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Brain Sciences Aug 2023Social cognition has a broad theoretical definition, which includes the ability to mentalise, i.e., recognise and infer mental states to explain and predict another's... (Review)
Review
Social cognition has a broad theoretical definition, which includes the ability to mentalise, i.e., recognise and infer mental states to explain and predict another's behaviour. There is growing recognition of the clinical, diagnostic, and prognostic value of assessing a person's ability to perform social cognitive tasks, particularly aspects of theory of mind, such as mentalising. One such measure of mentalising is the 'Reading the Mind in the Eyes' test (RMET). This systematic review and meta-analysis consider performance on the RMET, applied to people with neurodegenerative conditions in matched control studies, since its publication in 2001. Overall, this review includes 22 papers with data from N = 800 participants with neurodegenerative conditions: Alzheimer's disease, = 31; Parkinson's disease, = 221; Lewy body dementia, = 33; motor neuron disease, = 218; Huntington's disease = 80; multiple sclerosis, = 217; and N = 601 matched typical controls. Our meta-analyses show that deficits in mentalising, as measured by the RMET, are consistently reported across neurodegenerative conditions, with participants in both early and late disease stages being affected. Social cognition is an emerging field of cognitive neuroscience requiring specific and sensitive measurement across each subdomain. Adult-based meta-normative data feature, for which future groups or individuals could be compared against, and hypotheses relating to the source of these mentalising deficits are further discussed. This review was registered with PROSPERO (CRD42020182874).
PubMed: 37759869
DOI: 10.3390/brainsci13091268 -
Journal of Neurology Oct 2023Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder affecting the upper and lower motor neurons, which can lead to death from respiratory failure within... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder affecting the upper and lower motor neurons, which can lead to death from respiratory failure within 3-5 years after the onset of this disease. Nowadays, no drug can effectively slow down the progression of this disease. High-calorie therapy, an emerging complementary alternative treatment, has been reported in studies to prolong the survival time of patients, prevent muscle atrophy and provide a better prognosis. However, no systematic review and meta-analysis were performed to summarize the evidence of this therapy. This meta-analysis comprehensively evaluates the effectiveness and safety of high-calorie therapy for treating ALS.
METHODS
We searched the electronic databases from inception to 1 April 2023: PubMed, Embase, Web of Science, Cochrane Library, Scopus, Ovid/Medline, and ProQuest. Randomized controlled trials (RCTs) that met the inclusion criteria were performed by meta-analysis. All statistical analyses were performed in STATA software.
RESULTS
A total of six eligible RCTs were included in this meta-analysis, involving 370 ALS patients. The meta-analyses showed that high-calorie therapy had superiority in improving body weight (SMD = 1, 95% CI 0.36, 1.65) and BMI (SMD = 0.83, 95% CI 0.02, 1.63). With respect to safety, there was no difference between the high-calorie therapy and the control group regarding the number of adverse events (RR = 3.61, 95% CI 0.08, 162.49). However, ALSFRS-R scores (SMD = 0.34, 95% CI - 0.4, 1.08), survival rate (RR = 1.23, 95% CI 0.98, 1.55), and lipid profile (LDL: SMD = 0.21, 95% CI - 0.33, 0.75; HDL: SMD = 0.17, 95% CI - 0.37, 0.71; TC: SMD = 0.21, 95% CI - 0.33, 0.75), CRP (SMD = 0.85, 95% CI - 1.37, 3.06) showed no significant difference compared to the control groups.
CONCLUSIONS
High-calorie therapy is effective in gaining weight and BMI with few side effects. However, no significant superiority was detected in ALSFRS-R scores, survival time, lipid profile, and CRP indicator. The overall quality of the included studies is high, and the results have some credibility, but future corroboration by high-quality RCTs is also expected.
Topics: Humans; Amyotrophic Lateral Sclerosis; Lipids
PubMed: 37369861
DOI: 10.1007/s00415-023-11838-4 -
Neurologia Mar 2024To identify the neurological diseases for which euthanasia and assisted suicide are most frequently requested in the countries where these medical procedures are legal... (Review)
Review
OBJECTIVE
To identify the neurological diseases for which euthanasia and assisted suicide are most frequently requested in the countries where these medical procedures are legal and the specific characteristics of euthanasia in some of these diseases, and to show the evolution of euthanasia figures.
METHODS
We conducted a systematic literature review.
RESULTS
Dementia, motor neuron disease, multiple sclerosis, and Parkinson's disease are the neurological diseases that most frequently motivate requests for euthanasia or assisted suicide. Requests related to dementia constitute the largest group, are growing, and raise additional ethical and legal issues due to these patients' diminished decision-making capacity. In some countries, the ratios of euthanasia requests to all cases of multiple sclerosis, motor neuron disease, or Huntington disease are higher than for any other disease.
CONCLUSIONS
After cancer, neurological diseases are the most frequent reason for requesting euthanasia or assisted suicide.
Topics: Humans; Suicide, Assisted; Euthanasia; Nervous System Diseases; Huntington Disease; Multiple Sclerosis; Motor Neuron Disease
PubMed: 38272260
DOI: 10.1016/j.nrleng.2024.01.007 -
Journal of Neurology Dec 2023Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the degeneration of both upper and lower motoneurons, leading to motor and... (Review)
Review
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the degeneration of both upper and lower motoneurons, leading to motor and non-motor symptoms. Recent evidence suggests that ALS is indeed a multisystem disorder, associated with cognitive impairment, dysautonomia, pain and fatigue, excess of secretions, and sensory symptoms. To evaluate whether sensory neuropathy could broaden its spectrum, we systematically reviewed its presence and characteristics in ALS, extracting data on epidemiological, clinical, neurophysiological, neuropathological, and genetic features. Sensory neuropathy can be found in up to 20% of ALS patients, affecting both large and small fibers, although there is a great heterogeneity related to different techniques used for its detection (electromyography vs skin biopsy vs nerve biopsy). Moreover, the association between CIDP-like neuropathy and ALS needs to be better explored, although it could be interpreted as part of the neuroinflammatory process in the latter disease. Sensory neuropathy in ALS may be associated with a spinal onset and might be more frequent in SOD1 patients. Moreover, it seems mutually exclusive with cognitive impairment. No associations with sex and other genetic mutation were observed. All these data in the literature reveal the importance of actively looking for sensory neuropathy in ALS patients, and suggest including sensory neuropathy among ALS non-motor features, as it may explain sensory symptoms frequently reported throughout the course of the disease. Its early identification could help avoid diagnostic delays and improve patients' treatment and quality of life.
Topics: Humans; Amyotrophic Lateral Sclerosis; Neurodegenerative Diseases; Quality of Life; Motor Neurons; Electromyography
PubMed: 37610446
DOI: 10.1007/s00415-023-11954-1 -
Cureus Aug 2023Being one of the most prevalent progressive neurodegenerative disorders (falling second only to Alzheimer's disease) with a clinical pattern affecting millions of lives... (Review)
Review
Being one of the most prevalent progressive neurodegenerative disorders (falling second only to Alzheimer's disease) with a clinical pattern affecting millions of lives all over the world, Parkinson's disease (PD) has never failed to attract a formidable interest from the vast majority of neurologists and researchers worldwide. This review article will analyze the pathophysiology, etiology, genetics, and pathological stages of Parkinson's disease with their corresponding clinical sequels. A review article was conducted using research databases including PubMed, PubMed Central, Springer, and Elsevier. The research articles reviewed using databases were written in English, German, Japanese, and Chinese and published within the preceding 50 years. Based on the article's findings, we concluded that Parkinson's disease is a progressive disorder with a variety of motor and non-motor symptoms that are influenced by a cascade of pathological neuronal abnormalities such as Lewy neurites and Lewy bodies that gradually build up with an eventual consequence of neurodegeneration of dopamine-secreting neurons. Multiple genetic mutations, pathophysiological events, and environmental factors act as the foundation to initiate that cascade.
PubMed: 37664277
DOI: 10.7759/cureus.44353 -
Neurological Sciences : Official... Feb 2024This systematic review and meta-analysis aimed to determine the frequency and correlates of fatigue in patients with amyotrophic lateral sclerosis (ALS). (Meta-Analysis)
Meta-Analysis Review
OBJECTIVES
This systematic review and meta-analysis aimed to determine the frequency and correlates of fatigue in patients with amyotrophic lateral sclerosis (ALS).
METHODS
Three databases were searched up to 2nd May 2023 to identify studies reporting fatigue frequency in ALS. Studies included had to identify ALS patients through one of ALS diagnostic criteria and measure fatigue by a validated tool with a specific cut-off value. Meta-analysis was conducted using RStudio's "meta" package with a random-effects model. Subgroup analyses and meta-regression explored the relationship between fatigue frequency in ALS and different covariates.
RESULTS
Eleven studies, compromising 1072 patients, met the inclusion criteria and were included in our analysis. The pooled frequency of fatigue across all studies was 48% (95% CI = 40% to 57%). Our subgroup analysis based on the ALSFRS-R revealed a higher frequency of fatigue in studies with lower scores (< 30) compared to those with higher scores (≥ 30), with a pooled frequency of 62% (95% CI = 43% to 79%) and 43% (95% CI = 37% to 49%), respectively. Also, the meta-regression analysis showed a significant negative association between fatigue and ALSFRS-R mean (P = 0.02). The included studies reported an association between fatigue and lower functional status and poorer quality of life in patients with ALS.
CONCLUSION
Our findings suggest that fatigue is prevalent in almost half of ALS patients and is associated with lower functional status and poorer quality of life, highlighting the importance of assessing and managing fatigue in ALS patients.
Topics: Humans; Amyotrophic Lateral Sclerosis; Prevalence; Quality of Life; Fatigue
PubMed: 37837507
DOI: 10.1007/s10072-023-07119-7 -
NPJ Digital Medicine Dec 2023Motor Neuron Disease (MND) is a progressive and largely fatal neurodegeneritve disorder with a lifetime risk of approximately 1 in 300. At diagnosis, up to 25% of people... (Review)
Review
Motor Neuron Disease (MND) is a progressive and largely fatal neurodegeneritve disorder with a lifetime risk of approximately 1 in 300. At diagnosis, up to 25% of people with MND (pwMND) exhibit bulbar dysfunction. Currently, pwMND are assessed using clinical examination and diagnostic tools including the ALS Functional Rating Scale Revised (ALS-FRS(R)), a clinician-administered questionnaire with a single item on speech intelligibility. Here we report on the use of digital technologies to assess speech features as a marker of disease diagnosis and progression in pwMND. Google Scholar, PubMed, Medline and EMBASE were systematically searched. 40 studies were evaluated including 3670 participants; 1878 with a diagnosis of MND. 24 studies used microphones, 5 used smartphones, 6 used apps, 2 used tape recorders and 1 used the Multi-Dimensional Voice Programme (MDVP) to record speech samples. Data extraction and analysis methods varied but included traditional statistical analysis, CSpeech, MATLAB and machine learning (ML) algorithms. Speech features assessed also varied and included jitter, shimmer, fundamental frequency, intelligible speaking rate, pause duration and syllable repetition. Findings from this systematic review indicate that digital speech biomarkers can distinguish pwMND from healthy controls and can help identify bulbar involvement in pwMND. Preliminary evidence suggests digitally assessed acoustic features can identify more nuanced changes in those affected by voice dysfunction. No one digital speech biomarker alone is consistently able to diagnose or prognosticate MND. Further longitudinal studies involving larger samples are required to validate the use of these technologies as diagnostic tools or prognostic biomarkers.
PubMed: 38062079
DOI: 10.1038/s41746-023-00959-9 -
Neural Regeneration Research Jul 2024Parkinson's disease is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta, and although restoring striatal dopamine levels may...
Parkinson's disease is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta, and although restoring striatal dopamine levels may improve symptoms, no treatment can cure or reverse the disease itself. Stem cell therapy has a regenerative effect and is being actively studied as a candidate for the treatment of Parkinson's disease. Mesenchymal stem cells are considered a promising option due to fewer ethical concerns, a lower risk of immune rejection, and a lower risk of teratogenicity. We performed a meta-analysis to evaluate the therapeutic effects of mesenchymal stem cells and their derivatives on motor function, memory, and preservation of dopaminergic neurons in a Parkinson's disease animal model. We searched bibliographic databases (PubMed/MEDLINE, Embase, CENTRAL, Scopus, and Web of Science) to identify articles and included only peer-reviewed in vivo interventional animal studies published in any language through June 28, 2023. The study utilized the random-effect model to estimate the 95% confidence intervals (CI) of the standard mean differences (SMD) between the treatment and control groups. We use the systematic review center for laboratory animal experimentation's risk of bias tool and the collaborative approach to meta-analysis and review of animal studies checklist for study quality assessment. A total of 33 studies with data from 840 Parkinson's disease model animals were included in the meta-analysis. Treatment with mesenchymal stem cells significantly improved motor function as assessed by the amphetamine-induced rotational test. Among the stem cell types, the bone marrow MSCs with neurotrophic factor group showed largest effect size (SMD [95% CI] = -6.21 [-9.50 to -2.93], P = 0.0001, I2 = 0.0 %). The stem cell treatment group had significantly more tyrosine hydroxylase positive dopaminergic neurons in the striatum ([95% CI] = 1.04 [0.59 to 1.49], P = 0.0001, I2 = 65.1 %) and substantia nigra (SMD [95% CI] = 1.38 [0.89 to 1.87], P = 0.0001, I2 = 75.3 %), indicating a protective effect on dopaminergic neurons. Subgroup analysis of the amphetamine-induced rotation test showed a significant reduction only in the intracranial-striatum route (SMD [95% CI] = -2.59 [-3.25 to -1.94], P = 0.0001, I2 = 74.4 %). The memory test showed significant improvement only in the intravenous route (SMD [95% CI] = 4.80 [1.84 to 7.76], P = 0.027, I2 = 79.6 %). Mesenchymal stem cells have been shown to positively impact motor function and memory function and protect dopaminergic neurons in preclinical models of Parkinson's disease. Further research is required to determine the optimal stem cell types, modifications, transplanted cell numbers, and delivery methods for these protocols.
PubMed: 38051903
DOI: 10.4103/1673-5374.387976 -
Artificial Intelligence in Medicine Aug 2023Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterised by the progressive loss of motor neurons in the brain and spinal cord. The fact... (Review)
Review
BACKGROUND
Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterised by the progressive loss of motor neurons in the brain and spinal cord. The fact that ALS's disease course is highly heterogeneous, and its determinants not fully known, combined with ALS's relatively low prevalence, renders the successful application of artificial intelligence (AI) techniques particularly arduous.
OBJECTIVE
This systematic review aims at identifying areas of agreement and unanswered questions regarding two notable applications of AI in ALS, namely the automatic, data-driven stratification of patients according to their phenotype, and the prediction of ALS progression. Differently from previous works, this review is focused on the methodological landscape of AI in ALS.
METHODS
We conducted a systematic search of the Scopus and PubMed databases, looking for studies on data-driven stratification methods based on unsupervised techniques resulting in (A) automatic group discovery or (B) a transformation of the feature space allowing patient subgroups to be identified; and for studies on internally or externally validated methods for the prediction of ALS progression. We described the selected studies according to the following characteristics, when applicable: variables used, methodology, splitting criteria and number of groups, prediction outcomes, validation schemes, and metrics.
RESULTS
Of the starting 1604 unique reports (2837 combined hits between Scopus and PubMed), 239 were selected for thorough screening, leading to the inclusion of 15 studies on patient stratification, 28 on prediction of ALS progression, and 6 on both stratification and prediction. In terms of variables used, most stratification and prediction studies included demographics and features derived from the ALSFRS or ALSFRS-R scores, which were also the main prediction targets. The most represented stratification methods were K-means, and hierarchical and expectation-maximisation clustering; while random forests, logistic regression, the Cox proportional hazard model, and various flavours of deep learning were the most widely used prediction methods. Predictive model validation was, albeit unexpectedly, quite rarely performed in absolute terms (leading to the exclusion of 78 eligible studies), with the overwhelming majority of included studies resorting to internal validation only.
CONCLUSION
This systematic review highlighted a general agreement in terms of input variable selection for both stratification and prediction of ALS progression, and in terms of prediction targets. A striking lack of validated models emerged, as well as a general difficulty in reproducing many published studies, mainly due to the absence of the corresponding parameter lists. While deep learning seems promising for prediction applications, its superiority with respect to traditional methods has not been established; there is, instead, ample room for its application in the subfield of patient stratification. Finally, an open question remains on the role of new environmental and behavioural variables collected via novel, real-time sensors.
Topics: Humans; Amyotrophic Lateral Sclerosis; Artificial Intelligence; Brain; Cluster Analysis; Databases, Factual
PubMed: 37316101
DOI: 10.1016/j.artmed.2023.102588 -
Journal of Translational Medicine Sep 2023Cell-based strategies focusing on replacement or protection of dopaminergic neurons have been considered as a potential approach to treat Parkinson's disease (PD) for... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Cell-based strategies focusing on replacement or protection of dopaminergic neurons have been considered as a potential approach to treat Parkinson's disease (PD) for decades. However, despite promising preclinical results, clinical trials on cell-therapy for PD reported mixed outcomes and a thorough synthesis of these findings is lacking. We performed a systematic review and meta-analysis to evaluate cell-therapy for PD patients.
METHODS
We systematically identified all clinical trials investigating cell- or tissue-based therapies for PD published before July 2023. Out of those, studies reporting transplantation of homogenous cells (containing one cell type) were included in meta-analysis. The mean difference or standardized mean difference in quantitative neurological scale scores before and after cell-therapy was analyzed to evaluate treatment effects.
RESULTS
The systematic literature search revealed 106 articles. Eleven studies reporting data from 11 independent trials (210 patients) were eligible for meta-analysis. Disease severity and motor function evaluation indicated beneficial effects of homogenous cell-therapy in the 'off' state at 3-, 6-, 12-, or 24-month follow-ups, and for motor function even after 36 months. Most of the patients were levodopa responders (61.6-100% in different follow-ups). Cell-therapy was also effective in improving the daily living activities in the 'off' state of PD patients. Cells from diverse sources were used and multiple transplantation modes were applied. Autografts did not improve functional outcomes, while allografts exhibited beneficial effects. Encouragingly, both transplantation into basal ganglia and to areas outside the basal ganglia were effective to reduce disease severity. Some trials reported adverse events potentially related to the surgical procedure. One confirmed and four possible cases of graft-induced dyskinesia were reported in two trials included in this meta-analysis.
CONCLUSIONS
This meta-analysis provides preliminary evidence for the beneficial effects of homogenous cell-therapy for PD, potentially to the levodopa responders. Allogeneic cells were superior to autologous cells, and the effective transplantation sites are not limited to the basal ganglia. PROSPERO registration number: CRD42022369760.
Topics: Humans; Parkinson Disease; Levodopa; Transplantation, Autologous; Transplantation, Homologous; Allogeneic Cells
PubMed: 37679754
DOI: 10.1186/s12967-023-04484-x