Prestroke Cognitive Impairment: Frequency and Association With Premorbid Neuropsychiatric, Functional, and Neuroimaging Features.

BACKGROUND: Some patients with stroke have prestroke cognitive impairment (pre-SCI), but its etiology is not clear. The aim of this cross-sectional study was to assess the frequency of pre-SCI and its association with premorbid neuropsychiatric, functional, and neuroimaging features. METHODS: Patients hospitalized in stroke unit with an informant who could complete IQCODE (Informant Questionnaire for Cognitive Decline in the Elderly) were included. Pre-SCI was diagnosed if the IQCODE score was >3.3. Prestroke assessment also included NPI-Q (Neuropsychiatric Inventory Questionnaire), the basic Activities of Daily Living and Instrumental Activities of Daily Living scales, and the Clinical Dementia Rating scale. A multivariate logistic regression model was used to evaluate the association of pre-SCI with age, sex, education, arterial hypertension, atrial fibrillation, white matter lesions, cerebral microbleeds, and pathological medial temporal lobe atrophy. RESULTS: IQCODE was available in 474 of 520 patients (91.2%; 45% women; mean age 75.5±13.3 years). Pre-SCI had a prevalence of 32.5% and was associated with prestroke NPI-Q (pre-SCI absent versus present, 1.7±2.3 versus 5.5±4.9; P<0.001), Activities of Daily Living scale (0.3±0.8 versus 1.8±1.9; P<0.001), Instrumental Activities of Daily Living scale (0.6±1.3 versus 3.8±4.0; P<0.001), and Clinical Dementia Rating scale score (0.7±1.7 versus 7.2±6.2; P<0.001). In the 271 patients with a magnetic resonance imaging available, the multivariate logistic regression showed that age (odds ratio [OR], 1.05 [95% CI, 1.62-9.73]), white matter lesions (OR, 1.26 [95% CI, 1.003-1.58]), and a pathological medial temporal lobe atrophy score (OR, 3.97 [95% CI, 1.62-9.73]) were independently associated with pre-SCI. In the 218 patients with ischemic stroke, white matter lesions (OR, 1.34 [95% CI, 1.04-1.72]) and medial temporal lobe atrophy (OR, 3.56 [95% CI, 1.38-9.19]), but not age, were associated with pre-SCI. CONCLUSIONS: One-third of patients admitted to a stroke unit have pre-SCI that is associated with preexisting neuropsychiatric symptoms and functional performance. White matter lesions and medial temporal lobe atrophy are associated with pre-SCI, suggesting that both small vessel disease and neurodegeneration might be involved in its etiology.

Therapeutic strategies in vascular cognitive impairment: A systematic review of population, intervention, comparators, and outcomes.

INTRODUCTION: Vascular cognitive impairment (VCI) is a common and heterogeneous condition, clinically and pathophysiologically, that still lacks approved treatment. METHODS: We reviewed evidence from randomized and non-randomized clinical trials in VCI to explore whether any therapeutic option warrants further investigation and to assess possible flaws in previous studies. RESULTS: We identified 118 studies after searching PubMed and Embase, including 19,223 participants and 5 different VCI subtypes. We found 63 different types of intervention (51 pharmacologic, 5 employing physical agent application, 7 rehabilitation approaches) compared with either placebo, best medical treatment, or other interventions. Treatment efficacy was assessed through 125 outcome measures (with a clearly pre-specified primary outcome in 50.8% of studies). DISCUSSION: Therapeutic trials in VCI have been heterogeneous in terms of populations, types of interventions, and outcomes. Overall, a lack of clear pathophysiological rationale for tested interventions seems to emerge, together with the need to homogenize trial study design.

What do we mean by long COVID? A scoping review of the cognitive sequelae of SARS-CoV-2 infection.

BACKGROUND AND PURPOSE: Many COVID-19 patients report persistent symptoms, including cognitive disturbances. We performed a scoping review on this topic, focusing primarily on cognitive manifestations. METHODS: Abstracts and full texts of studies published on PubMed (until May 2023) addressing cognitive involvement persisting after SARS-CoV-2 infection were reviewed, focusing on terms used to name the cognitive syndrome, reported symptoms, their onset time and duration, and testing batteries employed. Reported psychiatric symptoms, their assessment tools, and more general manifestations were also extracted. RESULTS: Among the 947 records identified, 180 studies were included. Only one third of them used a label to define the syndrome. A minority of studies included patients according to stringent temporal criteria of syndrome onset (34%), whereas more studies reported a minimum required symptom duration (77%). The most frequently reported cognitive symptoms were memory and attentional-executive disturbances, and among psychiatric complaints, the most frequent were anxiety symptoms, depression, and sleep disturbances. Most studies reported fatigue among general symptoms. Thirty-six studies employed cognitive measures: screening tests alone (n = 19), full neuropsychological batteries (n = 25), or both (n = 29); 30 studies performed psychiatric testing. Cognitive deficits were demonstrated in 39% of subjects, the most frequently affected domains being attention/executive functions (90%) and memory (67%). CONCLUSIONS: Currently, no agreement exists on a label for post-COVID-19 cognitive syndrome. The time of symptom onset after acute infection and symptom duration are still discussed. Memory and attention-executive complaints and deficits, together with fatigue, anxiety, and depression symptoms, are consistently reported, but the objective evaluation of these symptoms is not standardized.

CSF p-tau/Aß42 ratio and brain FDG-PET may reliably detect MCI "imminent" converters to AD.

PURPOSE: To know whether mild cognitive impairment (MCI) patients will develop Alzheimer's disease (AD) dementia in very short time or remain stable is of crucial importance, also considering new experimental drugs usually tested within very short time frames. Here we combined cerebrospinal fluid (CSF) AD biomarkers and a neurodegeneration marker such as brain FDG-PET to define an objective algorithm, suitable not only to reliably detect MCI converters to AD dementia but also to predict timing of conversion. METHODS: We included 77 consecutive MCI patients with neurological/neuropsychological assessment, brain 18F-FDG-PET and CSF analysis available at diagnosis and a neuropsychological/neurological evaluation every 6 months for a medium- to a long-term follow-up (at least 2 and up to 8 years). Binomial logistic regression models and Kaplan-Meier survival analyses were performed to determine the best biomarker (or combination of biomarkers) in detecting MCI converters to AD dementia and then, among the converters, those who converted in short time frames. RESULTS: Thirty-five out of 77 MCI patients (45%) converted to AD dementia, with an average conversion time since MCI diagnosis of 26.07 months. CSF p-tau/Aß42 was the most accurate predictor of conversion from MCI to AD dementia (82.9% sensitivity; 90% specificity). CSF p-tau/Aß42 and FDG-PET-positive MCIs converted to AD dementia significantly earlier than the CSF-positive-only MCIs (median conversion time, 17.1 vs 31.3 months). CONCLUSIONS: CSF p-tau/Aß42 ratio and brain FDG-PET may predict both occurrence and timing of MCI conversion to full-blown AD dementia. MCI patients with both biomarkers suggestive for AD will likely develop an AD dementia shortly, thus representing the ideal target for any new experimental drug requiring short periods to be tested for.

The CSF p-tau181/Aß42 Ratio Offers a Good Accuracy "In Vivo" in the Differential Diagnosis of Alzheimer's Dementia.

BACKGROUND: The incoming disease-modifying therapies against Alzheimer's disease (AD) require reliable diagnostic markers to correctly enroll patients all over the world. CSF AD biomarkers, namely amyloid-ß 42 (Aß42), total tau (t-tau), and tau phosphorylated at threonine 181 (p-tau181), showed good diagnostic accuracy in detecting AD pathology, but their real usefulness in daily clinical practice is still a matter of debate. Therefore, further validation in complex clinical settings, that is patients with different types of dementia, is needed to uphold their future worldwide adoption. METHODS: We measured CSF AD biomarkers' concentrations in a sample of 526 patients with a clinical diagnosis of dementia (277 with AD and 249 with Other Type of Dementia, OTD). Brain FDG-PET was also considered in a subsample of 54 patients with a mismatch between the clinical diagnosis and the CSF findings. RESULTS: A p-tau181/Aß42 ratio higher than 0.13 showed the best diagnostic performance in differentiating AD from OTD (86% accuracy index, 74% sensitivity, 81% specificity). In cases with a mismatch between clinical diagnosis and CSF findings, brain FDG-PET partially agreed with the p-tau181/Aß42 ratio, thus determining an increase in CSF accuracy. CONCLUSION: The p-tau181/Aß42 ratio alone might reliably detect AD pathology in heterogeneous samples of patients suffering from different types of dementia. It might constitute a simple, cost-effective and reproducible in vivo proxy of AD suitable to be adopted worldwide not only in daily clinical practice but also in future experimental trials, to avoid the enrolment of misdiagnosed AD patients.