Costs and effects of telerehabilitation in neurological and cardiological diseases: A systematic review

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.This project has received funding from the European Union's Horizon 2020 Research and Innovation Program under grant agreement no: 769807

Foveal remodeling of retinal microvasculature in Parkinson’s disease

[EN] Background: Retinal microvascular alterations have been previously described in Parkinson’s disease (PD) patients using optical coherence tomography angiography (OCT-A). However, an extensive description of retinal vascular morphological features, their association with PD-related clinical variables and their potential use as diagnostic biomarkers has not been explored. Methods: We performed a cross-sectional study including 49 PD patients (87 eyes) and 40 controls (73 eyes). Retinal microvasculature was evaluated with Spectralis OCT-A and cognitive status with Montreal Cognitive Assessment. Unified PD Rating Scale and disease duration were recorded in patients. We extracted microvascular parameters from superficial and deep vascular plexuses of the macula, including the area and circularity of foveal avascular zone (FAZ), skeleton density, perfusion density, vessel perimeter index, vessel mean diameter, fractal dimension (FD) and lacunarity using Python and MATLAB. We compared the microvascular parameters between groups and explored their association with thickness of macular layers and clinical outcomes. Data were analyzed with General Estimating Equations (GEE) and adjusted for age, sex, and hypertension. Logistic regression GEE models were fitted to predict diagnosis of PD versus controls from microvascular, demographic, and clinical data. The discrimination ability of models was tested with receiver operating characteristic curves. Results: FAZ area was significantly smaller in patients compared to controls in superficial and deep plexuses, whereas perfusion density, skeleton density, FD and lacunarity of capillaries were increased in the foveal zone of PD. In the parafovea, microvascular parameters of superficial plexus were associated with ganglion cellinner plexiform layer thickness, but this was mainly driven by PD with mild cognitive impairment. No such associations were observed in controls. FAZ area was negatively associated with cognition in PD (non-adjusted models). Foveal lacunarity, combined with demographic and clinical confounding factors, yielded an outstanding diagnostic accuracy for discriminating PD patients from controls. Conclusion: Parkinson’s disease patients displayed foveal microvascular alterations causing an enlargement of the vascular bed surrounding FAZ. Parafoveal microvascular alterations were less pronounced but were related to inner retinal layer thinning. Retinal microvascular abnormalities helped discriminating PD from controls. All this supports OCT-A as a potential non-invasive biomarker to reveal vascular pathophysiology and improve diagnostic accuracy in PD.This study was partially co-funded by the Instituto de Salud Carlos III through the projects PI14/00679 and PI16/00005 (co-funded by European Regional Development Fund/European Social Fund “A way to make Europe”/“Investing in your future”), and by the Department of Health of the Basque Government through the projects “2019111100” and “2020333033”

Small fiber neuropathy and phosphorylated alpha-synuclein in the skin of E46K- SNCA mutation carriers

Background and objective: In 2004 we described the E46K mutation in alpha-synuclein gene (E46K-SNCA), a rare point mutation causing an aggressive Lewy body disease with early prominent non-motor features and small fiber denervation of myocardium. Considering the potential interest of the skin as a target for the development of biomarkers in Parkinson's Disease (PD), in this work we aimed to evaluate structural and functional integrity of small autonomic nerve fibers and phosphorylated alpha-synuclein (p-synuclein) deposition in the skin of E46K- SNCA carriers as compared to those observed in parkin gene mutation (PARK2) carriers and healthy controls. Patients and methods: We studied 7 E46K-SNCA carriers (3 dementia with Lewy bodies, 2 pure autonomic failure, 1 PD and 1 asymptomatic), 2 PARK2 carriers and 2 healthy controls to quantify intraepidermal nerve fiber density and p-synuclein deposition with cervical skin punch biopsies (immunohistochemistry against anti PGP9.5/UCHL-1, TH and p-synuclein) and sudomotor function with electrochemical skin conductance (ESC) (SudoScan). Results: All E46K-SNCA carriers had moderate to severe p-synuclein deposits and small fiber neurodegeneration in different epidermal and dermal structures including nerve fascicles and glands, especially in carriers with Pure Autonomic Failure, while p-synuclein aggregates where absent in healthy controls and in one of two PARK2 carriers. The severity of the latter skin abnormalities in E46K-SNCA were correlated with sudomotor dysfunction (lower ESC) in hands (p = 0.035). Interpretation: These results together with our previous findings support the relevance of E46K-SNCA mutation as a suitable model to study small fiber neuropathy in Lewy body diseases

Diagnostic classification of Parkinson’s disease based on non-motor manifestations and machine learning strategies

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.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was partially funded by the Department of Education, Universities and Research of the Basque Government (ADIAN, IT-980-16); by the Spanish Ministry of Science, Innovation and Universities - National Research Agency and the European Regional Development Fund - ERDF (PhysComp, TIN2017-85409-P), and from the State Research Agency (AEI, Spain) under grant agreement No RED2018-102312-T (IA-Biomed); by Michael J. Fox Foundation [RRIA 2014 (Rapid Response Innovation Awards) Program (Grant ID: 10189)]; by the Instituto de Salud Carlos III through the project “PI14/00679” and “PI16/00005”, the Juan Rodes grant “JR15/00008” (IG) (Co-funded by European Regional Development Fund/European Social Fund - “Investing in your future”); and by the Department of Health of the Basque Government through the projects “2016111009” and “2019111100”

Quantitative analysis of dysautonomia in patients with autonomic dysreflexia

Autonomic dysreflexia (AD) is a life-threatening condition for individuals with cervical or high-thoracic spinal cord injury (SCI). The profile of autonomic dysfunction in AD using validated clinical autonomic tests has not been described so far, although it could be useful to identify SCI patients at greater risk of developing AD non-invasively. With this objective, 37 SCI patients (27% female) were recruited, and hemodynamic and cardiac parameters were continuously monitored to determine the presence of AD, defined as an increase of systolic blood pressure of 20 mmHg or higher after bladder filling with saline. Then, standard autonomic function testing was performed, including Deep Breathing, Valsalva Manoeuvre and Tilt Table Test. Finally, baroreflex sensitivity (BRS), and spectral analysis of heart rate and blood pressure variability were measured at rest. Catecholamines and vasopressin levels were also measured at supine and upright positions. The severity of SCI was assessed through clinical and radiological examinations. AD was observed in 73.3% of SCI patients, being 63.6% of them asymptomatic during the dysreflexive episode. AD patients displayed a drop in sympathetic outflow, as determined by decreased noradrenalin plasma levels, reduced sympathovagal balance and increased BRS. In line with decreased sympathetic activity, the incidence of neurogenic orthostatic hypotension was higher in AD patients. Our results provide novel evidence regarding the autonomic dysfunction in SCI patients with AD compared to non-AD patients, posing non-invasively measured autonomic parameters as a powerful clinical tool to predict AD in SCI patients

Heart-brain synchronization breakdown in Parkinson's disease

Heart rate variability (HRV) abnormalities are potential early biomarkers in Parkinson's disease (PD) but their relationship with central autonomic network (CAN) activity is not fully understood. We analyzed the synchronization between HRV and brain activity in 31 PD patients and 21 age-matched healthy controls using blood-oxygen-level-dependent (BOLD) signals from resting-state functional brain MRI and HRV metrics from finger plethysmography recorded for 7.40 min. We additionally quantified autonomic symptoms (SCOPA-AUT) and objective autonomic cardiovascular parameters (blood pressure and heart rate) during deep breathing, Valsalva, and head-up tilt, which were used to classify the clinical severity of dysautonomia. We evaluated HRV and BOLD signals synchronization (HRV-BOLD-sync) with Pearson lagged cross-correlations and Fisher's statistics for combining window-length-dependent HRV-BOLD-Sync Maps and assessed their association with clinical dysautonomia. HRV-BOLD-sync was lower significantly in PD than in controls in various brain regions within CAN or in networks involved in autonomic modulation. Moreover, heart-brain synchronization index (HBSI), which quantifies heart-brain synchronization at a single-subject level, showed an inverse exposure-response relationship with dysautonomia severity, finding the lowest HBSI in patients with severe dysautonomia, followed by moderate, mild, and, lastly, controls. Importantly, HBSI was associated in PD, but not in controls, with Valsalva pressure recovery time (sympathetic), deep breathing E/I ratio (cardiovagal), and SCOPA-AUT. Our findings support the existence of heart-brain de-synchronization in PD with an impact on clinically relevant autonomic outcomes.We want to thank all the patients and participants involved in the study. This study was partially co-funded by Michael J. Fox Foundation [RRIA 2014 (Rapid Response Innovation Awards) Program (Grant ID: 10189)], by the Carlos III Health Institute, and the European Union (ERDF/ESF, "A Way to Make Europe"/"Investing in Your Future") through the projects PI14/00679 and PI16/00005, the Juan Rodes grant "JR15/00008" (I.G.), and by the Department of Health of the Basque Government through the project "2016111009" and "2020333033". A.J.M. was supported by a predoctoral grant from the Basque Government (PRE_2019_1_0070). M.I. acknowledges financial support from"La Caixa" Foundation (ID 100010434, fellowship LCF/BQ/EU20/11810065). The Edmond and Lily Safra Center for Brain Sciences and the Basque Government (POS_2019_2_0020) to A.E. J.M.C. is funded by Ikerbasque: The Basque Foundation for Science and from the Ministerial de Economia, Industria y Competitividad (Spain) and FEDER (grant DPI2016-79874-R), and from the Department of Economic and Infrastructure Development of the Basque Country (Elkartek Program, KK-2018/00032, KK-2018/00090, and KK-2021/00009/BCB)

Parafoveal thinning of inner retina is associated with visual dysfunction in Lewy body diseases

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 alpha-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. (c) 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.This study was partially cofunded by the Michael J. Fox Foundation (2014 Rapid Response Innovation Awards; Grant 10189), by the Carlos III Health Institute through Projects PI14/00679 and PI16/00005, and Juan Rodes Grant JR15/00008 (I.G.) (cofunded by the European Regional Development Fund/European Social Fund "Investing in Your Future"), and by the Department of Health of the Basque Government through Project 201611100

Brain fog of post-COVID-19 condition and Chronic Fatigue Syndrome, same medical disorder?

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.This study has been funded by Instituto de Salud Carlos III (ISCIII) through the project PI20/01076 and co-funded by the European Union, EITB maratoia (BIOS21/COV/006) and grants for health research projects from the Basque Government (2021111006). Azcue, N. received a pre-doctoral research grant from the basque government (PRE_2021_1_0186)

Retinal thickness predicts the risk of cognitive decline in Parkinson's disease

Objective: To analyze longitudinal changes of retinal thickness and their predictive value as biomarkers of disease progression in idiopathic Parkinson’s disease (iPD). Methods: Patients with Lewy body diseases (LBDs) were enrolled and prospectively evaluated at 3 years, including patients with iPD (n=42), dementia with Lewy bodies (DLB, n=4), E46K-SNCA mutation carriers (n=4) and controls (n=17). All participants underwent Spectralis retinal optical coherence tomography and Montreal Cognitive Assessment (MoCA), and Unified Parkinson’s Disease Rating Scale (UPDRS) score was obtained in patients. Macular ganglion-inner plexiform layer complex (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) thickness reduction rates were estimated with linear mixed models. Risk ratios were calculated to evaluate the association between baseline GCIPL and pRNFL thickness and the risk of subsequent cognitive and motor worsening, using clinically meaningful cut-offs. Results: GCIPL thickness in the parafoveal region (1- to 3-mm ring) presented the largest reduction rate. The annualized atrophy rate was 0.63 µm in iPD patients and 0.23 µm in controls (p<0.0001). iPD patients with lower parafoveal GCIPL and pRNFL thickness at baseline presented an increased risk of cognitive decline at 3 years (RR 3.49, 95% CI 1.10 – 11.1, p=0.03 and RR 3.28, 95% CI 1.03 – 10.45, p=0.045, respectively). We did not identify significant associations between retinal thickness and motor deterioration. Interpretation: Our results provide evidence of the potential use of OCT-measured parafoveal GCIPL thickness to monitor neurodegeneration and to predict the risk of cognitive worsening over time in iPD