risk of bias was assessed using funnel plots and between-study heterogeneity was assessed using meta-regression and sensitivity analyses. Entire statistical analysis was conducted in STATA version 13.0. Results A total of 40 studies including patients with 5001 ischemic strokes, 756 intracerebral hemorrhage, 554 stroke mimics, and 1774 healthy control subjects analyzing 25 biomarkers (within 24 h after symptoms onset/after the event) were included in our meta-analysis; 67.5% of studies had moderate evidence of quality. Brain natriuretic peptide, matrix metalloproteinase-9, and D-dimer significantly differentiated ischemic stroke from intracerebral hemorrhage, stroke mimics, and health control subjects ( p < 0.05). Glial fibrillary acidic protein successfully differentiated ischemic stroke from intracerebral hemorrhage (standardized mean difference −1.04; 95% confidence interval −1.46 to −0.63) within 6 h. No studies were found to conduct a meta-analysis of blood biomarkers differentiating transient ischemic attack from healthy controls and stroke mimics. Conclusion This meta-analysis highlights the potential of brain natriuretic peptide, matrix metalloproteinase-9, D-dimer, and glial fibrillary acidic protein as diagnostic biomarkers for stroke within 24 h. Results of our meta-analysis might serve as a platform for conducting further targeted proteomics studies and phase-III clinical trials. PROSPERO Registration ID: CRD42019139659.
The role of lipoprotein-A [Lp (a)] as a risk factor for stroke is less well documented than for coronary heart disease. Hence, we conducted a systematic review and meta-analysis for the published observational studies in order to investigate the association of Lp (a) levels with the risk of stroke and its subtypes. In our meta-analysis, 41 studies involving 7874 ischemic stroke (IS) patients and 32,138 controls; 13 studies for the IS subtypes based on TOAST classification and 7 studies with 871 Intracerebral hemorrhage (ICH) cases and 2865 control subjects were included. A significant association between increased levels of Lp (a) and risk of IS as compared to control subjects was observed (standardized mean difference (SMD) 0.76; 95% confidence interval (CIs) 0.53–0.99). Lp (a) levels were also found to be significantly associated with the risk of large artery atherosclerosis (LAA) subtype of IS (SMD 0.68; 95% CI 0.01–1.34) as well as significantly associated with the risk of ICH (SMD 0.65; 95% CI 0.13–1.17) as compared to controls. Increased Lp (a) levels could be considered as a predictive marker for identifying individuals who are at risk of developing IS, LAA and ICH.
Background: Several therapeutic agents have been investigated for treatment of novel coronavirus 2019 (nCOV-2019). We conducted a systematic review and metaanalysis to assess the efficacy of various treatment modalities in nCOV-2019 patients. Methods: A literature search was conducted before 29 June 2020 in PubMed, Google Scholar and Cochrane library databases. A fixed-effect model was applied if I 2 < 50%, else results were combined using random-effect model. Risk ratio (RR) or standardized mean difference (SMD) along with 95% confidence interval (95% CI) was used to pool the results. Between-study heterogeneity was explored using influence and sensitivity analyses, and publication bias was assessed using funnel plots. Entire statistical analysis was conducted in R version 3.6.2. Results: Fifty studies involving 15 in vitro and 35 clinical studies including 9170 nCOV-2019 patients were included. Lopinavir-ritonavir was significantly associated with shorter mean time to clinical recovery (SMD −0.32; 95% CI −0.57 to −0.06), remdesivir was significantly associated with better overall clinical recovery (RR 1.17; 95% CI 1.07 to 1.29), and tocilizumab was associated with less all-cause mortality (RR 0.38; 95% CI 0.16 to 0.93). Hydroxychloroquine was associated with longer time to clinical recovery and less overall clinical recovery. It additionally had higher all-cause mortality and more total adverse events. Conclusion: Our meta-analysis suggests that except in vitro studies, no treatment has shown overall favourable outcomes in nCOV-2019 patients. Lopinavir-ritonavir, remdesivir and tocilizumab may have some benefits, while hydroxychloroquine administration may cause harm in nCOV-2019 patients. Results from upcoming large clinical trials may further clarify role of these drugs. K E Y W O R D S humans, interventions, nCOV-2019, novel coronavirus 2019, treatments 2 of 21 | MISRA et Al. 2 | METHODS 2.1 | Electronic search Electronic databases including, PubMed, EMBASE, Medline, Google Scholar, Cochrane library and clinicaltrials.gov were searched till 29 June 2020. The following MeSH terms or free text terms were used: '2019 novel coronavirus', '2019 nCOV', 'COVID19', 'SARS-CoV-2', 'drug therapy', 'antiviral therapy', 'symptomatic treatment', 'immunotherapy'. The detailed search criteria are given in the Appendix S1. Furthermore, the reference list of all the relevant identified articles was thoroughly searched. Only those articles were included whose full texts were available in English language. Studies published on human subjects after 31 December 2019 since the nCOV-2019 outbreak initiated, were only searched. The protocol for this systematic review and meta-analysis was registered in PROSPERO (ID: CRD42020175792), and there were no major deviations from the published protocol in PROSPERO. 2.2 | Population Subjects diagnosed with pneumonia caused by new coronavirus 2019 infection (nCOV-2019) confirmed positive on highthroughput sequencing or real-time reverse-transcription polymerase chain reaction analysis of thro...
The 2019-Coronavirus (COVID-19) pandemic has had a global impact. The effect of environmental temperature on transmissibility and fatality rate of COVID-19 and protective efficacy of Bacillus Calmette-Guérin (BCG) vaccination towards COVID-19 remains ambiguous. Therefore, we explored the global impact of environmental temperature and neonatal BCG vaccination coverage on transmissibility and fatality rate of COVID-19. The COVID-19 data for reported cases, deaths and global temperature were collected from 31 st December 2020 to 3 rd April 2020 for 67 countries. Temperature data were split into quartiles for all three categories (minimum temperature, maximum temperature and mean temperature). The impact of three types of temperature data and policy of BCG vaccination on COVID-19 infection was determined by applying the multivariable two-level negative binomial regression analysis keeping daily new cases and daily mortality as outcome. The highest number of cases fell in the temperature categories as following: mean temperature in the second quartile (6˚C to 10.5˚C), median 26, interquartile range (IQR) 237; minimum temperature in the first quartile (-26˚C to 1˚C), median 23, IQR 173; maximum temperature in the second quartile (10˚C to 16˚C), median 27.5, IQR 219. For the minimum temperature category, 28% statistically significant lower incidence was noted for new cases from the countries falling in the second quartile (2˚C to 6˚C) compared with countries falling in the first quartile (-26˚C to 1˚C) (incidence rate ratio [IRR] 0.72, 95% confidence interval [CI] 0.57 to 0.93). However, no statistically significant difference in incidence rate was observed for mean temperature categories in comparison to the first quartile. Countries with BCG vaccination policy had 58% less mortality as compared with countries without BCG coverage (IRR 0.42; 95% CI 0.18 to 0.95). Our exploratory study provides evidence that high temperature might not be associated with low transmissibility and countries having neonatal BCG vaccination policy had a low fatality rate of COVID-19.
Introduction: An increase in the common carotid artery intima-media thickness (CCA-IMT) is generally considered an early marker of atherosclerosis and is a well-established predictor of cardiovascular disease (CVD). An association between changes in CCA-IMT and risk of stroke has been reported but has conflicting findings. Objective: The present meta-analysis was aimed to clarify the association between CCA-IMT with the risk of stroke and its subtype by estimating pooled analysis of published literature. Methods: Comprehensive search for all published articles was performed in electronic databases including PubMed, Embase, Cochrane Library, Trip Databases, Worldwide Science, CINAHL and Google Scholar from 01 January 1950 to 30 April 2020. Results: In our meta-analysis, a total of 19 studies, of which sixteen studies involving 3475 ischaemic stroke (IS) cases and 11 826 controls; six studies with 902 large vessel disease (LVD) and 548 small vessel disease (SVD) of IS subtypes; five studies with 228 intracerebral haemorrhage (ICH) and 1032 IS cases, were included. Our findings suggest a strong association between increased CCA-IMT with risk of IS as compared to control subjects [SMD = 1.46, 95% CI = 0.90-2.02]. However, there is an increased risk of LVD as compared to the SVD subtype of IS [SMD = 0.36, 95% CI = 0.19-0.52] and more chance of occurrence of IS rather than ICH [SMD = 0.71, 95% CI = 0.28-1.41]. Conclusions: Carotid intima thickness measurements are found to be associated with the risk of stroke along with its subtypes and may be used as a diagnostic marker for predicting the risk of stroke events.
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