Discrepancy Between Patient and Caregiver Estimate of Apathy Predicts Dementia in Patients with Amnestic Mild Cognitive Impairment.

BACKGROUND: Apathy is a frequent behavioral symptom of Alzheimer's disease (AD). The Apathy Evaluation Scale (AES) is a tool exploring the perception of apathy by both caregivers (CG-AES) and patients (PT-AES), and the discrepancy in their ratings is a proxy of patients' disease unawareness. OBJECTIVE: To assess in a cohort study of patients with amnesic mild cognitive impairment (aMCI) whether apathy and awareness of apathy predict progression to dementia and timing. METHODS: From the global AES scores of 110 patients with aMCI and their caregivers, we obtained two principal indices for analysis: 1) 'Apathy', the mean of PT-AES and CG-AES, and 2) 'Discrepancy', obtained by subtracting CG-AES from PT-AES. Patients were followed with visits every six months for three years or until dementia. AES indices and the principal demographical/neuropsychological variables were filtered from multicollinearity. The most robust variables entered a logistic regression model and survival analyses (Cox regression, log-rank test of Kaplan-Meier curves) to estimate which predicted the risk and timing of progression, respectively. RESULTS: Sixty patients (54.5%) developed dementia (57 AD) after 6.0-36.0 months, 22 (20%) remained in an MCI stage, and 28 (25.5%) dropped out. 'Discrepancy' was a robust and accurate predictor of the risk of progression (AUC = 0.73) and, after binarization according to a computed cutoff, of timing to dementia. CONCLUSION: A structured evaluation of apathy, both self-assessed and estimated by caregivers, can provide useful information on the risk and timing of progression from aMCI to dementia. The discrepancy between the two estimates is a fairly reliable index for prediction purposes as a proxy of disease unawareness.

Neurological long-COVID in the outpatient clinic: Two subtypes, two courses.

INTRODUCTION: Symptoms referable to central and peripheral nervous system involvement are often evident both during the acute phase of COVID-19 infection and during long-COVID. In this study, we evaluated a population of patients with prior COVID-19 infection who showed signs and symptoms consistent with neurological long-COVID. METHODS: We prospectively collected demographic and acute phase course data from patients with prior COVID-19 infection who showed symptoms related to neurological involvement in the long-COVID phase. Firstly, we performed a multivariate logistic linear regression analysis to investigate the impact of demographic and clinical data, the severity of the acute COVID-19 infection and hospitalization course, on the post-COVID neurological symptoms at three months follow-up. Secondly, we performed an unsupervised clustering analysis to investigate whether there was evidence of different subtypes of neurological long COVID-19. RESULTS: One hundred and nine patients referred to the neurological post-COVID outpatient clinic. Clustering analysis on the most common neurological symptoms returned two well-separated and well-balanced clusters: long-COVID type 1 contains the subjects with memory disturbances, psychological impairment, headache, anosmia and ageusia, while long-COVID type 2 contains all the subjects with reported symptoms related to PNS involvement. The analysis of potential risk-factors among the demographic, clinical presentation, COVID 19 severity and hospitalization course variables showed that the number of comorbidities at onset, the BMI, the number of COVID-19 symptoms, the number of non-neurological complications and a more severe course of the acute infection were all, on average, higher for the cluster of subjects with reported symptoms related to PNS involvement. CONCLUSION: We analyzed the characteristics of neurological long-COVID and presented a method to identify well-defined patient groups with distinct symptoms and risk factors. The proposed method could potentially enable treatment deployment by identifying the optimal interventions and services for well-defined patient groups, so alleviating long-COVID and easing recovery.

A case series of parainfectious Guillain-Barré syndrome linked to influenza A (H1N1) virus infection.

Guillain-Barré syndrome (GBS) is an immune-mediated peripheral neuropathy characterized by a typical post-infectious profile. Some post-Zika virus and post-severe acute respiratory syndrome-related coronavirus-2 GBS cases have been reported to occur with very short intervals between the infection and GBS onset. Evaluating 161 GBS patients consecutively admitted to two Italian Regional Hospitals between 2003 and 2019, we found that the only three with an antecedent influenza A (H1N1) virus infection developed GBS within an interval of less than 10 days from the influenza illness. The two of them with a demyelinating subtype promptly recovered without therapy. Overall, the parainfectious cases add heterogeneity to the GBS category, warranting pathogenetic insights.