The impact of Magnetic Resonance Imaging (MRI) on ischemic stroke detection and incidence: minimal impact within a population-based study

Biochemical, biomechanical and imaging biomarkers of ischemic stroke: Time for integrative thinking

Stroke is one of the leading causes of adult disability affecting millions of people worldwide. Post-stroke cognitive and motor impairments diminish quality of life and functional independence. There is an increased risk of having a second stroke and developing secondary conditions with long-term social and economic impacts. With increasing number of stroke incidents, shortage of medical professionals and limited budgets, health services are struggling to provide a care that can break the vicious cycle of stroke. Effective post-stroke recovery hinges on holistic, integrative and personalized care starting from improved diagnosis and treatment in clinics to continuous rehabilitation and support in the community. To improve stroke care pathways, there have been growing efforts in discovering biomarkers that can provide valuable insights into the neural, physiological and biomechanical consequences of stroke and how patients respond to new interventions. In this review paper, we aim to summarize recent biomarker discovery research focusing on three modalities (brain imaging, blood sampling and gait assessments), look at some established and forthcoming biomarkers, and discuss their usefulness and complementarity within the context of comprehensive stroke care. We also emphasize the importance of biomarker guided personalized interventions to enhance stroke treatment and post-stroke recovery.

Trends Over Time in Stroke Incidence by Race in the Greater Cincinnati Northern Kentucky Stroke Study

BACKGROUND AND OBJECTIVES

Understanding the current status of and temporal trends of stroke epidemiology by age, race, and stroke subtype is critical to evaluate past prevention efforts and to plan future interventions to eliminate existing inequities. We investigated trends in stroke incidence and case fatality over a 22-year time period.

METHODS

In this population-based stroke surveillance study, all cases of stroke in acute care hospitals within a 5-county population of southern Ohio/northern Kentucky in adults aged ≥20 years were ascertained during a full year every 5 years from 1993 to 2015. Temporal trends in stroke epidemiology were evaluated by age, race (Black or White), and subtype (ischemic stroke [IS], intracranial hemorrhage [ICH], or subarachnoid hemorrhage [SAH]). Stroke incidence rates per 100,000 individuals from 1993 to 2015 were calculated using US Census data and age-standardized, race-standardized, and sex-standardized as appropriate. Thirty-day case fatality rates were also reported.

RESULTS

Incidence rates for stroke of any type and IS decreased in the combined population and among White individuals (any type, per 100,000, 215 [95% CI 204-226] in 1993/4 to 170 [95% CI 161-179] in 2015, p = 0.015). Among Black individuals, incidence rates for stroke of any type decreased over the study period (per 100,000, 349 [95% CI 311-386] in 1993/4 to 311 [95% CI 282-340] in 2015, p = 0.015). Incidence of ICH was stable over time in the combined population and in race-specific subgroups, and SAH decreased in the combined groups and in White adults. Incidence rates among Black adults were higher than those of White adults in all time periods, and Black:White risk ratios were highest in adults in young and middle age groups. Case fatality rates were similar by race and by time period with the exception of SAH in which 30-day case fatality rates decreased in the combined population and White adults over time.

DISCUSSION

Stroke incidence is decreasing over time in both Black and White adults, an encouraging trend in the burden of cerebrovascular disease in the US population. Unfortunately, however, Black:White disparities have not decreased over a 22-year period, especially among younger and middle-aged adults, suggesting the need for more effective interventions to eliminate inequities by race.

Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease

Introduction

Cerebrovascular diseases are known to cause significant morbidity and mortality to the general population. In patients with cerebrovascular disease, prompt clinical evaluation and radiographic interpretation are both essential in optimizing clinical management and in triaging patients for critical and potentially life-saving neurosurgical interventions. With recent advancements in the domains of artificial intelligence (AI) and machine learning (ML), many AI and ML algorithms have been developed to further optimize the diagnosis and subsequent management of cerebrovascular disease. Despite such advances, further studies are needed to substantively evaluate both the diagnostic accuracy and feasibility of these techniques for their application in clinical practice. This review aims to analyze the current use of AI and MI algorithms in the diagnosis of, and clinical decision making for cerebrovascular disease, and to discuss both the feasibility and future applications of utilizing such algorithms.

Methods

We review the use of AI and ML algorithms to assist clinicians in the diagnosis and management of ischemic stroke, hemorrhagic stroke, intracranial aneurysms, and arteriovenous malformations (AVMs). After identifying the most widely used algorithms, we provide a detailed analysis of the accuracy and effectiveness of these algorithms in practice.

Results

The incorporation of AI and ML algorithms for cerebrovascular patients has demonstrated improvements in time to detection of intracranial pathologies such as intracerebral hemorrhage (ICH) and infarcts. For ischemic and hemorrhagic strokes, commercial AI software platforms such as RapidAI and Viz.AI have bene implemented into routine clinical practice at many stroke centers to expedite the detection of infarcts and ICH, respectively. Such algorithms and neural networks have also been analyzed for use in prognostication for such cerebrovascular pathologies. These include predicting outcomes for ischemic stroke patients, hematoma expansion, risk of aneurysm rupture, bleeding of AVMs, and in predicting outcomes following interventions such as risk of occlusion for various endovascular devices. Preliminary analyses have yielded promising sensitivities when AI and ML are used in concert with imaging modalities and a multidisciplinary team of health care providers.

Conclusion

The implementation of AI and ML algorithms to supplement clinical practice has conferred a high degree of accuracy, efficiency, and expedited detection in the clinical and radiographic evaluation and management of ischemic and hemorrhagic strokes, AVMs, and aneurysms. Such algorithms have been explored for further purposes of prognostication for these conditions, with promising preliminary results. Further studies should evaluate the longitudinal implementation of such techniques into hospital networks and residency programs to supplement clinical practice, and the extent to which these techniques improve patient care and clinical outcomes in the long-term.

Using Epidemiological Data to Inform Clinical Trial Feasibility Assessments: A Case Study

BACKGROUND

Clinical trial enrollment and completion is challenging, with nearly half of all trials not being completed or not completed on time. In 2014, the National Institutes of Health StrokeNet in collaboration with stroke epidemiologists from GCNKSS (Greater Cincinnati/Northern Kentucky Stroke Study) began providing proposed clinical trials with formal trial feasibility assessments. Herein, we describe the process of prospective feasibility analyses using epidemiological data that can be used to improve enrollment and increase the likelihood a trial is completed.

METHODS

In 2014, DEFUSE 3 (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke 3) trialists, National Institutes of Health StrokeNet, and stroke epidemiologists from GCNKSS collaborated to evaluate the initial inclusion/exclusion criteria for the DEFUSE 3 study. Trial criteria were discussed and an assessment was completed to evaluate the percent of the stroke population that might be eligible for the study. The DEFUSE 3 trial was stopped early with the publication of DAWN (Thrombectomy 6 to 24 Hours After Stroke With a Mismatch Between Deficit and Infarct), and the Wilcoxon rank-sum statistic was used to analyze whether the trial would have been stopped had the proposed changes not been made, following the DEFUSE 3 statistical analysis plan.

RESULTS

After initial epidemiological analysis, 2.4% of patients with acute stroke in the GCNKSS population would have been predicted to be eligible for the study. After discussion with primary investigators and modifying 4 key exclusion criteria (upper limit of age increased to 90 years, baseline modified Rankin Scale broadened to 0-2, time since last well expanded to 16 hours, and decreased lower limit of National Institutes of Health Stroke Scale score to <6), the number predicted to be eligible for the trial increased to 4%. At the time of trial conclusion, 57% of the enrolled patients qualified only by the modified criteria, and the trial was stopped at an interim analysis that demonstrated efficacy. We estimated that the Wilcoxon rank-sum value for the unadjusted predicted enrollment would not have crossed the threshold for efficacy and the trial not stopped.

CONCLUSIONS

Objectively assessing trial inclusion/exclusion criteria using a population-based resource in a collaborative and iterative process including epidemiologists can lead to improved recruitment and can increase the likelihood of successful trial completion.

Comparing Vascular Brain Injury and Stroke by Cranial Magnetic Resonance Imaging, Physician-Adjudication, and Self-Report: Data from the Strong Heart Study

BACKGROUND

Epidemiologic studies often use self-report as proxy for clinical history. However, whether self-report correctly identifies prevalence in minority populations with health disparities and poor health-care access is unknown. Furthermore, overlap of clinical vascular events with covert vascular brain injury (VBI), detected by imaging, is largely unexamined.

METHODS

The Strong Heart Study recruited American Indians from 3 regions, with surveillance and adjudication of stroke events from 1989 to 2013. In 2010-2013, all 817 survivors, aged 65-95 years, underwent brain imaging, neurological history interview, and cognitive testing. VBI was defined as imaged infarct or hemorrhage.

RESULTS

Adjudicated stroke was prevalent in 4% of participants and separately collected, self-reported stroke in 8%. Imaging-defined VBI was detected in 51% and not associated with any stroke event in 47%. Compared with adjudication, self-report had 76% sensitivity and 95% specificity. Participants with adjudicated or self-reported stroke had the poorest performance on cognitive testing; those with imaging-only (covert) VBI had intermediate performance.

CONCLUSION

In this community-based cohort, self-report for prior stroke had good performance metrics. A majority of participants with VBI did not have overt, clinically recognized events but did have neurological or cognitive symptoms. Data collection methodology for studies in a resource-limited setting must balance practical limitations in costs, accuracy, feasibility, and research goals.

A 5-Decade Analysis of Incidence Trends of Ischemic Stroke After Transient Ischemic Attack: A Systematic Review and Meta-analysis

Importance

Management of transient ischemic attack (TIA) has gained significant attention during the past 25 years after several landmark studies indicated the high incidence of a subsequent stroke.

Objective

To calculate the pooled event rate of subsequent ischemic stroke within 2, 7, 30, and 90 days of a TIA and compare this incidence among the population with TIA recruited before 1999 (group A), from 1999 to 2007 (group B), and after 2007 (group C).

Data Sources

All published studies of TIA outcomes were obtained by searching PubMed from 1996, to the last update on January 31, 2020, irrespective of the study design, document type, or language.

Study Selection

Of 11 516 identified citations, 175 articles were relevant to this review. Both the classic time-based definition of TIA and the new tissue-based definition were accepted. Studies with a combined record of patients with TIA and ischemic stroke, without clinical evaluation for the index TIA, with diagnosis of index TIA event after ischemic stroke occurrence, with low suspicion for TIA, or duplicate reports of the same database were excluded.

Data Extraction and Synthesis

The study was conducted and reported according to the PRISMA, MOOSE, and EQUATOR guidelines. Critical appraisal and methodological quality assessment used the Quality in Prognosis Studies tool. Publication bias was visualized by funnel plots and measured by the Begg-Mazumdar rank correlation Kendall τ2 statistic and Egger bias test. Data were pooled using double arcsine transformations, DerSimonian-Laird estimator, and random-effects models.

Main Outcomes and Measures

The proportion of the early ischemic stroke after TIA within 4 evaluation intervals (2, 7, 30, and 90 days) was considered as effect size.

Results

Systematic review yielded 68 unique studies with 223 866 unique patients from 1971 to 2019. The meta-analysis included 206 455 patients (58% women) during a span of 4 decades. The overall subsequent ischemic stroke incidence rates were estimated as 2.4% (95% CI, 1.8%-3.2%) within 2 days, 3.8% (95% CI, 2.5%-5.4%) within 7 days, 4.1% (95% CI, 2.4%-6.3%) within 30 days, and 4.7% (95% CI, 3.3%-6.4%) within 90 days. There was a recurrence risk of 3.4% among group A in comparison with 2.1% in group B or 2.1% in group C within 2 days; 5.5% in group A vs 2.9% in group B or 3.2% in group C within 7 days; 6.3% in group A vs 2.9% in group B or 3.4% in group C within 30 days, and 7.4% in group A vs 3.9% in group B or 3.9% in group C within 90 days.

Conclusions and Relevance

These findings suggest that TIA continues to be associated with a high risk of early stroke; however, the rate of post-TIA stroke might have decreased slightly during the past 2 decades.

Increasing false positive diagnoses may lead to overestimation of stroke incidence, particularly in the young: a cross-sectional study

Background

Stroke incidence is reportedly increasing in younger populations, although the reasons for this are not clear. We explored possible reasons by quantifying trends in neurologically focused emergency department (ED) visits, classification of stroke vs. TIA, and imaging use.

Methods

We performed a retrospective, serial, cross-sectional study using the National Hospital Ambulatory Medical Care Survey to examine time trends in age-stratified primary reasons for visit, stroke/TIA diagnoses, and MRI utilization from 1995 to 2000 and 2005–2015.

Results

Five million eight hundred thousand ED visits with a primary diagnosis of stroke (CI 5.3 M–6.4 M) were represented in the data. The incidence of neurologically focused reason for visits (Neuro RFVs) increased over time in both the young and in older adults (young: + 111 Neuro RFVs/100,000 population/year, CI + 94 − + 130; older adults: + 70 Neuro RFVs/100,000 population/year, CI + 34 − + 108). The proportion of combined stroke and TIA diagnoses decreased over time amongst older adults with a Neuro RFV (OR 0.95 per year, p < 0.01, CI 0.94–0.96) but did not change in the young (OR 1.00 per year, p = 0.88, CI 0.95–1.04). Within the stroke/TIA population, no changes in the proportion of stroke or TIA were identified. MRI utilization rates amongst patients with a Neuro RFV increased for both age groups.

Conclusions

We found, but did not anticipate, increased incidence of neurologically focused ED visits in both age groups. Given the lower pre-test probability of a stroke in younger adults, this suggests that false positive stroke diagnoses may be increasing and may be increasing more rapidly in the young than in older adults.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02172-1.

Stroke in young adults: Current trends, opportunities for prevention and pathways forward

Cardiovascular disease remains a major contributor to morbidity and mortality in the US and elsewhere, and stroke is a leading cause of disability worldwide. Despite recent success in diminishing stroke incidence in the general US population, in parallel there is now a concerning propensity for strokes to happen at younger ages. Specifically, the incidence of stroke for US adults 20-44 years of age increased from 17 per 100,000 US adults in 1993 to 28 per 100,000 in 2015. Occurrence of strokes in young adults is particularly problematic as these patients are often affected by physical disability, depression, cognitive impairment and loss of productivity, all of which have vast personal, social and economic implications. These concerning trends among young adults are likely due to increasing trends in the prevalence of modifiable risk factors amongst this population including hypertension, hyperlipidemia, obesity and diabetes, highlighting the importance of early detection and aggressive prevention strategies in the general population at early ages. In parallel and compounding to the issue, troublesome trends are evident regarding increasing rates of substance abuse among young adults. Higher rates of strokes have been noted particularly among young African Americans, indicating the need for tailored prevention and social efforts targeting this and other vulnerable groups, including the primordial prevention of risk factors in the first place, reducing stroke rates in the presence of prevalent risk factors such as hypertension, and improving outcomes through enhanced healthcare access. In this narrative review we aim to emphasize the importance of stroke in young adults as a growing public health issue and increase awareness among clinicians and the public health sector. For this purpose, we summarize the available data on stroke in young adults and discuss the underlying epidemiology, etiology, risk factors, prognosis and opportunities for timely prevention of stroke specifically at young ages. Furthermore, this review highlights the gaps in knowledge and proposes future directions moving forward.

Temporal Trends in Stroke Incidence Over Time by Sex and Age in the GCNKSS

Background and Purpose- Sex differences in stroke incidence over time were previously reported from the GCNKSS (Greater Cincinnati/Northern Kentucky Stroke Study). We aimed to determine whether these differences continued through 2015 and whether they were driven by particular age groups. Methods- Within the GCNKSS population of 1.3 million, incident (first ever) strokes among residents ≥20 years of age were ascertained at all local hospitals during 5 periods: July 1993 to June 1994 and calendar years 1999, 2005, 2010, and 2015. Out-of-hospital cases were sampled. Sex-specific incidence rates per 100 000 were adjusted for age and race and standardized to the 2010 US Census. Trends over time by sex were compared (overall and age stratified). Sex-specific case fatality rates were also reported. Bonferroni corrections were applied for multiple comparisons. Results- Over the 5 study periods, there were 9733 incident strokes (56.3% women). For women, there were 229 (95% CI, 215-242) per 100 000 incident strokes in 1993/1994 and 174 (95% CI, 163-185) in 2015 (P<0.05), compared with 282 (95% CI, 263-301) in 1993/1994 to 211 (95% CI, 198-225) in 2015 (P<0.05) in men. Incidence rates decreased between the first and last study periods in both sexes for IS but not for intracerebral hemorrhage or subarachnoid hemorrhage. Significant decreases in stroke incidence occurred between the first and last study periods for both sexes in the 65- to 84-year age group and men only in the ≥85-year age group; stroke incidence increased for men only in the 20- to 44-year age group. Conclusions- Overall stroke incidence decreased from the early 1990s to 2015 for both sexes. Future studies should continue close surveillance of sex differences in the 20- to 44-year and ≥85-year age groups, and future stroke prevention strategies should target strokes in the young- and middle-age groups, as well as intracerebral hemorrhage.

Temporal Trends of Sex Differences in Transient Ischemic Attack Incidence Within a Population

OBJECTIVE

Previously we reported that ischemic stroke incidence is declining over time for men but not women. We sought to describe temporal trends of sex differences in incidence of transient ischemic attack (TIA) within the same large, biracial population.

METHODS

Among the population of 1.3 million in the Greater Cincinnati Northern Kentucky Stroke Study (GCNKSS) region, TIAs among area residents (≥20 years old) were identified at all local hospitals. Out of hospital cases were ascertained using a sampling scheme. First-ever cases and first within each study period for a patient was included in incidence rates. All cases were physician-adjudicated. Incidence rates (during July 93-June 94 and calendar years 1999, 2005, and 2010) were calculated using the age-, race-, and sex-specific number of TIAs divided by the GCNKSS population in that group; rates were standardized to the 2010 U.S.

POPULATION

t Tests with Bonferroni correction were used to compare rates over time.

RESULTS

There were a total of 4746 TIA events; 53% were female, and 12% were black. In males, incidence decreased from 153 (95% confidence interval [CI] 139-167) per 100,000 in 1993/4 to 117 (95% CI 107-128) in 2010 (P < .05 for trend test) but was similar over time among females (107 (95% CI 97-116) to 102 (95%CI 94-111), P > .05).

CONCLUSIONS

Within the GCNKSS population, TIA incidence decreased significantly over time in males but not females, data which parallels trends in ischemic stroke in the GCNKSS over the same time period. Future research is needed to determine if these sex differences in incidence over time continue past 2010.

Temporal trends in age at ischemic stroke onset by ethnicity

PURPOSE

To explore temporal trends in age at first-ever ischemic stroke onset in a bi-ethnic, population-based study.

METHODS

Cases of first-ever ischemic stroke (n = 3252) were identified in the Brain Attack Surveillance in Corpus Christi Project (2000-2012). Demographics and risk factors were abstracted from medical records. Trends in age at stroke onset were assessed overall and by ethnicity (Mexican American [MA] and non-Hispanic white [NHW]) using generalized additive models. Differences by ethnicity were tested by including an interaction term between time and ethnicity. Models were run unadjusted and adjusted for age of the population at risk for stroke.

RESULTS

Mean age at first-ever ischemic stroke significantly decreased from an average of 71.7 years in 2000 to an average of 69.3 years in 2012 (p = .0043). Ethnicity significantly modified the temporal trends (p < .001) with declines greater in NHWs than in MAs; mean age was estimated to decrease from 74.8 to 71.3 over the 13 years for NHWs, whereas for MAs, mean age was estimated to decrease from 68.9 to 66.9 after adjusting for ethnic-specific average age of the population at risk.

CONCLUSIONS

Average age at first-ever stroke onset declined over time in this community. Efforts should be made to prevent stroke by controlling risk factors before and during midlife.

Stroke hospitalization trends of the working-aged in Finland

BACKGROUND

The age-standardized incidence of stroke has decreased globally but, for reasons unknown, conflicting results have been observed regarding trend in incidence of major stroke subtypes in young adults. We studied these trends among people of working age in a population-based setting in Finland, where cardiovascular risk factor profiles have developed favorably.

METHODS

All hospitalizations for stroke in 2004-2005 and 2013-2014 for persons 18-64 years of age were identified from a national register. The search included all hospitals that provide acute stroke care on mainland Finland.

RESULTS

Hospitalizations for both intracerebral hemorrhage (ICH; -15.2%; p = 0.0008) and subarachnoid hemorrhage (SAH; -26.5%; p<0.0001) decreased overall and for both sexes separately. Concerning IS, hospitalizations decreased only for men (-6.3%; p = 0.0190) but not for women or overall. However, there was an increase in IS hospitalizations in men 35-44 years of age (+37.5%; p = 0.0019). The length of stay (LOS) of IS patients declined in nearly all subgroups (overall -20.8%, p<0.0001) whereas no change in LOS was observed for patients with ICH or SAH. In-hospital mortality decreased in patients with IS (-42.8%; p = 0.0092) but remained unchanged in patients with ICH or SAH.

CONCLUSIONS

Stroke hospitalizations of young people declined in Finland, except for men 35-44 years of age for whom IS hospitalizations increased. Declining LOS and in-hospital mortality of IS patients suggests admission of less severe cases, improved care or both.

Towards phenotyping stroke: Leveraging data from a large-scale epidemiological study to detect stroke diagnosis

Objective

1) To develop a machine learning approach for detecting stroke cases and subtypes from hospitalization data, 2) to assess algorithm performance and predictors on real-world data collected by a large-scale epidemiology study in the US; and 3) to identify directions for future development of high-precision stroke phenotypic signatures.

Materials and methods

We utilized 8,131 hospitalization events (ICD-9 codes 430–438) collected from the Greater Cincinnati/Northern Kentucky Stroke Study in 2005 and 2010. Detailed information from patients’ medical records was abstracted for each event by trained research nurses. By analyzing the broad list of demographic and clinical variables, the machine learning algorithms predicted whether an event was a stroke case and, if so, the stroke subtype. The performance was validated on gold-standard labels adjudicated by stroke physicians, and results were compared with stroke classifications based on ICD-9 discharge codes, as well as labels determined by study nurses.

Results

The best performing machine learning algorithm achieved a performance of 88.57%/93.81%/92.80%/93.30%/89.84%/98.01% (accuracy/precision/recall/F-measure/area under ROC curve/area under precision-recall curve) on stroke case detection. For detecting stroke subtypes, the algorithm yielded an overall accuracy of 87.39% and greater than 85% precision on individual subtypes. The machine learning algorithms significantly outperformed the ICD-9 method on all measures (P value<0.001). Their performance was comparable to that of study nurses, with better tradeoff between precision and recall. The feature selection uncovered a subset of predictive variables that could facilitate future development of effective stroke phenotyping algorithms.

Discussion and conclusions

By analyzing a broad array of patient data, the machine learning technologies held promise for improving detection of stroke diagnosis, thus unlocking high statistical power for subsequent genetic and genomic studies.

Prevalence of Cardiovascular Risk Factors and Strokes in Younger Adults

Importance

While stroke mortality rates have decreased substantially in the past 2 decades, this trend has been primarily limited to older adults. Increasing trends in stroke incidence and hospitalizations have been noted among younger adults, but there has been concern that this reflected improved diagnosis through an increased use of imaging rather than representing a real increase.

Objectives

To determine whether stroke hospitalization rates have continued to increase and to identify the prevalence of associated stroke risk factors among younger adults.

Design, Setting, and Participants

Hospitalization data from the National Inpatient Sample from 1995 through 2012 were used to analyze acute stroke hospitalization rates among adults aged 18 to 64 years. Hospitalization data from 2003 to 2012 were used to identify the prevalence of associated risk factors for acute stroke. Acute stroke hospitalizations were identified by the principal International Classification of Diseases, Ninth Revision, Clinical Modification code and associated risk factors were identified by secondary International Classification of Diseases, Ninth Revision, Clinical Modification codes for each hospitalization.

Main Outcomes and Measures

Trends in acute stroke hospitalization rates by stroke type, age, sex, and race/ethnicity, as well as the prevalence of associated risk factors by stroke type, age, and sex.

Results

The 2003-2004 set included 362 339 hospitalizations and the 2011-2012 set included 421 815 hospitalizations. The major findings in this study are as follows: first, acute ischemic stroke hospitalization rates increased significantly for both men and women and for certain race/ethnic groups among younger adults aged 18 to 54 years; they have almost doubled for men aged 18 to 34 and 35 to 44 years since 1995-1996, with a 41.5% increase among men aged 35 to 44 years from 2003-2004 to 2011-2012. Second, the prevalence of stroke risk factors among those hospitalized for acute ischemic stroke continued to increase from 2003-2004 through 2011-2012 for both men and women aged 18 to 64 years (range of absolute increase: hypertension, 4%-11%; lipid disorders, 12%-21%; diabetes, 4%-7%; tobacco use, 5%-16%; and obesity, 4%-9%). Third, the prevalence of having 3 to 5 risk factors increased from 2003-2004 through 2011-2012 (men: from 9% to 16% at 18-34 years, 19% to 35% at 35-44 years, 24% to 44% at 45-54 years, and 26% to 46% at 55-64 years; women: 6% to 13% at 18-34 years, 15% to 32% at 35-44 years, 25% to 44% at 45-54 years, and 27% to 48% at 55-65 years; P for trend < .001). Finally, hospitalization rates for intracerebral hemorrhage and subarachnoid hemorrhage remained stable, with the exception of declines among men and non-Hispanic black patients aged 45 to 54 with subarachnoid hemorrhage (13.2/10 000 to 10.3/10 000 hospitalizations and 15.8/10 000 to 11.5/10 000 hospitalizations, respectively).

Conclusions and Relevance

The identification of increasing hospitalization rates for acute ischemic stroke in young adults coexistent with increasing prevalence of traditional stroke risk factors confirms the importance of focusing on prevention in younger adults.

Ischemic Stroke Rate Increases in Young Adults: Evidence for a Generational Effect?

BACKGROUND

The incidence rates of ischemic stroke and ST-segment elevation myocardial infarction (STEMI) have decreased significantly in the United States since 1950. However, there is evidence of flattening of this trend or increasing rates for stroke in patients younger than 50 years. The objective of this study was to examine the changes in incidence rates of stroke and STEMI using an age-period-cohort model with statewide data from New Jersey.

METHODS AND RESULTS

We obtained stroke and STEMI data for the years 1995-2014 from the Myocardial Infarction Data Acquisition System, a database of hospital discharges in New Jersey. Rates by age for the time periods 1994-1999, 2000-2004, 2005-2009, and 2010-2014 were obtained using census estimates as denominators for each age group and period. The rate of stroke more than doubled in patients aged 35 to 39 years from 1995-1999 to 2010-2014 (rate ratio [RR], 2.47; 95% CI, 2.07-2.96 [P<0.0001]). We also found increased rates of stroke in those aged 40 to 44, 45 to 49, and 50 to 54 years. Strokes rates in those older than 55 years decreased during these time periods. Those born from 1945-1954 had lower age-adjusted rates of stroke than those born both in the prior 20 years and in the following 20 years. STEMI rates, in contrast, decreased in all age groups and in each successive birth cohort.

CONCLUSIONS

There appears to be a significant birth cohort effect in the risk of stroke, where patients born from 1945-1954 have lower age-adjusted rates of stroke compared with those born in earlier and later years.

Potentially Missed Diagnosis of Ischemic Stroke in the Emergency Department in the Greater Cincinnati/Northern Kentucky Stroke Study

OBJECTIVE

Missed diagnoses of acute ischemic stroke (AIS) in the ED may result in lost opportunities to treat AIS. Our objectives were to describe the rate and clinical characteristics of missed AIS in the ED, to determine clinical predictors of missed AIS, and to report tissue plasminogen (tPA) eligibility among those with missed strokes.

METHODS

Among a population of 1.3 million in a five-county region of southwest Ohio and northern Kentucky, cases of AIS that presented to 16 EDs during 2010 were identified using ICD-9 codes followed by physician verification of cases. Missed ED diagnoses were physician-verified strokes that did not receive a diagnosis indicative of stroke in the ED. Bivariate analyses were used to compare clinical characteristics between patients with and without an ED diagnosis of AIS. Logistic regression was used to evaluate predictors of missed AIS diagnoses. Alternative diagnoses given to those with missed AIS were codified. Eligibility for tPA was reported between those with and without a missed stroke diagnosis.

RESULTS

Of 2,027 AIS cases, 14.0% (n = 283) were missed in the ED. Race, sex, and stroke subtypes were similar between those with missed AIS diagnoses and those identified in the ED. Hospital length of stay was longer in those with a missed diagnosis (5 days vs. 3 days, p < 0.0001). Younger age (adjusted odds ratio [aOR] = 0.94, 95% confidence interval [CI] = 0.89 to 0.98) and decreased level of consciousness (LOC) (aOR = 3.58, 95% CI = 2.63 to 4.87) were associated with higher odds of missed AIS. Altered mental status was the most common diagnosis among those with missed AIS. Only 1.1% of those with a missed stroke diagnosis were eligible for tPA.

CONCLUSION

In a large population-based sample of AIS cases, one in seven cases were not diagnosed as AIS in the ED, but the impact on acute treatment rates is likely small. Missed diagnosis was more common among those with decreased LOC, suggesting the need for improved diagnostic approaches in these patients.

High-Performance Upconversion Nanoprobes for Multimodal MR Imaging of Acute Ischemic Stroke

Multimodal magnetic resonance (MR) imaging, including MR angiography (MRA) and MR perfusion (MRP), plays a critical role in the diagnosis and surveillance of acute ischemic stroke. However, these techniques are hindered by the low T1 relaxivity, short circulation time, and high leakage rate from vessels of clinical Magnevist. To address these problems, nontoxic polyethylene glycol (PEG)ylated upconversion nanoprobes (PEG-UCNPs) are synthesized and first adopted for excellent MRA and MRP imaging, featuring high diagnostic sensitivity toward acute ischemic stroke in high-resolution imaging. The investigations show that the agent possesses superior advantages over clinical Magnevist, such as much higher relaxivity, longer circulation time, and lower leakage rate, which guarantee much better imaging efficiency. Remarkably, an extremely small dosage (5 mg Gd kg(-1) ) of PEG-UCNPs provides high-resolution MRA imaging with the vascular system delineated much clearer than the Magnevist with clinical dosage as high as 108 mg Gd kg(-1) . On the other hand, the long circulation time of PEG-UCNPs enables the surveillance of the progression of ischemic stroke using MRA or MRP. Once translated, these PEG-UCNPs are expected to be a promising candidate for substituting the clinical Magnevist in MRA and MRP, which will significantly lengthen the imaging time window and improve the overall diagnostic efficiency.