title: Age-dependent susceptibility to infarct growth in women.
abstract: OBJECTIVE
  It is not known if there is a relationship between gender and tissue outcome in human ischemic stroke. We sought to identify whether the proportion of initially ischemic to eventually infarcted tissue was different between men and women with ischemic stroke.
  
  
  METHODS
  We studied 141 consecutive patients with acute ischemic stroke who had a baseline MRI obtained within 12 hours of symptom onset, a follow-up imaging on Day 4 or later, and diffusion-weighted imaging/mean transmit time mismatch on initial MRI. Lesion growth was calculated as percentage of mismatch tissue that underwent infarction on follow-up (percentage mismatch lost). Multivariable analyses explored the effect of gender and other predictors of tissue outcome on percentage mismatch lost.
  
  
  RESULTS
  There was no difference in median percentage mismatch lost between men (19%) and women (11%; P=0.720). There was, however, an interaction between gender and age; median percentage mismatch lost was 7% (0% to 12%) in women and 18% (1% to 35%) in men younger than the population median (71 years, P=0.061). The percentage mismatch lost was not different between men and women ≥71 years old (25% in both groups). The linear regression model revealed gender (P=0.027) and the interaction between age and gender (P=0.023) as independent predictors of percentage mismatch lost.
  
  
  CONCLUSIONS
  There is an age-by-gender interaction in tissue outcome after ischemic stroke; brain infarcts in women <70 years grow approximately 50% less than infarcts in their male counterparts. These findings extend the well-known concept that there is a differential age-by-gender effect on stroke incidence, mortality, and functional outcome to the tissue level.
authors.affiliation: AA Martinos Center for Biomedical Imaging and Stroke Service, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Room 2301, Charlestown, MA 02129, USA.
authors.forename: Figen
authors.initials: F
authors.lastname: Gokcay
authors.forename: Ethem Murat
authors.initials: EM
authors.lastname: Arsava
authors.forename: Tuna
authors.initials: T
authors.lastname: Baykaner
authors.forename: Mark
authors.initials: M
authors.lastname: Vangel
authors.forename: Priya
authors.initials: P
authors.lastname: Garg
authors.forename: Ona
authors.initials: O
authors.lastname: Wu
authors.forename: Aneesh B
authors.initials: AB
authors.lastname: Singhal
authors.forename: Karen L
authors.initials: KL
authors.lastname: Furie
authors.forename: A Gregory
authors.initials: AG
authors.lastname: Sorensen
authors.forename: Hakan
authors.initials: H
authors.lastname: Ay
mesh_terms: D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000473:pathology*; D001921:Brain / Q000098:blood supply / Q000473:pathology* / Q000503:physiopathology; D020520:Brain Infarction / Q000453:epidemiology* / Q000473:pathology* / Q000503:physiopathology; D015984:Causality; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012727:Sex Characteristics; D017678:Sex Distribution