Abstract
BACKGROUND: We aimed to identify groups of patients with similar health status after stroke, assessed by patient reported outcome measures (PROMs), to improve initial risk stratification. METHODS: In a prospective study, inpatients were recruited during acute stroke treatment. Demographics, history, and cardio-vascular risk factors were assessed at baseline. Self-reported functional status, physical and mental health as well as anxiety and depressive symptoms were assessed 3 and 12 months after stroke and used to identify latent classes. The association of patient characteristics with latent class membership was investigated with multinomial logistic regression. RESULTS: Of the 650 patients included with a mean age of 75 years and 48% female, 70% had ischemic, 6% hemorrhagic strokes, and 24% transient ischemic attacks. Median NIHSS on admission was 2 (IQR:0,5). Values of PROMs remained comparable at 3 and 12 months. A three-class model was developed, differentiating between patients with mildly (75%), moderately (17%), and severely (8%) impaired self-reported health status. Adjusted for univariately significant baseline characteristics, initial NIHSS distinguished mild- from moderate-, and moderate- from severe-class-membership (p < 0.001). Length of inpatient stay (p < 0.001;OR = 1.1), diabetes (p = 0.021;OR = 1.91), and atrial fibrillation (p = 0.004;OR = 2.20) predicted allocation to the moderately vs. mildly affected class. CONCLUSIONS: Grading stroke patients by a standard set of PROMs up to 1 year after stroke allows to distinguish the diverse impact of baseline characteristics on differently affected groups. In addition to initial stroke severity, longer inpatient stay, presence of diabetes and atrial fibrillation correlate with greater impairment of self-reported health in the less affected groups. TRIAL REGISTRATION: http://www.ClinicalTrials.gov ; Unique identifier: NCT03795948 .