Pulmonary Function Tests Post-Stroke. Correlation between Lung Function, Severity of Stroke, and Improvement after Respiratory Muscle Training.

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.

Targeting Neutrophil Extracellular Traps for Stroke Prognosis: A Promising Path.

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.

From Admission to Discharge: Predicting National Institutes of Health Stroke Scale Progression in Stroke Patients Using Biomarkers and Explainable Machine Learning.

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.

Investigating the Predictive Value of Thyroid Hormone Levels for Stroke Prognosis.

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.

Leukoaraiosis as a Promising Biomarker of Stroke Recurrence among Stroke Survivors: A Systematic Review.

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.

Exploring the Utility of Autonomic Nervous System Evaluation for Stroke Prognosis.

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.

Exploring the Impact of Cerebral Microbleeds on Stroke Management.

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.

Monocyte to HDL and Neutrophil to HDL Ratios as Potential Ischemic Stroke Prognostic Biomarkers.

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.

Evaluation of Blood Biomarkers and Parameters for the Prediction of Stroke Survivors' Functional Outcome upon Discharge Utilizing Explainable Machine Learning.

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.

Copeptin Implementation on Stroke Prognosis.

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.

Stroke and Emerging Blood Biomarkers: A Clinical Prospective.

Stroke constitutes the primary source of adult functional disability, exhibiting a paramount socioeconomic burden. Thus, it is of great importance that the prediction of stroke outcome be both prompt and accurate. Although modern neuroimaging and neurophysiological techniques are accessible, easily available blood biomarkers reflecting underlying stroke-related pathophysiological processes, including glial and/or neuronal death, neuroendocrine responses, inflammation, increased oxidative stress, blood-brain barrier disruption, endothelial dysfunction, and hemostasis, are required in order to facilitate stroke prognosis. A literature search of two databases (MEDLINE and Science Direct) was conducted in order to trace all relevant studies published between 1 January 2010 and 31 December 2021 that focused on the clinical utility of brain natriuretic peptide, glial fibrillary acidic protein, the red cell distribution width, the neutrophil-to-lymphocyte ratio, matrix metalloproteinase-9, and aquaporin-4 as prognostic tools in stroke survivors. Only full-text articles published in English were included. Twenty-eight articles were identified and are included in this review. All studied blood-derived biomarkers proved to be valuable prognostic tools poststroke, the clinical implementation of which may accurately predict the survivors' functional outcomes, thus significantly enhancing the rehabilitation efficiency of stroke patients. Along with already utilized clinical, neurophysiological, and neuroimaging biomarkers, a blood-derived multi-biomarker panel is proposed as a reasonable approach to enhance the predictive power of stroke prognostic models.