Update on the Serum Biomarkers and Genetic Factors Associated with Safety and Efficacy of rt-PA Treatment in Acute Stroke Patients

Association of PAI-1 rs1799889 Polymorphism with Susceptibility to Ischemic Stroke: a Huge Meta-Analysis based on 44 Studies

BACKGROUND

the PAI-1 rs1799889 polymorphism has been reported to be associated with susceptibility to ischemic stroke. However, the results of previous studies have been inconsistent or controversial. Hence, we performed a systematic review and meta-analysis to evaluate the association of PAI-1 rs1799889 polymorphism with ischemic stroke risk.

METHODS

A comprehensive literature search was performed on PubMed, Web of Science, Scopus, SciELO, CNKI, and CBD databases up to November 05, 2019. Pooled odds ratio (OR) with 95% confidence interval (CI) were used to access the strength of this association in fixed- or random-effects model.

RESULTS

A total of 44 case-control studies with 8,620 cases and 10,260 controls were selected. Pooled data showed a significant association between PAI-1 rs1799889 polymorphism and ischemic stroke risk in the overall populations (GG vs. AA: OR = 0.791, 95% CI 0.633-0.988, p = 0.039; GA vs. AA: OR = 0.807, 95% CI 0.683-0.953, p = 0.012; and GG+GA vs. AA: OR = 0.795, 95% CI 0.637-0.993, p = 0.043). Subgroup analysis by ethnicity revealed a significant association in Asian and Mixed populations, but not in Caucasians. Moreover, stratified analysis by country of origin revealed an increased risk of ischemic stroke in Chinese populations, but not among Dutch (Netherlands) and Swedish.

CONCLUSIONS

This meta-analysis result suggested that PAI-1 rs1799889 polymorphism was associated with an increased risk of ischemic stroke, especially in Asian and Mixed populations.

Standardizing the structure of stroke clinical and epidemiologic research data: the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Common Data Element (CDE) project

BACKGROUND AND PURPOSE

The National Institute of Neurological Disorders and Stroke initiated development of stroke-specific Common Data Elements (CDEs) as part of a project to develop data standards for funded clinical research in all fields of neuroscience. Standardizing data elements in translational, clinical, and population research in cerebrovascular disease could decrease study start-up time, facilitate data sharing, and promote well-informed clinical practice guidelines.

METHODS

A working group of diverse experts in cerebrovascular clinical trials, epidemiology, and biostatistics met regularly to develop a set of stroke CDEs, selecting among, refining, and adding to existing, field-tested data elements from national registries and funded trials and studies. Candidate elements were revised on the basis of comments from leading national and international neurovascular research organizations and the public.

RESULTS

The first iteration of the National Institute of Neurological Disorders and Stroke (NINDS) stroke-specific CDEs comprises 980 data elements spanning 9 content areas: (1) biospecimens and biomarkers; (2) hospital course and acute therapies; (3) imaging; (4) laboratory tests and vital signs; (5) long-term therapies; (6) medical history and prior health status; (7) outcomes and end points; (8) stroke presentation; and (9) stroke types and subtypes. A CDE website provides uniform names and structures for each element, a data dictionary, and template case report forms, using the CDEs.

CONCLUSIONS

Stroke-specific CDEs are now available as standardized, scientifically vetted, variable structures to facilitate data collection and data sharing in cerebrovascular patient-oriented research. The CDEs are an evolving resource that will be iteratively improved based on investigator use, new technologies, and emerging concepts and research findings.