Hagen, Clinton

Background and purpose: In-hospital stroke-onset assessment and management present numerous challenges, especially in community hospitals. Comprehensive analysis of key stroke care metrics in community-based primary stroke centers is under-studied. Methods: Medical records were reviewed for patients admitted to a community hospital for non-cerebrovascular indications and for whom a stroke alert was activated between 2013 and 2019. Demographic, clinical, radiologic and laboratory information were collected for each incident stroke. Descriptive statistical analysis was employed. When applicable, Kruskal-Wallis and Chi-Square tests were used to compare median values and categorical data between pre-specified groups. Statistical significance was set at alpha = 0.05. Results: There were 192 patients with in-hospital stroke-alert activation; mean age (SD) was 71.0 years (15.0), 49.5% female. 51.6% (99/192) had in-hospital ischemic and hemorrhagic stroke. The most frequent mechanism of stroke was cardioembolism. Upon stroke activation, 45.8% had ischemic stroke while 40.1% had stroke mimics. Stroke team response time from activation was 26 minutes for all in-hospital activations. Intravenous thrombolysis was utilized in 8% of those with ischemic stroke; 3.4% were transferred for consideration of endovascular thrombectomy. In-hospital mortality was 17.7%, and the proportion of patients discharged to home was 34.4% for all activations. Conclusion: The in-hospital stroke mortality was high, and the proportions of patients who either received or were considered for acute intervention were low. Quality improvement targeting increased use of acute stroke intervention in eligible patients and reducing hospital mortality in this patient cohort is needed.

Background: Previous studies reported that slower gait speed might predict cognitive impairment and dementing illnesses, supporting the role of gait speed as a possible subclinical marker of cognitive impairment. However, the predictive value of other gait parameters for cognitive decline is unclear. Objective: To investigate and compare the association with, and prediction of, specific gait parameters for cognition in a population-based sample. Methods: The analysis included 3,426 cognitively normal participants enrolled in the Mayo Clinic Study of Aging. At baseline and every 15 months (mean follow-up = 1.93 years), participants had a study coordinator evaluation, neurological examination, and a neuropsychological assessment using nine tests that covered four domains. Gait parameters were assessed with the GAITRite ® instrument. General linear mixed effects models were used to compute the annualized rate of change in cognitive domain z-scores, controlling for age, sex, education, depression, comorbidities, body mass index, APOE ɛ 4 allele, and visit number, and excluding individuals with a history of stroke, alcoholism, Parkinson’s disease, subdural hematoma, and normal pressure hydrocephalus. Results: Spatial (stride length), temporal (ambulatory time, gait speed, step count, cadence, double support time), and spatiotemporal (cadence) gait parameters, and greater intraindividual variability in stride length, swing time, and stance time were associated with a significant decline in global cognition and in specific domains including memory, executive function, visuospatial, and language. Conclusions: Spatial, temporal, and spatiotemporal measures of gait and greater variability of gait parameters were associated with and predictive of both global- and domain-specific cognitive decline.