Red blood cell distribution width and mortality of spontaneous intracerebral hemorrhage patients

Association Between Red Blood Cell Distribution width and Long-Term Mortality in Patients with Intracerebral Hemorrhage

BACKGROUND

The association between the red cell distribution width (RDW) and long-term mortality in patients with intracerebral hemorrhage (ICH) has not been clearly established.

METHODS

We conducted a retrospective cohort study of patients with ICH admitted to two tertiary hospitals. The primary outcome was long-term mortality, and the effect of elevated RDW (RDW coefficient of variation [RDW-CV]; RDW standard deviation [RDW-SD]) on outcomes was assessed by using logistic regression analysis. Serum RDW levels was divided into four levels by quartiles (the lowest quartile [Q1]; the highest quartile [Q4]).

RESULTS

This study included 4223 patients with ICH. After adjustment for potential confounders, admission RDW-CV (Quartile 4 [Q4] vs. Quartile 1 [Q1], adjusted hazard ratio [HR] 1.61, 95% confidence interval [CI] 1.34-1.92) and median RDW-CV within the first month after admission (Q4 vs. Q1, adjusted HR 1.69, 95% CI 1.40-2.04) were both associated with 1-year mortality following ICH. Parallel results were found for RDW-SD. In the receiver operating characteristic analyses, both RDW-CV and RDW-SD outperformed some inflammatory biomarkers, such as albumin, hemoglobin, total cholesterol, platelet count, lymphocyte, and fibrinogen, in predicting long-term mortality following ICH. Additionally, compared with admission RDW, median RDW-CV and RDW-SD (areas under the curve [AUC] 0.668 and 0.652, respectively) was superior to predict long-term mortality, (P < 0.001). Furthermore, median RDW-CV level was a better predictor than RDW-SD (P = 0.03).

CONCLUSIONS

In patients with ICH, RDW independently predicted long-term mortality. Median RDW levels within the first month after admission were better predictors of long-term mortality compared with RDW levels on admission. Additionally, median RDW-CV showed superior predictive capacity than median RDW-SD for long-term mortality following ICH.

Red cell distribution width to lymphocyte ratio could serve as a new inflammatory biomarker for predicting hematoma expansion in patients with intracerebral hemorrhage

BACKGROUND

Hematoma expansion is a critical factor associated with increased mortality and adverse outcomes in patients with intracerebral hemorrhage (ICH). Identifying and preventing hematoma expansion early on is crucial for effective therapeutic intervention. This study aimed to investigate the potential association between the Red cell distribution width to lymphocyte ratio (RDWLR) and hematoma expansion in ICH patients.

METHODS

We conducted a retrospective analysis of clinical data from 303 ICH patients treated at our department between May 2018 and May 2023. Demographic, clinical, radiological, and laboratory data, including RDWLR upon admission, were assessed. Binary logistic regression analysis was employed to determine independent associations between various variables and hematoma expansion.

RESULTS

The study included 303 ICH patients, comprising 167 (55.1%) males and 136 (44.9%) females, with a mean age of 65.25 ± 7.32 years at admission. Hematoma expansion occurred in 73 (24.1%) cases. Multivariate analysis revealed correlations between hematoma volume at baseline (OR, 2.73; 95% CI: 1.45 -4,78; P < 0.001), admission systolic blood pressure (OR, 2.98 ; 95% CI: 1.54-4.98; P < 0.001), Glasgow Coma Scale (GCS) (OR, 1.58; 95% CI: 1.25-2.46; P = 0.017), and RDWLR (OR, 1.58; 95% CI: 1.13-2.85; P = 0.022) and hematoma expansion in these patients.

CONCLUSIONS

Our findings suggest that RDWLR could serve as a new inflammatory biomarker for hematoma expansion in ICH patients. This cost-effective and readily available biomarker has the potential for early prediction of hematoma expansion in these patients.

Red blood cell distribution width as a predictor of mortality and poor functional outcome after acute ischemic stroke: a meta-analysis and meta-regression

BACKGROUND

This study aimed to review evidence on the ability of red cell distribution width (RDW) to predict mortality and poor functional outcomes after acute ischemic stroke (AIS).

METHODS

Databases of PubMed, CENTRAL, Scopus, Embase, and Web of Science were searched online from inception to 25th Jul 2023 for all studies reporting the association between RDW and outcomes as adjusted ratios. A random-effects meta-analysis was done. Meta-regression was conducted using multiple moderators.

RESULTS

15 studies with 14,968 patients were included. Meta-analysis found that RDW, both as a categorical variable (OR: 2.10 95% CI: 1.74, 2.55 I2 = 42%) and continuous variable OR: 1.16 95% CI: 1.05, 1.28 I2 = 64%) was a significant predictor of mortality after AIS. Age and number of hypertensives were found to be significant moderators in the meta-regression. Also, high RDW, as a categorical variable (OR: 1.68 95% CI: 1.20, 2.35 I2 = 84%), was associated with significantly higher odds of poor functional outcomes after AIS, but not as a continuous variable (OR: 1.07 95% CI: 0.99, 1.16 I2 = 61%). Meta-regression showed that the association was stronger in small sample-sized studies.

CONCLUSION

RDW can be a useful, readily available, and cost-effective biomarker to rapidly stratify AIS patients at risk of poor outcomes. High RDW was consistently associated with an increased risk of mortality after AIS, however, its ability to predict poor functional outcomes needs to be verified by further studies.

The relationship between hemoglobin/red blood cell distribution width ratio and mortality in patients with intracranial hemorrhage: a possible protective effect for the elderly?

Intracranial hemorrhage (ICH) is a neurological emergency with a poor prognosis. This study aimed to understand the association between hemoglobin levels, red blood cell distribution width ratio (HRR), and mortality in patients with ICH. Information on patients with ICH was extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Cox proportional risk models were used to assess the relationship between HRR and 28-day and 90-day mortality, and constructed by adjusting for relevant covariates. Segmented regression models and smoothing curves were used to analyze the linear relationship between HRR and mortality. This study recruited 4,716 patients with ICH. The HRR Q4 group was negatively associated with the 28- and 90-day mortality. For patients aged > 65 years, the right-hand threshold inflection points of the HRR were 0.92 and 0.93, respectively, which were negatively associated with 28-day mortality (HR:0.06, 95% CI 0.01, 0.35, p = 0.0016) and with 90-day mortality (p = 0.0006). In the non-linear model, both 28-day mortality (HR, 0.17; 95% CI 0.04-0.75, p = 0.0191; HRR > 0.89) and 90-day mortality (HR, 0.13; 95% CI 0.04-0.49, p = 0.0022; HRR > 0.85) were associated in men. In the subgroup analysis, the negative association between HRR and mortality was more pronounced in patients > 65 years of age, as well as in patients with non-dementia, diabetes, and malignant cancer. We found a non-linear relationship between mortality and the HRR in elderly patients, and a higher HRR was negatively associated with mortality in patients with ICH.

Elevated red blood cell distribution width levels predict depression after intracerebral hemorrhage: A 3-month follow-up study

Objectives

Inflammation vitally impacts the progression of depression resulting from intracerebral hemorrhage (ICH), while red blood cell distribution width (RDW) marks inflammatory-related diseases. The present study aimed at evaluating how RDW affects depression after ICH.

Methods

From prospective analyses of patients admitted to our department between January 2017 and September 2022, ICH patients with complete medical records were evaluated. The 17-item Hamilton Depression (HAMD-17) scale was used for measuring the depressive symptoms at 3 months after ICH. Diagnosis of post-ICH depression was conducted for patients based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) criteria.

Results

A total of 438 patients were enrolled in the study, out of which 93 (21.23%) patients had PSD at the 3-month follow-up. Accordingly, patients with depression had higher RDW levels (13.70 [IQR: 13.56–13.89] vs.13.45 [IQR: 12.64–13.75], p &lt; 0.001) at admission compared with those without depression. In multivariate analyses, RDW was used for independently predicting the depression after ICH at 3 months (OR: 2.832 [95% CI: 1.748–4.587], p &lt; 0.001). After adjusting the underlying confounding factors, the odds ratio (OR) of depression after ICH was 4.225 (95% CI: 1.686–10.586, p = 0.002) for the highest tertile of RDW relative to the lowest tertile. With an AUC of 0.703 (95% CI: 0.649–0.757), RDW demonstrated a significantly better discriminatory ability relative to CRP and WBC. RDW as an indicator for predicting depression after ICH had an optimal cutoff value of 13.68, and the sensitivity and specificity were 63.4% and 64.6%, respectively.

Conclusions

Elevated RDW level predicted post-ICH depression at 3 months, confirming RDW as an effective inflammatory marker for predicting depression after ICH.

Neutrophil-to-leukocyte ratio and admission glycemia as predictors of short-term death in very old elderlies with lobar intracerebral hemorrhage

BACKGROUND

The incidence of spontaneous intracerebral hemorrhage (SICH) is highest in very old elderlies (≥75 years). The increasing use of antithrombotic drugs is shifting the epidemiology of SICH towards predominance of lobar subtype, suggesting an incremented propensity of bleeding associated with underlying cerebral amyloid angiopathy. With population aging and antithrombotic use, a parallel raise of proportion of lobar SICH is occurring. Improvement of prognostication in this specific age group and SICH type is needed. Routine blood biomarkers can contribute to prediction of short-term mortality after SICH.

OBJECTIVE

Our aim was to investigate the contribution of routine blood biomarkers for short-term mortality (30-days) in elderly patients with lobar SICH.

METHODS

Retrospective analysis of consecutive 130 patients with ≥ 75 years and lobar SICH. The outcome was 30-day mortality. Logistic regression analysis was used to investigate whether admission routine biomarkers can be used as predictors.

RESULTS

The case fatality was 40.8%. Admission glycaemia level, neutrophil to lymphocyte ratio and mean platelet volume were significantly different between groups (p = 0.001, p = 0.024, p = 0.038, respectively). There was no significant difference in all other routine biomarkers. On multivariate analysis, admission higher mean BG level (odds ratio [OR]: 1.010, 95% confidence interval [CI]: 1.001-1.019, p = 0.026) and neutrophil to lymphocyte ratio (OR: 1.070, 95% CI: 1.008-1.136, p = 0.027) emerged as predictors.

CONCLUSION

In very old patients with lobar SICH, higher BG level and neutrophil to lymphocyte ratio are associated with increased risk of short-term death.

Development and Validation of a Risk Prediction Model for In-Hospital Mortality in Patients With Acute Upper Gastrointestinal Bleeding

Acute upper gastrointestinal bleeding (UGIB) is a common life-threatening clinical emergency with a poor prognosis. The aim of this study was to develop a risk prediction model for in-hospital mortality in patients with UGIB. We performed a post hoc analysis of a publicly available retrospective clinical data. A total of 360 patients with UGIB were included in this study. The least absolute shrinkage and selection operator regression was used to screen predictors and a restricted cubic spline function was used to investigate the assumption of linear relationships between continuous predictors and the risk of in-hospital mortality. Backward stepwise selection with the Akaike information criterion was used to identify variables for the best prediction model. A nomogram was developed based on the results of the best prediction model. The receiver operating characteristic curve, GiViTI calibration plot, and decision curve analysis were used to evaluate the performance of the nomogram. The optimal prediction model consisting of 4 predictors: red cell distribution width (odds ratio [OR] = 8.44; 95% confidence interval [CI]: 1.77-89.10), platelet count (OR = 0.99; 95% CI: 0.99-1.00), pulse rate (OR = 1.03; 95% CI: 1.01-1.05), and SpO2 (OR = 0.92; 95% CI: 0.86-0.96). The nomogram model had good discrimination (area under the curve  =  0.86, 95% CI: 0.78-0.95), calibration, and clinical usefulness. In this study, we developed a nomogram model for predicting death during hospitalization in patients with UGIB based on blood biomarkers and baseline vital signs at the time of admission. The model has good performance, allowing rapid risk stratification of patients with UGIB.

Correlation between red blood cell distribution width, neutrophil to lymphocyte ratio, and neutrophil to platelet ratio with 3-month prognosis of patients with intracerebral hemorrhage: a retrospective study

BACKGROUND

Red cell distribution width (RDW) is a parameter that indsicates the heterogeneity of red blood cell size and could be a prognostic factor in some diseases. Also, intracerebral hemorrhage (ICH) is considered a vascular event with a high mortality rate. We aimed to examine the role of RDW, neutrophil to lymphocyte ratio (NLR), and neutrophil to platelet ratio (NPR) in predicting the prognosis of patients with ICH.

METHODS

This is a retrospective cohort study conducted on 140 patients with ICH admitted to the neurology ward and intensive care unit (ICU) in Imam Reza Hospital, Tabriz, Iran. Demographic data, National Institutes of Health Stroke Scale (NIHSS), and complete blood count test parameters were evaluated within 24 h after hospitalization. These variables were collected and re-evaluated three months later.

RESULTS

The mean age of the study population was 61.14 (± 16) years and 51% were male. The mean NLR (p = 0.05), neutrophil count (p=0.04), platelet count (p = 0.05), and NIHSS (p<0.01)  had a significant difference between the deceased patients and those who partially recovered after three months. The ROC curve showed that NIHSS (area under curve (AUC): 0.902), followed by NPR (AUC: 0.682) variables had the highest AUC.

CONCLUSION

RDW could be a relevant prognostic factor and predictor in determining 3-months survival in ICH. Nevertheless, further large-scale prospective cohorts might be needed to evaluate the associations.

Biomembrane-mimetic hemoperfusion adsorbent for efficient removal of low-density lipoprotein from hyperlipemia blood

Lowering of low-density lipoprotein (LDL) levels in blood of patients with hyperlipidaemia can effectively prevent the progression of atherosclerosis and coronary heart disease. The present study demonstrated a facile synthesis strategy to prepare biomembrane-mimetic LDL adsorbent (PVA@COOH-PE) via directional immobilization of phospholipid onto macro-porous cross-linked poly(vinyl alcohol) spheres. The binding between the prepared adsorbent and LDL particles simulates the cytosolic lipid droplets to form a lipid-packing structure. The adsorbent possesses satisfactory removal efficiency for LDL and total cholesterol (TCH) in hyperlipemia serum, while remains high-density lipoprotein (HDL) concentration within the normal range. The adsorption capacities for LDL and TCH are about 1.13 and 1.74 mg/ml respectively, which are nearly three and four times higher than that of HDL (0.42 mg/ml). The adsorbent also possesses satisfactory anticoagulant properties, causes negligible effect on blood cells and produces low hemolysis ratios. The excellent blood compatibility plus LDL removal efficiency of PVA@COOH-PE indicates its good application prospect as hemoperfusion adsorbent in the treatment of hyperlipidaemia.

Enhancing Robustness of Machine Learning Integration With Routine Laboratory Blood Tests to Predict Inpatient Mortality After Intracerebral Hemorrhage

Objective: The accurate evaluation of outcomes at a personalized level in patients with intracerebral hemorrhage (ICH) is critical clinical implications. This study aims to evaluate how machine learning integrates with routine laboratory tests and electronic health records (EHRs) data to predict inpatient mortality after ICH.

Methods: In this machine learning-based prognostic study, we included 1,835 consecutive patients with acute ICH between October 2010 and December 2018. The model building process incorporated five pre-implant ICH score variables (clinical features) and 13 out of 59 available routine laboratory parameters. We assessed model performance according to a range of learning metrics, such as the mean area under the receiver operating characteristic curve [AUROC]. We also used the Shapley additive explanation algorithm to explain the prediction model.

Results: Machine learning models using laboratory data achieved AUROCs of 0.71–0.82 in a split-by-year development/testing scheme. The non-linear eXtreme Gradient Boosting model yielded the highest prediction accuracy. In the held-out validation set of development cohort, the predictive model using comprehensive clinical and laboratory parameters outperformed those using clinical alone in predicting in-hospital mortality (AUROC [95% bootstrap confidence interval], 0.899 [0.897–0.901] vs. 0.875 [0.872–0.877]; P <0.001), with over 81% accuracy, sensitivity, and specificity. We observed similar performance in the testing set.

Conclusions: Machine learning integrated with routine laboratory tests and EHRs could significantly promote the accuracy of inpatient ICH mortality prediction. This multidimensional composite prediction strategy might become an intelligent assistive prediction for ICH risk reclassification and offer an example for precision medicine.

Red blood cell distribution width in glioblastoma

INTRODUCTION

Glioblastoma (GBM) is the most common and deadly adult brain tumor. Red blood cell distribution width (RDW) has been found in non-central nervous system neoplasms to be associated with survival. This study aims to assess the prognostic value of pre-operative RDW and trends in RDW over time during the disease course.

METHODS

This single-institution retrospective cohort study identified patients ≥ 18 years old with pathology-proved glioblastoma treated between April 2003-May 2017 from an institutional database. A Cox proportional hazards model was developed using known prognostic clinical variables to predict overall survival time; a second model incorporating continuously valued RDW was then created. The additional prognostic value of RDW was assessed with a joint model F-test. The variation of RDW-CV over time was evaluated with linear mixed model of RDW. A post-hoc exploratory analysis was performed to assess the trend in RDW lab value leading up to time of death.

RESULTS

346 adult GBM patients were identified; complete survival data was available for all patients. The addition of RDW to the multivariable Cox proportional hazards model did not increase prognostic value. There was an upward trend in RDW throughout the post-operative disease course. In a post-hoc analysis, there was an upward trend in RDW leading up to the time of death.

CONCLUSION

Although RDW has been prognostic of survival for many inflammatory, prothrombotic, and neoplastic diseases, pre-operative RDW was not associated with overall survival in GBM patients. RDW trended upwards throughout the disease course, suggesting possible systemic inflammatory effects of either glioblastoma or treatment.

Ultraefficiently Calming Cytokine Storm Using Ti3C2T x MXene

During the global outbreak of COVID-19 pandemic, "cytokine storm" conditions are regarded as the fatal step resulting in most mortality. Hemoperfusion is widely used to remove cytokines from the blood of severely ill patients to prevent uncontrolled inflammation induced by a cytokine storm. This article discoveres, for the first time, that 2D Ti3C2T x MXene sheet demonstrates an ultrahigh removal capability for typical cytokine interleukin-6. In particular, MXene shows a 13.4 times higher removal efficiency over traditional activated carbon absorbents. Molecular-level investigations reveal that MXene exhibits a strong chemisorption mechanism for immobilizing cytokine interleukin-6 molecules, which is different from activated carbon absorbents. MXene sheet also demonstrates excellent blood compatibility without any deleterious side influence on the composition of human blood. This work can open a new avenue to use MXene sheets as an ultraefficient hemoperfusion absorbent to eliminate the cytokine storm syndrome in treatment of severe COVID-19 patients.