The Role of the Blood Neutrophil-to-Lymphocyte Ratio in Aneurysmal Subarachnoid Hemorrhage

Trajectory clustering of immune cells and its association with clinical outcomes after aneurysmal subarachnoid hemorrhage

Background and purpose

The immune response following aneurysmal subarachnoid hemorrhage (aSAH) can exacerbate secondary brain injury and impact clinical outcomes. As the immune response after aSAH is a dynamic process, we aim to track and characterize immune cell trajectories over time to identify patterns associated with various clinical outcomes.

Methods

In this retrospective single-center study of patients with aSAH, we analyzed immune cell count trajectories, including neutrophil, monocyte, and lymphocyte counts, collected from day 1 to day 14. These trajectories were classified into four distinct clusters utilizing the k-means longitudinal clustering method. A comprehensive multivariable analysis was performed to explore the associations of these immune cell clusters with various clinical outcomes. These outcomes included a Modified Rankin Scale score (mRS) of 3 to 6, indicative of poor functional outcomes, along with complications including shunt dependency, vasospasm, and secondary cerebral infarction.

Results

In this study, 304 patients with aSAH were analyzed. The trajectories of immune cell counts, including neutrophils, monocytes, and lymphocytes, were successfully categorized into four distinct clusters for each immune cell type. Within neutrophil clusters, both persistent neutrophilia and progressive neutrophilia were associated with poor functional outcomes, shunt dependency, and vasospasm, with resolving neutrophilia showing a lesser degree of these associations. Within monocyte clusters, early monocytosis was associated with vasospasm, whereas delayed monocytosis was associated with shunt dependency. Within lymphocyte clusters, both early transient lymphopenia and early prolonged lymphopenia were associated with poor functional outcomes.

Conclusion

Our study demonstrates that distinct immune cell trajectories post-aSAH, identified through unsupervised clustering, are significantly associated with specific clinical outcomes. Understanding these dynamic immune responses may provide key insights with potential for future therapeutic strategies.

The Trends of Neutrophil-to-Lymphocyte Ratio, Platelet-to-Lymphocyte Ratio, and Systemic Immunoinflammatory Index in Patients with Intracerebral Hemorrhage and Clinical Value in Predicting Pneumonia 30 Days After Surgery

BACKGROUND

Inflammatory response is closely associated with secondary brain injury and pneumonia in intracerebral hemorrhage (ICH). In this study, we aimed to investigate the value of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immunoinflammatory index (SII) in the development of pneumonia in ICH patients 30 days after surgery.

METHODS

We retrospectively collected clinical data on patients with ICH who underwent surgical treatment at our institution from January 2016 to December 2022, mainly including NLR, PLR, and SII at different time points. Receiver operating characteristic curves were used to compare the value of different inflammatory indicators in predicting the development of postoperative pneumonia 30 days after surgery in ICH patients, and multivariate logistic regression analyses were used to identify independent risk factors for pneumonia 30 days after surgery.

RESULTS

Among 112 patients with ICH undergoing surgical treatment, 31 (27.7%) developed pneumonia postoperatively. The results of the univariate analysis demonstrated that patients in the pneumonia group experienced significantly higher blood glucose, NLR at 72 hours postoperatively, PLR at 72 hours postoperatively, and SII at 72 hours postoperatively (SII3) than those in the nonpneumonia group, and significantly lower admission Glasgow Coma Scale scores than those in the nonpneumonia group (all P < 0.05). NLR, PLR, and SII showed increasing and then decreasing in the disease process of ICH and peaked at 48 hours postoperatively. Multivariable logistic regression analysis revealed that SII3 was an independent risk factor for postoperative pneumonia 30 days after surgery in ICH patients (odds ratio = 1.001, 95% confidence interval: 1.000-1.002, P = 0.008). The area under the curve of the developed nomogram model was 0.895 (95% confidence interval = 0.823-0.967), with a sensitivity and specificity of 0.903 and 0.815, respectively, providing good predictive power.

CONCLUSIONS

In the course of ICH, NLR, PLR, and SII increased and then decreased and peaked at 48 hours postoperatively. The SII3 was the best predictor of the occurrence of pneumonia postoperatively in ICH patients.

Predicting who has delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage using machine learning approach: a multicenter, retrospective cohort study

BACKGROUND

Early prediction of delayed cerebral ischemia (DCI) is critical to improving the prognosis of aneurysmal subarachnoid hemorrhage (aSAH). Machine learning (ML) algorithms can learn from intricate information unbiasedly and facilitate the early identification of clinical outcomes. This study aimed to construct and compare the ability of different ML models to predict DCI after aSAH. Then, we identified and analyzed the essential risk of DCI occurrence by preoperative clinical scores and postoperative laboratory test results.

METHODS

This was a multicenter, retrospective cohort study. A total of 1039 post-operation patients with aSAH were finally included from three hospitals in China. The training group contained 919 patients, and the test group comprised 120 patients. We used five popular machine-learning algorithms to construct the models. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, and f1 score were used to evaluate and compare the five models. Finally, we performed a Shapley Additive exPlanations analysis for the model with the best performance and significance analysis for each feature.

RESULTS

A total of 239 patients with aSAH (23.003%) developed DCI after the operation. Our results showed that in the test cohort, Random Forest (RF) had an AUC of 0.79, which was better than other models. The five most important features for predicting DCI in the RF model were the admitted modified Rankin Scale, D-Dimer, intracranial parenchymal hematoma, neutrophil/lymphocyte ratio, and Fisher score. Interestingly, clamping or embolization for the aneurysm treatment was the fourth button-down risk factor in the ML model.

CONCLUSIONS

In this multicenter study, we compared five ML methods, among which RF performed the best in DCI prediction. In addition, the essential risks were identified to help clinicians monitor the patients at high risk for DCI more precisely and facilitate timely intervention.

All Three Supersystems-Nervous, Vascular, and Immune-Contribute to the Cortical Infarcts After Subarachnoid Hemorrhage

The recently published DISCHARGE-1 trial supports the observations of earlier autopsy and neuroimaging studies that almost 70% of all focal brain damage after aneurysmal subarachnoid hemorrhage are anemic infarcts of the cortex, often also affecting the white matter immediately below. The infarcts are not limited by the usual vascular territories. About two-fifths of the ischemic damage occurs within ~ 48 h; the remaining three-fifths are delayed (within ~ 3 weeks). Using neuromonitoring technology in combination with longitudinal neuroimaging, the entire sequence of both early and delayed cortical infarct development after subarachnoid hemorrhage has recently been recorded in patients. Characteristically, cortical infarcts are caused by acute severe vasospastic events, so-called spreading ischemia, triggered by spontaneously occurring spreading depolarization. In locations where a spreading depolarization passes through, cerebral blood flow can drastically drop within a few seconds and remain suppressed for minutes or even hours, often followed by high-amplitude, sustained hyperemia. In spreading depolarization, neurons lead the event, and the other cells of the neurovascular unit (endothelium, vascular smooth muscle, pericytes, astrocytes, microglia, oligodendrocytes) follow. However, dysregulation in cells of all three supersystems-nervous, vascular, and immune-is very likely involved in the dysfunction of the neurovascular unit underlying spreading ischemia. It is assumed that subarachnoid blood, which lies directly on the cortex and enters the parenchyma via glymphatic channels, triggers these dysregulations. This review discusses the neuroglial, neurovascular, and neuroimmunological dysregulations in the context of spreading depolarization and spreading ischemia as critical elements in the pathogenesis of cortical infarcts after subarachnoid hemorrhage.

The dynamic changes of peripheral blood cell counts predict the clinical outcomes of aneurysmal subarachnoid hemorrhage

Background

Aneurysmal subarachnoid hemorrhage (aSAH) is a serious type of hemorrhagic stroke. It is very important to predict the prognosis at early phase. In this work, we intend to characterize early changes in peripheral blood cells after aSAH and explore the association between peripheral blood cells and clinical outcomes after aSAH.

Methods

aSAH patients admitted between December 2019 and September 2022 were enrolled. A retrospective observational study was performed. Total leukocytes, monocytes, neutrophils, erythrocytes, lymphocytes and platelets counts were recorded on the day of admission (day 1), day 3, day 5 and day 7. Statistical tests included Chi-square test, analysis of variance and multivariate logistic regression (MLR) models. 197 patients were analyzed.

Results

Leukocytes and neutrophils were higher in poor outcome groups from day 1 to day 7 and in delayed cerebral ischemia (DCI) groups from day 3 to day 7. Lymphocytes were higher at day 5 and day 7 in good outcome groups and no DCI groups. Neutrophil-to-lymphocyte ratio (NLR) was lower from day 3 to day 7 in good outcome groups and no DCI groups. Erythrocytes were higher from day 3 to day 7 in good outcome groups and no DCI groups. Lymphocytes were negatively related to poor outcomes on day 1 (OR = 0.457), indicating higher lymphocytes predicted good outcomes, Neutrophils were positively related to poor outcomes on day 3 (OR = 3.003) indicating higher neutrophils predicted poor outcomes. Lymphocytes were negatively related to DCI on day 5 (OR = 0.388) indicating higher lymphocytes predicted no DCI, Erythrocytes were negatively related to DCI on day 5 (OR = 0.335) and day 7 (OR = 0.204) indicating higher erythrocytes predicted no DCI. The improved ability of neutrophils, lymphocytes and erythrocytes to predict DCI or poor functional outcomes were revealed by ROC curve analysis.

Conclusions

The dynamic changes of peripheral blood cell counts were related to poor functional outcomes and DCI after aSAH. Elevated neutrophils, leukocytes, NLR, and decreased lymphocytes, erythrocytes were accompanied by DCI and poor outcome. Neutrophils, lymphocytes and erythrocytes counts could be beneficial to predict DCI and outcomes after aSAH.

Development and performance assessment of novel machine learning models for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage patients: external validation in MIMIC-IV

Background

Postoperative pneumonia (POP) is one of the primary complications after aneurysmal subarachnoid hemorrhage (aSAH) and is associated with postoperative mortality, extended hospital stay, and increased medical fee. Early identification of pneumonia and more aggressive treatment can improve patient outcomes. We aimed to develop a model to predict POP in aSAH patients using machine learning (ML) methods.

Methods

This internal cohort study included 706 patients with aSAH undergoing intracranial aneurysm embolization or aneurysm clipping. The cohort was randomly split into a train set (80%) and a testing set (20%). Perioperative information was collected from participants to establish 6 machine learning models for predicting POP after surgical treatment. The area under the receiver operating characteristic curve (AUC), precision-recall curve were used to assess the accuracy, discriminative power, and clinical validity of the predictions. The final model was validated using an external validation set of 97 samples from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database.

Results

In this study, 15.01% of patients in the training set and 12.06% in the testing set with POP after underwent surgery. Multivariate logistic regression analysis showed that mechanical ventilation time (MVT), Glasgow Coma Scale (GCS), Smoking history, albumin level, neutrophil-to-albumin Ratio (NAR), c-reactive protein (CRP)-to-albumin ratio (CAR) were independent predictors of POP. The logistic regression (LR) model presented significantly better predictive performance (AUC: 0.91) than other models and also performed well in the external validation set (AUC: 0.89).

Conclusion

A machine learning model for predicting POP in aSAH patients was successfully developed using a machine learning algorithm based on six perioperative variables, which could guide high-risk POP patients to take appropriate preventive measures.

Neutrophils and Neutrophil Extracellular Traps Cause Vascular Occlusion and Delayed Cerebral Ischemia After Subarachnoid Hemorrhage in Mice

BACKGROUND

After subarachnoid hemorrhage (SAH), neutrophils are deleterious and contribute to poor outcomes. Neutrophils can produce neutrophil extracellular traps (NETs) after ischemic stroke. Our hypothesis was that, after SAH, neutrophils contribute to delayed cerebral ischemia (DCI) and worse outcomes via cerebrovascular occlusion by NETs.

METHODS

SAH was induced via endovascular perforation, and SAH mice were given either a neutrophil-depleting antibody, a PAD4 (peptidylarginine deiminase 4) inhibitor (to prevent NETosis), DNAse-I (to degrade NETs), or a vehicle control. Mice underwent daily neurological assessment until day 7 and then euthanized for quantification of intravascular brain NETs (iNETs). Subsets of mice were used to quantify neutrophil infiltration, NETosis potential, iNETs, cerebral perfusion, and infarction. In addition, NET markers were assessed in the blood of aneurysmal SAH patients.

RESULTS

In mice, SAH led to brain neutrophil infiltration within 24 hours, induced a pro-NETosis phenotype selectively in skull neutrophils, and caused a significant increase in iNETs by day 1, which persisted until at least day 7. Neutrophil depletion significantly reduced iNETs, improving cerebral perfusion, leading to less neurological deficits and less incidence of DCI (16% versus 51.9%). Similarly, PAD4 inhibition reduced iNETs, improved neurological outcome, and reduced incidence of DCI (5% versus 30%), whereas degrading NETs marginally improved outcomes. Patients with aneurysmal SAH who developed DCI had elevated markers of NETs compared with non-DCI patients.

CONCLUSIONS

After SAH, skull-derived neutrophils are primed for NETosis, and there are persistent brain iNETs, which correlated with delayed deficits. The findings from this study suggest that, after SAH, neutrophils and NETosis are therapeutic targets, which can prevent vascular occlusion by NETs in the brain, thereby lessening the risk of DCI. Finally, NET markers may be biomarkers, which can predict which patients with aneurysmal SAH are at risk for developing DCI.

The neutrophil-to-lymphocyte ratio is associated with the frequency of delayed neurologic sequelae in patients with carbon monoxide poisoning

Delayed neurologic sequelae (DNS) is a common complication in patients with carbon monoxide poisoning (COP). We aimed to investigate the association of the neutrophil-to-lymphocyte ratio (NLR) with the frequency of DNS in COP patients. A total of 371 COP patients were investigated in retrospective and prospective studies. A receiver operator curve (ROC) test was performed to evaluate the ability of the NLR to predict DNS in COP patients. The retrospective study included 288 COP patients, of whom 84 (29.2%) were confirmed to have DNS, and 1 (0.3%) died within 28 days. The NLR in the DNS group was significantly higher than that in the non-DNS group (6.84 [4.22-12.43] vs. 3.23 [1.91-5.60] × 109/L). NLR was a significant predictor of the frequency of DNS [odds ratio (OR): 1.130, 95% confidence interval (CI): 1.030, 1.240] in COP patients. The area under the ROC curve of NLR for predicting DNS was 0.766 (95% CI 0.701, 0.832), and the cut-off value was 3.745 (sensitivity, 83.3%; specificity, 58.8%). The prospective study included 83 COP patients, of whom 19 (22.9%) were confirmed to have DNS, and all patients survived. Moreover, the frequency of DNS in the patients with an NLR ≥ 3.745 was notably higher than that in the patients with an NLR < 3.745 [41.4% (12/29) vs. 13.0 (7/54)]. In conclusion, the NLR was a significant, independent predictor of the frequency of DNS in COP patients.

Predicting the Outcome of Patients with Aneurysmal Subarachnoid Hemorrhage: A Machine-Learning-Guided Scorecard

Aneurysmal subarachnoid hemorrhage (aSAH) frequently causes long-term disability, but predicting outcomes remains challenging. Routine parameters such as demographics, admission status, CT findings, and blood tests can be used to predict aSAH outcomes. The aim of this study was to compare the performance of traditional logistic regression with several machine learning algorithms using readily available indicators and to generate a practical prognostic scorecard based on machine learning. Eighteen routinely available indicators were collected as outcome predictors for individuals with aSAH. Logistic regression (LR), random forest (RF), support vector machines (SVMs), and fully connected neural networks (FCNNs) were compared. A scorecard system was established based on predictor weights. The results show that machine learning models and a scorecard achieved 0.75~0.8 area under the curve (AUC) predicting aSAH outcomes (LR 0.739, RF 0.749, SVM 0.762~0.793, scorecard 0.794). FCNNs performed best (~0.95) but lacked interpretability. The scorecard model used only five factors, generating a clinically useful tool with a total cutoff score of ≥5, indicating poor prognosis. We developed and validated machine learning models proven to predict outcomes more accurately in individuals with aSAH. The parameters found to be the most strongly predictive of outcomes were NLR, lymphocyte count, monocyte count, hypertension status, and SEBES. The scorecard system provides a simplified means of applying predictive analytics at the bedside using a few key indicators.

HDL anti-inflammatory function is impaired and associated with high SAA1 and low APOA4 levels in aneurysmal subarachnoid hemorrhage

Aneurysmal subarachnoid hemorrhage (aSAH) is a devastating disease with high morbidity and mortality rates. Within 24 hours after aSAH, monocytes are recruited and enter the subarachnoid space, where they mature into macrophages, increasing the inflammatory response and contributing, along with other factors, to delayed neurological dysfunction and poor outcomes. High-density lipoproteins (HDL) are lipid-protein complexes that exert anti-inflammatory effects but under pathological conditions undergo structural alterations that have been associated with loss of functionality. Plasma HDL were isolated from patients with aSAH and analyzed for their anti-inflammatory activity and protein composition. HDL isolated from patients lost the ability to prevent VCAM-1 expression in endothelial cells (HUVEC) and subsequent adhesion of THP-1 monocytes to the endothelium. Proteomic analysis showed that HDL particles from patients had an altered composition compared to those of healthy subjects. We confirmed by western blot that low levels of apolipoprotein A4 (APOA4) and high of serum amyloid A1 (SAA1) in HDL were associated with the lack of anti-inflammatory function observed in aSAH. Our results indicate that the study of HDL in the pathophysiology of aSAH is needed, and functional HDL supplementation could be considered a novel therapeutic approach to the treatment of the inflammatory response after aSAH.

Neutrophil to Lymphocyte Ratio and Serum Biomarkers : A Potential Tool for Prediction of Clinically Relevant Cerebral Vasospasm after Aneurysmal Subarachnoid Hemorrhage

OBJECTIVE

Subarachnoid hemorrhage (SAH) is a condition characterized by bleeding in the subarachnoid space, often resulting from the rupture of a cerebral aneurysm. Delayed cerebral ischemia caused by vasospasm is a significant cause of mortality and morbidity in SAH patients, and inflammatory markers such as systemic inflammatory response index (SIRI), systemic inflammatory index (SII), neutrophil-to-lymphocyte ratio (NLR), and derived NLR (dNLR) have shown potential in predicting clinical vasospasm and outcomes in SAH patients. This article aims to investigate the relationship between inflammatory markers and cerebral vasospasm after aneurysmatic SAH (aSAH) and evaluate the predictive value of various indices, including SIRI, SII, NLR, and dNLR, in predicting clinical vasospasm.

METHODS

A retrospective analysis was performed on a cohort of 96 patients who met the inclusion criteria out of a total of 139 patients admitted Trakya University Hospital with a confirmed diagnosis of aSAH between January 2013 and December 2021. Diagnostic procedures, neurological examinations, and laboratory tests were performed to assess the patients' condition. The Student's t-test compared age variables, while the chi-square test compared categorical variables between the non-vasospasm (NVS) and vasospasm (VS) groups. Receiver operating characteristic (ROC) curve analyses were used to evaluate the diagnostic accuracy of laboratory parameters, calculating the area under the ROC curve, cut-off values, sensitivity, and specificity. A significance level of p<0.05 was considered statistically significant.

RESULTS

The study included 96 patients divided into two groups : NVS and VS. Various laboratory parameters, such as NLR, SII, and dNLR, were measured daily for 15 days, and statistically significant differences were found in NLR on 7 days, with specific cut-off values identified for each day. SII showed a significant difference on day 9, while dNLR had significant differences on days 2, 4, and 9. Graphs depicting the values of these markers for each day are provided.

CONCLUSION

Neuroinflammatory biomarkers, when used alongside radiology and scoring scales, can aid in predicting prognosis, determining severity and treatment decisions for aSAH, and further studies with larger patient groups are needed to gain more insights.

A dynamic online nomogram for predicting death in hospital after aneurysmal subarachnoid hemorrhage

BACKGROUND

This study aimed to validate the efficacy the multiplication of neutrophils and monocytes (MNM) and a novel dynamic nomogram for predicting in-hospital death in patients with aneurysmal subarachnoid hemorrhage (aSAH).

METHODS

Retrospective study was done on 986 patients with endovascular coiling for aSAH. Independent risk factors associated with in-hospital death were identified using both univariate and multivariate logistic regression analysis. In the development cohort, a dynamic nomogram of in-hospital deaths was introduced and made available online as a straightforward calculator. To predict the in-hospital death from the external validation cohort by nomogram, calibration analysis, decision curve analysis, and receiver operating characteristic analysis were carried out.

RESULTS

72/687 patients (10.5%) in the development cohort and 31/299 patients (10.4%) in the validation cohort died. MNM was linked to in-hospital death in univariate and multivariate regression studies. In the development cohort, a unique nomogram demonstrated a high prediction ability for in-hospital death. According to the calibration curves, the nomogram has a reliable degree of consistency and calibration. With threshold probabilities between 10% and 90%, the nomogram's net benefit was superior to the basic model. The MNM and nomogram also exhibited good predictive values for in-hospital death in the validation cohort.

CONCLUSIONS

MNM is a novel predictor of in-hospital mortality in patients with aSAH. For aSAH patients, a dynamic nomogram is a useful technique for predicting in-hospital death.

Inflammatory Burden Index: Association Between Novel Systemic Inflammatory Biomarkers and Prognosis as Well as in-Hospital Complications of Patients with Aneurysmal Subarachnoid Hemorrhage

Purpose

Systemic inflammation plays an important role in the pathophysiology and progression of aneurysmal subarachnoid hemorrhage (aSAH). In this study, we aimed to investigate the association between a new biomarker, the inflammatory burden index (IBI) and the prognosis as well as in-hospital complications of aSAH patients.

Patients and Methods

We analyzed data from patients with aSAH between January 2019 and September 2022 who were included in the LongTEAM (Long-term Prognosis of Emergency Aneurysmal Subarachnoid Hemorrhage) registry study. The IBI was formulated as C-reactive protein × neutrophils/lymphocytes. The unfavorable functional prognosis was assessed by the modified Rankin Scale (mRS). Receiver operating characteristic (ROC) curve analysis was conducted to determine the optimal cut-off values for IBI to distinguish the unfavorable functional prognosis. Multivariate logistic regression was applied to investigate the association between IBI and in-hospital complications. Propensity score matching was adjusted for imbalances in baseline characteristics to assess the effect of IBI on prognosis.

Results

A total of 408 consecutive patients with aSAH enrolled in the study, of which 235 (57.6%) were female patients and the mean age was 55.28 years old. An IBI equal to 138.03 was identified as the best cut-off threshold to distinguish the unfavorable prognosis at 3 months (area under the curve [AUC] [95% CI] 0.637 [0.568-0.706]). ln IBI was independently associated with 3-month functional prognosis (OR [95% CI] 1.362 [1.148-1.615]; P<0.001), pneumonia (OR [95% CI] 1.427 [1.227-1.659]; P<0.001) and deep venous thrombosis (DVT). (OR [95% CI] 1.326 [1.124-1.564]; P=0.001). After propensity score matching (57:57), an increased proportion of patients with IBI ≥138.03 had a poor functional prognosis at 3 months and in-hospital complications including developed pneumonia and DVT.

Conclusion

In patients with aSAH, high IBI level at admission was associated with unfavorable functional prognosis as well as pneumonia and deep vein thrombosis.

Prognostic nomogram for predicting lower extremity deep venous thrombosis in ruptured intracranial aneurysm patients who underwent endovascular treatment

Background

Lower extremity deep vein thrombosis (DVT) is one of the major postoperative complications in patients with ruptured intracranial aneurysms (RIA) who underwent endovascular treatment (EVT). However, patient-specific predictive models are still lacking. This study aimed to construct and validate a nomogram model for estimating the risk of lower extremity DVT for RIA patients who underwent EVT.

Methods

This cohort study enrolled 471 RIA patients who received EVT in our institution between 1 January 2020 to 4 February 2022. Perioperative information on participants is collected to develop and validate a nomogram for predicting lower extremity DVT in RIA patients after EVT. Predictive accuracy, discriminatory capability, and clinical effectiveness were evaluated by concordance index (C-index), calibration curves, and decision curve analysis.

Result

Multivariate logistic regression analysis showed that age, albumin, D-dimer, GCS score, middle cerebral artery aneurysm, and delayed cerebral ischemia were independent predictors for lower extremity DVT. The nomogram for assessing individual risk of lower extremity DVT indicated good predictive accuracy in the primary cohort (c-index, 0.92) and the validation cohort (c-index, 0.85), with a wide threshold probability range (4-82%) and superior net benefit.

Conclusion

The present study provided a reliable and convenient nomogram model developed with six optimal predictors to assess postoperative lower extremity DVT in RIA patients, which may benefit to strengthen the awareness of lower extremity DVT control and supply appropriate resources to forecast patients at high risk of RIA-related lower extremity DVT.

A correlation and prediction study of the poor prognosis of high-grade aneurysmal subarachnoid hemorrhage from the neutrophil percentage to albumin ratio

OBJECTIVE

Inflammatory response and nutritional status play crucial roles in patients with aneurysmal subarachnoid hemorrhage (aSAH). This study mainly investigated the correlation between neutrophil percentage to albumin ratio (NPAR) and clinical prognosis in aSAH patients with high-grade Hunt-Hess and its predictive model.

METHODS

A retrospective analysis was conducted based on 806 patients with aneurysmal subarachnoid hemorrhage who were admitted to the studied hospital from January 2017 to December 2021. Modified Fisher grade and Hunt-Hess grade were obtained according to their status at admission and hematological parameters within 48 h after hemorrhage. Univariate and multivariate logistic regression analysis were conducted to evaluate the relationship between NPAR and the clinical prognosis of patients with aSAH. And propensity matching analysis of patients with aSAH in the severe group. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cut-off value of NPAR at admission to predict prognosis and its sensitivity and specificity. The nomogram diagram and Calibration curve were further used to examine the prediction model.

RESULTS

According to the mRS score at discharge, 184 (22.83 %) cases were classified as having poor outcomes (mRS > 2). Through multivariate logistic regression analysis, it was found that the Modified Fisher grade at admission, Hunt-Hess grade, eosinophils, neutrophil to lymphocyte ratio (NLR), and NPAR were independent risk factors for poor outcome in patients with aSAH (p < 0.05). The NPAR of aSAH patients with poor outcomes in the high-grade group was significantly higher than that in the low-grade group. The optimal cut-off value for NPAR was 21.90, the area under the ROC curve was 0.780 (95 % CI 0.700 - 0.861, p < 0.001). The Calibration curves show that the predicted probability of the drawn nomogram is overall consistent with the actual probability. (Mean absolute error = 0.031) CONCLUSION: The NPAR value of patients with aSAH at admission is significantly correlated with Hunt-Hess grade in a positive manner, namely, the higher the Hunt-Hess grade, the higher the NPAR value, and the worse the prognosis. Findings indicate that early NPAR value can be used as a feasible biomarker to predict the clinical prognosis of patients with aSAH.

Neutrophil-to-lymphocyte ratio predicted cerebral infarction and poor discharge functional outcome in aneurysmal subarachnoid hemorrhage: A propensity score matching analysis

Background

Neutrophil-lymphocyte-ratio (NLR) and platelet-lymphocyte-ratio (PLR) have emerged as potential biomarkers in predicting the outcomes of aneurysmal subarachnoid hemorrhage (aSAH). Since a study was never conducted on the Southeast Asian and Indonesian population, we designed the present study to evaluate the potential of NLR and PLR in predicting cerebral infarction and functional outcomes and find the optimal cutoff value.

Methods

We retrospectively reviewed patients admitted for aSAH in our hospital between 2017 and 2021. The diagnosis was made using a computed tomography (CT) scan or magnetic resonance imaging and CT angiography. Association between admission NLR and PLR and the outcomes were analyzed using a multivariable regression model. A receiver operating characteristic (ROC) analysis was done to identify the optimal cutoff value. A propensity score matching (PSM) was then carried out to reduce the imbalance between the two groups before comparison.

Results

Sixty-three patients were included in the study. NLR was independently associated with cerebral infarction (odds ratio, OR 1.197 [95% confidence interval, CI 1.027-1.395] per 1-point increment; P = 0.021) and poor discharge functional outcome (OR 1.175 [95% CI 1.036-1.334] per 1-point increment; P = 0.012). PLR did not significantly correlate with the outcomes. ROC analysis identified 7.09 as the cutoff for cerebral infarction and 7.50 for discharge functional outcome. Dichotomizing and performing PSM revealed that patients with NLR above the identified cutoff value significantly had more cerebral infarction and poor discharge functional outcome.

Conclusion

NLR demonstrated a good prognostic capability in Indonesian aSAH patients. More studies should be conducted to find the optimal cutoff value for each population.

Immunological Profile of Vasospasm after Subarachnoid Hemorrhage

Subarachnoid hemorrhage (SAH) carries high mortality and disability rates, which are substantially driven by complications. Early brain injury and vasospasm can happen after SAH and are crucial events to prevent and treat to improve prognosis. In recent decades, immunological mechanisms have been implicated in SAH complications, with both innate and adaptive immunity involved in mechanisms of damage after SAH. The purpose of this review is to summarize the immunological profile of vasospasm, highlighting the potential implementation of biomarkers for its prediction and management. Overall, the kinetics of central nervous system (CNS) immune invasion and soluble factors' production critically differs between patients developing vasospasm compared to those not experiencing this complication. In particular, in people developing vasospasm, a neutrophil increase develops in the first minutes to days and pairs with a mild depletion of CD45+ lymphocytes. Cytokine production is boosted early on after SAH, and a steep increase in interleukin-6, metalloproteinase-9 and vascular endothelial growth factor (VEGF) anticipates the development of vasospasm after SAH. We also highlight the role of microglia and the potential influence of genetic polymorphism in the development of vasospasm and SAH-related complications.

Systemic innate myeloid responses to acute ischaemic and haemorrhagic stroke

Acute ischaemic and haemorrhagic stroke account for significant disability and morbidity burdens worldwide. The myeloid arm of the peripheral innate immune system is critical in the immunological response to acute ischaemic and haemorrhagic stroke. Neutrophils, monocytes, and dendritic cells (DC) contribute to the evolution of pathogenic local and systemic inflammation, whilst maintaining a critical role in ongoing immunity protecting against secondary infections. This review aims to summarise the key alterations to myeloid immunity in acute ischaemic stroke, intracerebral haemorrhage (ICH), and subarachnoid haemorrhage (SAH). By integrating clinical and preclinical research, we discover how myeloid immunity is affected across multiple organ systems including the brain, blood, bone marrow, spleen, and lung, and evaluate how these perturbations associate with real-world outcomes including infection. These findings are placed in the context of the rapidly developing field of human immunology, which offers a wealth of opportunity for further research.

Systemic Inflammatory Response in Spontaneous Subarachnoid Hemorrhage from Aneurysmal Rupture versus Subarachnoid Hemorrhage of Unknown Origin

OBJECTIVE

It is well known that spontaneous non-aneurysmal subarachnoid hemorrhage (SAH), also known as sine materia SAH (smSAH), has usually a better course and prognosis than its aneurysmal counterpart (aSAH). This might depend on different inflammatory mechanisms initiated by bleeding events of different origins. The aim of the present study was to explore the systemic inflammatory response in spontaneous SAH, comparing aSAH and smSAH.

METHODS

We performed a prospective observational study over a consecutive series of patients with SAH. For these patients, we collected all clinical data and, furthermore, performed venous blood sampling over six time points to analyze blood cells. We further performed the analysis of lymphocytes and monocytes by means of flow cytometry to quantify common subtypes. Statistical analysis included a t-student test, Chi-square test, multivariate logistic regression, and ROC analysis.

RESULTS

48 patients were included: six (12.5%) with a diagnosis of spontaneous smSAH, and forty-two patients (87.5%) with aSAH. Significant differences on Day 0 were found for neutrophils and a systemic neuro-inflammatory index, namely, systemic inflammatory response index (SIRI). At the ROC analysis, neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and SIRI exhibited satisfactory predictive power on day 0. At the multivariable logistic regression analysis, the combined index (NLR, LMR, SIRI at day 0) yielded an OR of 0.59 (95% CI 0.29-1.21]). LMR at day 0 yielded an OR of 1.25 ([95% CI 0.94-1.68]), NLR at day 0 exhibited an OR of 0.68 ([95% CI 0.42-1.09]), and SIRI at day 0 displayed an OR of 0.31 ([95% CI 0.06-1.49]).

CONCLUSION

This preliminary study indicated a possible role of some inflammatory indices that point out the importance of innate and adaptive immunity in the etiopathogenetic mechanisms. Drugs modulating these responses could eventually counteract or, at least, reduce secondary damage associated with SAH.

Correlation between the Neutrophil-to-Lymphocyte Ratio and Multiple Sclerosis: Recent Understanding and Potential Application Perspectives

Multiple sclerosis (MS) is a chronic debilitating immune-mediated disease of the central nervous system, which causes demyelination and neuroaxonal damage. Low-grade systemic inflammation has been considered to lead to pathogenesis owing to the amplification of pathogenic immune response activation. However, there is a shortage of reliable systemic inflammatory biomarkers to predict the disease activity and progression of MS. In MS patients, a series of cytokines and chemokines promote the proliferation of neutrophils and lymphocytes and their transfer to the central nervous system. The neutrophil-to-lymphocyte ratio (NLR), which combines the information of the inherent and adaptive parts of the immune system, represents a reliable measure of the inflammatory burden. In this review, we aimed to discuss the inflammatory response in MS, mainly the function of lymphocytes and neutrophils, which can be implemented in the utility of NLR as a diagnostic tool in MS patients. The underlying pathophysiology is highlighted to identify new potential targets for neuroprotection and to develop novel therapeutic strategies.

Admission Serum Iron as an Independent Risk Factor for Postoperative Delayed Cerebral Ischemia Following Aneurysmal Subarachnoid Hemorrhage: A Propensity-Matched Analysis

This study aimed to investigate the association between serum iron (SI) and postoperative delayed cerebral ischemia (DCI) following aneurysmal subarachnoid hemorrhage (aSAH). We retrospectively analyzed 985 consecutive adult patients diagnosed with aSAH. Demographic, clinical, and laboratory data were recorded. Univariate and multivariate analyses were employed to assess the association between SI and DCI. Propensity-score matching (PSM) analysis was implemented to reduce confounding. Postoperative DCI developed in 14.38% of patients. Lower SI upon admission was detected in aSAH patients with severe clinical conditions and severe aSAH. SI was negatively correlated with WFNS grade (r = −0.3744, p < 0.001) and modified Fisher (mFisher) grade (r = −0.2520, p < 0.001). Multivariable analysis revealed lower SI was independently associated with DCI [odds ratios (OR) 0.281, 95% confidence interval (CI) 0.177−0.448, p < 0.001], while WFNS grade and mFisher grade were not. The receiver-operating characteristics (ROC) curve analysis of SI for DCI gave an area under the curve (AUC) of 0.7 and an optimal cut-off of 7.5 μmol/L (95% CI 0.665 to 0.733, p < 0.0001). PSM demonstrated the DCI group had a significantly lower SI than the non-DCI group (10.91 ± 6.86 vs. 20.34 ± 8.01 μmol/L, p < 0.001). Lower SI remained a significant independent predictor for DCI and an independent poor prognostic factor of aSAH in multivariate analysis (OR 0.363, 95% CI 0.209−0.630, p < 0.001). The predictive performance of SI for poor outcome had a corresponding AUC of 0.718 after PSM. Lower SI upon admission is significantly associated with WFNS grade, mFisher grade, and predicts postoperative DCI and poor outcome at 90 days following aSAH.

Routine laboratory parameters, including complete blood count, predict COVID-19 in-hospital mortality in geriatric patients

To reduce the mortality of COVID-19 older patients, clear criteria to predict in-hospital mortality are urgently needed. Here, we aimed to evaluate the performance of selected routine laboratory biomarkers in improving the prediction of in-hospital mortality in 641 consecutive COVID-19 geriatric patients (mean age 86.6 ± 6.8) who were hospitalized at the INRCA hospital (Ancona, Italy). Thirty-four percent of the enrolled patients were deceased during the in-hospital stay. The percentage of severely frail patients, assessed with the Clinical Frailty Scale, was significantly increased in deceased patients compared to the survived ones. The age-adjusted Charlson comorbidity index (CCI) score was not significantly associated with an increased risk of death. Among the routine parameters, neutrophilia, eosinopenia, lymphopenia, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein, procalcitonin, IL-6, and NT-proBNP showed the highest predictive values. The fully adjusted Cox regressions models confirmed that high neutrophil %, NLR, derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), and low lymphocyte count, eosinophil %, and lymphocyte-to-monocyte ratio (LMR) were the best predictors of in-hospital mortality, independently from age, gender, and other potential confounders. Overall, our results strongly support the use of routine parameters, including complete blood count, in geriatric patients to predict COVID-19 in-hospital mortality, independent from baseline comorbidities and frailty.

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.

Clinical Value of Inflammatory Cytokines in Patients with Aneurysmal Subarachnoid Hemorrhage

Background

Inflammation is closely associated with prognosis in patients with aneurysmal subarachnoid hemorrhage (aSAH), which is orchestrated by inflammatory cytokines. Therefore, this study aimed to investigate the levels of inflammatory cytokines in the early stage of aSAH and their predictive value for prognosis.

Methods

In this retrospective study, 206 patients with aSAH were recruited and assigned to a severe group (WFNS grade ≥ 4) and a mild group (WFNS grade < 4) according to the severity of patients on admission. Flow cytometry was performed to detect the levels of 12 inflammatory cytokines in the serum of patients. Then, patients were grouped into a poor prognosis group (mRS score ≥ 4) and a good prognosis group (mRS score < 4) based on their prognosis after 3 months of discharge to compare the relationship between cytokines and prognosis. Propensity score matching (PSM) was utilized to control confounding factors. The correlation between inflammatory factors and prognosis was determined using Spearman correlation, and the predictive efficacy of inflammatory factors was tested by a receiver operating characteristic curve.

Results

Serum IL-1β, IL-5, IL-6, IL-8, IL-10, IFN-γ, and TNF-α levels were significantly higher in the mild group than in the severe group and in the poor prognosis group than in the good prognosis group. After PSM, the differences in IL-1β, IL-5, IFN-α, and IFN-γ levels disappeared between the two groups, whereas IL-2, IL-6, IL-8, IL-10, and TNF-α levels remained higher in the poor prognosis group than in the good prognosis group. Additionally, IL-2, IL-6, IL-8, and IL-10 levels were positively correlated with mRS scores. Moreover, the predictive value was found to be the highest for IL-6 and the lowest for TNF-α.

Conclusion

Inflammation degree was related to the severity of aSAH. Inflammatory markers, including IL-6, IL-10, IL-8, IL-2, and TNF-α, might predict the poor prognosis of aSAH.