Coronary microvascular dysfunction is associated with impaired cognitive function: the Cerebral-Coronary Connection study (C3 study).

BACKGROUND: It remains unknown whether the presence of coronary microcirculatory dysfunction (CMD) correlates with its equivalent condition in the brain, cerebral small vessel disease (CSVD). The cerebral-coronary connection (C3), a prospective blinded study, investigated the prevalence of CMD in patients with coronary artery disease (CAD) and its association with CSVD and cognitive function. METHODS AND RESULTS: Patients with documented CAD fulfilling inclusion criteria underwent physiological assessment of epicardial vessels and the microcirculation using intracoronary pressure and Doppler. Coronary microcirculation-related indices included coronary flow reserve (CFR) and hyperaemic microvascular resistance. Brain magnetic resonance imaging, transcranial Doppler (TCD), and neurocognitive examination were performed. Overall, 67 patients were included in the study (mean age 66 years, 73% female). Patients with abnormal CFR (<2.0) (55.2%) showed higher burden of white-matter hyperintensities: 43.2 vs. 20.0% (P = 0.044). After statistical adjustment, low CFR was associated with lower grey matter volume (P = 0.024) and with parameters of white-matter microstructural damage in diffusion-tensor imaging (lower fractional anisotropy and higher mean diffusivity, P = 0.029 and P = 0.032, respectively). Low CFR was associated with higher resistive (P = 0.027) and pulsatility (P = 0.043) values on TCD, and worse neurocognitive test scores (lower mini mental state examination, P = 0.025, and slower Trail Making Test A, P = 0.034). CONCLUSIONS: Coronary microcirculatory dysfunction is frequent in patients with CAD and correlates with CSVD, abnormal cerebral flow haemodynamics, and significant cognitive impairment. These findings support the hypothesis that microvascular dysfunction in the heart and the brain are part of a single pathological process affecting microcirculation in patients with CAD. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT04131075.

Abnormal functional connectivity in radiologically isolated syndrome: A resting-state fMRI study.

BACKGROUND: Radiologically isolated syndrome (RIS) patients might have psychiatric and cognitive deficits, which suggests an involvement of major resting-state functional networks. Notwithstanding, very little is known about the neural networks involved in RIS. OBJECTIVE: To examine functional connectivity differences between RIS and healthy controls using resting-state functional magnetic resonance imaging (fMRI). METHODS: Resting-state fMRI data in 25 RIS patients and 28 healthy controls were analyzed using an independent component analysis; in addition, seed-based correlation analysis was used to obtain more information about specific differences in the functional connectivity of resting-state networks. Participants also underwent neuropsychological testing. RESULTS: RIS patients did not differ from the healthy controls regarding age, sex, and years of education. However, in memory (verbal and visuospatial) and executive functions, RIS patients' cognitive performance was significantly worse than the healthy controls. In addition, fluid intelligence was also affected. Twelve out of 25 (48%) RIS patients failed at least one cognitive test, and six (24.0%) had cognitive impairment. Compared to healthy controls, RIS patients showed higher functional connectivity between the default mode network and the right middle and superior frontal gyri and between the central executive network and the right thalamus (pFDR < 0.05; corrected). In addition, the seed-based correlation analysis revealed that RIS patients presented higher functional connectivity between the posterior cingulate cortex, an important hub in neural networks, and the right precuneus. CONCLUSION: RIS patients had abnormal brain connectivity in major resting-state neural networks and worse performance in neurocognitive tests. This entity should be considered not an "incidental finding" but an exclusively non-motor (neurocognitive) variant of multiple sclerosis.

Design and Verbal Fluency in Alzheimer's Disease and Frontotemporal Dementia: Clinical and Metabolic Correlates.

OBJECTIVE: Cognitive processes underlying verbal and design fluency, and their neural correlates in patients with Alzheimer's disease (AD) and behavioural variant Frontotemporal Dementia (bvFTD) remain unclear. We hypothesised that verbal and design fluency may be associated with distinct neuropsychological processes in AD and FTD, showing different patterns of impairment and neural basis. METHODS: We enrolled 142 participants including patients with AD (n = 80, mean age = 74.71), bvFTD (n = 34, mean age = 68.18), and healthy controls (HCs) (n = 28, mean age = 71.14), that underwent cognitive assessment and 18F-fluorodeoxyglucose positron emission tomography imaging. RESULTS: Semantic and phonemic fluency showed the largest effect sizes between groups, showing lower scores in bvFTD than AD and HCs, and lower scores in AD than HC. Both AD and bvFTD showed a lower number of unique designs in design fluency in comparison to HC. Semantic fluency was correlated with left frontotemporal lobe in AD, and with left frontal, caudate, and thalamus in bvFTD. Percentage of unique designs in design fluency was associated with the metabolism of the bilateral fronto-temporo-parietal cortex in AD, and the bilateral frontal cortex with right predominance in bvFTD. Repetitions in AD were correlated with bilateral frontal, temporal, and parietal lobes, and with left prefrontal cortex in bvFTD. CONCLUSIONS: Our findings demonstrate differential underlying cognitive processes in verbal and design fluency in AD and bvFTD. While memory and executive functioning associated with fronto-temporo-parietal regions were key in AD, attention and executive functions correlated with the frontal cortex and played a more significant role in bvFTD during fluency tasks.

Diagnosis of Alzheimer's disease and behavioural variant frontotemporal dementia with machine learning-aided neuropsychological assessment using feature engineering and genetic algorithms.

BACKGROUND: Neuropsychological assessment is considered a valid tool in the diagnosis of neurodegenerative disorders. However, there is an important overlap in cognitive profiles between Alzheimer's disease (AD) and behavioural variant frontotemporal dementia (bvFTD), and the usefulness in diagnosis is uncertain. We aimed to develop machine learning-based models for the diagnosis using cognitive tests. METHODS: Three hundred and twenty-nine participants (170 AD, 72 bvFTD, 87 healthy control [HC]) were enrolled. Evolutionary algorithms, inspired by the process of natural selection, were applied for both mono-objective and multi-objective classification and feature selection. Classical algorithms (NativeBayes, Support Vector Machines, among others) were also used, and a meta-model strategy. RESULTS: Accuracies for the diagnosis of AD, bvFTD and the differential diagnosis between them were higher than 84%. Algorithms were able to significantly reduce the number of tests and scores needed. Free and Cued Selective Reminding Test, verbal fluency and Addenbrooke's Cognitive Examination were amongst the most meaningful tests. CONCLUSIONS: Our study found high levels of accuracy for diagnosis using exclusively neuropsychological tests, which supports the usefulness of cognitive assessment in diagnosis. Machine learning may have a role in improving the interpretation and test selection.

Conversion between the Rowland Universal Dementia Assessment Scale and Mini-Mental State Examination test scores in majority and minority populations.

INTRODUCTION: Despite the Rowland Universal Dementia Assessment Scale (RUDAS) having significant advantages as a cognitive screening tool, particularly for minority populations, the Mini-Mental State Examination (MMSE) test is the most widely used test for cognitive screening in Alzheimer's disease (AD). This study aimed to develop a conversion table to predict MMSE scores from observed RUDAS scores, allowing an easy-to-use method to compare both screening tests. METHODS: The equipercentile equating method was used to develop the conversion table using a training sample consisting of cognitively intact participants and individuals with early-stage AD. The resulting conversion table was validated in two samples, comprising participants from majority and minority populations assessed in Spanish. RESULTS: The conversion table demonstrated excellent reliability with intraclass correlation coefficients of.92 in both validation samples. CONCLUSION: This study provides a conversion table between RUDAS and MMSE scores, improving the comparability of these cognitive screening tools for use in clinical and research purposes.

A data-driven approach to complement the A/T/(N) classification system using CSF biomarkers.

AIMS: The AT(N) classification system not only improved the biological characterization of Alzheimer's disease (AD) but also raised challenges for its clinical application. Unbiased, data-driven techniques such as clustering may help optimize it, rendering informative categories on biomarkers' values. METHODS: We compared the diagnostic and prognostic abilities of CSF biomarkers clustering results against their AT(N) classification. We studied clinical (patients from our center) and research (Alzheimer's Disease Neuroimaging Initiative) cohorts. The studied CSF biomarkers included Aß(1-42), Aß(1-42)/Aß(1-40) ratio, tTau, and pTau. RESULTS: The optimal solution yielded three clusters in both cohorts, significantly different in diagnosis, AT(N) classification, values distribution, and survival. We defined these three CSF groups as (i) non-defined or unrelated to AD, (ii) early stages and/or more delayed risk of conversion to dementia, and (iii) more severe cognitive impairment subjects with faster progression to dementia. CONCLUSION: We propose this data-driven three-group classification as a meaningful and straightforward approach to evaluating the risk of conversion to dementia, complementary to the AT(N) system classification.

Comparison of the Diagnostic Accuracy of Five Cognitive Screening Tests for Diagnosing Mild Cognitive Impairment in Patients Consulting for Memory Loss.

Objectives: We aimed to evaluate and compare the diagnostic capacity of five cognitive screening tests for the diagnosis of mild cognitive impairment (MCI) in patients consulting by memory loss. Methods: A cross-sectional study involving 140 participants with a mean age of 74.42 ± 7.60 years, 87 (62.14%) women. Patients were classified as MCI or cognitively unimpaired according to a comprehensive neuropsychological battery. The diagnostic properties of the following screening tests were compared: Mini-Mental State Examination (MMSE), Addenbrooke's Cognitive Examination III (ACE-III) and Mini-Addenbrooke (M-ACE), Memory Impairment Screen (MIS), Montreal Cognitive Assessment (MoCA), and Rowland Universal Dementia Assessment Scale (RUDAS). Results: The area under the curve (AUC) was 0.861 for the ACE-III, 0.867 for M-ACE, 0.791 for MoCA, 0.795 for MMSE, 0.731 for RUDAS, and 0.672 for MIS. For the memory components, the AUC was 0.869 for ACE-III, 0.717 for MMSE, 0.755 for MoCA, and 0.720 for RUDAS. Cronbach's alpha was 0.827 for ACE-III, 0.505 for MMSE, 0.896 for MoCA, and 0.721 for RUDAS. Correlations with Free and Cued Selective Reminding Test were moderate with M-ACE, ACE-III, and MoCA, and moderate for the other tests. The M-ACE showed the best balance between diagnostic capacity and time of administration. Conclusions: ACE-III and its brief version M-ACE showed better diagnostic properties for the diagnosis of MCI than the other screening tests. MoCA and MMSE showed adequate properties, while the diagnostic capacity of MIS and RUDAS was limited.

European cross-cultural neuropsychological test battery (CNTB) for the assessment of cognitive impairment in multiple sclerosis: Cognitive phenotyping and classification supported by machine learning techniques.

BACKGROUND: The European Cross-Cultural Neuropsychological Test Battery (CNTB) has been proposed as a comprehensive battery for cognitive assessment, reducing the potential impact of cultural variables. In this validation study, we aimed to evaluate the diagnostic capacity of CNTB for the assessment of participants with multiple sclerosis (pwMS) compared to the Neuronorma battery (NN) according to the International Classification of Cognitive Disorders in MS criteria, and to develop machine learning (ML) algorithms to improve the diagnostic capacity of CNTB and to select the most relevant tests. METHODS: Sixty pwMS and 60 healthy controls (HC) with no differences in sex, age, or years of education were enrolled. All participants completed the CNTB and pwMS were also examined with NN, depression, and fatigue scales. Impaired domains and cognitive phenotypes were defined following ICCoDiMS based on CNTB scores and compared to NN, according to -1SD and -1.5SD cutoff scores. To select the most relevant tests, random forest (RF) was performed for different binary classifications. RESULTS: PwMS showed a lower performance compared to HC with medium-large effect sizes, in episodic memory, executive function, attention, and processing speed, in accordance with their characteristic cognitive profile. There were no differences in impaired domains or cognitive phenotypes between CNTB and NN, highlighting the role of episodic memory, executive function, attention, and processing speed tests. The most relevant tests identified by RF were consistent with inter-group comparisons and allowed a better classification than SD cutoff scores. CONCLUSION: CNTB is a valid test for cognitive diagnosis in pwMS, including key tests for the most frequently impaired cognitive domains in MS. The use of ML techniques may also be useful to improve diagnosis, especially in some tests with lower sensitivity.

Cognitive dysfunction characteristics of multiple sclerosis with aging.

BACKGROUND: We aimed to investigate the characteristics of cognitive impairment in older people with multiple sclerosis (MS). METHODS: Cross-sectional study that included participants that were examined with a common and comprehensive neuropsychological protocol. The subjects were matched by sociodemographic variables and the following groups were generated for comparisons: young MS versus healthy controls (HC) (n = 246), old MS versus HC (n = 198), young MS vs old MS (n = 226), MS vs Alzheimer's disease (AD)(n = 70), and MS vs Parkinson's disease (PD) (n = 62). The ICCoDiMS criteria were used to define cognitive impairment in MS. RESULTS: Cognitive impairment was more frequent in young than old patients (70.8 % vs 52.2 %). Attention and speed processing is the most frequent cognitive domain impaired in MS (54.9 % of young MS vs 32.7 % of old MS). The frequency of impairment in attention/processing speed (54.9 % vs 32.7 %) and episodic memory (27.9 % vs 14.3) was higher in the young group than in the old group. There were no statistically significant differences in the distribution of impairment in executive function (46.0 % vs 35.3 %), visuospatial (17.9 % vs 9.5 %), and language (12.4 % vs 17.7 %). In those patients meeting the criteria for cognitive impairment, young MS patients showed lower performance in attention/processing speed tests. Conversely, old MS patients showed lower performance in episodic memory, verbal fluency, and planning. There were no differences in the correlations between SDMT and other neuropsychological tests in young and old patients, which suggests similar cognitive processes underlying SDMT performance in both groups. There were differences between old MS and prodromal AD, especially in episodic memory, while the cognitive profile of old MS was largely shared with PD. CONCLUSIONS: Our study found that the cognitive profile of MS is defined by a characteristic impairment in attention and processing speed, which is present during the lifespan. The impairment in processing speed is less prominent in old age, whereas the impairment of other cognitive functions becomes more relevant. These findings suggest potential differences in the pathophysiological processes associated with cognitive impairment between young and old ages that warrant further investigation.

Cognitive profile in multiple sclerosis and post-COVID condition: a comparative study using a unified taxonomy.

Post-COVID condition (PCC) and multiple sclerosis (MS) share some clinical and demographic features, including cognitive symptoms and fatigue. Some pathophysiological mechanisms well-known in MS, such as autoimmunity, neuroinflammation and myelin damage, have also been implicated in PCC. In this study, we aimed to compare the cognitive phenotypes of two large cohorts of patients with PCC and MS, and to evaluate the relationship between fatigue and cognitive performance. Cross-sectional study including 218 patients with PCC and 218 with MS matched by age, sex, and years of education. Patients were evaluated with a comprehensive neuropsychological protocol and were categorized according to the International Classification of Cognitive Disorders system. Fatigue and depression were also assessed. Cognitive profiles of PCC and MS largely overlapped, with a greater impairment in episodic memory in MS, but with small effect sizes. The most salient deficits in both disorders were in attention and processing speed. The severity of fatigue was greater in patients with PCC. Still, the correlations between fatigue severity and neuropsychological tests were more prominent in the case of MS. There were no differences in the severity of depression among groups. Our study found similar cognitive profiles in PCC and MS. Fatigue was more severe in PCC, but was more associated with cognitive performance in MS. Further comparative studies addressing the mechanisms related to cognitive dysfunction and fatigue may be of interest to advance the knowledge of these disorders and develop new therapies.

Neural basis of fatigue in post-COVID syndrome and relationships with cognitive complaints and cognition.

The main objective was to evaluate structural and functional connectivity correlates of fatigue in post-COVID syndrome, and to investigate the relationships with an objective measure of mental fatigue and with subjective cognitive complaints. One-hundred and twenty-nine patients were recruited after 14.79 ± 7.17 months. Patients were evaluated with fatigue, neuropsychological, and subjective cognitive complaints assessments. Structural and functional magnetic resonance imaging were acquired, and functional connectivity, white matter diffusivity and grey matter volume were evaluated. Fatigue was present in 86 % of patients, and was highly correlated to subjective cognitive complaints. Fatigue was associated with structural and functional connectivity mostly in frontal areas but also temporal, and cerebellar areas, showing mental fatigue different pattern of functional connectivity correlates compared to physical fatigue. White matter diffusivity correlates were similar in fatigue and subjective cognitive complaints, located in the forceps minor, anterior corona radiata and anterior cingulum. Findings confirm that fatigue in post-COVID syndrome is related to cerebral connectivity patterns, evidencing its brain substrates. Moreover, results highlight the relationship between fatigue and subjective cognitive complaints. These findings point out the relevance of the multidisciplinary assessment of post-COVID syndrome patients with subjective cognitive complaints, in order to unravel the symptomatology beneath the patient's complaints.

Detection of cerebrospinal fluid biomarkers changes of Alzheimer's disease using a cognitive stress test in persons with subjective cognitive decline and mild cognitive impairment.

Introduction: Timely and accurate diagnosis of the earliest manifestations of Alzheimer's disease (AD) is critically important. Cognitive challenge tests such as the Loewenstein Acevedo Scales for Semantic Interference and Learning (LASSI-L) have shown favorable diagnostic properties in a number of previous investigations using amyloid or FDG PET. However, no studies have examined LASSI-L performance against cerebrospinal fluid biomarkers of AD, which can be affected before the distribution of fibrillar amyloid and other changes that can be observed in brain neuroimaging. Therefore, we aimed to evaluate the relationship between LASSI-L scores and CSF biomarkers and the capacity of the cognitive challenge test to detect the presence of amyloid and tau deposition in patients with subjective cognitive decline and amnestic mild cognitive impairment (MCI). Methods: One hundred and seventy-nine patients consulting for memory loss without functional impairment were enrolled. Patients were examined using comprehensive neuropsychological assessment, the LASSI-L, and cerebrospinal fluid (CSF) biomarkers (Aß1-42/Aß1-40 and ptau181). Means comparisons, correlations, effect sizes, and ROC curves were calculated. Results: LASSI-L scores were significantly associated with CSF biomarkers Aß1-42/Aß1-40 in patients diagnosed with MCI and subjective cognitive decline, especially those scores evaluating the capacity to recover from proactive semantic interference effects and delayed recall. A logistic regression model for the entire sample including LASSI-L and age showed an accuracy of 0.749 and an area under the curve of 0.785 to detect abnormal amyloid deposition. Conclusion: Our study supports the biological validity of the LASSI-L and its semantic interference paradigm in the context of the early stages of AD. These findings emphasize the utility and the convenience of including sensitive cognitive challenge tests in the assessment of patients with suspicion of early stages of AD.

Comorbidity Patterns and Mortality Among Hospitalized Patients with Psychiatric Disorders and COVID-19.

OBJECTIVE: To examine the association between psychiatric and non-psychiatric comorbidity and 28-day mortality among patients with psychiatric disorders and COVID-19. METHODS: We performed a multicenter observational retrospective cohort study of adult patients with psychiatric disorders hospitalized with laboratory-confirmed COVID-19 at 36 Greater Paris University hospitals (January 2020-May 2021) (N=3,768). First, we searched for different subgroups of patients according to their psychiatric and non-psychiatric comorbidities through cluster analysis. Next, we compared 28-day all-cause mortality rates across the identified clusters, while taking into account sex, age, and the number of medical conditions. RESULTS: We found 5 clusters of patients with distinct psychiatric and non-psychiatric comorbidity patterns. Twenty-eight-day mortality in the cluster of patients with mood disorders was significantly lower than in other clusters. There were no significant differences in mortality across other clusters. CONCLUSIONS: All psychiatric and non-psychiatric conditions may be associated with increased mortality in patients with psychiatric disorders and COVID-19. The lower risk of death among patients with mood disorders might be in line with the potential beneficial effect of certain antidepressants in COVID-19, but requires further research. These findings help identify at-risk patients with psychiatric disorders who should benefit from vaccine booster prioritization and other prevention measures.

Normative Data in Cross-Cultural Neuropsychological Instruments in Spaniards and Colombians Living in Spain.

BACKGROUND: Cross-Cultural Dementia Screening (CCD), Rowland Universal Dementia Assessment Scale (RUDAS), and European Cross-cultural Neuropsychological Test Battery (CNTB) are three novel neuropsychological instruments developed from a cross-cultural perspective to reduce the impact of culture in cognitive assessment and improve the assessment in diverse populations. OBJECTIVE: We aimed to collect and present normative data on these tests in a majority population sample (Spaniards living in Spain) and in a minority population sample (Colombians living in Spain). METHODS: CCD, RUDAS, and CNTB were administered to a group of 300 cognitively healthy participants (150 Spaniards and 150 Colombians). Linear regression modeling strategy was used to provide adjusted norms for demographic factors and to explore the influence of these factors on test performance. RESULTS: Most of the CCD and CNTB scores were predicted by age and years of education, with some tests only predicted by age or showing a ceiling effect. The comparison of normative data between the two samples confirmed the favorable cross-cultural properties of these instruments, with only some differences in processing speed and executive functioning scores. CONCLUSIONS: Our study finds a comparable influence of demographic factors in both populations on the performance of CCD, RUDAS, and CNTB, confirming their adequate cross-cultural properties. We provide normative data for these tests in Spaniards and Colombians living in Spain.

Multi-Disease Validation of the RUDAS for Cognitive Screening in Alzheimer's Disease, Parkinson's Disease, and Multiple Sclerosis.

BACKGROUND: The Rowland Universal Dementia Assessment Scale (RUDAS) is a cognitive test with favorable diagnostic properties for detecting dementia and a low influence of education and cultural biases. OBJECTIVE: We aimed to validate the RUDAS in people with Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS). METHODS: We enrolled one hundred and fifty participants (60 with AD, 30 with PD, 60 with MS, and 120 healthy controls (HC)). All clinical groups completed a comprehensive neuropsychological battery, RUDAS, and standard cognitive tests of each disorder: MMSE, SCOPA-COG, and Symbol Digit Modalities Test. Intergroup comparisons between clinical groups and HC and ROC curves were estimated. Random Forest algorithms were trained and validated to detect cognitive impairment using RUDAS and rank the most relevant scores. RESULTS: The RUDAS scores were lower in patients with AD, and patients with PD and MS showed cognitive impairment compared to healthy controls. Effect sizes were generally large. The total score was the most discriminative, followed by the memory score. Correlations with standardized neuropsychological tests were moderate to high. Random Forest algorithms obtained accuracies over 80-90% using the RUDAS for diagnosing AD and cognitive impairment associated with PD and MS. CONCLUSION: Our results suggest the RUDAS is a valid test candidate for multi-disease cognitive screening tool in AD, PD, and MS.

Validation of the European Cross-Cultural Neuropsychological Test Battery (CNTB) for the assessment of mild cognitive impairment due to Alzheimer's disease and Parkinson's disease.

Background: The Cross-Cultural Neuropsychological Test Battery (CNTB) is a novel test battery specifically designed to reduce the impact of multiculturality in cognitive assessment. Objective: We aimed to validate the CNTB in Spaniards in patients with Alzheimer's disease (AD), including patients at mild cognitive impairment (MCI) and mild dementia stages, and Parkinson's disease with MCI (PD-MCI). Methods: Thirty patients with AD-MCI, 30 with AD-dementia (AD-D), and 30 with PD-MCI were recruited. Each clinical group was compared against a healthy control group (HC) with no differences in sex, age, or years of education. Intergroup comparisons, ROC analysis, and cut-off scores were calculated. Results: AD-MCI scored lower than HC in those subtests associated with episodic memory and verbal fluency. AD-D also showed lower scores in executive functions and visuospatial tests. Effect sizes for all the subtests were large. PD-MCI showed lower performance than HC in memory and executive functions, particularly on error scores, with large effect sizes. Comparing AD-MCI and PD-MCI, AD-MCI had lower memory scores, while PD-MCI showed the worst performance in executive functions. CNTB showed appropriate convergent validity with standardized neuropsychological tests measuring the same cognitive domains. We obtained similar cut-off scores to previous studies performed in other populations. Conclusions: The CNTB showed appropriate diagnostic properties in AD and PD, including those stages with mild cognitive impairment. This supports the utility of the CNTB for the early detection of cognitive impairment in AD and PD.

Medications Modulating the Acid Sphingomyelinase/Ceramide System and 28-Day Mortality among Patients with SARS-CoV-2: An Observational Study.

Prior evidence indicates the potential central role of the acid sphingomyelinase (ASM)/ceramide system in the infection of cells with SARS-CoV-2. We conducted a multicenter retrospective observational study including 72,105 adult patients with laboratory-confirmed SARS-CoV-2 infection who were admitted to 36 AP-HP (Assistance Publique-Hôpitaux de Paris) hospitals from 2 May 2020 to 31 August 2022. We examined the association between the ongoing use of medications functionally inhibiting acid sphingomyelinase (FIASMA), which reduces the infection of cells with SARS-CoV-2 in vitro, upon hospital admission with 28-day all-cause mortality in a 1:1 ratio matched analytic sample based on clinical characteristics, disease severity and other medications (N = 9714). The univariate Cox regression model of the matched analytic sample showed that FIASMA medication use at admission was associated with significantly lower risks of 28-day mortality (HR = 0.80; 95% CI = 0.72-0.88; p < 0.001). In this multicenter observational study, the use of FIASMA medications was significantly and substantially associated with reduced 28-day mortality among adult patients hospitalized with COVID-19. These findings support the continuation of these medications during the treatment of SARS-CoV-2 infections. Randomized clinical trials (RCTs) are needed to confirm these results, starting with the molecules with the greatest effect size in the study, e.g., fluoxetine, escitalopram, and amlodipine.

FDG-PET-based neural correlates of Addenbrooke's cognitive examination III scores in Alzheimer's disease and frontotemporal degeneration.

Introduction: The Addenbrooke's Cognitive Examination III (ACE-III) is a brief test useful for neuropsychological assessment. Several studies have validated the test for the diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD). In this study, we aimed to examine the metabolic correlates associated with the performance of ACE-III in AD and behavioral variant FTD. Methods: We enrolled 300 participants in a cross-sectional study, including 180 patients with AD, 60 with behavioral FTD (bvFTD), and 60 controls. An 18F-Fluorodeoxyglucose positron emission tomography study was performed in all cases. Correlation between the ACE-III and its domains (attention, memory, fluency, language, and visuospatial) with the brain metabolism was estimated. Results: The ACE-III showed distinct neural correlates in bvFTD and AD, effectively capturing the most relevant regions involved in these disorders. Neural correlates differed for each domain, especially in the case of bvFTD. Lower ACE-III scores were associated with more advanced stages in both disorders. The ACE-III exhibited high discrimination between bvFTD vs. HC, and between AD vs. HC. Additionally, it was sensitive to detect hypometabolism in brain regions associated with bvFTD and AD. Conclusion: Our study contributes to the knowledge of the brain regions associated with ACE-III, thereby facilitating its interpretation, and highlighting its suitability for screening and monitoring. This study provides further validation of ACE-III in the context of AD and FTD.

Transcranial direct current stimulation for post-COVID fatigue: a randomized, double-blind, controlled pilot study.

Fatigue is one of the most frequent and disabling symptoms of the post-COVID syndrome. In this study, we aimed to assess the effects of transcranial direct current stimulation on fatigue severity in a group of patients with post-COVID syndrome and chronic fatigue. We conducted a double-blind, parallel-group, sham-controlled study to evaluate the short-term effects of anodal transcranial direct current stimulation (2 mA, 20 min/day) on the left dorsolateral prefrontal cortex. The modified fatigue impact scale score was used as the primary endpoint. Secondary endpoints included cognition (Stroop test), depressive symptoms (Beck depression inventory) and quality of life (EuroQol-5D). Patients received eight sessions of transcranial direct current stimulation and were evaluated at baseline, immediately after the last session, and one month later. Forty-seven patients were enrolled (23 in the active treatment group and 24 in the sham treatment group); the mean age was 45.66 ± 9.49 years, and 37 (78.72%) were women. The mean progression time since the acute infection was 20.68 ± 6.34 months. Active transcranial direct current stimulation was associated with a statistically significant improvement in physical fatigue at the end of treatment and 1 month as compared with sham stimulation. No significant effect was detected for cognitive fatigue. In terms of secondary outcomes, active transcranial direct current stimulation was associated with an improvement in depressive symptoms at the end of treatment. The treatment had no effects on the quality of life. All the adverse events reported were mild and transient, with no differences between the active stimulation and sham stimulation groups. In conclusion, our results suggest that transcranial direct current stimulation on the dorsolateral prefrontal cortex may improve physical fatigue. Further studies are needed to confirm these findings and optimize stimulation protocols.