Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is characterized by persistent physical and mental fatigue. The post-COVID-19 condition patients refer physical fatigue and cognitive impairment sequelae. Given the similarity between both conditions, could it be the same pathology with a different precipitating factor? Objective: To describe the cognitive impairment, neuropsychiatric symptoms, and general symptomatology in both groups, to find out if it is the same pathology. As well as verify if the affectation of smell is related to cognitive deterioration in patients with post-COVID-19 condition. Methods: The sample included 42 ME/CFS and 73 post-COVID-19 condition patients. Fatigue, sleep quality, anxiety and depressive symptoms, the frequency and severity of different symptoms, olfactory function and a wide range of cognitive domains were evaluated. Results: Both syndromes are characterized by excessive physical fatigue, sleep problems and myalgia. Sustained attention and processing speed were impaired in 83.3% and 52.4% of ME/CFS patients while in post-COVID-19 condition were impaired in 56.2% and 41.4% of patients, respectively. Statistically significant differences were found in sustained attention and visuospatial ability, being the ME/CFS group who presented the worst performance. Physical problems and mood issues were the main variables correlating with cognitive performance in post-COVID-19 patients, while in ME/CFS it was anxiety symptoms and physical fatigue. Conclusions: The symptomatology and cognitive patterns were similar in both groups, with greater impairment in ME/CFS. This disease is characterized by greater physical and neuropsychiatric problems compared to post-COVID-19 condition. Likewise, we also propose the relevance of prolonged hyposmia as a possible marker of cognitive deterioration in patients with post-COVID-19.

Non-motor manifestations of Parkinson’s disease (PD) appear early and have a significant impact on the quality of life of patients, but few studies have evaluated their predictive potential with machine learning algorithms. We evaluated 9 algorithms for discriminating PD patients from controls using a wide collection of non-motor clinical PD features from two databases: Biocruces (96 subjects) and PPMI (687 subjects). In addition, we evaluated whether the combination of both databases could improve the individual results. For each database 2 versions with different granularity were created and a feature selection process was performed. We observed that most of the algorithms were able to detect PD patients with high accuracy (>80%). Support Vector Machine and Multi-Layer Perceptron obtained the best performance, with an accuracy of 86.3% and 84.7%, respectively. Likewise, feature selection led to a significant reduction in the number of variables and to better performance. Besides, the enrichment of Biocruces database with data from PPMI moderately benefited the performance of the classification algorithms, especially the recall and to a lesser extent the accuracy, while the precision worsened slightly. The use of interpretable rules obtained by the RIPPER algorithm showed that simply using two variables (autonomic manifestations and olfactory dysfunction), it was possible to achieve an accuracy of 84.4%. Our study demonstrates that the analysis of non-motor parameters of PD through machine learning techniques can detect PD patients with high accuracy and recall, and allows us to select the most discriminative non-motor variables to create potential tools for PD screening.

Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and post-COVID condition can present similarities such as fatigue, brain fog, autonomic and neuropathic symptoms. Methods: The study included 87 patients with post-COVID condition, 50 patients with ME/CFS, and 50 healthy controls (HC). The hemodynamic autonomic function was evaluated using the deep breathing technique, Valsalva maneuver, and Tilt test. The presence of autonomic and sensory small fiber neuropathy (SFN) was assessed with the Sudoscan and with heat and cold evoked potentials, respectively. Finally, a complete neuropsychological evaluation was performed. The objective of this study was to analyze and compare the autonomic and neuropathic symptoms in post-COVID condition with ME/CFS, and HC, as well as, analyze the relationship of these symptoms with cognition and fatigue. Results: Statistically significant differences were found between groups in heart rate using the Kruskal–Wallis test (H), with ME/CFS group presenting the highest (H = 18.3; p ≤ .001). The Postural Orthostatic Tachycardia Syndrome (POTS), and pathological values in palms on the Sudoscan were found in 31% and 34% of ME/CFS, and 13.8% and 19.5% of post-COVID patients, respectively. Concerning evoked potentials, statistically significant differences were found in response latency to heat stimuli between groups (H = 23.6; p ≤ .01). Latency was highest in ME/CFS, and lowest in HC. Regarding cognition, lower parasympathetic activation was associated with worse cognitive performance. Conclusions: Both syndromes were characterized by inappropriate tachycardia at rest, with a high percentage of patients with POTS. The prolonged latencies for heat stimuli suggested damage to unmyelinated fibers. The higher proportion of patients with pathological results for upper extremities on the Sudoscan suggested a non-length-dependent SFN.

Introduction: Telerehabilitation in neurological and cardiological diseases is an alternative rehabilitation that improves the quality of life and health conditions of patients and enhances the accessibility to health care. However, despite the reported benefits of telerehabilitation, it is necessary to study its impact on the healthcare system.Methods: The systematic review aims to investigate the costs and results of telerehabilitation in neurological and cardiological diseases. MEDLINE and EMBASE databases were searched from 2005 to 2021, for studies that assess the costs and results of telerehabilitation compared to traditional rehabilitation (center-based programs) in neurological and cardiological diseases. A narrative synthesis of results was carried out.Results: A total of 8 studies (865 participants) of 430 records were included. Three studies were related to the costs and results of telerehabilitation in neurological diseases (specifically in stroke). In total, five studies assessed telerehabilitation in cardiological diseases (chronic heart failure, coronary heart disease, acute coronary syndrome, and cardiovascular diseases). The duration of the telerehabilitation ranged from 6 to 48 weeks. The studies included cost-analysis, cost-benefit, cost-effectiveness, or cost-utility. In total, four studies found significant cost/savings per person between $565.66 and $2,352.00 (p < 0.05). In contrast, most studies found differences in costs and clinical effects between the telerehabilitation performed and the rehabilitation performed at the clinic. Just one study found quality-adjusted life years (QALY) significant differences between groups [Incremental cost-effectiveness ratio (ICER) per QALY ($−21,666.41/QALY).Discussion: Telerehabilitation is an excellent alternative to traditional center rehabilitation, which increases the accessibility to rehabilitation to more people, either due to the geographical situation of the patients or the limitations of the health systems. Telerehabilitation seems to be as clinical and cost-effective as traditional rehabilitation, even if, generally, telerehabilitation is less costly. More research is needed to evaluate health-related quality of life and cost-effectiveness in other neurological diseases.Systematic review registration: [https://figshare.com/articles/journal_ contribution/Review_Protocol_Costs_and_effects_of_Telerehabilitation_in_ Neurological_and_Cardiological_Diseases_A_Systematic_Review/19619838], identifier [19619838].

Background: Retinal optical coherence tomography findings in Lewy body diseases and their implications for visual outcomes remain controversial. We investigated whether region‐specific thickness analysis of retinal layers could improve the detection of macular atrophy and unravel its association with visual disability in Parkinson's disease.Methods: Patients with idiopathic Parkinson's disease (n = 63), dementia with Lewy bodies (n = 8), and E46K mutation carriers in the α‐synuclein gene (E46K‐SNCA) (n = 4) and 34 controls underwent Spectralis optical coherence tomography macular scans and a comprehensive battery of visual function and cognition tests. We computed mean retinal layer thicknesses of both eyes within 1‐, 2‐, 3‐, and 6‐mm diameter macular discs and in concentric parafoveal (1‐ to 2‐mm, 2‐ to 3‐mm, 1‐ to 3‐mm) and perifoveal (3‐ to 6‐mm) rings. Group differences in imaging parameters and their relationship with visual outcomes were analyzed. A multivariate logistic model was developed to predict visual impairment from optical coherence tomography measurements in Parkinson's disease, and cutoff values were determined with receiver operating characteristic analysis.Results: When compared with controls, patients with dementia with Lewy bodies had significant thinning of the ganglion cell–inner plexiform layer complex within the central 3‐mm disc mainly because of differences in 1‐ to 3‐mm parafoveal thickness. This parameter was strongly correlated in patients, but not in controls, with low contrast visual acuity and visual cognition outcomes (P < .05, False Discovery Rate), achieving 88% of accuracy in predicting visual impairment in Parkinson's disease.Conclusion: Our findings support that parafoveal thinning of ganglion cell–inner plexiform complex is a sensitive and clinically relevant imaging biomarker for Lewy body diseases, specifically for Parkinson's disease. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.