Development and Validation of a Predictive Score for Three-Year Mortality in Acute Ischemic Stroke Patients.

Background and Objectives: Acute ischemic stroke (AIS) is a leading cause of death and disability with poor long-term outcomes. Creating a predictive score for long-term mortality in AIS might be important for optimizing treatment strategies. The aim of this study is to develop and validate a predictive score for three-year mortality in patients with AIS using several demographic, clinical, laboratory and imaging parameters. Materials and Methods: This study included 244 AIS patients admitted to a tertiary center and followed up for three years. The patients' data included demographics, clinical features, laboratory tests (including resistin and leptin levels) and imaging parameters. The patients were randomly divided into a predictive group (n = 164) and a validation group (n = 80). Results: Advanced age, a high NIHSS score, low levels of hemoglobin, elevated resistin levels and the presence of carotid plaques were independently associated with three-year mortality. The predictive model incorporated these variables, and it was validated in a separate cohort. Leptin levels did not significantly predict mortality. Conclusions: This study developed and validated a promising predictive score for three-year mortality in patients with AIS. Advanced age, high NIHSS scores, low hemoglobin levels, elevated resistin levels and the presence of carotid plaques were the independent predictors of long-term mortality.

In Silico Decoding of Parkinson's: Speech & Writing Analysis.

Background: Parkinson's disease (PD) has transitioned from a rare condition in 1817 to the fastest-growing neurological disorder globally. The significant increase in cases from 2.5 million in 1990 to 6.1 million in 2016, coupled with predictions of a further doubling by 2040, underscores an impending healthcare challenge. This escalation aligns with global demographic shifts, including rising life expectancy and a growing global population. The economic impact, notably in the U.S., reached $51.9 billion in 2017, with projections suggesting a 46% increase by 2037, emphasizing the substantial socio-economic implications for both patients and caregivers. Coupled with a worldwide demand for health workers that is expected to rise to 80 million by 2030, we have fertile ground for a pandemic. Methods: Our transdisciplinary research focused on early PD detection through running speech and continuous handwriting analysis, incorporating medical, biomedical engineering, AI, and linguistic expertise. The cohort comprised 30 participants, including 20 PD patients at stages 1-4 on the Hoehn and Yahr scale and 10 healthy controls. We employed advanced AI techniques to analyze correlation plots generated from speech and handwriting features, aiming to identify prodromal PD biomarkers. Results: The study revealed distinct speech and handwriting patterns in PD patients compared to controls. Our ParkinsonNet model demonstrated high predictive accuracy, with F1 scores of 95.74% for speech and 96.72% for handwriting analyses. These findings highlight the potential of speech and handwriting as effective early biomarkers for PD. Conclusions: The integration of AI as a decision support system in analyzing speech and handwriting presents a promising approach for early PD detection. This methodology not only offers a novel diagnostic tool but also contributes to the broader understanding of PD's early manifestations. Further research is required to validate these findings in larger, diverse cohorts and to integrate these tools into clinical practice for timely PD pre-diagnosis and management.

Decoding visual evoked potential latency: revealing neurological connections in Parkinson's disease.

Parkinson's disease (PD) is a complex neurodegenerative disorder characterized by diverse motor and non-motor symptoms. Visual evoked potentials (VEPs) provide valuable insights into the neurological changes in PD. This study examines VEP latency to explore potential connections between visual processing and PD progression, focusing on whether inter-eye latency differences are influenced by disease severity and symptomatology. A cross-sectional observational study was conducted with 59 PD patients at the Neurology I Clinic, Cluj-Napoca County Emergency Clinical Hospital, from October 2019 to October 2021. Patients underwent neurological and psychological evaluations, including VEP testing with a reversal pattern technique. P100 wave latency was assessed for both eyes, and associations with clinical indicators like Hoehn and Yahr stages, UPDRS scores, and non-motor symptoms were analyzed. VEP latencies for the right and left eyes were 108.7 ± 10.6 ms and 108.4 ± 9.7 ms, respectively, with no significant inter-eye differences (P = 0.8). UPDRS item 4 scores correlated significantly with both latencies (P = 0.003 for the left eye and P <0.001 for the right). Latency differences between eyes were shorter in patients with symmetrical parkinsonism compared to those with unilateral predominance. Age correlated weakly with P100 latency, and a weak correlation was found between anhedonia scores and right-eye latency. VEP latency is sensitive to PD motor severity, with shorter inter-eye latency differences in symmetrical parkinsonism, suggesting balanced dopaminergic dysfunction. VEP latency differences offer insights into neurophysiological changes in PD, reflecting dopaminergic dysfunction and its impact on visual processing. These findings support the potential of VEPs as diagnostic and prognostic tools in PD assessment.

Resistin and In-Hospital Mortality in Patients with Acute Ischemic Stroke: A Prospective Study.

Background/Objectives: Understanding the prognostic factors of acute ischemic stroke (AIS) is essential for improving patient outcomes. The aim of this study was to establish the predictive role of plasmatic resistin and leptin on short-term mortality in adult patients with a first episode of AIS. Methods: This study enrolled 277 patients who were consecutively hospitalized for AIS. Demographic data, cardiovascular risk, comorbidities, and laboratory tests were collected. Death was noted if it occurred during hospitalization. Results: Death was recorded in 33 (11.9%) patients. Conducting multivariate analysis, the following variables were independent variables associated with in-hospital mortality: a resistin value of >11 ng/mL (OR 10.81 (95%CI 2.31;50.57), p = 0.002), a lesion volume of >18.8 mL (OR 4.87 (95%CI 1.87;12.67), p = 0.001), a NIHSS score of >7 (OR 5.88 (95%CI 2.01;17.16), p = 0.001), and the presence of IHD (OR 4.33 (95%CI 1.66;11.27), p = 0.003). This study has some limitations: single-center design (which may affect the generalizability of the results) and the potential impact of the COVID-19 pandemic on patient outcomes. Conclusions: This study demonstrated that resistin is a significant predictor of in-hospital mortality in AIS patients. Other established factors, such as a high NIHSS score, large lesion volume, and the presence of IHD, were reaffirmed as important predictors.

Association among VKORC1 rs9923231, CYP4F2 rs2108622, GGCX rs11676382 polymorphisms and acute ischemic stroke.

Acute ischemic stroke is a major cause of morbidity and mortality worldwide, and genetic factors play a role in the risk of stroke. Single nucleotide polymorphisms (SNPs) in the VKORC1, CYP4F2, and GGCX genes have been linked to clinical outcomes, such as bleeding and cardiovascular diseases. This study aimed to investigate the association between specific polymorphisms in these genes and the risk of developing the first episode of acute ischemic stroke in patients without a known embolic source. This retrospective, cross-sectional, observational, analytical, case-control study included adult patients diagnosed with acute ischemic stroke. The SNPs in VKORC1 rs9923231, CYP4F2 rs2108622, GGCX rs11676382 genes were genotyped and analyzed together with the demographic and clinical factors of the 2 groups of patients. The presence of SNPs in VKORC1 or CYP4F2 genes significantly increased the risk of ischemic stroke in the context of smoking, arterial hypertension, and carotid plaque burden. The multivariate logistic model revealed that smoking (odds ratio [OR] = 3.920; P < .001), the presence of carotid plaques (OR = 2.661; P < .001) and low-density lipoprotein cholesterol values >77 mg/dL (OR = 2.574; P < .001) were independently associated with stroke. Polymorphisms in the VKORC1 and CYP4F2 genes may increase the risk of ischemic stroke in patients without a determined embolic source. Smoking, the presence of carotid plaques, and high low-density lipoprotein cholesterol levels were reconfirmed as important factors associated with ischemic stroke.

CNN-Based Identification of Parkinson's Disease from Continuous Speech in Noisy Environments.

Parkinson's disease is a progressive neurodegenerative disorder caused by dopaminergic neuron degeneration. Parkinsonian speech impairment is one of the earliest presentations of the disease and, along with tremor, is suitable for pre-diagnosis. It is defined by hypokinetic dysarthria and accounts for respiratory, phonatory, articulatory, and prosodic manifestations. The topic of this article targets artificial-intelligence-based identification of Parkinson's disease from continuous speech recorded in a noisy environment. The novelty of this work is twofold. First, the proposed assessment workflow performed speech analysis on samples of continuous speech. Second, we analyzed and quantified Wiener filter applicability for speech denoising in the context of Parkinsonian speech identification. We argue that the Parkinsonian features of loudness, intonation, phonation, prosody, and articulation are contained in the speech, speech energy, and Mel spectrograms. Thus, the proposed workflow follows a feature-based speech assessment to determine the feature variation ranges, followed by speech classification using convolutional neural networks. We report the best classification accuracies of 96% on speech energy, 93% on speech, and 92% on Mel spectrograms. We conclude that the Wiener filter improves both feature-based analysis and convolutional-neural-network-based classification performances.

Parkinson's disease and cardiovascular involvement: Edifying insights (Review).

Parkinson's disease (PD) is one of the most common neurodegenerative illnesses, and is a major healthcare burden with prodigious consequences on life-quality, morbidity, and survival. Cardiovascular diseases are the leading cause of mortality worldwide and growing evidence frequently reports their co-existence with PD. Cardiac dysautonomia due to autonomic nervous system malfunction is the most prevalent type of cardiovascular manifestation in these patients, comprising orthostatic and postprandial hypotension, along with supine and postural hypertension. Moreover, many studies have endorsed the risk of patients with PD to develop ischemic heart disease, heart failure and even arrhythmias, but the underlying mechanisms are not entirely clear. As importantly, the medication used in treating PD, such as levodopa, dopamine agonists or anticholinergic agents, is also responsible for cardiovascular adverse reactions, but further studies are required to elucidate the underlying mechanisms. The purpose of this review was to provide a comprehensive overview of current available data regarding the overlapping cardiovascular disease in patients with PD.

An overview of the visual dysfunctions in Parkinson's disease - Update from a prospective study in Transylvania.

Being a highly prevalent neurodegenerative disorder worldwide, Parkinson's disease (PD) shows its complexity not only in the variability of its pathology, but also in the complex constellation of its clinical picture. PD does not affect only the nervous system; instead, it is today recognized as having both motor and non-motor features. The purpose of this article is to report up-to-date information of an ongoing study, which correlates the motor features of Parkinson's disease (PD) with the visual disturbances (non-motor features) related to this disease. Abbreviations: PD = Parkinson's disease, HY = Hoehn-Yahr scale, MMSE = Mini-Mental state exam, UPDRS = Unified Parkinson's disease rating scale, RE = right eye, LE = left eye.

Evaluation of post-traumatic stress disorder (PTSD) and related comorbidities in clinical studies.

Patients with traumatic brain injury (TBI) of varying severities are experiencing adverse outcomes during and after rehabilitation. Besides depression and anxiety, post-traumatic stress disorder (PTSD) is highly encountered in civilian and military populations. As more prospective and retrospective studies - focused on evaluating new or old psychological therapies in inpatient, outpatient, or controlled environments, targeting patients with PTSD with or without a history of TBI - are carried out, researchers are employing various scales to measure PTSD as well as other psychiatric diagnoses or cognitive impairments that might appear following TBI. We aimed to explore the literature published between January 2010 and October 2021 by querying three databases. Our preliminary results showed that several scales - such as the Clinician-Administered PTSD Scale (CAPS), the Posttraumatic Stress Disorder Checklist Military Version (PCL-M) as well as Specific Version (PCL-S), and Civilian Version (PCL-C) - have been frequently used for PTSD diagnosis and symptom severity. However, heterogeneity in the scales used when assessing and evaluating additional psychiatric comorbidities and cognitive impairments are due to the study aim and therapeutic approaches. Therefore, conducting an intervention focusing on post-TBI PTSD patients requires increased attention to patients' medical history in capturing multiple cognitive impairments and affected neuropsychological processes when designing the study and including validated instruments for measuring primary and secondary neuropsychological outcomes.

The Effect of Cerebrolysin on Anxiety, Depression, and Cognition in Moderate and Severe Traumatic Brain Injury Patients: A CAPTAIN II Retrospective Trial Analysis.

Background and Objectives: Traumatic brain injuries represent an important source of disease burden requiring emergency inpatient care and continuous outpatient tailored rehabilitation. Although most TBIs are mild, patients are still developing post-TBI depression, anxiety, and cognitive impairments. Our secondary retrospective trial analysis aimed to (1) analyze correlations between HADS-Anxiety/HADS-Depression and scales that measure cognitive and motor processes in patients treated with Cerebrolysin compared to the placebo group and (2) compare anxiety and depression scores among the two treatment groups. Materials and Methods: Our secondary retrospective analysis focused on TBI patients with moderate and severe disability divided into two groups: Cerebrolysin (treatment) and saline solution (procedural placebo). We analyzed data from 125 patients. We computed descriptive statistics for nominal and continuous variables. We used Spearman's correlation to find associations between HADS and other neuropsychological scales and the Mann-Whitney U test to compare HADS-Anxiety and HADS-Depression scores among the two study arms. Results: Our sample consisted of patients with a mean age of 45.3, primarily men, and with a 24 h GCS (Glasgow Coma Scale) mean of 12.67. We obtained statistically significant differences for HADS-Anxiety during the second and third visits for patients treated with Cerebrolysin. Our results show that Cerebrolysin has a large effect size (0.73) on anxiety levels. In addition, there are positive and negative correlations between HADS-Anxiety and Depression subscales and other neuropsychological scales. Conclusions: Our secondary database analysis supports the existing body of evidence on the positive effect of Cerebrolysin on post-TBI mental health status. Future confirmatory trials are necessary to clarify the link between the intervention and measured outcomes.

Proof of Concept in Artificial-Intelligence-Based Wearable Gait Monitoring for Parkinson's Disease Management Optimization.

Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder, affecting 6.2 million patients and causing disability and decreased quality of life. The research is oriented nowadays toward artificial intelligence (AI)-based wearables for early diagnosis and long-term PD monitoring. Our primary objective is the monitoring and assessment of gait in PD patients. We propose a wearable physiograph for qualitative and quantitative gait assessment, which performs bilateral tracking of the foot biomechanics and unilateral tracking of arm balance. Gait patterns are assessed by means of correlation. The surface plot of a correlation coefficient matrix, generated from the recorded signals, is classified using convolutional neural networks into physiological or PD-specific gait. The novelty is given by the proposed AI-based decisional support procedure for gait assessment. A proof of concept of the proposed physiograph is validated in a clinical environment on five patients and five healthy controls, proving to be a feasible solution for ubiquitous gait monitoring and assessment in PD. PD management demonstrates the complexity of the human body. A platform empowering multidisciplinary, AI-evidence-based decision support assessments for optimal dosing between drug and non-drug therapy could lay the foundation for affordable precision medicine.

Admission Emergency Department Point-of-care Biomarkers for Prediction of Early Mortality in Spontaneous Intracerebral Hemorrhage.

BACKGROUND/AIM: Spontaneous intracerebral hemorrhage (sICH) has a significant morbidity and mortality, despite representing a non-dominant hemorrhagic stroke. The aim of the study was to assess the impact of the emergency department (ED) point-of-care (POC) biomarkers on early mortality in sICH patients. PATIENTS AND METHODS: Demographic data, medical history and admission clinical parameters from adult patients with imaging-based sICH diagnosis were collected retrospectively, upon their ED presentation over a period of 18 months. ED-based POC analyzers were used for blood biomarkers [complete blood count, C reactive protein (CRP), glycemia, hepatic and renal function, D-dimer and cardiac troponin I]. Derived inflammatory indexes were calculated. Mortality endpoints were collected (on day 7 and at discharge). RESULTS: Of the 219 included patients, mortality rates reached 30.14% on day 7 and 46.12% at discharge. In the univariate analysis, day 7 mortality was significantly associated with history of diabetes, atrial fibrillation, ongoing anticoagulant treatment, the need of endotracheal intubation and ED cardiopulmonary resuscitation, and the presence of intraventricular hemorrhage and mass effect on the initial CT scan. White blood cells and granulocytes (but not the neutrophil-to-lymphocytes ratio, nor the CRP) were significantly higher in the deceased groups, alongside serum glucose. Derived inflammatory indexes were not significantly correlated with mortality endpoints. Cut-off values of 9.6×109/l for granulocytes and 132 mg/dl for glucose were identified as day 7 mortality predictors. CONCLUSION: sICH is a potentially severe condition causing high early mortality. Emergency department point-of-care biomarkers could represent a readily available and simple to use prognostic tool.

Emergency department point-of-care biomarkers and day 90 functional outcome in spontaneous intracerebral hemorrhage: A single-center pilot study.

Spontaneous intracerebral hemorrhage (sICH) results in high morbidity and mortality rates, thus identifying strategies for timely prognosis and treatment is important. The present study aimed to analyze the relationship between emergency department point-of-care (POC) blood biomarkers and day 90 functional outcome (FO) in patients with acute (<8 h) sICH. On-site POC determinations, including complete blood count, glucose, cardiac troponin I, D-dimer and C-reactive protein, and derived inflammatory indexes were performed for a cohort of 35 patients. The primary endpoint was a favorable day 90 FO (modified Rankin Score ≤3). Secondary endpoints included early neurological worsening (ENW), day 7/discharge neurological impairment, day 90 independence assessment (Barthel Index <60), hematoma enlargement and perihematomal edema (PHE) growth. A favorable three-month FO was reported in 16 (46%) participants. Older age, previous history of ischemic stroke and initial imagistic parameters, including intraventricular hemorrhage, enlarged contralateral ventricle and cerebral atrophy, significantly predicted an unfavorable FO. The admission D-dimer similarly predicted day 90 FO and the independence status, along with ENW and a more severe day 7/discharge neurological status. The D-dimer also correlated with the initial neurological status and PHE. PHE growth correlated with granulocytes, systemic immune-inflammation index and glycemia. The results suggested that a lower admission D-dimer could indicate an improved day 90 FO of patients with sICH, while also anticipating the development of PHE growth and ENW.

Artificial intelligence applications and robotic systems in Parkinson's disease (Review).

Parkinson's disease (PD) is the second most frequent neurodegenerative disorder following Alzheimer's disease. Advanced stages of PD, 4 or 5 of the Hoehn and Yahr Scale, are characterized by severe motor complications, limited mobility without assistance, risk of falling, and non-motor complications. The aim of this review was to provide a practical overview on specific artificial intelligence (AI) systems for the management of advanced stages of PD, as well as relevant technological limitations. The authors conducted a systematic search on PubMed and EMBASE with predefined keywords searching for studies published until December 2020. Full articles that satisfied the inclusion criteria were included in the systematic review. To minimize results bias, the reference list was manually searched for pertinent articles to identify any additional relevant missed publications. Exclusion criteria included the following: Other stages of PD than 4 and 5 of the Hoehn and Yahr Scale, case reports, reviews, practice guidelines, commentaries, opinions, letters, editorials, short surveys, articles in press, conference abstracts, conference papers, and abstracts published without a full article. The search identified 21 studies analyzing AI-based applications and robotic systems used for the management of advanced stages of PD, out of which 6 articles analyzed AI-based applications for autonomous management of pharmacologic therapy, 5 articles analyzed home-based telemedicine systems and 10 articles analysed robot-assisted gait training systems. The authors identified significant evidence demonstrating that current AI-based technologies are feasible for automatic management of patients with advanced stages of PD. Improving the quality of care and reducing the cost for patients and healthcare systems are the most important advantages.

Circumpapillary Retinal Nerve Fiber Layer OCT Imaging in a Parkinson's Disease Cohort-A Multidisciplinary Approach in a Clinical Research Hospital.

(1) Background: The purpose of this paper is to report the data of the first study in a Clinical Research Hospital, in the Transylvania region, focusing on the Spectral Domain Optical Coherence Tomography (SD-OCT) measurements in the early stages of Parkinson's disease (PD), and to compare the results with age-matched healthy controls. (2) Methods: This study assessed the circumpapillary retinal nerve fiber layer (cpRNFL) SD-OCT measurements (Heidelberg Spectralis, Heidelberg Engineering, Germany) of two study groups: patients suffering from PD (Hoehn-Yahr stages 1-3) and healthy controls. Secondary objectives were to investigate the reported visual symptoms by evaluating the color vision, contrast sensitivity, and the central visual defects for macular disease using standardized charts. Subjects with prior history of ophthalmologic diseases, advanced stages of PD (Hoehn-Yahr stages 4-5), or with psychiatric conditions were not included in this study. The same team of neurologists and ophthalmologists evaluated all individuals in order to have comparable data and to eliminate inter-examiner differences. All subjects were recruited from the same Clinical Research Hospital in the Transylvania region, Romania. (3) Results: 72% of the PD patients (n = 17) in this study reported visual symptoms. In respect to the ophthalmologic chart evaluation for PD patients, the most frequent disturbances were identified in the Ishihara color perception testing (33%). The regression analysis showed significant results for the Ishihara testing in relation to the cpRNFL thinning in the temporal retinal sectors for both eyes. cpRNFL thinning was predominantly contralateral to the parkinsonism (p = 0.001). The temporal and global values of the cpRNFL were significantly lower in all PD patients < 70 years old, compared to the age-matched healthy controls. (4) Conclusions: Specific patterns of cpRNFL thinning were found in the PD subjects younger than 70 years. A multidisciplinary approach is essential for a complete evaluation of PD patients.

Nursing procedures for advanced dementia: Traditional techniques versus autonomous robotic applications (Review).

The purpose of this study was to perform a comparative analysis of traditional nursing techniques and autonomous robotic applications used for managing patients with advanced stages of dementia. PubMed, Cochrane Library, EMBASE, and WILEY databases were searched for relevant articles concerning nursing techniques applied in the treatment of patients with advanced dementia. The search terms included: (advanced dementia OR severe dementia) AND [artificial intelligence (AI) OR robotic OR robots OR neural networks OR deep learning OR automated procedures OR autonomous application]. This search identified a total of 2,679 articles and 298 articles were selected. Finally, 23 articles were included in this systematic review, out of which 8 studies analyzed traditional nursing techniques and 15 studies analyzed autonomous robotic applications. Significant evidence was revealed, demonstrating that autonomous robotic applications used for patients with advanced stages of dementia are a feasible, cost-efficient solution and represent an excellent benefit for patients and the healthcare system.

Feasibility of a pilot study on point-of-care biomarkers in spontaneous intracerebral hemorrhage in an emergency setting.

BACKGROUND AND AIMS: Stroke is a worldwide leading cause of death and disability and spontaneous intracerebral hemorrhage (sICH) has significant economic and social impact, regardless of recent efforts towards outcome-bettering acute interventions. The aim of the study was to assess the feasibility of a prospective observational research regarding point-of-care (POC) biomarkers in sICH, conducted in a level one emergency department (ED). METHODS: Patients with acute (<8 hours) sICH were enrolled in this study. Patients presenting a Glasgow Coma Scale score <8, secondary causes of intracerebral hemorrhage, seizures, recent ischemic events, known thromboembolic disease, anticoagulant treatment, severe pre-stroke disability, terminal disease, scheduled neurosurgery/hemostatic treatment were excluded. Feasibility was defined as ED inclusion and follow-up rates, time-to-inclusion, and frequency of missing data. Baseline demographic, imaging and POC biochemical status of the study group were documented, including inflammatory (complete blood count, C-reactive protein), metabolic (glucose, hepatic, and renal function) and cardiovascular markers (cardiac troponin I, D-dimer). RESULTS: The inclusion rate was 2.16 patients/month with a final sample of 35 patients out of 239 potentially eligible patients. The median time from symptom onset to ED presentation was 128 minutes (IQR 96-239), with 21/35 patients having presented within the first 3 hours from ictus. Median times between symptoms' onset to Computer Tomography (CT) scan and ED presentation to CT scan were 170 minutes (IQR 126-317) and 25 minutes (IQR 17-62), respectively. The median time from patient's presentation to CBC result was 12 minutes (IQR 6.5-20), with 21/35 study participants having the results available within 15 minutes from ED arrival. The median cohort age was 72-years, with a 19/16 male/female ratio. Hypertension was the most frequent risk factor (77%), along with ischemic heart disease (31%) and diabetes (29%). One-third of the hypertensive patients did not undergo blood pressure lowering treatment. Median values of POC biomarkers on ED admission were within normal range. CONCLUSIONS: It was feasible to determine point-of-care biomarkers in spontaneous intracerebral hemorrhage on admission in ED, despite the urgency of the medical condition.

Implications of Circadian Rhythm in Stroke Occurrence: Certainties and Possibilities.

Stroke occurrence is not randomly distributed over time but has circadian rhythmicity with the highest frequency of onset in the morning hours. This specific temporal pattern is valid for all subtypes of cerebral infarction and intracerebral hemorrhage. It also correlates with the circadian variation of some exogenous factors such as orthostatic changes, physical activity, sleep-awake cycle, as well as with endogenous factors including dipping patterns of blood pressure, or morning prothrombotic and hypofibrinolytic states with underlying cyclic changes in the autonomous system and humoral activity. Since the internal clock is responsible for these circadian biological changes, its disruption may increase the risk of stroke occurrence and influence neuronal susceptibility to injury and neurorehabilitation. This review aims to summarize the literature data on the circadian variation of cerebrovascular events according to physiological, cellular, and molecular circadian changes, to survey the available information on the chronotherapy and chronoprophylaxis of stroke and its risk factors, as well as to discuss the less reviewed impact of the circadian rhythm in stroke onset on patient outcome and functional status after stroke.

Apathy and Anhedonia: Clinical and Neurophysiological Assessment of a Romanian Cohort.

BACKGROUND: Patients with Parkinson's disease (PD) often have, besides the characteristic motor manifestations, a wide variety of non-motor symptoms. These include apathy and anhedonia, common issues in PD, which can be quantified with the help of evaluation scales recommended by the literature. There are sensory non-motor manifestations of PD, some of which are easy to detect through electrophysiological studies. Our aim was to investigate the possible association of apathy and anhedonia with the severity of the motor status in a sample of PD patients in Romania. We also examined the prevalence of latency changes in the P100 wave of visual evoked potentials (VEPs) and how they correlated with motor status, apathy, and anhedonia in PD patients. METHODS: Thirty-four patients with PD participated in this study. All were assessed for motor status using the Unified Parkinson's Disease Rating Scale (UPDRS) and were rated on the Hoehn and Yahr scales. The presence and severity of apathy and anhedonia were assessed using the Apathy Evaluation Scale (AES), the Dimensional Apathy Scale (DAS), the Lille Apathy Rating Scale (LARS), and the Snaith-Hamilton Pleasure Scale (SHAPS). The latency of the P100 wave of the VEP was measured in all the patients. RESULTS: Apathy and anhedonia were common among the patients with PD (35% and 58.8%, respectively). The presence of apathy/anhedonia was correlated with the severity of motor symptoms, as assessed using the UPDRS scale (p < 0.001), and with the stage of the disease according to the Hoehn and Yahr scale (p < 0.001). A prolonged latency of the P100 wave of the VEP was observed among apathetic (p < 0.001)/anhedonic (p < 0.01) patients and those with increased disease severity (p < 0.001). CONCLUSION: Apathy and anhedonia are common in PD and may correlate with the severity of motor symptoms. There may be visual impairment in these patients, evidenced by a prolonged P100 latency, which correlates with the severity of disease. SIGNIFICANCE: Scales for assessing apathy and anhedonia, as well as measuring VEP latency, could be useful in assessing the severity of disease.

Life-threatening complications of hyperemesis gravidarum.

Hyperemesis gravidarum (HG) refers to severe nausea and emesis noted during pregnancy. However, no consensus exists on the specific diagnostic criteria that can be used for this condition. The aim of the present systematic review was to summarize the available evidence regarding the severe complications observed during HG with a heightened risk of fatality. A systematic search was conducted on PubMed, Cochrane Library, EMBASE and WILEY databases for the relevant publications regarding the severe and life-threatening complications of HG. The search terms were as follows: '(Hyperemesis gravidarum)' AND ('complications' OR 'severe' OR 'adverse pregnancy outcomes' OR 'stroke' OR 'seizures' OR 'Wernicke's encephalopathy' OR 'arrhythmias' OR 'pneumomediastinum' OR 'coagulopathy' OR 'electrolytic imbalance'). Abstracts, conference presentations, letters to the editor, studies written in languages other than English and editorials were all excluded. This search identified 43 studies analyzing life-threatening complications of HG, of which 11, seven, eight and 17 articles analyzed neurological, cardiovascular, thoracic and systemic complications, respectively. Reports on life-threatening complications were exceptionally rare in HG. The most frequent severe complications noted were Wernicke's encephalopathy, electrolyte imbalance and vitamin K deficiency. The low mortality rate for patients with HG over the last decade could be explained by the high efficiency of modern therapy, and the precise management of every complication according to current guidelines.