Apathy After Stroke: Incidence, Symptom Trajectory, and Impact on Quality of Life and Disability

BACKGROUND AND OBJECTIVES: Apathy is one of the most common symptoms following stroke and is often associated with worse functional outcome and poor quality of life (QoL). The trajectory of apathy symptoms has been previously described, and different trajectories have been identified. We determined group and individual changes in apathy symptomatology from the acute phase until 1 year after stroke. We also examined the association of apathy and depression with disability and QoL 1 year after stroke. METHODS: We measured apathy in a cohort of ischemic stroke survivors at 4 time points from 0 to 12 months after stroke. The Apathy Evaluation Scale (AES) and Dimensional Apathy Scale (DAS) were administered at each time point. Where possible we obtained apathy measured from carers. Depression was assessed with the Geriatric Depression Scale (GDS). Disability and QoL were assessed with the modified Rankin Scale (mRS) and 36-Item Short Form Survey (SF-36). We examined the cross-sectional and individual trajectory of apathy symptoms in each dimension and looked at associations of apathy and depression soon after stroke with mRS and SF-36 at 1 year. RESULTS: Of 200 participants enrolled, 165 completed apathy measures at 12 months. Patient-rated apathy scores increased in both tests at the group level (AES: χ2(3) = 9.86, p = 0.019; DAS: χ2(3) = 8.49, p = 0.037) and individual level (AES: ß = 0.13, p = 0.002; DAS ß = 0.13, p = 0.005; DAS: executive ß = 0.08, p < 0.001). By contrast, carer-rated apathy did not significantly increase (AES: χ2(3) = 0.75, p = 0.862; DAS: χ2(3) = 2.45, p = 0.484). Apathy scores were associated with worse mRS and SF-36, although most associations were no longer significant when controlling for depression. GDS was associated with worse mRS and SF-36 after controlling for covariates and apathy (mRS: ß = 0.08, p = 0.006; SF-36 Mental Component Summary: ß = -1.53, p < 0.001; SF-36 Physical Component Summary: ß = -0.57, p = 0.016). DISCUSSION: Self-reported apathy progressively increases after stroke, especially in the executive dimension. Apathy is associated with worse QoL and greater disability, although some of these associations might be mediated by depression.

Prevalence of, and risk factors for, cognitive impairment in lacunar stroke.

BACKGROUND: Small vessel disease (SVD) is associated with vascular cognitive impairment (VCI) but why VCI occurs in some, but not other patients, is uncertain. We determined the prevalence of, and risk factors for, VCI in a large cohort of patients with lacunar stroke. METHODS: Participants with magnetic resonance imaging (MRI)-confirmed lacunar stroke were recruited in the multicenter DNA Lacunar 2 study and compared with healthy controls. A logistic regression model was used to determine which vascular risk factors and MRI parameters were independent predictors of VCI, assessed using the Brief Memory and Executive Test (BMET). RESULTS: A total of 912 lacunar stroke patients and 425 controls were included, with mean (SD) age of 64.6 (12.26) and 64.7 (12.29) years, respectively. VCI was detected in 38.8% lacunar patients and 13.4% controls. In a logistic regression model, diabetes mellitus (odds ratio (OR) = 1.98 (95% confidence interval (CI) = 1.40-2.80), p < 0.001) and higher body mass index (BMI) (OR = 1.03 (95% CI = 1.00-1.05), p = 0.029) were independently associated with increased risk of VCI, and years of full-time education with lower risk (OR = 0.92 (95% CI = 0.86-0.99), p = 0.018). When entering both lacune count and white matter hyperintensity (WMH) in the same logistic regression model, only WMH grade was significantly associated with VCI (OR = 1.46 (95% CI = 1.24-1.72), p < 0.001). CONCLUSION: VCI is common in lacunar stroke patients, affecting almost 40%. This prevalence suggests that it should be routinely screened for in clinical practice. Risk factors for VCI in patients with lacunar stroke include diabetes mellitus, depressive symptoms, higher BMI, and WMH severity, while education is protective.

White-Matter Hyperintensity Load and Differences in Resting-State Network Connectivity Based on Mild Cognitive Impairment Subtype.

"Mild cognitive impairment" (MCI) is a diagnosis characterised by deficits in episodic memory (aMCI) or in other non-memory domains (naMCI). Although the definition of subtypes is helpful in clinical classification, it provides little insight on the variability of neurofunctional mechanisms (i.e., resting-state brain networks) at the basis of symptoms. In particular, it is unknown whether the presence of a high load of white-matter hyperintensities (WMHs) has a comparable effect on these functional networks in aMCI and naMCI patients. This question was addressed in a cohort of 123 MCI patients who had completed an MRI protocol inclusive of T1-weighted, fluid-attenuated inversion recovery (FLAIR) and resting-state fMRI sequences. T1-weighted and FLAIR images were processed with the Lesion Segmentation Toolbox to quantify whole-brain WMH volumes. The CONN toolbox was used to preprocess all fMRI images and to run an independent component analysis for the identification of four large-scale haemodynamic networks of cognitive relevance (i.e., default-mode, salience, left frontoparietal, and right frontoparietal networks) and one control network (i.e., visual network). Patients were classified based on MCI subtype (i.e., aMCI vs. naMCI) and WMH burden (i.e., low vs. high). Maps of large-scale networks were then modelled as a function of the MCI subtype-by-WMH burden interaction. Beyond the main effects of MCI subtype and WMH burden, a significant interaction was found in the salience and left frontoparietal networks. Having a low WMH burden was significantly more associated with stronger salience-network connectivity in aMCI (than in naMCI) in the right insula, and with stronger left frontoparietal-network connectivity in the right frontoinsular cortex. Vice versa, having a low WMH burden was significantly more associated with left-frontoparietal network connectivity in naMCI (than in aMCI) in the left mediotemporal lobe. The association between WMH burden and strength of connectivity of resting-state functional networks differs between aMCI and naMCI patients. Although exploratory in nature, these findings indicate that clinical profiles reflect mechanistic interactions that may play a central role in the definition of diagnostic and prognostic statuses.

Anti-Cholinergic Derangement of Cortical Metabolism on 18F-FDG PET in a Patient with Frontotemporal Lobar Degeneration Dementia: A Case of the TREDEM Registry.

We present the case of a patient with an atypical course of frontotemporal lobar degeneration (FTLD) complicated by the use of an anticholinergic drug. A 70-year-old patient, followed by psychiatrists for depression and behavioral disorders, received a diagnosis of dementia with Lewy bodies (DLB) at another Center due to auditory hallucinations, gait impairment, and tendency to fall. He was then admitted to our Memory Clinic Unit for behavioral disturbances, such as delusional thinking, auditory hallucinations, and memory complaints. At that time, the patient's therapy included Lorazepam, Quetiapine, Promazine, and Biperiden. The latter was immediately suspended for the absence of extrapyramidal signs and to avoid the anticholinergic cognitive side effects. A 18F-FDG PET showed a derangement of cortical metabolism with diffusely reduced activity, and limited areas of hyperactivity involving lateral frontal and lateral temporal inferior regions bilaterally. The patient underwent a series of exams, including neuropsychological tests, 123I-MIBG scintigraphy, cerebrospinal fluid examination, and genetic analysis. A second 18F-FDG PET showed an extensive remodulation of metabolic activity: relative higher concentration of the tracer in the prefrontal and inferior temporal cortex was no more detectable. Similarly, the diffuse reduced metabolic activity could not be traced anymore. Nonetheless, the metabolic activity still appeared reduced in the frontal lobe, in the anterior cingulate bilaterally, and in the anterior part of the hemispheric fissure. Taken together, clinical and neuroimaging features would point to a FTLD-like form. Furthermore, the diagnostic work-up was likely confounded by the anticholinergic drug on 18F-FDG PET, highlighting the importance of carefully checking the patient's pharmacology during the diagnostic process.

Artificial Neural Networks Help to Better Understand the Interplay Between Cognition, Mediterranean Diet, and Physical Performance: Clues from TRELONG Study.

BACKGROUND: Nutrition plays an important role in the aging process. Adherence to the Mediterranean diet (MedDiet) has been shown to be associated with lower rates of diseases. Cognitive status seems to be strongly interrelated with physical well-being, so that one influences the other. Physical performance measures are not only associated with clinical and subclinical age-related modifications, but are also able to predict disability, institutionalization, and mortality. OBJECTIVE: To evaluate prospectively the associations between Mediterranean-Style Dietary Pattern Score (MSDPS), clinical characteristics, and cognition of the population sample of The TREVISO LONGEVA (TRELONG) Study, in Treviso, Italy. METHODS: Global cognition, physical performance measures, MSDPS, and other clinical features were detected in 2010 in 82 men and 108 women. These characteristics were evaluated in relation to the physical performance measures identified 3.8 years later in 2013 in the same subjects, using a semantic connectivity map, through Auto-CM system, to grasp further and non-linear associations between variables which might remain, otherwise, undetected. RESULTS: The Auto-CM system's map showed a close association between better levels of global cognition and MSDPS in 2010 and higher physical performance in 2013. On the other hand, worse levels of global cognition and MSDPS in 2010 were associated with lower physical performance in 2013. CONCLUSION: The prevention models for successful aging may benefit from integrated programs that include cognitive, physical, and dietary interventions, since these aspects are mutually interrelated.