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The growing number of stroke survivors face physical, cognitive, and psychosocial impairments, making stroke a significant contributor to global disability. Various factors have been identified as key predictors of post-stroke outcomes. The aim of this study was to develop a standardized predictive model that integrates various demographic and clinical factors to better predict post-stroke cognitive recovery and depression in patients with ischemic stroke (IS). We included IS patients during both the acute phase and six months post-stroke and considered neuropsychological measures (screening scales, individual tests, functional cognitive scales), stroke severity and laterality, as well as functional disability measures. The study identified several key predictors of post-stroke cognitive recovery and depression in IS patients. Higher education and younger age were associated with better cognitive recovery. Lower stroke severity, indicated by lower National Institutes of Health Stroke Scale (NIHSS) scores, also contributed to better cognitive outcomes. Patients with lower modified Rankin Scale (mRS) scores showed improved performance on cognitive tests and lower post-stroke depression scores. The study concluded that age, education, stroke severity and functional status are the most critical predictors of cognitive recovery and post-stroke emotional status in IS patients. Tailoring rehabilitation strategies based on these predictive markers can significantly improve patient outcomes. [ABSTRACT FROM AUTHOR]

The increasing interest in physical therapy in sports neurorehabilitation stems from the high incidence of neurological injuries among athletes and the crucial role of rehabilitation in facilitating their safe return to sports. This study aims to provide a comprehensive analysis of research trends in physical therapy and neurorehabilitation in athletes. This study presents a bibliometric analysis of 103 documents from the Scopus database, followed by a narrative review of the identified thematic areas. Together, these approaches offer a comprehensive overview of the international literature on the application of physical therapy in sports neurorehabilitation, highlighting key trends and contributors. The software VOSviewer and Power BI (2.136.1202.0) were used for the bibliometric analysis and the visualization of the results. Techniques such as performance analysis (documents per year, top sources and countries in documents, and top authors in citations) and science mapping (co-authorship, bibliographic coupling, co-citation, and co-occurrence) were conducted. The results revealed the journals and the authors with the greatest impact in the field and collaborations between various countries. From the co-occurrence analysis of the keywords, three key thematic clusters were identified, Clinical Approaches and Outcomes in Neurorehabilitation, Athlete-Centered Neurorehabilitation Techniques, and Specialized Interventions in Sports Medicine and Neurorehabilitation, which were used to conduct the narrative review. These findings provide a solid foundation for future research and clinical practice aimed at enhancing recovery times and overall performance in athletes with neurological injuries. [ABSTRACT FROM AUTHOR]

Evidence shows that neurodegenerative and neuropsychiatric disorders are influenced by alterations in the gut microbiome. Various diseases have been linked to microbiome dysbiosis, yet there are inconclusive data regarding which microorganisms are associated with each disorder. The aim of our study is to systematically review the recent literature of the past decade to clarify whether the gut microbiome contributes to the understanding of pathogenesis and progression of neurodegenerative disorders. Most included studies showed a strong correlation between the relative abundance of certain microorganisms, mainly species of the phyla Firmicutes and Bacteroidetes, and disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD). It is speculated that the microorganisms and their byproducts have a significant role in brain protein accumulation, neuro-inflammation, and gut permeability. The estimation of microbial populations could potentially improve clinical outcomes and hinder the progression of the disease. However, further research is needed to include more diseases and larger patient samples and identify specific species and subspecies associated with these disorders. [ABSTRACT FROM AUTHOR]

In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson's disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management. [ABSTRACT FROM AUTHOR]

This systematic review explores the multifaceted challenges faced by caregivers of stroke survivors, addressing the global impact of strokes and the anticipated rise in survivors over the coming decades. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a thorough literature search identified 34 relevant studies published between 2018 and 2023. The review categorizes caregiver burden into four domains: physical health, social functioning, financial issues, and psychological health. Caregivers often experience a decline in physical health, marked by chronic fatigue, sleep disturbances, and pain. Emotional distress is prevalent, leading to anxiety and depression, especially in cases of high burden. Financial strains arise from medical expenses and employment changes, exacerbating the overall burden. Contextual factors, such as cultural norms and resource availability, influence the caregiver experience. The Newcastle–Ottawa scale assessed the methodological quality of studies. The conclusion emphasizes tailored interventions and support systems for caregivers, with practical recommendations for healthcare professionals, therapists, mental health professionals, financial counselors, and policymakers. This comprehensive review enhances the understanding of caregiver experiences and provides actionable insights to improve stroke care and rehabilitation The study's novelty lies in its holistic examination of caregiver burden in stroke care, its focus on the recent literature, and its emphasis on forecasting caregiver outcomes, contributing valuable insights for proactive intervention strategies. [ABSTRACT FROM AUTHOR]

Changes in the gut microbiome can affect cognitive and psychological functions via the microbiota–gut–brain (MGB) axis. Probiotic supplements are thought to have largely positive effects on mental health when taken in sufficient amounts; however, despite extensive research having been conducted, there is a lack of consistent findings on the effects of probiotics on anxiety and depression and the associated microbiome alterations. The aim of our study is to systematically review the most recent literature of the last 10 years in order to clarify whether probiotics could actually improve depression and anxiety symptoms. Our results indicate that the majority of the most recent literature suggests a beneficial role of probiotics in the treatment of depression and anxiety, despite the existence of a substantial number of less positive findings. Given probiotics' potential to offer novel, personalized treatment options for mood disorders, further, better targeted research in psychiatric populations is needed to address concerns about the exact mechanisms of probiotics, dosing, timing of treatment, and possible differences in outcomes depending on the severity of anxiety and depression. [ABSTRACT FROM AUTHOR]

The Trail Making Test (TMT) is one of the most commonly administered tests in clinical and research neuropsychological settings. The two parts of the test (part A (TMT-A) and part B (TMT-B)) enable the evaluation of visuoperceptual tracking and processing speed (TMT-A), as well as divided attention, set-shifting and cognitive flexibility (TMT-B). The main cognitive processes that are assessed using TMT, i.e., processing speed, divided attention, and cognitive flexibility, are often affected in patients with stroke. Considering the wide use of TMT in research and clinical settings since its introduction in neuropsychological practice, the purpose of our review was to provide a comprehensive overview of the use of TMT in stroke patients. We present the most representative studies assessing processing speed and attentional shift/mental flexibility in stroke settings using TMT and applying scoring methods relying on conventional TMT scores (e.g., time-to-complete part A and part B), as well as derived measures (e.g., TMT-(B-A) difference score, TMT-(B/A) ratio score, errors in part A and part B). We summarize the cognitive processes commonly associated with TMT performance in stroke patients (e.g., executive functions), lesion characteristics and neuroanatomical underpinning of TMT performance post-stroke, the association between TMT performance and patients' instrumental activities of daily living, motor difficulties, speech difficulties, and mood statue, as well as their driving ability. We also highlight how TMT can serve as an objective marker of post-stroke cognitive recovery following the implementation of interventions. Our comprehensive review underscores that the TMT stands as an invaluable asset in the stroke assessment toolkit, contributing nuanced insights into diverse cognitive, functional, and emotional dimensions. As research progresses, continued exploration of the TMT potential across these domains is encouraged, fostering a deeper comprehension of post-stroke dynamics and enhancing patient-centered care across hospitals, rehabilitation centers, research institutions, and community health settings. Its integration into both research and clinical practice reaffirms TMT status as an indispensable instrument in stroke-related evaluations, enabling holistic insights that extend beyond traditional neurological assessments. [ABSTRACT FROM AUTHOR]

Stroke is a major leading cause of chronic disability, often affecting patients' motor and sensory functions. Functional magnetic resonance imaging (fMRI) is the most commonly used method of functional neuroimaging, and it allows for the non-invasive study of brain activity. The time-dependent coactivation of different brain regions at rest is described as resting-state activation. As a non-invasive task-independent functional neuroimaging approach, resting-state fMRI (rs-fMRI) may provide therapeutically useful information on both the focal vascular lesion and the connectivity-based reorganization and subsequent functional recovery in stroke patients. Considering the role of a prompt and accurate prognosis in stroke survivors along with the potential of rs-fMRI in identifying patterns of neuroplasticity in different post-stroke phases, this review provides a comprehensive overview of the latest literature regarding the role of rs-fMRI in stroke prognosis in terms of motor and sensory outcomes. Our comprehensive review suggests that with the advancement of MRI acquisition and data analysis methods, rs-fMRI emerges as a promising tool to study the motor and sensory outcomes in stroke patients and evaluate the effects of different interventions. [ABSTRACT FROM AUTHOR]

Stroke is a significant cause of mortality and chronic morbidity caused by cardiovascular disease. Respiratory muscles can be affected in stroke survivors, leading to stroke complications, such as respiratory infections. Respiratory function can be assessed using pulmonary function tests (PFTs). Data regarding PFTs in stroke survivors are limited. We reviewed the correlation between PFTs and stroke severity or degree of disability. Furthermore, we reviewed the PFT change in stroke patients undergoing a respiratory muscle training program. We searched PubMed until September 2023 using inclusion and exclusion criteria in order to identify studies reporting PFTs post-stroke and their change after a respiratory muscle training program. Outcomes included lung function parameters (FEV1, FVC, PEF, MIP and MEP) were measured in acute or chronic stroke survivors. We identified 22 studies of stroke patients, who had undergone PFTs and 24 randomised controlled trials in stroke patients having PFTs after respiratory muscle training. The number of patients included was limited and studies were characterised by great heterogeneity regarding the studied population and the applied intervention. In general, PFTs were significantly reduced compared to healthy controls and predicted normal values and associated with stroke severity. Furthermore, we found that respiratory muscle training was associated with significant improvement in various PFT parameters and functional stroke parameters. PFTs are associated with stroke severity and are improved after respiratory muscle training. [ABSTRACT FROM AUTHOR]

Byline: Dimitrios. Tsiptsios, Christoph. Mueller, Konstantinos. Tsamakis Sir, Isolated spinal accessory neuropathy (SAN) is an uncommon motor neuropathy most often related to local surgical procedures at the posterior cervical triangle, [...]

Frontotemporal dementia (FTD) is a neurodegenerative disorder characterized by progressive impairments in behavior, executive function, and language, primarily affecting individuals under the age of 65. This disorder is associated with expressive and receptive anomia, word comprehension deficits, and behavioral symptoms such as apathy, loss of empathy, and disinhibition, all of which closely correlate with functional impairment in daily activities. Despite substantial efforts, research on occupational therapy (OT) interventions has yet to demonstrate clear benefits in managing the disease. The aim of this study is to investigate OT interventions and assess their efficacy, with a specific focus on individuals suffering from FTD. We systematically conducted searches on two databases, namely Medline and Science Direct, spanning a ten-year period from 2003 to 2023, in accordance with the PRISMA guidelines. Eleven studies met the inclusion criteria. OT interventions targeted both patients and caregivers and yielded significant positive improvements in their lives. A key focus of these interventions was to teach acceptable alternatives to the behaviors exhibited by FTD patients, as these behaviors are strongly influenced by the disease itself. OT contributes positively to enhancing the quality of life of FTD patients and alleviating the caregiving burden experienced by those providing long-term care to these patients. [ABSTRACT FROM AUTHOR]

Stroke has become the first cause of functional disability and one of the leading causes of mortality worldwide. Therefore, it is of crucial importance to develop accurate biomarkers to assess stroke risk and prognosis. Emerging evidence suggests that neutrophil extracellular trap (NET) levels may serve as a valuable biomarker to predict stroke occurrence and functional outcome. NETs are known to create a procoagulant state by serving as a scaffold for tissue factor (TF) and platelets inducing thrombosis by activating coagulation pathways and endothelium. A literature search was conducted in two databases (MEDLINE and Scopus) to trace all relevant studies published between 1 January 2016 and 31 December 2022, addressing the potential utility of NETs as a stroke biomarker. Only full-text articles in English were included. The current review includes thirty-three papers. Elevated NET levels in plasma and thrombi seem to be associated with increased mortality and worse functional outcomes in stroke, with all acute ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage included. Additionally, higher NET levels seem to correlate with worse outcomes after recanalization therapies and are more frequently found in strokes of cardioembolic or cryptogenic origin. Additionally, total neutrophil count in plasma seems also to correlate with stroke severity. Overall, NETs may be a promising predictive tool to assess stroke severity, functional outcome, and response to recanalization therapies. [ABSTRACT FROM AUTHOR]

Stroke remains a predominant cause of mortality and disability worldwide. The endeavor to diagnose stroke through biomechanical time-series data coupled with Artificial Intelligence (AI) poses a formidable challenge, especially amidst constrained participant numbers. The challenge escalates when dealing with small datasets, a common scenario in preliminary medical research. While recent advances have ushered in few-shot learning algorithms adept at handling sparse data, this paper pioneers a distinctive methodology involving a visualization-centric approach to navigating the small-data challenge in diagnosing stroke survivors based on gait-analysis-derived biomechanical data. Employing Siamese neural networks (SNNs), our method transforms a biomechanical time series into visually intuitive images, facilitating a unique analytical lens. The kinematic data encapsulated comprise a spectrum of gait metrics, including movements of the ankle, knee, hip, and center of mass in three dimensions for both paretic and non-paretic legs. Following the visual transformation, the SNN serves as a potent feature extractor, mapping the data into a high-dimensional feature space conducive to classification. The extracted features are subsequently fed into various machine learning (ML) models like support vector machines (SVMs), Random Forest (RF), or neural networks (NN) for classification. In pursuit of heightened interpretability, a cornerstone in medical AI applications, we employ the Grad-CAM (Class Activation Map) tool to visually highlight the critical regions influencing the model's decision. Our methodology, though exploratory, showcases a promising avenue for leveraging visualized biomechanical data in stroke diagnosis, achieving a perfect classification rate in our preliminary dataset. The visual inspection of generated images elucidates a clear separation of classes (100%), underscoring the potential of this visualization-driven approach in the realm of small data. This proof-of-concept study accentuates the novelty of visual data transformation in enhancing both interpretability and performance in stroke diagnosis using limited data, laying a robust foundation for future research in larger-scale evaluations. [ABSTRACT FROM AUTHOR]

As a result of social progress and improved living conditions, which have contributed to a prolonged life expectancy, the prevalence of strokes has increased and has become a significant phenomenon. Despite the available stroke treatment options, patients frequently suffer from significant disability after a stroke. Initial stroke severity is a significant predictor of functional dependence and mortality following an acute stroke. The current study aims to collect and analyze data from the hyperacute and acute phases of stroke, as well as from the medical history of the patients, in order to develop an explainable machine learning model for predicting stroke-related neurological deficits at discharge, as measured by the National Institutes of Health Stroke Scale (NIHSS). More specifically, we approached the data as a binary task problem: improvement of NIHSS progression vs. worsening of NIHSS progression at discharge, using baseline data within the first 72 h. For feature selection, a genetic algorithm was applied. Using various classifiers, we found that the best scores were achieved from the Random Forest (RF) classifier at the 15 most informative biomarkers and parameters for the binary task of the prediction of NIHSS score progression. RF achieved 91.13% accuracy, 91.13% recall, 90.89% precision, 91.00% f1-score, 8.87% FNrate and 4.59% FPrate. Those biomarkers are: age, gender, NIHSS upon admission, intubation, history of hypertension and smoking, the initial diagnosis of hypertension, diabetes, dyslipidemia and atrial fibrillation, high-density lipoprotein (HDL) levels, stroke localization, systolic blood pressure levels, as well as erythrocyte sedimentation rate (ESR) levels upon admission and the onset of respiratory infection. The SHapley Additive exPlanations (SHAP) model interpreted the impact of the selected features on the model output. Our findings suggest that the aforementioned variables may play a significant role in determining stroke patients' NIHSS progression from the time of admission until their discharge. [ABSTRACT FROM AUTHOR]

The purpose of the present study was to review all available work published within the last decade focusing on coping strategies in stroke caregivers and their impact on quality of Life (QoL) and psycho-emotional status. A literature search of two databases (MEDLINE, Scopus) was conducted to identify all relevant full-text English studies published between 2013–2023. Sixteen articles were traced and were finally included. Cognitive and behavioral coping strategies were beneficial for stroke caregivers' and survivors' QoL. The level of mutuality in the caregiver-survivor relationship was associated with the impact of depressive symptoms on caregivers' QoL and the protective effect of mutuality on survivors' QoL over time. The level and quality of social support were positively associated with QoL for stroke caregivers and survivors. Caregivers' preparedness was a moderator for the impact of depression on both caregivers' and survivors' QoL. High levels of spirituality had a significant role in ameliorating the negative impact of depressive symptoms on the psychological and physical QoL of stroke caregivers and survivors. In conclusion, the study of coping strategies can be used as a psychological reserve in the process of stroke rehabilitation and actively contribute to improving the QoL of both caregivers and stroke survivors. [ABSTRACT FROM AUTHOR]

Given the expansion of life expectancy, the aging of the population, and the anticipated rise in the number of stroke survivors in Europe with severe neurological consequences in the coming decades, stroke is becoming the most prevalent cause of functional disability. Therefore, the prognosis for a stroke must be timely and precise. Two databases (MEDLINE and Scopus) were searched to identify all relevant studies published between 1 January 2005 and 31 December 2022 that investigated the relationship between thyroid hormone levels and acute stroke severity, mortality, and post-hospital prognosis. Only full-text English-language articles were included. This review includes Thirty articles that were traced and incorporated into the present review. Emerging data regarding the potential predictive value of thyroid hormone levels suggests there may be a correlation between low T3 syndrome, subclinical hypothyroidism, and poor stroke outcome, especially in certain age groups. These findings may prove useful for rehabilitation and therapy planning in clinical practice. Serum thyroid hormone concentration measurement is a non-invasive, relatively harmless, and secure screening test that may be useful for this purpose. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is a chronic immune-mediated disease of the central nervous system (CNS), characterized by the diffuse grey and white matter damage. Cognitive impairment (CI) is a frequent clinical feature in patients with MS (PwMS) that can be prevalent even in early disease stages, affecting the physical activity and active social participation of PwMS. Limited information is available regarding the influence of MS in social cognition (SC), which may occur independently from the overall neurocognitive dysfunction. In addition, the available information regarding the factors that influence SC in PwMS is limited, e.g., factors such as a patient's physical disability, different cognitive phenotypes, mood status, fatigue. Considering that SC is an important domain of CI in MS and may contribute to subjects' social participation and quality of life, we herein conceptualize and present the methodological design of a cross-sectional study in 100 PwMS of different disease subtypes. The study aims (a) to characterize SC impairment in PwMS in the Greek population and (b) to unveil the relationship between clinical symptoms, phenotypes of CI, mood status and fatigue in PwMS and the potential underlying impairment on tasks of SC. [ABSTRACT FROM AUTHOR]

Stroke is the leading cause of functional disability worldwide, with increasing prevalence in adults. Given the considerable negative impact on patients' quality of life and the financial burden on their families and society, it is essential to provide stroke survivors with a timely and reliable prognosis of stroke recurrence. Leukoaraiosis (LA) is a common neuroimaging feature of cerebral small-vessel disease. By researching the literature of two different databases (MEDLINE and Scopus), the present study aims to review all relevant studies from the last decade, dealing with the clinical utility of pre-existing LA as a prognostic factor for stroke recurrence in stroke survivors. Nineteen full-text articles published in English were identified and included in the present review, with data collected from a total of 34,546 stroke patients. A higher rate of extended LA was strongly associated with stroke recurrence in all stroke subtypes, even after adjustment for clinical risk factors. In particular, patients with ischemic stroke or transient ischemic attack with advanced LA had a significantly higher risk of future ischemic stroke, whereas patients with previous intracerebral hemorrhage and severe LA had a more than 2.5-fold increased risk of recurrent ischemic stroke and a more than 30-fold increased risk of hemorrhagic stroke. Finally, in patients receiving anticoagulant treatment for AF, the presence of LA was associated with an increased risk of recurrent ischemic stroke and intracranial hemorrhage. Because of this valuable predictive information, evaluating LA could significantly expand our knowledge of stroke patients and thereby improve overall stroke care. [ABSTRACT FROM AUTHOR]

Background, aim: Insomnia constitutes a common and very debilitating disorder in modern societies. A better understanding of the etiologies and risk factors, modifiable or not, of insomnia is essential for a swifter diagnosis and a more appropriate treatment, mitigating its toll on individuals and society. To this purpose, the present study assessed the prevalence of insomnia in a randomly-selected adult population and its relation with a diverse range of socio-demographic characteristics and medical conditions. Methods: A sample of 771 participants aged 24 to 89 years (mean age 58±13 years; 42.7% women) was randomly selected from the general population of Thrace, a prefecture in Northeastern Greece with special cultural considerations, using a two-stage stratified sampling scheme. The Greek version of the Athens Insomnia Scale (AIS) was utilized to evaluate the presence of insomnia. Moreover, the Berlin Questionnaire for Obstructive Sleep Apnea and the Epworth Sleepiness Scale for Excessive Daytime Sleepiness were also utilized. Results: A total of 141 study participants (18.3%) were found to suffer from insomnia. Impaired sleep maintenance was reported as the most frequent symptom (62%). The following independent statistically significant risk factors emerged (p-value <0.05): BMI ≥35 (aOR=2.91), divorced or widowed individuals (aOR=2.23), female gender (aOR=1.76), age >70 years (aOR=1.61), snoring (aOR=1.61), midday sleep (aOR=1.58) and presence of chronic disease (aOR=1.55). Conclusions: The prevalence of insomnia in Thrace aligns with similar studies conducted in Greece and internationally. A multitude of socio-demographic characteristics and diseases, especially chronic, predispose to insomnia. [ABSTRACT FROM AUTHOR]

Stroke is a major cause of functional disability and is increasing in frequency. Therefore, stroke prognosis must be both accurate and timely. Among other biomarkers, heart rate variability (HRV) is investigated in terms of prognostic accuracy within stroke patients. The literature research of two databases (MEDLINE and Scopus) is performed to trace all relevant studies published within the last decade addressing the potential utility of HRV for stroke prognosis. Only the full-text articles published in English are included. In total, forty-five articles have been traced and are included in the present review. The prognostic value of biomarkers of autonomic dysfunction (AD) in terms of mortality, neurological deterioration, and functional outcome appears to be within the range of known clinical variables, highlighting their utility as prognostic tools. Moreover, they may provide additional information regarding poststroke infections, depression, and cardiac adverse events. AD biomarkers have demonstrated their utility not only in the setting of acute ischemic stroke but also in transient ischemic attack, intracerebral hemorrhage, and traumatic brain injury, thus representing a promising prognostic tool whose clinical application may greatly facilitate individualized stroke care. [ABSTRACT FROM AUTHOR]

Stroke constitutes a major cause of functional disability and mortality, with increasing prevalence. Thus, the timely and accurate prognosis of stroke outcomes based on clinical or radiological markers is vital for both physicians and stroke survivors. Among radiological markers, cerebral microbleeds (CMBs) constitute markers of blood leakage from pathologically fragile small vessels. In the present review, we evaluated whether CMBs affect ischemic and hemorrhagic stroke outcomes and explored the fundamental question of whether CMBs may shift the risk–benefit balance away from reperfusion therapy or antithrombotic use in acute ischemic stroke patients. A literature review of two databases (MEDLINE and Scopus) was conducted to identify all the relevant studies published between 1 January 2012 and 9 November 2022. Only full-text articles published in the English language were included. Forty-one articles were traced and included in the present review. Our findings highlight the utility of CMB assessments, not only in the prognostication of hemorrhagic complications of reperfusion therapy, but also in forecasting hemorrhagic and ischemic stroke patients' functional outcomes, thus indicating that a biomarker-based approach may aid in the provision of counseling for patients and families, improve the selection of more appropriate medical therapies, and contribute to a more accurate choice of patients for reperfusion therapy. [ABSTRACT FROM AUTHOR]

Ischemic stroke (IS) exhibits significant heterogeneity in terms of etiology and pathophysiology. Several recent studies highlight the significance of inflammation in the onset and progression of IS. White blood cell subtypes, such as neutrophils and monocytes, participate in the inflammatory response in various ways. On the other hand, high-density lipoproteins (HDL) exhibit substantial anti-inflammatory and antioxidant actions. Consequently, novel inflammatory blood biomarkers have emerged, such as neutrophil to HDL ratio (NHR) and monocyte to HDL ratio (MHR). Literature research of two databases (MEDLINE and Scopus) was conducted to identify all relevant studies published between 1 January 2012 and 30 November 2022 dealing with NHR and MHR as biomarkers for IS prognosis. Only full-text articles published in the English language were included. Thirteen articles have been traced and are included in the present review. Our findings highlight the utility of NHR and MHR as novel stroke prognostic biomarkers, the widespread application, and the calculation of which, along with their inexpensive cost, make their clinical application extremely promising. [ABSTRACT FROM AUTHOR]

Predicting functional outcome following stroke is considered to be of key importance in an attempt to optimize overall stroke care. Although clinical prognostic tools have been widely implemented, optimal blood biomarkers might be able to yield additional information regarding each stroke survivor's propensity for recovery. Copeptin seems to have interesting prognostic potential poststroke. The present review aims to explore the prognostic significance of copeptin in stroke patients. Literature research of two databases (MEDLINE and Scopus) was conducted to trace all relevant studies published between 16 February 2012 and 16 February 2022 that focused on the utility of copeptin as a prognostic marker in acute stroke setting. 25 studies have been identified and included in the present review. The predictive ability of copeptin regarding both functional outcome and mortality appears to be in the range of established clinical variables, thus highlighting the added value of copeptin evaluation in stroke management. Apart from acute ischemic stroke, the discriminatory accuracy of the biomarker was also demonstrated among patients with transient ischemic attack, intracerebral hemorrhage, and subarachnoid hemorrhage. Overall, copeptin represents a powerful prognostic tool, the clinical implementation of which is expected to significantly facilitate the individualized management of stroke patients. [ABSTRACT FROM AUTHOR]

Stroke is one of the main causes of long-term disabilities, increasing the cost of national healthcare systems due to the elevated costs of rigorous treatment that is required, as well as personal cost because of the decreased ability of the patient to work. Traditional rehabilitation strategies rely heavily on individual clinical data and the caregiver's experience to evaluate the patient and not in data extracted from population data. The use of machine learning (ML) algorithms can offer evaluation tools that will lead to new personalized interventions. The aim of this scoping review is to introduce the reader to key directions of ML techniques for the prediction of functional outcomes in stroke rehabilitation and identify future scientific research directions. The search of the relevant literature was performed using PubMed and Semantic Scholar online databases. Full-text articles were included if they focused on ML in predicting the functional outcome of stroke rehabilitation. A total of 26 out of the 265 articles met our inclusion criteria. The selected studies included ML approaches and were directly related to the inclusion criteria. ML can play a key role in supporting decision making during pre- and post-treatment interventions for post-stroke survivors, by utilizing multidisciplinary data sources. [ABSTRACT FROM AUTHOR]

Stroke constitutes the second highest cause of morbidity and mortality worldwide while also impacting the world economy, triggering substantial financial burden in national health systems. High levels of blood glucose, homocysteine, and cholesterol are causative factors for atherothrombosis. These molecules induce erythrocyte dysfunction, which can culminate in atherosclerosis, thrombosis, thrombus stabilization, and post-stroke hypoxia. Glucose, toxic lipids, and homocysteine result in erythrocyte oxidative stress. This leads to phosphatidylserine exposure, promoting phagocytosis. Phagocytosis by endothelial cells, intraplaque macrophages, and vascular smooth muscle cells contribute to the expansion of the atherosclerotic plaque. In addition, oxidative stress-induced erythrocytes and endothelial cell arginase upregulation limit the pool for nitric oxide synthesis, leading to endothelial activation. Increased arginase activity may also lead to the formation of polyamines, which limit the deformability of red blood cells, hence facilitating erythrophagocytosis. Erythrocytes can also participate in the activation of platelets through the release of ADP and ATP and the activation of death receptors and pro-thrombin. Damaged erythrocytes can also associate with neutrophil extracellular traps and subsequently activate T lymphocytes. In addition, reduced levels of CD47 protein in the surface of red blood cells can also lead to erythrophagocytosis and a reduced association with fibrinogen. In the ischemic tissue, impaired erythrocyte 2,3 biphosphoglycerate, because of obesity or aging, can also favor hypoxic brain inflammation, while the release of damage molecules can lead to further erythrocyte dysfunction and death. [ABSTRACT FROM AUTHOR]

Stroke survivors are at increased risk of developing depression and cognitive decline. Thus, it is crucial for both clinicians and stroke survivors to be provided with timely and accurate prognostication of post-stroke depression (PSD) and post-stroke dementia (PSDem). Several biomarkers regarding stroke patients' propensity to develop PSD and PSDem have been implemented so far, leukoaraiosis (LA) being among them. The purpose of the present study was to review all available work published within the last decade dealing with pre-existing LA as a predictor of depression (PSD) and cognitive dysfunction (cognitive impairment or PSDem) in stroke patients. A literature search of two databases (MEDLINE and Scopus) was conducted to identify all relevant studies published between 1 January 2012 and 25 June 2022 that dealt with the clinical utility of preexisting LA as a prognostic indicator of PSD and PSDem/cognitive impairment. Only full-text articles published in the English language were included. Thirty-four articles were traced and are included in the present review. LA burden, serving as a surrogate marker of "brain frailty" among stroke patients, appears to be able to offer significant information about the possibility of developing PSD or cognitive dysfunction. Determining the extent of pre-existing white matter abnormalities can properly guide decision making in acute stroke settings, as a greater degree of such lesioning is usually coupled with neuropsychiatric aftermaths, such as PSD and PSDem. [ABSTRACT FROM AUTHOR]

Despite therapeutic advancements, stroke remains a leading cause of death and long-term disability. The quality of current stroke prognostic models varies considerably, whereas prediction models of post-stroke disability and mortality are restricted by the sample size, the range of clinical and risk factors and the clinical applicability in general. Accurate prognostication can ease post-stroke discharge planning and help healthcare practitioners individualize aggressive treatment or palliative care, based on projected life expectancy and clinical course. In this study, we aimed to develop an explainable machine learning methodology to predict functional outcomes of stroke patients at discharge, using the Modified Rankin Scale (mRS) as a binary classification problem. We identified 35 parameters from the admission, the first 72 h, as well as the medical history of stroke patients, and used them to train the model. We divided the patients into two classes in two approaches: "Independent" vs. "Non-Independent" and "Non-Disability" vs. "Disability". Using various classifiers, we found that the best models in both approaches had an upward trend, with respect to the selected biomarkers, and achieved a maximum accuracy of 88.57% and 89.29%, respectively. The common features in both approaches included: age, hemispheric stroke localization, stroke localization based on blood supply, development of respiratory infection, National Institutes of Health Stroke Scale (NIHSS) upon admission and systolic blood pressure levels upon admission. Intubation and C-reactive protein (CRP) levels upon admission are additional features for the first approach and Erythrocyte Sedimentation Rate (ESR) levels upon admission for the second. Our results suggest that the said factors may be important predictors of functional outcomes in stroke patients. [ABSTRACT FROM AUTHOR]