Predictive ability of admission neutrophil to lymphocyte ratio on short-term outcome in patients with spontaneous cerebellar hemorrhage

Genetically predicted hypotaurine levels mediate the relationship between immune cells and intracerebral hemorrhage

The evidence supports a strong link between immune cells and intracerebral hemorrhage (ICH). Nonetheless, the specific cause-and-effect associations between immune cells and ICH remain indeterminate. Here, our primary investigation compared immune cell infiltration in the ICH and sham groups using the GSE24265 dataset. Afterward, we extensively examined the relationship between immune cells and ICH by applying a two-sample Mendelian randomization (MR) analysis to identify the particular immune cells that may be associated with the initiation and advancement of ICH. Nevertheless, the specific processes that regulate the cause-and-effect connection between immune cells and ICH remain unknown. In this study, our objective was to investigate the connections between immune cell characteristics and plasma metabolites, as well as the links between plasma components and ICH. Our investigation uncovered that the levels of hypotaurine play a key role in the advancement of ICH, influencing the ratio of switched memory B cells among lymphocytes. Thus, our findings provide novel insights into the potential biological mechanisms underlying immune cell-mediated ICH.

Neutrophil-to-lymphocyte ratio, white blood cell, and C-reactive protein predicts poor outcome and increased mortality in intracerebral hemorrhage patients: a meta-analysis

Objective

Inflammation participates in the pathology and progression of secondary brain injury after intracerebral hemorrhage (ICH). This meta-analysis intended to explore the prognostic role of inflammatory indexes, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), white blood cell (WBC), and C-reactive protein (CRP) in ICH patients.

Methods

Embase, PubMed, Web of Science, and Cochrane Library were searched until June 2023. Two outcomes, including poor outcome and mortality were extracted and measured. Odds ratio (OR) and 95% confidence interval (CI) were presented for outcome assessment.

Results

Forty-six studies with 25,928 patients were included in this meta-analysis. The high level of NLR [OR (95% CI): 1.20 (1.13-1.27), p < 0.001], WBC [OR (95% CI): 1.11 (1.02-1.21), p = 0.013], and CRP [OR (95% CI): 1.29 (1.08-1.54), p = 0.005] were related to poor outcome in ICH patients. Additionally, the high level of NLR [OR (95% CI): 1.06 (1.02-1.10), p = 0.001], WBC [OR (95% CI): 1.39 (1.16-1.66), p < 0.001], and CRP [OR (95% CI): 1.02 (1.01-1.04), p = 0.009] were correlated with increased mortality in ICH patients. Nevertheless, PLR was not associated with poor outcome [OR (95% CI): 1.00 (0.99-1.01), p = 0.749] or mortality [OR (95% CI): 1.00 (0.99-1.01), p = 0.750] in ICH patients. The total score of risk of bias assessed by Newcastle-Ottawa Scale criteria ranged from 7-9, which indicated the low risk of bias in the included studies. Publication bias was low, and stability assessed by sensitivity analysis was good.

Conclusion

This meta-analysis summarizes that the high level of NLR, WBC, and CRP estimates poor outcome and higher mortality in ICH patients.

Intracranial hemorrhages in patients with COVID-19: a systematic review of the literature, regarding six cases in an Amazonian population

BACKGROUND

 Coronavirus disease 2019 (COVID-19) has emerged as a public health emergency worldwide, predominantly affecting the respiratory tract. However, evidence supports the involvement of extrapulmonary sites, including reports of intracranial hemorrhages.

OBJECTIVE

 To describe six original cases and review the literature on intracranial hemorrhages in patients diagnosed with COVID-19 by molecular methods.

METHODS

 A systematic literature review was performed on MEDLINE, PubMed, and NCBI electronic databases to identify eligible studies. Of the total 1,624 articles retrieved, only 53 articles met the inclusion criteria.

RESULTS

 The overall incidence of intracranial hemorrhage in patients hospitalized for COVID-19 was 0.26%. In this patient group, the mean age was 60 years, and the majority were male (68%) with initial respiratory symptoms (73%) and some comorbidity. Before the diagnosis of hemorrhage, 43% of patients were using anticoagulants, 47.3% at therapeutic doses. The intraparenchymal (50%) was the most affected compartment, followed by the subarachnoid (34%), intraventricular (11%), and subdural (7%). There was a predominance of lobar over non-lobar topographies. Multifocal or multicompartmental hemorrhages were described in 25% of cases. Overall mortality in the cohort studies was 44%, while around 55% of patients were discharged from hospital.

CONCLUSION

 Despite the unusual association, the combination of these two diseases is associated with high rates of mortality and morbidity, as well as more severe clinicoradiological presentations. Further studies are needed to provide robust evidence on the exact pathophysiology behind the occurrence of intracranial hemorrhages after COVID-19 infection.

The predictive value of neutrophil to lymphocyte ratio on 30-day outcomes in spontaneous intracerebral hemorrhage patients after surgical treatment: A retrospective analysis of 128 patients

Objective

The purpose of this study was to explore the predictive value of the neutrophil-to-lymphocyte ratio (NLR) on 30-day outcomes in patients with spontaneous intracerebral hemorrhage (ICH) after surgical treatment.

Methods

This retrospective study utilized data from patients with ICH who underwent craniotomy or minimally invasive puncture and drainage (MIPD) between January 2015 and June 2021. The patients meeting the inclusion criteria were divided into two groups according to 30-day outcomes, namely, the favorable outcome group and the poor outcome group. Sex, age, time from onset to admission, vital signs at admission, admission Glasgow Coma Scale (GCS) score, diabetes mellitus, hypertension, hematoma volume, hematoma location, surgical approach, and NLR at different time points were all recorded and analyzed.

Results

A total of 128 patients were finally enrolled in this study, including 32 and 96 patients in the favorable outcome group and the poor outcome group, respectively. During the course of ICH, the changing trend of NLR was to increase first and then decrease and peaked within 48 h after surgery. In the univariate analysis, systolic blood pressure, admission GCS score, hematoma volume, surgical approach, and NLR within 48 h after surgery were statistically significant. In the multivariable analysis, NLR within 48 h after surgery (odds ratio [OR] = 1.342, p < 0.001) was an independent risk factor of the 30-day outcomes in patients with ICH after surgical treatment. The receiver operating characteristic (ROC) analysis showed that the best predictive cut-off value for NLR within 48 h after surgery was 12.35 [sensitivity 82.9%, specificity 81.8%, and area under the curve (AUC) 0.877] and 14.46 (sensitivity 55.1%, specificity 87.5%, and area under the curve 0.731) for the MIPD group and the craniotomy group, respectively.

Conclusions

In the process of ICH, the value of NLR was increased first and then decreased and peaked within 48 h after surgery. NLR within 48 h after surgery was an independent risk factor of the 30-day outcomes in patients with ICH. The peak NLR >12.35 or 14.46 in patients receiving MIPD or craniotomy reflected a poor prognosis, respectively.

Prognostic Role of the Neutrophil-to-Lymphocyte Ratio in Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis

The neutrophil-to-lymphocyte ratio (NLR) plays an important role in the progression of intracerebral hemorrhage (ICH). An increasing number of studies have reported that a high NLR is correlated with poor clinical outcomes among patients with ICH. Here, we conducted a systematic review and meta-analysis to evaluate the prognostic value of NLR in the setting of ICH. We performed a comprehensive search of electronic literature databases to identify all relevant studies evaluating the prognostic role of NLR in patients with ICH. Two researchers independently screened the studies and extracted relevant data. We extracted, pooled, and weighted odds ratio (OR) and 95% confidence interval (CI) values using a generic inverse-variance method, and then evaluated the heterogeneity among studies using Q test and I² statistic. Finally, we selected a total of 26 studies including 7,317 patients for the current study. Overall, our results indicated that a high NLR was significantly associated with a poor outcome (OR, 1.32; 95% CI, 1.19–1.46; P < 0.00001), mortality (OR, 1.05; 95% CI, 1.01–1.09; P = 0.02), and neurological deterioration (OR, 1.65; 95% CI, 1.08–2.52; P = 0.02). We did not observe a significant association between NLR and hematoma expansion (OR, 1.04; 95% CI, 0.99–1.08; P = 0.09). Our study indicated that a high NLR is significantly associated with poor clinical outcomes in patients with ICH. As NLR is a simple and easily available biomarker, future studies should focus on exploring its application in the prognostic evaluation of patients with ICH.

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.

Potential mechanisms of hemorrhagic stroke in elderly COVID-19 patients

The novel severe acute respiratory syndrome coronavirus 2 is the causative agent of coronavirus disease 2019, a new human infectious disease. While fever, cough, and respiratory distress are typical first symptoms, a fraction of those affected present instead with neurological symptoms suggestive of central nervous system compromise. This review summarizes the potential contribution of coronavirus disease 2019 to hemorrhagic stroke in the elderly and proposes possible mechanisms. Reports show that the most affected patients have underlying chronic diseases such as hypertension and diabetes, which are two key risk factors for hemorrhagic stroke. Angiotensin-converting enzyme 2 is the main host cell surface receptor interacting with the severe acute respiratory syndrome coronavirus 2 spike glycoprotein to allow viral entry and infection. We speculate that ensuing downregulation of angiotensin-converting enzyme 2 expression may compound the risk conferred by pre-existing comorbidities and critically influence the pathogenesis of hemorrhagic stroke by elevating blood pressure and impairing cerebrovascular endothelial function. Additionally, both age- and/or disease-related immune dysfunction and enhanced catecholamine release secondary to anxiety and stress may also aggravate central nervous system symptoms of severe acute respiratory syndrome coronavirus 2 infection. Thus, assessment of systemic inflammatory biomarkers and tight control of hemodynamic parameters upon admission are crucial to minimize mortality and morbidity in coronavirus disease 2019 patients with central nervous system symptoms suggestive of incipient stroke.

The Predictive Role of Postoperative Neutrophil to Lymphocyte Ratio for 30-Day Mortality After Intracerebral Hematoma Evacuation

OBJECTIVE

To evaluate whether the postoperative neutrophil-to-lymphocyte ratio (NLR) is a prognostic marker for patients with intracerebral hemorrhage (ICH) undergoing surgical hematoma evacuation.

METHODS

This retrospective cohort study was conducted to identify patients with ICH who underwent hematoma evacuation between January 2013 and December 2018. Data on demographics, clinical features, laboratory tests (admission and postoperative), and imaging information were collected. The associations between variables and 30-day mortality were assessed by multivariable logistic regression analysis. The predictive power of independent predictors was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

A total of 380 patients were included. Multivariable analysis identified admission Glasgow Coma Scale score (odds ratio [OR], 0.61; 95% confidence interval [CI], 0.53-0.70; P < 0.001) and initial hematoma volume (OR, 1.01; 95% CI, 1.01-1.02; P = 0.022) were independently associated with 30-day mortality. With regard to laboratory biomarkers, postoperative NLR (OR, 1.04; 95% CI, 1.01-1.08; P = 0.014) was independently correlated with 30-day death, but admission NLR (OR, 1.00; 95% CI, 0.97-1.03; P = 0.944) was not. The best predictive cutoff point of 12.97 for postoperative NLR (area under the ROC curve, 0.606; P = 0.006) for predicting 30-day mortality was determined by ROC analysis.

CONCLUSIONS

In patients with ICH undergoing hematoma evacuation, admission Glasgow Coma Scale score, initial hematoma volume, and postoperative NLR were independently associated with 30-day mortality. Postoperative NLR may be a prognostic marker in surgical ICH patients, and future studies are needed to confirm this finding.