Assessing the Predictive Validity of Simple Dementia Risk Models in Harmonized Stroke Cohorts.

BACKGROUND AND PURPOSE: Stroke is associated with an increased risk of dementia. To assist in the early identification of individuals at high risk of future dementia, numerous prediction models have been developed for use in the general population. However, it is not known whether such models also provide accurate predictions among stroke patients. Therefore, the aim of this study was to determine whether existing dementia risk prediction models that were developed for use in the general population can also be applied to individuals with a history of stroke to predict poststroke dementia with equivalent predictive validity. METHODS: Data were harmonized from 4 stroke studies (follow-up range, ≈12-18 months poststroke) from Hong Kong, the United States, the Netherlands, and France. Regression analysis was used to test 3 risk prediction models: the Cardiovascular Risk Factors, Aging and Dementia score, the Australian National University Alzheimer Disease Risk Index, and the Brief Dementia Screening Indicator. Model performance or discrimination accuracy was assessed using the C statistic or area under the curve. Calibration was tested using the Grønnesby and Borgan and the goodness-of-fit tests. RESULTS: The predictive accuracy of the models varied but was generally low compared with the original development cohorts, with the Australian National University Alzheimer Disease Risk Index (C-statistic, 0.66) and the Brief Dementia Screening Indicator (C-statistic, 0.61) both performing better than the Cardiovascular Risk Factors, Aging and Dementia score (area under the curve, 0.53). CONCLUSIONS: Dementia risk prediction models developed for the general population do not perform well in individuals with stroke. Their poor performance could have been due to the need for additional or different predictors related to stroke and vascular risk factors or methodological differences across studies (eg, length of follow-up, age distribution). Future work is needed to develop simple and cost-effective risk prediction models specific to poststroke dementia.

Prevalence of poststroke anxiety and its associations with global cognitive impairment: An individual participant data analysis.

BACKGROUND AND PURPOSE: Anxiety is frequent after stroke; however, little is known about its determinants. This study aims to assess the prevalence and correlates of post stroke anxiety (PSA) within 3-6 months following ischemic stroke. METHODS: Three cohort studies from the STROKOG consortium were involved. Demographic and clinical data were standardized. PSA and PSD were assessed using inventories. The criteria for post-stroke cognitive impairment (PSCI) were at least one cognitive domain impaired if applicable, or a Montreal Cognitive Assessment (MoCA) score. Descriptive analyses were conducted to ascertain the prevalence of anxiety. Comparisons between anxious and non-anxious patients in the total sample were made using χ2 and t-tests. A two-step individual participant data (IPD) meta-analysis was employed to identify factors associated with PSA. RESULTS: 584 patients were included. The total prevalence of PSA was 35 % (95%CI = [31.23;38.97]) and ranged from 27 % to 45 % across cohorts. In the total sample, there was a higher proportion of females in the anxiety group than the non-anxiety group (χ2 = 19.62; p < 0.001). Anxious patients had lower education, (χ2 = 6.59; p = 0.03), higher stroke severity (t = 2.77; p = 0.002), and higher rates of PSD (χ2 = 118.09; p < 0.001), and PSCI (χ2 = 23.81, p < 0.001). The analysis demonstrates that the odds of presenting with PSA is larger in patients with PSCI (OR = 1.84, 95%CI = [1.14; 2.91]). CONCLUSIONS: Anxiety is frequent after stroke, especially in females, and is associated with depression and cognitive impairment.

Endothelial Dysfunction and Pre-Existing Cognitive Disorders in Stroke Patients.

BACKGROUND: The origin of pre-existing cognitive impairment in stroke patients remains controversial, with a vascular or a degenerative hypothesis. OBJECTIVE: To determine whether endothelial dysfunction is associated with pre-existing cognitive problems, lesion load and biological anomalies in stroke patients. METHODS: Patients originated from the prospective STROKDEM study. The baseline cognitive state, assessed using the IQ-CODE, and risk factors for stroke were recorded at inclusion. Patients with an IQ-CODE score >64 were excluded. Endothelial function was determined 72 h after stroke symptom onset by non-invasive digital measurement of endothelium-dependent flow-mediated dilation and calculation of the reactive hyperemia index (RHI). RHI ≤ 1.67 indicated endothelial dysfunction. Different biomarkers of endothelial dysfunction were analysed in blood or plasma. All patients underwent MRI 72 h after stroke symptom onset. RESULTS: A total of 86 patients were included (52 males; mean age 63.5 ± 11.5 years). Patients with abnormal RHI have hypertension or antihypertensive treatment more often. The baseline IQ-CODE was abnormal in 33 (38.4%) patients, indicating a pre-existing cognitive problem. Baseline IQ-CODE > 48 was observed in 15 patients (28.3%) with normal RHI and in 18 patients (54.6%) with abnormal RHI (p = 0.016). The RHI median was significantly lower in patients with abnormal IQ-CODE. Abnormal RHI was associated with a significantly higher median FAZEKAS score (2.5 vs. 2; p = 0.008), a significantly higher frequency of periventricular lesions (p = 0.015), more white matter lesions (p = 0.007) and a significantly higher cerebral atrophy score (p < 0.001) on MRI. Vascular biomarkers significantly associated with abnormal RHI were MCP-1 (p = 0.009), MIP_1a (p = 0.042), and homocysteinemia (p < 0.05). CONCLUSIONS: A vascular mechanism may be responsible for cognitive problems pre-existing stroke. The measurement of endothelial dysfunction after stroke could become an important element of follow-up, providing an indication of the functional and cognitive prognosis of stroke patients.