Serum Albumin and Risks of Stroke and Its Subtypes - The Circulatory Risk in Communities Study (CIRCS)

A Retrospective Analysis of Central and Peripheral Metabolic Characteristics in Patients with Cryptococcal Meningitis

INTRODUCTION

Most current treatment strategies and investigations on cryptococcal meningitis (CM) focus primarily on the central nervous system (CNS), often overlooking the complex interplay between the CNS and the peripheral system. This study aims to explore the characteristics of central and peripheral metabolism in patients with CM.

METHODS

Patients diagnosed with CM as per the hospital records of the Fourth People's Hospital of Nanning were retrospectively analyzed. Patients were divided into two groups, non-structural damage of the brain (NSDB) and structural damage of the brain (SDB), according to the presence of brain lesions as detected with imaging. Based on the presence of enlarged cerebral ventricles, the cases in the SDB group were classified into non-ventriculomegaly (NVM) and ventriculomegaly (VM). Various parameters of cerebrospinal fluid (CSF) and peripheral blood (PB) were analyzed.

RESULTS

A significant correlation was detected between CSF and PB parameters. The levels of CSF-adenosine dehydrogenase (ADA), CSF-protein, CSF-glucose, and CSF-chloride ions were significantly correlated with the levels of PB-aminotransferase, PB-bilirubin, PB-creatinine (Cr), PB-urea nitrogen, PB-electrolyte, PB-protein, and PB-lipid. Compared with NSDB, the levels of CSF-glucose were significantly decreased in the SDB group, while the levels of CSF-lactate dehydrogenase (LDH) and CSF-protein were significantly increased in the SDB group. In the SDB group, the levels of PB-potassium, PB-hemoglobin(Hb), and PB-albumin were significantly decreased in the patients with VM, while the level of PB-urea nitrogen was significantly increased in these patients.

CONCLUSION

Metabolic and structural alterations in the brain may be associated with peripheral metabolic changes.

Association between advanced lung cancer inflammation index and all-cause and cardiovascular mortality among stroke patients: NHANES, 1999-2018

Background

Stroke was a major global public health challenge, and its prognosis was remarkably associated with inflammation levels and nutritional status. The advanced lung cancer inflammation index (ALI) was a comprehensive indicator that combined inflammation and nutritional status. Currently, the relationship between ALI and the prognosis of stroke patients was not yet known. The purpose of the current study was to estimate their relationship.

Methods

Cohort data from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 were collected. The association between ALI and all-cause and cardiovascular disease (CVD) mortality in stroke patients was estimated using a multivariable adjusted Cox model. Their non-linear relationship was analyzed by restricted cubic spline analysis. Sensitivity analysis was constructed through stratified analysis and interaction analysis.

Results

1,440 stroke patients were included in this study. An elevated ALI was significantly related to a reduced risk of all-cause mortality in stroke patients but not related to CVD mortality. A reverse J-shaped non-linear association between ALI and all-cause mortality in stroke patients, with an inflection point at 83.76 (the lowest of the mortality risk). On the left side of the inflection point, for each 10 U increase in ALI, there was a 16% reduction in the risk of all-cause mortality. However, on the right side, the risk increased by 6%. There was no remarkable interaction between stratified variables and ALI.

Conclusion

This was the first study on the relationship between ALI and all-cause and CVD mortality in stroke patients. Elevated ALI was closely associated with a reduced risk of all-cause mortality. A reverse J-shaped non-linear relationship existed between the two, with an inflection point at 83.76. These findings implied that controlling the ALI of stroke patients within an appropriate range was crucial for their prognosis (such as weight management, albumin supplementation, anti-inflammatory treatment). The dynamic variation in ALI was also advantageous for clinicians in establishing personalized ALI criteria to maximize the long-term survival of stroke patients.

Prediction of atrial fibrillation and stroke using machine learning models in UK Biobank

Objective

Atrial fibrillation (AF) is the most common cardiac arrythmia, and it is associated with increased risk for ischemic stroke, which is underestimated, as AF can be asymptomatic. The aim of this study was to develop optimal ML models for prediction of AF in the population, and secondly for ischemic stroke in AF patients.

Methods

To develop ML models for prediction of 1) AF in the general population and 2) ischemic stroke in patients with AF we constructed XGBoost, LightGBM, Random Forest, Deep Neural Network, Support Vector Machine and Lasso penalised logistic regression models using UK-Biobank's extensive real-world clinical data, questionnaires, as well as biochemical and genetic data, and their predictive performances were compared. Ranking and contribution of the different features was assessed by SHapley Additive exPlanations (SHAP) analysis. The clinical tool CHA2DS2-VASc for prediction of ischemic stroke among AF patients, was used for comparison to the best performing ML model.

Findings

The best performing model for AF prediction was LightGBM, with an area-under-the-roc-curve (AUROC) of 0.729 (95% confidence intervals (CI): 0.719, 0.738). The best performing model for ischemic stroke prediction in AF patients was XGBoost with AUROC of 0.631 (95% CI: 0.604, 0.657). The improved AUROC in the XGBoost model compared to CHA2DS2-VASc was statistically significant based on DeLong's test (p-value = 2.20E-06). In addition, the SHAP analysis showed that several peripheral blood biomarkers (e.g. creatinine, glycated haemoglobin, monocytes) were associated with ischemic stroke, which are not considered by CHA2DS2-VASc.

Implications

The best performing ML models presented have the potential for clinical use, but further validation in independent studies is required. Our results endorse the incorporation of some routinely measured blood biomarkers for ischemic stroke prediction in AF patients.

Acute albumin administration as therapy for intracerebral hemorrhage: A literature review

Intracerebral hemorrhage (ICH) is a subtype of stroke with high mortality. Secondary brain injury after surviving the initial ictus leads to severe neurological deficits, and has emerged as an attractive therapeutic target. Human serum albumin (HSA), a pluripotent protein synthesized mainly in the liver, has shown remarkable efficacy by targeting secondary brain injury pathways in rodent models of ICH, while results from relevant clinical research on albumin therapy remain unclear. Preclinical studies have shown albumin-mediated neuroprotection may stem from its biological functions, including its major antioxidation activity, anti-inflammatory responses, and anti-apoptosis. HSA treatment provides neuroprotective and recovery enhancement effects via improving short and long-term neurologic function, maintaining blood-brain barrier (BBB) integrity and reducing neuronal oxidative stress and apoptosis. Retrospective clinical studies have shown that admission hypoalbuminemia is a prognostic factor for poor outcomes in patients with ICH. However, clinical trial was terminated due to poor enrollment and its potential adverse effects. This review provides an overview of the physiological properties of albumin, as well as its potential neuroprotective and prognostic value and the resulting clinical implications.

Fibrinogen-to-Albumin Ratio and Clinical Outcomes in Patients With Large Artery Atherosclerosis Stroke

BACKGROUND

A high fibrinogen-to-albumin ratio (FAR), a novel inflammatory marker, is considered to be a prognostic marker in vascular diseases. However, the association of FAR with large artery atherosclerosis (LAA) stroke is still unknown. This study was conducted to evaluate the association between FAR levels and clinical outcomes in patients with acute LAA stroke.

METHODS AND RESULTS

A total of 809 patients within 72 hours of LAA stroke were included and followed up to 1 year. FAR was calculated as fibrinogen (g/L)/albumin (g/L). The associations of FAR with clinical outcomes were assessed by multivariate Cox regression or logistic regression analysis. Clinical outcomes included stroke recurrence, all-cause death, poor functional outcome (modified Rankin Scale score 3-6), and dependence (modified Rankin Scale score 3-5). Among the 809 patients with acute LAA stroke, the median FAR was 0.075 (interquartile range, 0.064-0.087). At 1 year, 103 (12.7%) patients had stroke recurrence, 105 (13.0%) had poor functional outcome, 76 (9.8%) had dependence, and 29 (3.6%) had died. After adjusting for all confounding risk factors, a high FAR level was associated with stroke recurrence (hazard ratio, 2.57 [95% CI, 1.32-5.02]), poor functional outcome (odds ratio, 3.30 [95% CI, 1.57-6.94]), and dependence (odds ratio, 3.49 [95% CI, 1.49-8.19]).

CONCLUSIONS

A high FAR level was associated with an increased risk of stroke recurrence, poor functional outcome, and dependence in patients with acute LAA stroke.

Association of serum albumin levels and stroke risk in adults over 40 years: A population-based study

This study assessed the relationship between serum albumin levels and adult stroke risk. From the 2009 to 2018 National Health and Nutrition Examination Survey, we performed a cross-sectional study with 17,303 participants who were 40 years of age or higher. A multivariate logistic regression model investigated serum albumin levels and stroke. To investigate apparent nonlinear connections, smoothed curve fitting was used. When a nonlinear relationship was discovered, the inflection point was determined using a recursive method. Serum albumin levels were significantly and inversely linked with the risk of stroke after controlling for possible variables [odds ratio 0.02, 95% confidence interval (0.00, 0.18), P = .0003]. An examination of subgroups revealed that the inverse relationship between serum albumin levels and risk of stroke was statistically significant in men, participants under 60 years old, non-diabetic participants, and hypertensive participants. Serum albumin levels and the risk of stroke were negatively correlated. An increased risk of stroke was linked to lower serum albumin levels.

Nutritional and inflammatory peripheral blood markers for risk assessment of chronic subdural hematoma: a case-control study

BACKGROUND

Some peripheral blood markers have been demonstrated to be correlated with the re-formation of chronic subdural hematoma (CSDH). The aim of this study was to identify the correlation between nutritional/inflammatory peripheral blood markers and CSDH.

METHODS

188 CSDH patients and 188 age-matched healthy controls were included in this research. The clinical characteristics and peripheral blood markers associated with nutritional or inflammatory status were obtained and analyzed. Conditional logistic regression analysis was applied to identify the potential CSDH risk factors. All the participants were divided into 3 groups based on the tertiles of change in risk factors. The Cochran-Armitage test and one way ANOVA were applied to identify the association between baseline characteristics and independent risk factors. Moreover, the net reclassification index (NRI) and integrated discrimination index (IDI) were calculated to evaluate the improvement in model performance after adding the independent risk factors in the conventional model.

RESULTS

The logistic regression analysis demonstrated that the increased albumin (OR, 0.615; 95 %CI,0.489-0.773; P < 0.001) and lymphocyte count (OR, 0.141; 95 %CI,0.025-0.796; P = 0.027) were associated with lower risk of CSDH. Moreover, addition of albumin and lymphocyte to conventional risk factors significantly improved the risk prediction of CSDH(NRI: 46.47 %, P < 0.001; IDI: 30.92 %, P < 0.001; NRI: 22.45 %, P = 0.027; IDI: 1.23 %, P = 0.037, respectively) CONCLUSION: The decreased albumin and lymphocyte levels were correlated with a high risk of chronic subdural hematoma. The nutritional and inflammatory serum markers should be put great attention because these markers may play roles in finding the cause of CSDH and predicting its risk.

Prognostic value of inflammation biomarkers for 30-day mortality in critically ill patients with stroke

Objective

To explore the values of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), neutrophil to albumin ratio (NAR), prognostic nutritional index (PNI), systemic immune inflammatory index (SII) and red cell distribution width to albumin ratio (RA) for evaluating the risk of 30-day mortality of ischemic stroke or hemorrhagic stroke patients.

Methods

In this cohort study, the data of 1,601 patients diagnosed with stroke were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Among them, 908 were hemorrhagic stroke patients and 693 were ischemic stroke patients. Demographic and clinical variables of patients were collected. Univariate and multivariable Cox regression were performed to evaluate the predictive values of NLR, PLR, SII, NAR, RA, and PNI for 30-day mortality in hemorrhagic stroke or ischemic stroke patients. The receiver operator characteristic (ROC) curves were plotted to assess the predictive values of NLR, NAR, and RA for 30-day mortality of hemorrhagic stroke patients.

Results

At the end of follow-up, 226 hemorrhagic stroke patients and 216 ischemic stroke patients died. The elevated NLR level was associated with increased risk of 30-day mortality in hemorrhagic stroke [hazard ratio (HR) = 1.17, 95% confidence interval (CI): 1.06-1.29]. The increased NAR level was associated with elevated risk of 30-day mortality in hemorrhagic stroke (HR = 1.16, 95% CI: 1.02-1.30). The high RA level was linked with increased risk of 30-day mortality (HR = 1.44, 95% CI: 1.23-1.69). No significant correlation was observed in these inflammation biomarkers with the risk of 30-day mortality in ischemic stroke patients. The area under the curves (AUCs) of NLR, RA, and NAR for evaluating the risk of 30-day mortality of hemorrhagic stroke patients were 0.552 (95% CI: 0.503-0.601), 0.644 (95% CI: 0.590-0.699) and 0.541 (95% CI: 0.490-0.592).

Conclusion

NLR, NAR, and RA were potential prognostic biomarkers for predicting 30-day mortality of hemorrhagic stroke patients, which might provide clinicians an easy and cheap way to quickly identify patients with high risk of mortality.