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.

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.

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.

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.

The study aimed to identify predictors of 6-month outcomes in acute ischemic stroke (AIS) patients using the modified Rankin Scale (mRS). A prospective observational cohort study was conducted on 277 AIS patients admitted to the Neurology Departments of Cluj-Napoca Emergency County Clinical Hospital between December 2020 and July 2021. After excluding those lost to follow-up or who withdrew due to COVID-19 concerns, 121 patients were followed for six months. Data collected included demographic details, clinical assessments (including NIHSS and mRS scores), laboratory tests, and imaging results. The study found significant differences between patients with mild/moderate disability (mRS 0-3) and those with severe disability (mRS 4-5) at six months. Age, heart failure, NIHSS score, resistin levels, C-reactive protein, and lesion volume were significantly associated with worse outcomes. Multivariate logistic regression revealed that heart failure was an independent predictor of severe disability, increasing the risk by over seven times. Specific clinical and biochemical markers at admission may be able to predict long-term functional outcomes in AIS patients, which may inform individualized patient management and rehabilitation strategies.

Background and Objectives: The aim of this study was to evaluate the potential predictive value of VKORC1, CYP4F2, and GGCX polymorphisms, as well as other clinical and demographic factors, for 5-year mortality in patients with acute ischemic stroke (AIS). Materials and Methods: The study enrolled 252 patients who were consecutively hospitalized for AIS. Demographic data, comorbidities, and laboratory tests were collected. Genotyping of the VKORC1 rs9923231 (-1639G > A; VKORC1*2), CYP4F2 rs2108622 (1347C > T), and GGCX rs11676382 (12970C > G) polymorphisms was performed. Mortality was noted if it occurred within five years following the 30 days after discharge, using the National Health Insurance House registry. Results: Death was recorded in 71 (28.1%) patients. In multivariate analysis the following variables were independent variables associated with 5-year mortality: age > 72 years (OR 2.83 (95%CI 1.32; 6.08), p = 0.007), a lesion volume > 12.6 mL (OR 4.05 (95%CI 2.05; 7.99), p < 0.001), and an NIHSS score > 7 (OR—2.64 (95%CI 1.31; 5.31), p = 0.006). VKORC1 (-1639G > A) SNP m/m variant was only marginally associated with mortality. Conclusions: In this study which included AIS patients, VKORC1, CYP4F2, and GGCX polymorphisms did not independently predict mortality. The VKORC1 variant was only marginally associated with mortality, but this was attenuated after correction for multiple testing. Advanced age, NIHSS score, and the lesion volume were independent predictors of long-term mortality in AIS patients.