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Hypercoagulability Is a Stronger Risk Factor for Ischaemic Stroke than for Myocardial Infarction: A Systematic Review.

ABSTRACT: Hypercoagulability increases the risk of arterial thrombosis; however, this effect may differ between various manifestations of arterial disease.In this study, we compared the effect of coagulation factors as measures of hypercoagulability on the risk of ischaemic stroke (IS) and myocardial infarction (MI) by performing a systematic review of the literature. The effect of a risk factor on IS (relative risk for IS, RRIS) was compared with the effect on MI (RRMI) by calculating their ratio (RRR = RRIS/RRMI). A relevant differential effect was considered when RRR was >1+ its own standard error (SE) or <1-SE.We identified 70 publications, describing results from 31 study populations, accounting for 351 markers of hypercoagulability. The majority (203/351, 58%) had an RRR greater than 1. A larger effect on IS risk than MI risk (RRE>1+1SE) was found in 49/343 (14%) markers. Of these, 18/49 (37%) had an RRR greater than 1+2SE. On the opposite side, a larger effect on MI risk (RRR<1-1SE) was found in only 17/343 (5%) markers.These results suggest that hypercoagulability has a more pronounced effect on the risk of IS than that of MI.

SUBMITTER: Maino A

PROVIDER: S-EPMC4529149 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Hypercoagulability Is a Stronger Risk Factor for Ischaemic Stroke than for Myocardial Infarction: A Systematic Review.

Maino Alberto A Rosendaal Frits R FR Algra Ale A Peyvandi Flora F Siegerink Bob B

PloS one 20150807 8

<h4>Background and purpose</h4>Hypercoagulability increases the risk of arterial thrombosis; however, this effect may differ between various manifestations of arterial disease.<h4>Methods</h4>In this study, we compared the effect of coagulation factors as measures of hypercoagulability on the risk of ischaemic stroke (IS) and myocardial infarction (MI) by performing a systematic review of the literature. The effect of a risk factor on IS (relative risk for IS, RRIS) was compared with the effect ...[more]

PMID: 26252207

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Project description:BACKGROUND:The effect of antipsychotic (AP) drugs on risk of stroke and myocardial infarction (MI) remains unclear due to methodological limitations of, and inconsistencies across, existing studies. We aimed to systematically review studies reporting on the associations between AP drug use and stroke or MI risk, and to investigate whether associations differed among different sub-populations. METHODS:We searched Medline, EMBASE, PsychINFO and Cochrane Library (from inception to May 28, 2017) for observational studies reporting on AP drug use and MI or stroke occurrence. We performed random-effects meta-analyses for each outcome, performing sub-groups analyses by study population - specifically general population (i.e. those not restricted to patients with a particular indication for AP drug use), people with dementia only and psychiatric illness only. Where feasible we performed subgroup analyses by AP drug class. RESULTS:From 7008 articles, we included 29 relevant observational studies, 19 on stroke and 10 on MI. Results of cohort studies that included a general population indicated a more than two-fold increased risk of stroke, albeit with substantial heterogeneity (pooled HR 2.31, 95% CI 1.13, 4.74, I2 = 83.2%). However, the risk among patients with dementia was much lower, with no heterogeneity (pooled HR 1.16, 95% CI 1.00, 1.33, I2 = 0%) and there was no clear association among studies of psychiatric populations (pooled HR 1.44, 95% CI 0.90, 2.30; substantial heterogeneity [I2 = 78.8])). Associations generally persisted when stratifying by AP class, but few studies reported on first generation AP drugs. We found no association between AP drug use and MI risk (pooled HR for cohort studies: 1.29, 95% CI 0.88, 1.90 and case-control studies: 1.07, 95% CI 0.94, 1.23), but substantial methodological and statistical heterogeneity among a relatively small number of studies limits firm conclusions. CONCLUSIONS:AP drug use may be associated with an increased risk of stroke, but there is no clear evidence that this risk is further elevated in patients with dementia. Further studies are need to clarify the effect of AP drug use on MI and stroke risk in different sub-populations and should control for confounding by indication and stratify by AP drug class.

Project description:IntroductionPremature myocardial infarction (MI) generally refers to MI in men ≤55 years or women ≤65 years. Premature MI is a major contributor to cardiovascular disease (CVD), which claimed 17.6 million lives globally in 2016. Reducing premature MI and CVD is a key priority for all nations; however, there is sparse synthesis of information on risk factors associated with premature MI. To address this knowledge gap, we are conducting a systematic review to describe the association between risk factors (demographics, lifestyle factors and biomarkers) and premature MI.Methods and analysisThe following databases were searched from inception to June 2018: CENTRAL, CINAHL, Clinical Trials, EMBASE and MEDLINE. We will include original research articles (case-control, cohort and cross-sectional studies) that report a quantitative relationship between at least one risk factor and premature MI. Two investigators will use predetermined selection criteria and independently screen articles based on title and abstract (primary screening). Articles that meet selection criteria will undergo full-text screening based on criteria used for primary screening (secondary screening). Data will be extracted using predetermined data extraction forms. The Newcastle-Ottawa Scale for case-control and cohort studies will be used to evaluate the risk of bias and will be adapted for cross-sectional studies. Whenever feasible, data will be summarised into a random-effects meta-analysis.Ethics and disseminationTo our knowledge, this will be the first study to synthesise results on the relationship between risk factors and premature MI. These findings will inform healthcare providers on factors associated with risk of premature MI and potentially improve primary prevention efforts by guiding development of interventions. These findings will be summarised and presented at conferences and through publication in a peer-reviewed journal.Prospero registration numberCRD42018076862.

Project description:BackgroundHospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown.Methods and resultsWe systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models.ConclusionsCurrent AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions.

Dataset Information

Hypercoagulability Is a Stronger Risk Factor for Ischaemic Stroke than for Myocardial Infarction: A Systematic Review.

Publications

Hypercoagulability Is a Stronger Risk Factor for Ischaemic Stroke than for Myocardial Infarction: A Systematic Review.

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