New Silent Cerebral Infarction in Patients with Acute Non-Cerebral Amyloid Angiopathy Intracerebral Hemorrhage as a Predictor of Recurrent Cerebrovascular Events

Predictive value of white blood cell to hemoglobin ratio for 30-day mortality in patients with severe intracerebral hemorrhage

Aim

To explore the predictive value of white blood cell to hemoglobin ratio (WHR) for 30-day mortality in patients with intracerebral hemorrhage (ICH).

Methods

In this cohort study, 2,848 patients with ICH were identified in the Medical Information Mart for Intensive Care (MIMIC)-III and MIMIC-IV. Least absolute shrinkage and selection operator (LASSO) regression screened covariates of 30-day mortality of ICH patients. COX regression analysis was used to study the association of different levels of WHR, white blood cell (WBC), and hemoglobin (Hb) with 30-day mortality. The median follow-up time was 30 (20.28, 30.00) days.

Results

In total, 2,068 participants survived at the end of the follow-up. WHR was negatively correlated with the Glasgow Coma Score (GCS) (spearman correlation coefficient = -0.143, p < 0.001), and positively associated with the Sepsis-related Organ Failure Assessment (SOFA) score (spearman correlation coefficient = 0.156, p < 0.001), quick SOFA (qSOFA) score (spearman correlation coefficient = 0.156, p < 0.001), and Simplified Acute Physiology Score II (SAPS-II) (spearman correlation coefficient = 0.213, p < 0.001). After adjusting for confounders, WHR >0.833 (HR = 1.64, 95%CI: 1.39-1.92) and WBC >10.9 K/uL (HR = 1.49, 95%CI: 1.28-1.73) were associated with increased risk of 30-day mortality of patients with ICH. The area under the curve (AUC) value of the prediction model based on WHR and other predictors was 0.78 (95%CI: 0.77-0.79), which was higher than SAPSII (AUC = 0.75, 95%CI: 0.74-0.76), SOFA score (AUC = 0.69, 95%CI: 0.68-0.70) and GCS (AUC = 0.59, 95%CI: 0.57-0.60).

Conclusion

The level of WHR was associated with 30-day mortality in patients with severe ICH, and the WHR-based prediction model might provide a tool to quickly predict 30-day mortality in patients with ICH.

Diffusion-weighted Imaging Detection of Acute Ischemia Brain Lesions in Spontaneous Intracerebral Hemorrhage Associated with White Matter Hyperintensities, Enlarged Perivascular Spaces and Diabetes Mellitus

OBJECTIVE

Diffusion-weighted imaging (DWI) is commonly detected after spontaneous intracerebral hemorrhage (sICH) and is associated with poor functional outcomes. However, the etiology and significance of DWI lesions remain unclear. Thus, our study aimed to explore the prevalence and risk factors of acute ischemic lesions in sICH and discussed the possible mechanisms.

METHODS

We conducted a retrospective review of a consecutive cohort of 408 patients from June 2013 to October 2019 with sICH, who had brain computed tomography (CT) and magnetic resonance imaging (MRI) within 14 days of symptoms onset. Acute ischemic lesions were assessed on MRI using DWI lesions. We compared the clinical and imaging characteristics of patients with and without DWI lesions. The data were analyzed by univariate and multivariate logistic regression.

RESULTS

Among the enrolled 408 patients, the mean age was 56.8 ± 14.5 years, 68 (16.7%) of them had been diagnosed with diabetes mellitus (DM). DWI lesions were observed in 89 (21.8%) patients, and most of them had a history of lacunar infarctions, which were located in cortical or subcortical. In multivariate logistic regression analysis, DM (odds ratio (OR) 3.962, p <0.001), severe deep white matter hypertensities (DWMH) (OR 2.463, p =0.001) and severe centrum semiovale enlarged perivascular spaces (CSO-EPVS) (OR 2.679, p =0.001) were independently associated with the presence of DWI lesions.

CONCLUSION

In our cohort, we found DM, severe DWMH and severe CSO-EPVS were the independent risk factors in sICH patients with DWI lesions.

White Blood Cell Count Predicts Mortality in Patients with Spontaneous Intracerebral Hemorrhage

BACKGROUND

The association between white blood cell (WBC) counts and mortality in patients with intracerebral hemorrhage (ICH) has not been established. The aim of this study is to determine whether higher WBC is associated with mortality at 90 days.

METHODS

A retrospective observational study was conducted at two medical hospitals in China. Baseline WBC count on admission served as the primary predictor variable. Longitudinal WBC counts within the first week after admission were collected to assess the effects of WBC trajectory and the median and maximum WBC counts on outcomes following ICH. Associations of WBC count with outcomes were evaluated in multivariable regression analyses.

RESULTS

We identified 3613 patients with ICH who met the inclusion criteria. After adjusting primary confounding variables, patients with increased WBC count had a significantly higher risk of 90-day mortality (p < 0.001 for trend). In the receiver operating characteristic analyses, the capacity for all-cause mortality prediction by WBC count on admission (area under the ROC curve (AUC) = 0.65) was superior to other important inflammatory markers, including neutrophil (AUC = 0.64) , lymphocyte (AUC = 0.57), albumin (AUC = 0.57), and platelet count (AUC = 0.53), p < 0.001 for WBC vs. neutrophil, and the median WBC count (AUC = 0.66) within the first week after admission was a better marker than admission WBC count (p = 0.02).

CONCLUSIONS

In patients with ICH, WBC count on admission was associated with all-cause mortality at 90 days. Additionally, the median and maximum WBC counts within the first week after admission showed better predictive ability for the 90-day mortality compared with the WBC count on admission.

Deep Learning-Based Computed Tomography Perfusion Imaging to Evaluate the Effectiveness and Safety of Thrombolytic Therapy for Cerebral Infarct with Unknown Time of Onset

This study was aimed to discuss the effectiveness and safety of deep learning-based computed tomography perfusion (CTP) imaging in the thrombolytic therapy for acute cerebral infarct with unknown time of onset. A total of 100 patients with acute cerebral infarct with unknown time of onset were selected as the research objects. All patients received thrombolytic therapy. According to different image processing methods, they were divided into the algorithm group (artificial intelligence algorithm-based image processing group) and the control group (conventional method-based image processing group). After that, the evaluations of effectiveness and safety of thrombolytic therapy for the patients with acute cerebral infarct in the two groups were compared. The research results demonstrated that artificial intelligence algorithm-based CTP imaging showed significant diagnostic effects and the image quality in the algorithm group was remarkably higher than that in the control group (P < 0.05). Besides, the overall image quality of algorithm group was relatively higher. The differences in the National Institute of Health stroke scale (NIHSS) scores for the two groups indicated that the thrombolytic effect on the algorithm group was superior to that on the control group. Thrombolytic therapy for the algorithm group showed therapeutic effects on neurologic impairment. The symptomatic intracranial hemorrhage rate of the algorithm group within 24 hours was lower than the hemorrhage conversion rate of the control group, and the difference between the two groups was 14%. The data differences between the two groups showed statistical significance (P < 0.05). The results demonstrated that the safety of guided thrombolytic therapy for the algorithm group was higher than that in the control group. To sum up, deep learning-based CTP images showed the clinical application values in the diagnosis of cerebral infarct.

Prediction Model of Ischemic Stroke Recurrence Using PSO-LSTM in Mobile Medical Monitoring System

Aiming at the problems of low prediction accuracy and low sensitivity of traditional ischemic stroke recurrence prediction methods, which limits its application range, by introducing an adaptive particle swarm optimization (PSO) algorithm into the Long and Short-Term Memory (LSTM) model, a prediction model of ischemic stroke recurrence using deep learning in mobile medical monitoring system is proposed. First, based on the clustering idea, the particles are divided into local optimal particles and ordinary particles according to the characteristic information and distribution of different particles. By updating the particles with different strategies, the diversity of the population is improved and the problem of local optimal solution is eliminated. Then, by introducing the adaptive PSO algorithm into the LSTM, the PSO-LSTM prediction model is constructed. The optimal super parameters of the model are determined quickly and accurately, and the model is trained combined with the patient's clinical data. Finally, by using SMOTE method to process the original data, the imbalance of positive and negative sample data is eliminated. Under the same conditions, the proposed PSO-LSTM prediction model is compared with two traditional LSTM models. The results show that the prediction accuracy of PSO-LSTM model is 92.0%, which is better than two comparison models. The effective prediction of ischemic stroke recurrence is realized.

Long non-coding RNA SNHG1 relieves microglia activation by downregulating miR-329-3p expression in an in vitro model of cerebral infarction

Following cerebral infarction, activated microglia cells can release a large amount of inflammatory cytokines, thereby exacerbating neuronal damage. It has been demonstrated that the long non-coding RNA small nucleolar RNA host gene 1 (SNHG1) exerts a protective effect against cerebral infarction. However, its specific role in cerebral infarction and underlying mechanism have yet to be fully elucidated. The present study aimed to investigate the effects of the SNHG1 and microRNA (miR)-329-3p in cerebral infarction and to determine the underlying molecular mechanisms. An in vitro oxygen-glucose deprivation (OGD) model was established using the BV-2 microglial cell line. The mRNA expression levels of SNHG1 and miR-329-3p were analyzed using reverse transcription-quantitative PCR and the protein expression levels of cleaved caspase-3 and caspase-3 were detected using western blotting. The binding relationship between SNHG1 and miR-329-3p was predicted using starBase and verified using a dual luciferase reporter assay. The release of TNF-α and nitric oxide, as well as caspase-3 activity, were detected using appropriate commercial kits. Flow cytometry analysis was performed to measure cell apoptosis. The results of the present study revealed that the expression levels of SNHG1 were upregulated in the OGD-induced BV-2 cell model. miR-329-3p was discovered to directly target SNHG1, and its mRNA expression levels were downregulated in the OGD-induced BV-2 cell model. The SNHG1-plasmid downregulated miR-329-3p expression levels, while this effect was reversed by transfection with the miR-329-3p mimic. The overexpression of SNHG1 or knockdown of miR-329-3p inhibited OGD-induced BV-2 cell activation. In conclusion, the results of the present study suggested that SNHG1 may reduce microglial cell activity by regulating the expression of miR-329-3p, indicating its potential protective role in cerebral infarction.

Predicting new silent cerebral infarction after intracerebral hemorrhage using serum white blood cell count

Background

It has been confirmed that incidental silent cerebral infarctions (SCIs) found in healthy people may be risk factors for cerebrovascular diseases such as strokes and vascular dementia. The prospective study aimed to determine the utility of baseline serum white blood cell (WBC) counts to predict the emergence of new SCI after intracranial hemorrhage (ICH).

Methods

This is a prospective study. From January 2016 to December 2017, we recruited 171 patients admitted to the neurology department of the Affiliated Shuyang Hospital of Xuzhou Medical University with a first episode of ICH. Serum WBC count was measured on admission. SCI was detected by cranial magnetic resonance imaging (MRI) 14 days after the onset of the ICH. Receiver operating characteristic curve analysis was used to calculate the most appropriate cut-off values of the WBC count for differentiating patients with and without SCI at the end of the study period.

Results

New SCIs were detected in 28.07% of patients by cranial MRI. Multivariate logistic regression analysis showed that cerebral microbleeds (CMBs), raised WBC counts, and leukoaraiosis were independent risk factors for SCI. The most appropriate cut-off WBC count differentiating the two groups was 7.65×10⁹/L (sensitivity: 77.08%, specificity: 63.41%).

Conclusion

Elevated levels of serum WBC counts in patients with ICH are associated with SCI. There is potential value in using serum WBC counts to predict new SCI after an acute hemorrhagic stroke.

The Predictive Values of Different Small Vessel Disease Scores on Clinical Outcomes in Mild ICH Patients

Aim: To explore the predictive values of different small vessel disease (SVD) scores on functional recoveries and the clinical cerebrovascular events in mild intracerebral hemorrhage (ICH).

Methods: In this study, we enrolled conscious and mild ICH patients without surgery and further divided them into the cerebral amyloid angiopathy (CAA)-ICH group and hypertension (HTN)-ICH group. The severity of individual SVD markers, including lacunes, cerebral microbleeds (CMBs), enlarged perivascular spaces (EPVS), white matter hyperintensity (WMH), and cortical superficial siderosis (cSS), was evaluated. The original SVD score, modified SVD score, refined SVD score, and CAA-SVD score and the total number of SVD markers were further calculated. Functional recoveries were evaluated using the modified Rankin scale. Recurrences of stroke were defined as readmission to the hospital with a definite diagnosis of stroke.

Results: A total of 163 ICH patients (60 CAA-ICH and 103 HTN-ICH) were included in the study. The CAA-SVD score (OR=3.429; 95% confidence interval (CI)=1.518–7.748) had the best predictive effect on functional dependence in the CAA-ICH group, among which cSS severities probably played a vital role (OR=4.665; 95% CI=1.388–15.679). The total number of SVD markers [hazard ratio (HR)=3.765; 95% CI=1.467–9.663] can better identify stroke recurrences in CAA-ICH. In HTN-ICH, while the total number of SVD markers (HR=2.136; 95% CI=1.218–3.745) also demonstrated association with recurrent stroke, this effect seems to be related with the influence of lacunes (HR=5.064; 95% CI=1.697–15.116).

Conclusions: The CAA-SVD score and the total number of SVD markers might identify mild CAA-ICH patients with poor prognosis. However, it would be better to focus on lacunes rather than on the overall burden of SVD to predict recurrent strokes in HTN-ICH.

Effects of intravenous thrombolysis with alteplase combined with edaravone on cerebral hemodynamics and T lymphocyte level in patients with acute cerebral infarction

Our study aimed to investigate the effect of intravenous thrombolysis with alteplase and edaravone on cerebral hemodynamics and T lymphocyte level in patients harboring acute cerebral infarction.There involved a total of 118 patients with acute cerebral infarction from November 2017 to May 2019 in our hospital were randomly divided into 2 groups: the observation group (59 patients were treated with intravenous thrombolysis with alteplase combined with edaravone) and the control group (59 patients were treated with intravenous thrombolysis of alteplase). The clinical effect, neurological function, cerebral hemodynamic index, T lymphocyte level, oxygen free radical scavenging level and oxidative stress index of the 2 groups were observed and compared.Before the treatment, there were no significant differences in neurological function, cerebral hemodynamic indexes, T-lymphocyte level, oxygen free radical scavenging level and oxidative stress indexes between the 2 groups (P > .05). After the treatment, the neurological function, cerebral hemodynamic indexes, T-lymphocyte level, oxygen free radical scavenging level and oxidative stress indexes of the 2 groups were significantly improved. In addition, the observation group exerted greater beneficial effect in terms of the clinical effect, neurologic function, cerebral hemodynamic index, T lymphocyte level, oxygen free radical scavenging level and oxidative stress index than those of the control group (P < .05).The intravenous thrombolysis with alteplase and edaravone is effective in the treatment of acute cerebral infarction, which also provides better results in terms of improving the clinical efficacy and prognosis of patients and might be an alternative option for clinical practice.