Literature DB >> 33431950

Associating cryptogenic ischemic stroke in the young with cardiovascular risk factor phenotypes.

Joseph M Dardick1, David Flomenbaum2, Daniel L Labovitz2,3, Natalie Cheng2,3, Ava L Liberman2,3, Charles Esenwa2,3.   

Abstract

Acute Ischemic Stroke (AIS) in the young is increasing in prevalence and the largest subtype within this cohort is cryptogenic. To curb this trend, new ways of defining cryptogenic stroke and associated risk factors are needed. We aimed to gain insights into the presence or absence of cardiovascular risk factors in cases of cryptogenic stroke. We conducted a retrospective cohort study of patients aged 18-49 who presented to an urban tertiary care center with AIS. We manually collected predefined demographic, clinical, laboratory and radiological variables. Clinical risk phenotypes were determined using these variables through multivariate analysis of patients with the small and large vessel disease subtypes (vascular phenotype) and cardioembolic subtype (cardiac phenotype). The resultant phenotype models were applied to cases deemed cryptogenic. Within the 449 patients who met criteria, patients with small and large vessel disease (vascular phenotype) had higher rates of hypertension, intracranial atherosclerosis, and diabetes mellitus, and higher admission glucose, HbA1c, admission blood pressure, and cholesterol compared to the patients with cardioembolic AIS. The cardioembolic subgroup (cardiac phenotype) had significantly higher rates of congestive heart failure (CHF), rheumatic heart disease, atrial fibrillation, clotting disorders, left ventricular hypertrophy, larger left atrial sizes, lower ejection fractions, and higher B-type natriuretic peptide and troponin levels. Adjusted multivariate analysis produced six variables independently associated with the vascular phenotype (age, male sex, hemoglobin A1c, ejection fraction (EF), low-density lipoprotein (LDL) cholesterol, and family history of AIS) and five independently associated with the cardiac phenotype (age, female sex, decreased EF, CHF, and absence of intracranial atherosclerosis). Applying these models to cryptogenic stroke cases yielded that 51.5% fit the vascular phenotype and 3.1% fit the cardiac phenotype. In our cohort, half of young patients with cryptogenic stroke fit the risk factor phenotype of small and large vessel strokes.

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Year:  2021        PMID: 33431950      PMCID: PMC7801422          DOI: 10.1038/s41598-020-79499-1

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  24 in total

1.  Carotid Webs in Cryptogenic Ischemic Strokes: A Matched Case-Control Study.

Authors:  Song J Kim; Jason W Allen; Mehdi Bouslama; Fadi Nahab; Michael R Frankel; Raul G Nogueira; Diogo C Haussen
Journal:  J Stroke Cerebrovasc Dis       Date:  2019-09-26       Impact factor: 2.136

2.  Recurrent cerebrovascular events associated with patent foramen ovale, atrial septal aneurysm, or both.

Authors:  J L Mas; C Arquizan; C Lamy; M Zuber; L Cabanes; G Derumeaux; J Coste
Journal:  N Engl J Med       Date:  2001-12-13       Impact factor: 91.245

3.  Carotid Bulb Webs as a Cause of "Cryptogenic" Ischemic Stroke.

Authors:  P I Sajedi; J N Gonzalez; C A Cronin; T Kouo; A Steven; J Zhuo; O Thompson; R Castellani; S J Kittner; D Gandhi; P Raghavan
Journal:  AJNR Am J Neuroradiol       Date:  2017-05-11       Impact factor: 3.825

4.  Trends in stroke hospitalizations and associated risk factors among children and young adults, 1995-2008.

Authors:  Mary G George; Xin Tong; Elena V Kuklina; Darwin R Labarthe
Journal:  Ann Neurol       Date:  2011-09-02       Impact factor: 10.422

5.  Forecasting the future of stroke in the United States: a policy statement from the American Heart Association and American Stroke Association.

Authors:  Bruce Ovbiagele; Larry B Goldstein; Randall T Higashida; Virginia J Howard; S Claiborne Johnston; Olga A Khavjou; Daniel T Lackland; Judith H Lichtman; Stephanie Mohl; Ralph L Sacco; Jeffrey L Saver; Justin G Trogdon
Journal:  Stroke       Date:  2013-05-22       Impact factor: 7.914

6.  Interobserver agreement in the trial of org 10172 in acute stroke treatment classification of stroke based on retrospective medical record review.

Authors:  James F Meschia; Kevin M Barrett; Felix Chukwudelunzu; W Mark Brown; L Douglas Case; Brett M Kissela; Robert D Brown; Thomas G Brott; Tammy S Olson; Stephen S Rich; Scott Silliman; Bradford B Worrall
Journal:  J Stroke Cerebrovasc Dis       Date:  2006 Nov-Dec       Impact factor: 2.136

7.  Risk factor profile by etiological subtype of ischemic stroke in the young.

Authors:  Aude Jaffre; Jean Bernard Ruidavets; Lionel Calviere; Alain Viguier; Jean Ferrieres; Vincent Larrue
Journal:  Clin Neurol Neurosurg       Date:  2014-03-01       Impact factor: 1.876

8.  Increasing prevalence of vascular risk factors in patients with stroke: A call to action.

Authors:  Fadar Oliver Otite; Nicholas Liaw; Priyank Khandelwal; Amer M Malik; Jose G Romano; Tatjana Rundek; Ralph L Sacco; Seemant Chaturvedi
Journal:  Neurology       Date:  2017-10-11       Impact factor: 9.910

9.  Embolic strokes of undetermined source: the case for a new clinical construct.

Authors:  Robert G Hart; Hans-Christoph Diener; Shelagh B Coutts; J Donald Easton; Christopher B Granger; Martin J O'Donnell; Ralph L Sacco; Stuart J Connolly
Journal:  Lancet Neurol       Date:  2014-04       Impact factor: 44.182

Review 10.  Strokes in young adults: epidemiology and prevention.

Authors:  Dževdet Smajlović
Journal:  Vasc Health Risk Manag       Date:  2015-02-24
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