title: Improved survival after stroke: is admission to hospital the major explanation? Trend analyses of the Auckland Regional Community Stroke Studies.
abstract: BACKGROUND
  There is uncertainty regarding the impact of changes in stroke care and natural history of stroke in the community. We examined factors responsible for trends in survival after stroke in a series of population-based studies.
  
  
  METHODS
  We used statistical models to assess temporal trends in 28-day and 1-year case fatality after first-ever stroke cases registered in 3 stroke incidence studies undertaken in Auckland, New Zealand, over uniform 12-month calendar periods in 1981-1982 (n = 1,030), 1991-1992 (1,305) and 2001-2002 (1,423). Cox proportional hazards regression was used to evaluate the significance of pre-defined 'patient', 'disease' and 'service/care' factors on these trends.
  
  
  RESULTS
  Overall, there was a 40% decline in 28-day case fatality after stroke over the study periods, from 32% (95% confidence interval, 29-35%) in 1981-1982 to 23% (21-25%) in 1991-1992 and then 19% (17-21%) in 2002-2003. Similar relative declines were seen in 1-year case fatality. In regression models, the trends were still significant after adjusting for patient and disease factors. However, further adjustment for care factors (higher hospital admission and neuroimaging) explained most of the improvement in survival.
  
  
  CONCLUSIONS
  These data show significant downwards trends in case fatality after stroke in Auckland over 20 years, which can largely be attributed to improved stroke care associated with increases in hospital admission and brain imaging during the acute phase of the illness.
authors.affiliation: George Institute for International Health, University of Sydney, Royal Prince Alfred Hospital, Sydney, Australia. kcarter@thegeorgeinstitute.org
authors.forename: Kristie N
authors.initials: KN
authors.lastname: Carter
authors.forename: Craig S
authors.initials: CS
authors.lastname: Anderson
authors.forename: Maree L
authors.initials: ML
authors.lastname: Hackett
authors.forename: P Alan
authors.initials: PA
authors.lastname: Barber
authors.forename: Ruth
authors.initials: R
authors.lastname: Bonita
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000473:pathology*; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009026:Mortality / Q000639:trends; D009520:New Zealand / Q000453:epidemiology; D011159:Population Surveillance; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012042:Registries; D012720:Severity of Illness Index; D017678:Sex Distribution; D020521:Stroke / Q000175:diagnosis* / Q000208:ethnology / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data*