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Cognitive and visual impairment are common in Huntington’s Disease (HD) and may precede motor diagnosis. We investigate the early presence of visual cognitive deficits in 181 participants, including HD carriers (40 pre-manifest, 30 early manifest, 27 manifest, and 6 reduced penetrance) and 78 healthy controls (HC). Significant differences in visual memory were observed between reduced penetrance and pre-manifest groups ( p  = .003), with pre-manifest showing worse performance. Age, education, CAG repeats, motor status, executive function, and verbal fluency, accounted for up to 72.8% of the variance in general and visual cognitive functions, with motor status having the strongest impact on visual domains in HD carriers. In pre-manifest HD, visual cognitive domains were primarily influenced by executive function, verbal fluency, age, and CAG repeats, while in early and manifest stages motor status and verbal fluency becomes more influential. ROC analyses showed that especially visuospatial abilities, visual memory, and visual attention (AUC = 0.927, 0.878, 0.874, respectively) effectively differentiated HC and pre-manifest from early and manifest HD. Early assessment of visual cognitive domains, particularly visual memory, could be an early marker of cognitive decline in HD. Our findings highlight the different profiles of impairment in visual cognition across HD carriers.

BackgroundHD is an autosomal dominant, hereditary, and neurodegenerative disease that presents neurological, psychiatric, and cognitive impairment, with visual cognition being one of the affected areas.AimsThis study aims to analyze the visual cognition profile of asymptomatic and symptomatic carriers of Huntington’s disease (HD), compared with healthy controls (HC), and to evaluate the differences between asymptomatic and symptomatic patients with different years of progression of HD.MethodsWe evaluated 99 participants, 51 HD carriers [17 asymptomatic, 13 symptomatic ( < 5 years of evolution), 21 symptomatic ( > 5 years of evolution)] and 48 HC matched by sex and educational level. Motor function was rated with UHDRS scale, the general cognitive status was assessed with MoCA test, and a comprehensive battery of visual cognitive instruments was used. The following visual cognitive domains were assessed: visual memory, visuospatial skills and visuoconstructive abilities. One- way ANOVA and Tukey’s test for post hoc analysis were performed to analyze and compare the cognitive performance between the four groups.ResultsStatistically significant differences were found in the motor function (F(3.1)=14.129; p < .001) and in the general cognitive status (F(6.1)=9.63; p < .001) between groups. Specifically, we found significant differences in visual memory and visuospatial and visuoconstructive abilities between asymptomatic and both symptomatic subgroups of HD patients (p=.058), and also between the two groups of symptomatic patients with different years of evolution of HD (p=.014).ConclusionsFindings suggest that both symptomatic and asymptomatic HD patients present an increased visual cognitive impairment compared to HC. This impairment worsens with HD progression.

Alterations in time-varying functional connectivity (FC) have been found in Parkinson’s disease (PD) patients. To date, very little is known about the influence of sex on brain FC in PD patients and how this could be related to disease severity. The first objective was to evaluate the influence of sex on dynamic FC characteristics in PD patients and healthy controls (HC), while the second aim was to investigate the temporal patterns of dynamic connectivity related to PD motor and non-motor symptoms. Ninety-nine PD patients and sixty-two HC underwent a neuropsychological and clinical assessment. Rs-fMRI and T1-weighted MRI were also acquired. Dynamic FC analyses were performed in the GIFT toolbox. Dynamic FC analyses identified two States: State I, characterized by within-network positive coupling; and State II that showed between-network connectivity, mostly involving somatomotor and visual networks. Sex differences were found in dynamic indexes in HC but these differences were not observed in PD. Hierarchical clustering analysis identified three phenotypically distinct PD subgroups: (1) Subgroup A was characterized by mild motor symptoms; (2) Subgroup B was characterized by depressive and motor symptoms; (3) Subgroup C was characterized by cognitive and motor symptoms. Results revealed that changes in the temporal properties of connectivity were related to the motor/non-motor outcomes of PD severity. Findings suggest that while in HC sex differences may play a certain role in dynamic connectivity patterns, in PD patients, these effects may be overcome by the neurodegenerative process. Changes in the temporal properties of connectivity in PD were mainly related to the clinical markers of PD severity.

More than half of patients with high spinal cord injury (SCI) suffer from episodes of autonomic dysreflexia (AD), a condition that can lead to lethal situations, such as cerebral haemorrhage, if not treated correctly. Clinicians assess AD using clinical variables obtained from the patient’s history and physiological variables obtained invasively and non-invasively. This work aims to design a machine learning-based system to assist in the initial diagnosis of AD. For this purpose, 29 patients with SCI participated in a test at Cruces University Hospital in which data were collected using both invasive and non-invasive methods. The system proposed in this article is based on a two-level hierarchical classification to diagnose AD and only uses 35 features extracted from the non-invasive stages of the experiment (clinical and physiological features). The system achieved a 93.10% accuracy with a zero false negative rate for the class of having the disease, an essential condition for treating patients according to medical criteria.

Background Although SARS-Cov-2 outcomes have improved in the Omicron era, the synergistic or additive effects between SARS-CoV-2 Omicron variants and other microbiological agents in adult hematologic patients have been little explored. We aimed to characterize co-infection types, identify risk factors for co-infection and determine co-infection-related mortality in hematologic patients and recipients of cellular therapy with a first episode of SARS-CoV-2 infection in the Omicron era. Methods Retrospective national Spanish registry analysis of 692 consecutive patients with hematological disease including receptors of cellular therapy from December 2021 to May 2023. Results The co-infection rate was 9% ( n  = 64), 30% of which were polymicrobial. Bacterial, viral, and fungal agents affected 64%, 30%, and 11% of patients, respectively. Among the microbiologically confirmed agents ( n  = 82), the most common sites of identification were lower respiratory tract (33%), urinary tract (27%) and bloodstream (17%). Multivariable analysis identified cardiopathy (hazard ratio [HR] 1.69), CAR-T therapy (HR 3.42) and pneumonia (HR 5.54) as conditions associated with co-infection. Considering all-cause mortality at day 180 after SARS-CoV-2 detection, co-infection was associated with lower survival (71% versus 92%). Risk factors at COVID-19 diagnosis for non-relapse mortality (NRM) were co-infection (HR 4.28), age ≥ 64 years old (HR 2.55), active hematological treatment (HR 2.13) and under corticosteroid treatment (HR 3.21). In co-infected patients, the only identified factor increasing NRM was corticosteroid use (HR 3.33) at the time of SARS-CoV-2 detection. Conclusions SARS-CoV-2 co-infection are relatively frequent in hematologic patients and cellular therapy recipients in the Omicron era. Patients with ischemic cardiopathy, those presenting with pneumonia and recipients of CAR-T are at a higher risk of developing a co-infection, while co-infection, age ≥ 64 years old, active hematological therapy and corticosteroid treatment showed higher NRM. Improvements in identifying and managing concurrent infections during SARS-CoV-2 are needed to further reduce morbimortality in hematologic patients. Highlights • Hematological patients with SARS-CoV-2 had a co-infection rate of 9% (30% with polymicrobial agents). • Ischemic cardiopathy, CAR-T therapy and pneumonia increase the risk of co-infection. • Co-infection significantly increases non-relapse mortality.