Introduction: Improvements in stroke patient care have led to increases in stroke survivors. However, these survivors are prone to hospital readmission, a burden for both patients and health system deserving of greater investigation. We hypothesize rates and risk factors for stroke patient readmission are not consistent across age. Thus, our aim was to characterize age related patterns of post stroke readmission including trends in patient and healthcare factors.
Methods: Using the Discharge Abstract Database, a collection of hospital discharge records maintained by the Canadian Institute for Health Information, patients aged 18+ discharged with the main diagnosis of stroke/TIA between 2003-2014 were identified. Three age groups (18-44, 45-64, 65+) were determined for comparison of age related trends in stroke readmission. Trends were identified using the Cochran-Armitage and Jonckheere-Terpstra tests for binary and larger categorical events respectively. Kaplan-Meier analysis for 90-day recurrence, Chi-squared and multivariable Cox regression analysis for probability and risk of readmission were also performed.
Results: A total of 267,768 patients had at least one stroke admission and were discharged alive. The mean age overall was 72 ±14.34 where 4% were aged 18-44, 23% aged 45-64, and 73% aged 65+. The younger groups were predominantly male and the oldest more female (p<0.0001). There were 48,078 (18%) patients readmitted to hospital of which 69% had a recurrent stroke. Rates of death and recurrence were highest among older patients (p<0.0001). Older patients had longer hospital stay than young (p<0.0001), suffered more comorbidities (p<0.0001), and more discharges to long-term care (p<0.0001). Patients aged 18-44 had the shortest time to readmission (mean=478 ±729 days, p<0.0001) and were more likely to be treated by a neuro-specialist. Cohen’s Kappa analysis revealed patients aged 18-44 had the highest agreement between index and recurrent stroke type (κ=0.44 (95%CI 0.38-0.49))
Conclusions: Age related differences in stroke readmission is evident. With this information better targeted treatment and prevention strategies can be implemented.