The significance of eosinophils in predicting the severity of acute ischemic stroke

Symptomatic intracranial hemorrhage mediates the association between eosinophils and 90-day outcomes after mechanical thrombectomy for acute ischemic stroke

BACKGROUND

Decreased eosinophil level is associated with poor outcomes after mechanical thrombectomy in patients with acute ischemic stroke (AIS), but the underlying mechanism of this association is elusive. We aimed to assess the mediation effect of symptomatic intracranial hemorrhage (sICH) on the aforementioned association.

METHODS

A total of 328 consecutive AIS patients undergoing mechanical thrombectomy between May 2017 and March 2021 were analyzed. SICH was defined as any evidence of brain hemorrhage on CT scan with neurological deterioration. Regression analysis was used to assess the effect of eosinophils on sICH, and its effect on poor outcome. Mediation analysis was performed to assess the proportion of total effect by sICH on the association between eosinophils and poor outcome.

RESULTS

Multivariate analysis revealed an independent association between eosinophil count and sICH after adjusting for potential confounders (odds ratio, 0.00; 95% CI, 0.00-0.01; P = 0.0141), which is consistent with the result of eosinophil count (dichotomous) as a categorical variable (odds ratio, 0.22; 95% CI, 0.11-0.46; P < 0.0001). Eosinophil count was negatively associated with poor outcome (odds ratio, 0.00; 95% CI, 0.00-0.02; P = 0.0021). Mediation analysis revealed that sICH partially mediated the negative relationship between eosinophil count and poor outcome (indirect effect=-0.1896; 95%CI: -0.3654 - -0.03, P < 0.001).

CONCLUSION

This study showed an important effect of sICH on the association between eosinophils and poor outcome.

Stroke mortality prediction based on ensemble learning and the combination of structured and textual data

For severe cerebrovascular diseases such as stroke, the prediction of short-term mortality of patients has tremendous medical significance. In this study, we combined machine learning models Random Forest classifier (RF), Adaptive Boosting (AdaBoost), Extremely Randomised Trees (ExtraTree) classifier, XGBoost classifier, TabNet, and DistilBERT to construct a multi-level prediction model that used bioassay data and radiology text reports from haemorrhagic and ischaemic stroke patients to predict six-month mortality. The performances of the prediction models were measured using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), precision, recall, and F1-score. The prediction models were built with the use of data from 19,616 haemorrhagic stroke patients and 50,178 ischaemic stroke patients. Novel six-month mortality prediction models for these patients were developed, which enhanced the performance of the prediction models by combining laboratory test data, structured data, and textual radiology report data. The achieved performances were as follows: AUROC = 0.89, AUPRC = 0.70, precision = 0.52, recall = 0.78, and F1 score = 0.63 for haemorrhagic patients, and AUROC = 0.88, AUPRC = 0.54, precision = 0.34, recall = 0.80, and F1 score = 0.48 for ischaemic patients. Such models could be used for mortality risk assessment and early identification of high-risk stroke patients. This could contribute to more efficient utilisation of healthcare resources for stroke survivors.

Peripheral eosinophil trends and clinical outcomes after non-traumatic subarachnoid hemorrhage

Background/objective

Uncontrolled systemic inflammation after non-traumatic subarachnoid hemorrhage (SAH) is associated with worse outcomes. Changes in the peripheral eosinophil count have been linked to worse clinical outcomes after ischemic stroke, intracerebral hemorrhage, and traumatic brain injury. We aimed to investigate the association of eosinophil counts with clinical outcomes after SAH.

Methods

This retrospective observational study included patients with SAH admitted from January 2009 to July 2016. Variables included demographics, modified Fisher scale (mFS), Hunt-Hess Scale (HHS), global cerebral edema (GCE), and the presence of any infection. Peripheral eosinophil counts were examined as part of routine clinical care on admission and daily for 10 days after aneurysmal rupture. Outcome measures included dichotomized discharge mortality, modified Ranked Scale (mRS) score, delayed cerebral ischemia (DCI), vasospasm, and need for ventriculoperitoneal shunt (VPS). Statistical tests included the chi-square test, Student's t-test, and multivariable logistic regression (MLR) model.

Results

A total of 451 patients were included. The median age was 54 (IQR 45, 63) years, and 295 (65.4%) were female patients. On admission, 95 patients (21.1%) had a high HHS (>4), and 54 (12.0%) had GCE. A total of 110 (24.4%) patients had angiographic vasospasm, 88 (19.5%) developed DCI, 126 (27.9%) had an infection during hospitalization, and 56 (12.4%) required VPS. Eosinophil counts increased and peaked on days 8-10. Higher eosinophil counts on days 3-5 and day 8 were seen in patients with GCE (p < 0.05). Higher eosinophil counts on days 7-9 (p < 0.05) occurred in patients with poor discharge functional outcomes. In multivariable logistic regression models, higher day 8 eosinophil count was independently associated with worse discharge mRS (OR 6.72 [95% CI 1.27, 40.4], p = 0.03).

Conclusion

This study demonstrated that a delayed increase in eosinophils after SAH occurs and may contribute to functional outcomes. The mechanism of this effect and the relationship with SAH pathophysiology merit further investigation.

Identification of pyroptosis-related immune signature and drugs for ischemic stroke

Background: Ischemic stroke (IS) is a common and serious neurological disease, and multiple pathways of cell apoptosis are implicated in its pathogenesis. Recently, extensive studies have indicated that pyroptosis is involved in various diseases, especially cerebrovascular diseases. However, the exact mechanism of interaction between pyroptosis and IS is scarcely understood. Thus, we aimed to investigate the impact of pyroptosis on IS-mediated systemic inflammation.

Methods: First, the RNA regulation patterns mediated by 33 pyroptosis-related genes identified in 20 IS samples and 20 matched-control samples were systematically evaluated. Second, a series of bioinformatics algorithms were used to investigate the contribution of PRGs to IS pathogenesis. We determined three composition classifiers of PRGs which potentially distinguished healthy samples from IS samples according to the risk score using single-variable logistic regression, LASSO-Cox regression, and multivariable logistic regression analyses. Third, 20 IS patients were classified by unsupervised consistent cluster analysis in relation to pyroptosis. The association between pyroptosis and systemic inflammation characteristics was explored, which was inclusive of immune reaction gene sets, infiltrating immunocytes and human leukocyte antigen genes.

Results: We identified that AIM2, SCAF11, and TNF can regulate immuno-inflammatory responses after strokes via the production of inflammatory factors and activation of the immune cells. Meanwhile, we identified distinct expression patterns mediated by pyroptosis and revealed their immune characteristics, differentially expressed genes, signaling pathways, and target drugs.

Conclusion: Our findings lay a foundation for further research on pyroptosis and IS systemic inflammation, to improve IS prognosis and its responses to immunotherapy.

Use of deep artificial neural networks to identify stroke during triage via subtle changes in circulating cell counts

Background

The development of tools that could help emergency department clinicians recognize stroke during triage could reduce treatment delays and improve patient outcomes. Growing evidence suggests that stroke is associated with several changes in circulating cell counts. The aim of this study was to determine whether machine-learning can be used to identify stroke in the emergency department using data available from a routine complete blood count with differential.

Methods

Red blood cell, platelet, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts were assessed in admission blood samples collected from 160 stroke patients and 116 stroke mimics recruited from three geographically distinct clinical sites, and an ensemble artificial neural network model was developed and tested for its ability to discriminate between groups.

Results

Several modest but statistically significant differences were observed in cell counts between stroke patients and stroke mimics. The counts of no single cell population alone were adequate to discriminate between groups with high levels of accuracy; however, combined classification using the neural network model resulted in a dramatic and statistically significant improvement in diagnostic performance according to receiver-operating characteristic analysis. Furthermore, the neural network model displayed superior performance as a triage decision making tool compared to symptom-based tools such as the Cincinnati Prehospital Stroke Scale (CPSS) and the National Institutes of Health Stroke Scale (NIHSS) when assessed using decision curve analysis.

Conclusions

Our results suggest that algorithmic analysis of commonly collected hematology data using machine-learning could potentially be used to help emergency department clinicians make better-informed triage decisions in situations where advanced imaging techniques or neurological expertise are not immediately available, or even to electronically flag patients in which stroke should be considered as a diagnosis as part of an automated stroke alert system.

The Construction and Analysis of Immune Infiltration and Competing Endogenous RNA Network in Acute Ischemic Stroke

Acute ischemic stroke (AIS) is a common neurological disease that seriously endangers both the physical and mental health of human. After AIS, activated immune cells are recruited to the stroke site, where inflammatory mediators are released locally, and severe immune inflammatory reactions occur within a short time, which affects the progress and prognosis of IS. Circular RNA (circRNA) is a type of non-coding RNA (ncRNA) with a closed-loop structure and high stability. Studies have found that circRNA can affect the course of IS. However, there is no report on ceRNA’s pathogenesis in AIS that is mediated by circRNA. In this study, the CIBERSORT algorithm was used to analyze the distribution of immune cells in patients with AIS. mRNA dataset was downloaded from the GEO database, and the weighted gene co-expression network analysis (WGCNA) method was used to construct weighted gene co-expression to determine 668 target genes, using GO, KEGG enrichment analysis, construction of protein-protein interaction (PPI) network analysis, and molecular complex detection (MCODE) plug-in analysis. The results showed that the biological function of the target gene was in line with the activation and immune regulation of neutrophils; signal pathways were mostly enriched in immune inflammation-related pathways. A Venn diagram was used to obtain 52 intersection genes between target genes and disease genes. By analyzing the correlation between the intersection genes and immune cells, we found that the top 5 hub genes were TOM1, STAT3, RAB3D, MDM2, and FOS, which were all significantly positively correlated with neutrophils and significantly negatively correlated with eosinophils. A total of 52 intersection genes and the related circRNA and miRNA were used as input for Cytoscape software to construct a circRNA-mediated ceRNA competition endogenous network, where a total of 18 circRNAs were found. Further analysis of the correlation between circRNA and immune cells found that 4 circRNAs are positively correlated with neutrophils. Therefore, we speculate that there may be a regulatory relationship between circRNA-mediated ceRNA and the immune mechanism in AIS. This study has important guiding significance for the progress, outcome of AIS, and the development of new medicine.

Eosinophil-to-Neutrophil Ratio Predicts Poor Prognosis of Acute Ischemic Stroke Patients Treated With Intravenous Thrombolysis

Background and Purpose: The eosinophil-to-neutrophil ratio (ENR) was recently reported as a novel inflammatory marker in acute ischemic stroke (AIS). However, few studies reported the predictive value of ENR in AIS patients, especially for those with intravenous thrombolysis.

Methods: Two hundred sixty-six AIS patients receiving intravenous thrombolysis were retrospectively recruited in this study and followed up for 3 months and 1 year. The Modified Rankin Scale (mRS) and the time of death were recorded. Poor outcome was defined as mRS 3–6. After excluding patients who were lost to follow-up, the remaining 250 patients were included in the 3-month prognosis analysis and the remaining 223 patients were included in the 1-year prognosis analysis.

Results: ENR levels in the patients were lower than those in the healthy controls. The optimal cutoff values for the ability of ENR × 10² to predict 3-month poor outcome were 0.74 with 67.8% sensitivity and 77.3% specificity. Patients with ENR × 10² ≥ 0.74 have a lower baseline National Institutes of Health Stroke Scale (NIHSS) score (median: 7 vs. 11, p < 0.001). After multivariate adjustment, patients with ENR × 10² ≥ 0.74 were more likely to come to a better 3-month outcome (OR = 0.163; 95% CI, 0.076–0.348, p < 0.001). At the 1-year follow-up, the patients with ENR × 10² ≥ 0.74 showed a lower risk of mortality (HR = 0.314; 95% CI, 0.135–0.731; p = 0.007).

Conclusions: A lower ENR is independently associated with a 3-month poor outcome and a 3-month and 1-year mortality in AIS patients treated with intravenous thrombolysis.

Dynamic Decrease in Eosinophil After Intravenous Thrombolysis Predicts Poor Prognosis of Acute Ischemic Stroke: A Longitudinal Study

Background and Purpose

Blood eosinophil counts are thought to be associated with atherosclerosis in acute ischemic stroke (AIS) and AIS severity. We aimed to investigate 1): the temporal profile of eosinophil in AIS patients treated with recombinant tissue plasminogen activator (r-tPA); 2): The association between dynamic eosinophil and 3-month outcomes in different AIS etiologies; 3): incremental predictive ability of dynamic eosinophil adding to conventional model; and 4): the longitudinal change of neutrophil-to-lymphocyte ratio (NLR) and compared its prognostic value with eosinophils.

Methods

A total of 623 AIS patients with intravenous thrombolysis in two hospitals were included. Blood samples were obtained on admission, within 24 h after an intravenous thrombolysis and on the seventh day. A multivariate logistic regression model with restricted cubic spline was performed to explore the association between dynamic eosinophil and a 3-month poor outcome. C-statistic, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were adopted to explore the incremental predictive ability.

Results

Percent change in eosinophil counts after intravenous thrombolysis was median -25.00% (IQR -68.25%-+14.29%). Decrease in eosinophil >75% after intravenous thrombolysis was associated with 2.585 times risk for poor outcome and 13.836 times risk for death. However, the association were weak for patients outside of cardioembolic stroke. Adding eosinophil changes to a conventional model improved the discriminatory ability of poor outcome (NRI = 53.3%; IDI = 2.2%) and death (NRI = 101.0%; IDI = 6.9%).

Conclusions

Dynamic decrease in eosinophil after intravenous thrombolysis predicts a 3-month poor outcome and death in AIS patients with r-tPA treatment and improved the predictive ability of conventional model. However, this result needs to be interpreted carefully in non-cardioembolic AIS patients.

Pathophysiological and pharmacological relevance of TLR4 in peripheral immune cells after stroke

Stroke is a very common disease being the leading cause of death and disability worldwide. The immune response subsequent to an ischemic stroke is a crucial factor in its physiopathology and outcome. This response is not limited to the injury site. In fact, the immune response to the ischemic process mobilizes mainly circulating cells which upon activation will be recruited to the injury site. When a stroke occurs, molecules that are usually retained inside the cell bodies are released into the extracellular space by uncontrolled cell death. These molecules can bind to the Toll-like receptor 4 (TLR4) in circulating immune cells which are then activated, eliciting, although not exclusively, the inflammatory response to the stroke. In this review, we present an up-to-date summary of the role of the different peripheral immune cells in stroke as well as the role of TLR4 in the function of each cell type in ischemia. Also, we summarize the different antagonists developed against TLR4 and their potential as a pharmacological tool for stroke treatment.

Eosinophil-to-Monocyte Ratio is a Potential Predictor of Prognosis in Acute Ischemic Stroke Patients After Intravenous Thrombolysis

Background

Eosinophil and monocyte have been demonstrated separately to be independent predictors of acute ischemic stroke (AIS). This study aimed to evaluate the association between eosinophil-to-monocyte ratio (EMR) and 3-month clinical outcome after treatment with recombinant tissue plasminogen activator (rt-PA) for AIS patients. Simultaneously, we made a simple comparison with other prognostic indicators, such as 24h neutrophil-to-lymphocyte ratio (NLR) and 24h platelet-to-lymphocyte ratio (PLR) to investigate the prognostic value of EMR.

Methods and Results

A total of 280 AIS patients receiving intravenous thrombolysis were retrospectively recruited for this study. Complete blood count evaluations for EMR were conducted on 24 hours admission. The poor outcome at 3-month was defined as the modified Rankin Scale (mRS) of 3–6 and the mRS score for death was 6. The EMR levels in patients with AIS were lower than those in the healthy controls and showed a negative correlation with the NIHSS score. At the 3-month follow-up, multivariate logistic regression analysis indicated an association among EMR, poor outcome and mortality. In addition, EMR had a higher predictive ability than popular biomarkers like NLR and PLR for 3-month mortality.

Conclusion

The lower levels of EMR were independently associated with poor outcome and dead status in AIS patients.

Leukocyte subtypes and adverse clinical outcomes in patients with acute ischemic cerebrovascular events

Background

Our study aimed to evaluate whether the effects on adverse clinical outcomes, defined as death, recurrent stroke, and poor functional outcomes, differed by leukocyte subtype in patients with acute ischemic cerebrovascular events, including both ischemic stroke and transient ischemic attack (TIA).

Methods

We derived data from the Third China National Stroke Registry (CNSR-III). The counts and percentages of each leukocyte subtype were collected within the first 24 hours after admission. Enrolled patients were classified into four groups by the quartiles of each leukocyte subtype count or percentage. Hazard ratios (HRs) or odds ratios (ORs) and their 95% confidence intervals (CIs) of adverse clinical outcomes were calculated, with the lowest quartile group as the reference category. We used C statistics, integrated discrimination improvement (IDI), and the net reclassification index (NRI) to evaluate each leukocyte subtype's incremental predictive value beyond conventional risk factors.

Results

A total of 14,174 patients were enrolled. Higher counts of leukocytes, neutrophils, and monocytes were associated with elevated risks of adverse clinical outcomes. In contrast, higher counts of lymphocytes and eosinophils were related to reduced risks of adverse clinical outcomes. Meanwhile, basophil counts seemed to not correlate with adverse clinical outcomes. Furthermore, there were also significant associations between the percentages of leukocyte subtypes and adverse clinical outcomes.

Conclusions

Leukocyte subtypes had different relationships with adverse clinical outcomes at 3-month and 1-year follow-up in patients with acute ischemic cerebrovascular events and could slightly increase the predictive value compared with the conventional model.

Relationship between blood eosinophil levels and COVID-19 mortality

OBJECTIVES

A novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is causing the worldwide coronavirus disease 2019 (COVID-19) outbreak with high mortality. A unique finding among COVID-19 patients was a decline of eosinophil levels (eosinopenia). However, results from previous studies on the relationship between eosinopenia and disease severity were inconsistent. The objective of this study is to determine the relationship between eosinopenia and COVID-19 mortality as well as the clinical conditions that could potentially lead to mortality.

METHODS

One hundred ninety patients diagnosed as moderate, severe, or critical COVID-19 at hospital admission were enrolled. Data collected from patients' medical records on the second day after hospital admission included medical histories, clinical symptoms, chest images of computed tomography (CT), laboratory examinations, and outcomes.

RESULTS

Eosinophil levels were significantly lower in patients with critical disease, when compared to those with moderate and severe diseases. After controlled for confounding factors, ie, age, gender, hypertension, coronary heart disease, diabetes, and chronic lung disease, a progressive decline of eosinophil levels was independently associated with mortality. Moreover, eosinophil levels significantly and positively correlated with platelet and D-dimer levels but significantly and inversely correlated with serum levels of urea, creatinine, aspartate aminotransferase, lactate dehydrogenase, and creatine kinase.

CONCLUSIONS

Eosinopenia, if progressively worsening, indicates that COVID-19 patients may progress to critical disease and have a significantly higher chance of mortality. Additionally, eosinopenia correlates with biomarkers of coagulation disorder and those of tissue damage in kidney, liver, and other tissues.

Eosinophil-to-monocyte ratio is a potential biomarker in the prediction of functional outcome among patients with acute ischemic stroke

BACKGROUND

It has been shown that eosinophils are decreased and monocytes are elevated in patients with acute ischemic stroke (AIS), but the impact of eosinophil-to-monocyte ratio (EMR) on clinical outcomes among AIS patients remains unclear. We aimed to determine the relationship between EMR on admission and 3-month poor functional outcome in AIS patients.

METHODS

A total of 521 consecutive patients admitted to our hospital within 24 h after onset of AIS were prospectively enrolled and categorized in terms of quartiles of EMR on admission between August 2016 and September 2018. The endpoint was the poor outcome defined as modified Rankin Scale score of 3 to 6 at month 3 after admission.

RESULTS

As EMR decreased, the risk of poor outcome increased (p < 0.001). Logistic regression analysis revealed that EMR was independently associated with poor outcome after adjusting potential confounders (odds ratio, 0.09; 95% CI 0.03-0.34; p = 0.0003), which is consistent with the result of EMR (quartile) as a categorical variable (odds ratio, 0.23; 95% CI 0.10-0.52; p_trend < 0.0001). A non-linear relationship was detected between EMR and poor outcome, whose point was 0.28. Subgroup analyses further confirmed these associations. The addition of EMR to conventional risk factors improved the predictive power for poor outcome (net reclassification improvement: 2.61%, p = 0.382; integrated discrimination improvement: 2.41%, p < 0.001).

CONCLUSIONS

EMR on admission was independently correlated with poor outcome in AIS patients, suggesting that EMR may be a potential prognostic biomarker for AIS.

High Eosinophil Rates in Patients With Right-to-Left Shunts: An Expected Role, or an Unexpected Risk?

Background and objective Eosinophils are associated with thromboembolic events. Since eosinophils are eliminated in the pulmonary vasculature, right-to-left shunt (RLS) through patent foramen ovale may increase eosinophils in the peripheral blood. In this report, we evaluated the eosinophils of patients with regard to the presence of RLS and its quantity. Patients and methods In this retrospective observational study, we analyzed the complete blood cell count (CBC) of patients with RLS (n=47) and without RLS (n=31) diagnosed by contrast echocardiography (CE). RLS was identified as mild (5-10 bubbles) and moderate shunt (10-25 bubbles). Results Age and CBC were not significantly different between the groups, with the exception of eosinophils. Patients with RLS had higher eosinophils percentage compared to patients without RLS (3.1 ±1.5 vs. 1.7 ±0.7, p=0.001). Additionally, eosinophils percentage was significantly higher in the mild RLS group (2.4 ±0.9 vs. 1.7 ±0.7, p=0.016) and the moderate RLS group (4.3 ±1.6 vs. 1.7 ±0.7, p=0.001) compared to normal subjects. Also, it was significantly higher in the moderate RLS group compared to the mild group (4.3 ±1.6 vs. 2.4 ±0.9, p=0.001). Conclusions Eosinophils percentage was higher in patients with mild and moderate RLS compared to normal individuals. Moreover, the eosinophil rate was higher in patients with moderate RLS than in patients with mild RLS.

Cellular and Molecular Mechanisms of R/S-Roscovitine and CDKs Related Inhibition under Both Focal and Global Cerebral Ischemia: A Focus on Neurovascular Unit and Immune Cells

Ischemic stroke is the second leading cause of death worldwide. Following ischemic stroke, Neurovascular Unit (NVU) inflammation and peripheral leucocytes infiltration are major contributors to the extension of brain lesions. For a long time restricted to neurons, the 10 past years have shown the emergence of an increasing number of studies focusing on the role of Cyclin-Dependent Kinases (CDKs) on the other cells of NVU, as well as on the leucocytes. The most widely used CDKs inhibitor, (R)-roscovitine, and its (S) isomer both decreased brain lesions in models of global and focal cerebral ischemia. We previously showed that (S)-roscovitine acted, at least, by modulating NVU response to ischemia. Interestingly, roscovitine was shown to decrease leucocytes-mediated inflammation in several inflammatory models. Specific inhibition of roscovitine majors target CDK 1, 2, 5, 7, and 9 showed that these CDKs played key roles in inflammatory processes of NVU cells and leucocytes after brain lesions, including ischemic stroke. The data summarized here support the investigation of roscovitine as a potential therapeutic agent for the treatment of ischemic stroke, and provide an overview of CDK 1, 2, 5, 7, and 9 functions in brain cells and leucocytes during cerebral ischemia.

Is neutrophil/eosinophil ratio at admission a prognostic marker for in-hospital mortality of acute ischemic stroke?

OBJECTIVES

There has been a recent focus on hematological parameters affecting the prognosis of acute ischemic stroke (AIS). However, there are no studies investigating the neutrophil/eosinophil ratio (NER). This study aimed to investigate whether NER at admission is a prognostic marker for in-hospital mortality in patients with AIS.

METHODS

204 AIS patients with similar vascular occlusion were included in the study, including 135 patients who survived and 69 patients who died in the hospital. Multivariate logistic regression analysis was performed to investigate the prognostic factors of AIS. The receiver operating characteristics (ROC) curve analysis was used to evaluate the predictive value of the variables and calculate the cut-off values.

RESULTS

69 patients died in the hospital [24 men and 45 women, median age: 78 (49-99)], and 135 patients survived [58 men and 77 women, median age: 74 (22-99)]. The mean age of patients with mortality was higher compared to the patients who survived (p value=0.007). Multivariate logistic regression model revealed that only NER and red blood cell distribution width (RDW-SD) were prognostic factors (p = 0.036 and p = 0.032, respectively). Areas under the ROC curve were 0.675 for NER (95% CI, 0.59-0.75), 0.636 for neutrophil (95% CI, 0.55-0.71), 0.602 for RDW-SD (95% CI, 0.51-0.69) and 0.656 for eosinophil (95% CI, 0.57-0.74).

CONCLUSION

Our results showed that there is a correlation between the in-hospital mortality of AIS and high NER at admission. NER at admission can be used as a poor prognostic marker for AIS.

Inequity in Distribution of Psychiatry Trainee Seats and Institutes Across Indian States: A Critical Analysis

Background  The delivery of mental health services largely depends on the adequacy of human resources. In India, the deficit of psychiatrists is more than 90% and is one of the major challenges that needs to be tackled to address the huge burden of mental illness. Psychiatry trainee institutes play a vital role in reducing human resource deficit and inequality in delivering mental health care. However, the distribution pattern of psychiatry trainee seats and institutes across Indian states is unknown. Therefore, we estimated the number of psychiatry trainee seats and institutes in each Indian state and union territory (UT). Materials and Methods  In this cross-sectional study, psychiatry trainee seats and institutes were searched on the official web sites of Medical Council of India and National Board of Examinations. The data available on these web sites until December 2019 were included. State-wise data were compared using proportion and percentages. The psychiatry trainee index (PTI) was calculated and compared across Indian states and UTs. Results  Among 221 Indian psychiatry trainee institutes considered in the present study, 116 (52.48%) were private institutes and 105 (47.51%) were government institutes. Overall, more psychiatry trainee seats were reported in government institutes ( n = 565, 65.89%) than in private institutes. National PTI was considered fair (0.06), and based on their PTIs, Indian states and UTs were classified as follows: worst ( n = 9), poor ( n = 8), fair ( n = 9), average ( n = 7), good ( n = 1), and excellent ( n = 2). Conclusion  A huge deficit of psychiatry trainees and institutes exists in more than two-thirds of Indian states and UTs, along with a huge maldistribution of seats. PTI and its distribution across the states and UTs are a crucial indicator of the need to improve the access and equity of mental health care.

Absolute blood eosinophil count could be a potential biomarker for predicting haemorrhagic transformation after intravenous thrombolysis for acute ischaemic stroke

Background

Immune cells are involved in all stages of acute ischaemic stroke (AIS) and possess both neuroprotective and neurodamaging properties. It has been suggested that immune system activation after stroke may be associated with the development of haemorrhagic transformation (HT), which is the main complication limiting the clinical use of intravenous thrombolysis with recombinant tissue plasminogen activator (rtPA) for AIS. The purpose of our study was to analyse the association between absolute eosinophil count (AEC) at admission and the occurrence of HT after intravenous rtPA therapy for AIS.

Methods

In this retrospective study we enrolled AIS patients who were treated with rtPA within 4.5 h of symptom onset. Baseline stroke severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS). Patients underwent head computed tomography scans at admission which were repeated 24 h after treatment with rtPA or promptly in case of clinical deterioration. HT was defined as blood at any site in the brain on follow-up head computed tomography scans. Spearman’s rank correlation test was used to analyse the correlation between AEC and NIHSS scores. The optimal AEC cut-off value for predicting HT was calculated using the area under the receiver operating characteristic curve. Multiple logistic regression was used to determine the association between AEC included as a binary variable and the incidence of HT.

Results

The data of 201 patients was analysed (59.7% females; median age 77 years); 23 (11.4%) of them developed HT. The median of AEC was 62.5% greater in the non-HT group compared to the HT group (0.13 ×  10⁹/l and 0.08 × 10⁹/l, respectively, p = 0.026). No correlation was found between AEC and baseline NIHSS scores (r = 0.061, p = 0.393). AEC ≥ 0.11 × 10⁹/l predicted the occurrence of HT with 69.6% sensitivity and 60.7% specificity. AEC ≥ 0.11 × 10⁹/l was independently associated with a 78% reduction in the odds of developing HT (adjusted odds ratio = 0.223, 95% confidence interval = 0.069–0.723, p = 0.012).

Conclusion

Higher values of AEC were associated with lower odds of developing HT, thus, AEC at admission could be considered an independent predictive marker of HT after treatment with rtPA for AIS.

Eosinophils count in peripheral circulation is associated with coronary artery disease

BACKGROUND AND AIMS

Allergic asthma can accelerate atherosclerosis, a disease in which plaque is deposited onto arterial walls and that may lead to coronary artery disease (CAD). Eosinophils are the most important effector cells in allergic asthma and are likely to become novel biomarkers for risk stratification of patients with CAD, but the relationship between eosinophil count and CAD remains unclear. We aimed to evaluate this relationship and the use of eosinophils in predicting CAD.

METHODS

A total of 5287 patients who underwent coronary angiography were recruited. Their biochemical parameters, including eosinophil count, were measured and their correlation with the severity of coronary artery stenosis, as quantified by the Gensini score system, was evaluated.

RESULTS

The percentages of eosinophils in leukocytes (PELs) were lower in CAD patients (p < 0.001), and had a significant negative correlation with Gensini scores (r = -0.112, p < 0.001). PELs were also significantly lower in acute myocardial infarction patients (p < 0.001). After adjusting for baseline differences, low PELs remained strongly associated with severe CAD and acute coronary arterial thrombotic event. Receiver-operating characteristic curve analysis showed that combining PELs with traditional risk factors in predictive models for CAD severity (z = 4.470, p < 0.001) or acute coronary arterial thrombotic event (z = 9.435, p < 0.001) improved the predictive capabilities of those models.

CONCLUSIONS

PELs, at least in patients undergoing coronary angiography, may be strongly related to the subtype and severity of CAD and, therefore, eosinophil count may be an accurate and independent biomarker to predict CAD severity and acute coronary arterial thrombotic events.

Eosinopenia is a predictive factor for the severity of acute ischemic stroke

Previous data have revealed an association between eosinopenia and mortality of acute ischemic stroke. However, the relationship of eosinopenia with infarct volume, infection rate, and poor outcome of acute ischemic stroke is still unknown. The retrospective study included 421 patients (273 males, 65%; mean age, 68.0 ± 13.0 years) with first acute ischemic stroke who were hospitalized in the Second Affiliated Hospital of Soochow University, China, from January 2017 to February 2018. Laboratory data, neuroimaging results, and modified Rankin Scale scores were collected. Patients were divided into four groups according to their eosinophil percentage level (< 0.4%, 0.4–1.1%, 1.1–2.3%, ≥ 2.3%). Spearman’s correlation analysis showed that the percentage of eosinophils was negatively correlated with infarct volume (r_s = −0.514, P < 0.001). Receiver operating characteristic analysis demonstrated that eosinopenia predicted a large infarct volume more accurately than neutrophilia; the area under curve was 0.906 and 0.876, respectively; a large infarct was considered as that with a diameter larger than 3 cm and involving more than two major arterial blood supply areas. Logistic regression analysis revealed that eosinophil percentage was an independent risk factor for acute ischemic stroke (P = 0.002). Moreover, eosinophil percentage was significantly associated with large infarct volume, high infection rate (pulmonary and urinary tract infections), and poor outcome (modified Rankin Scale score > 3) after adjusting for potential confounding factors (P-trend < 0.001). These findings suggest that eosinopenia has the potential to predict the severity of acute ischemic stroke. This study was approved by the Ethics Committee of the Second Affiliated Hospital of Soochow University, China (approval number: K10) on November 10, 2015.

Analysis of Early Stroke-induced Changes in Circulating Leukocyte Counts using Transcriptomic Deconvolution

Growing evidence suggests that stroke alters the phenotype of the peripheral immune system; better characterization of this response could provide new insights into stroke pathophysiology. In this investigation, we employed a deconvolution approach to informatically infer the cellular composition of the circulating leukocyte pool at multiple timepoints following stroke onset based on whole blood mRNA expression. Microarray data generated from the peripheral blood of 23 cardiovascular disease controls and 23 ischemic stroke patients at 3, 5, and 24 hours post-symptom onset were obtained from a public repository. Transcriptomic deconvolution was used to estimate the relative counts of nine leukocyte populations based on the expression of cell-specific transcripts, and cell counts were compared between groups across timepoints. Inferred counts of lymphoid cell populations including B-cells, CD4+ T-cells, CD8+ T-cells, γδ T-cells, and NK-cells were significantly lower in stroke samples relative to control samples. With respect to myeloid cell populations, inferred counts of neutrophils and monocytes were significantly higher in stroke samples compared to control samples, however inferred counts of eosinophils and dendritic cells were significantly lower. These collective differences were most dramatic in samples collected at 5 and 24 hours post-symptom onset. Findings were subsequently confirmed in a second dataset generated from an independent population of 24 controls and 39 ischemic stroke patients. Collectively, these results offer a comprehensive picture of the early stroke-induced changes to the complexion of the circulating leukocyte pool, and provide some of the first evidence that stroke triggers an acute decrease in eosinophil counts.