Hemoglobin Concentration and Clinical Outcomes After Acute Ischemic Stroke or Transient Ischemic Attack

Relationship between the hemoglobin-to-red cell distribution width ratio and post-stroke cognitive impairment: a prospective study

Background

Post-stroke cognitive impairment (PSCI) is one of the main complications after stroke. The association between the hemoglobin-to-red cell distribution width ratio (HRR) and PSCI remains inadequately explored. Consequently, we performed a prospective study to assess whether HRR levels are associated with changes in cognitive function after acute ischemic stroke (AIS).

Methods

A total of 296 AIS patients were recruited. HRR was measured within 24 h of admission, and cognitive function was assessed using the Mini-Mental State Examination (MMSE) one month post-onset. Logistic regression analysis was performed to identify independent risk and protective factors for the occurrence of PSCI. Restricted cubic splines (RCS) were used to explore the dose-response relationship between HRR and PSCI.

Results

129 of 296 participants (43.6%) developed cognitive impairment at 1 month. HRR in PSCI group was significantly lower than that in non-cognitive impairment group (P < 0.001). When HRR was taken as the categorical variable and with Q4 as the reference, the risk of PSCI in Q1 was the highest after adjusting multiple potential confounding factors (odds ratio [OR] = 2.702, 95% confidence interval [CI]= 1.222-5.977, P = 0.014). In addition, RCS curve exhibited that the relationship between HRR and PSCI was linear (P for nonlinear = 0.972, P for overall = 0.012). Subgroup analysis verified the stability of the results.

Conclusion

Reduced HRR levels were linked to an increased risk of cognitive impairment, indicating that HRR may serve as a predictive factor for PSCI.

Assessing anemia in stroke patients through virtual non-contrast imaging with photon-counting detector CT: validation on supra-aortic vessel CT-Angiography

BACKGROUND AND PURPOSE

Anemia is a common comorbidity in stroke patients, traditionally detected via blood tests. This study evaluates the feasibility of using virtual non-contrast (VNC) imaging from photon counting detector-CT (PCD-CT) angiography to detect anemia and identifies the optimal anatomical site for assessment.

MATERIALS AND METHODS

In this retrospective study of 80 patients undergoing PCD-CT angiography of supra-aortic vessels, VNC series were analyzed at various anatomical sites, including the jugular veins, aorta, and cerebral sinuses. Correlations between serum hemoglobin (Hb) levels and VNC Hounsfield Unit (HU) values were assessed using Pearson's coefficients. Linear regression and ROC analysis evaluated diagnostic performance.ResultsThe jugular veins showed the strongest correlation between VNC HU values and Hb levels (R2 = 0.49, p < 0.001), with weaker correlations in arterial vessels like the aorta (R2 = 0.11, p < 0.001). ROC analysis of jugular vein VNC values yielded an AUC of 0.79 for anemia detection. Correlation strength declined with longer intervals between imaging and blood tests, suggesting temporal Hb variability.

CONCLUSIONS

VNC imaging in CT angiography is a feasible method for detecting anemia, with the jugular veins providing the most reliable site for assessment. VNC imaging could be a valuable alternative when blood tests are delayed or unavailable.

Association of Butyryl Cholinesterase and Recurrent Ischemic Stroke: A Cross-Sectional Study

Objective

Exploring novel relevant factors associated with recurrent ischemic stroke.

Methods

This is a retrospective study, patients were divided into first-ever ischemic stroke group and recurrent ischemic stroke groups. We conducted a comparative analysis of baseline data between the two groups. Multifactorial logistic regression analysis was performed to identify factors associated with recurrent ischemic stroke. Grouped according to butyryl cholinesterase levels, to elucidate the relationship between butyryl cholinesterase levels and stroke recurrence.

Results

A total of 2029 patients were included, with 1174 in the first-ever ischemic stroke group and 855 in the recurrent ischemic stroke group. Age, hypertension, diabetes, alanine aminotransferase, and lipoprotein(a) were identified as risk factors for recurrent ischemic stroke (ALL p<0.05). Erythrocyte count, butyryl cholinesterase, low-density lipoprotein, and non-atherosclerotic type of large arteries were found to be negative associated with recurrent ischemic stroke (ALL p<0.05). Subgroup analyses indicated that butyryl cholinesterase levels were significantly negatively associated with recurrent ischemic stroke in males (OR=0.814, p<0.001, 95% CI: 0.761 ~ 0.871), especially under 60 years (OR=0.781, p<0.001, 95% CI: 0.708 ~ 0.862). After adjusting for multifactorial regression analyses, the recurrent rate in the lowest quartile of butyryl cholinesterase levels was 2.281 times that of the highest quartile (OR=2.281, p<0.05, 95% CI: 1.318 ~ 3.948).

Conclusion

Age, hypertension, diabetes, alanine aminotransferase, and lipoprotein(a) are independent risk factors for the recurrence of ischemic stroke. The inverse association between butyryl cholinesterase levels and stroke recurrence suggests butyryl cholinesterase may serve as a potential target for therapeutic intervention to improve the prognosis of ischemic stroke.

Association between hemoglobin level and clinical outcomes in ischemic stroke patients with high-grade carotid artery stenosis

OBJECTIVE

Abnormal hemoglobin levels may influence stroke outcome, while high-grade carotid artery stenosis (CAS) is linked to distal hemodynamic compromise. The relationship between hemoglobin and ischemic stroke (IS) outcome in patients with high-grade CAS remains unclear. We aimed to investigate this association in acute IS patients with high-grade CAS.

METHODS

To compare the characteristics and outcome in acute IS patients with high-grade CAS across different hemoglobin levels, we conducted an observational cohort study from January 2007 to April 2012 and followed for 5 years.

RESULTS

Among 372 enrolled patients, 75 had hemoglobin < 12 g/dL, 153 had 12-14 g/dL, and 144 had > 14 g/dL. Hemoglobin < 12 g/dL was associated with higher rates of congestive heart failure, gout, and chronic kidney disease, but lower rate of hyperlipidemia. Hemoglobin< 12 g/dL had lower levels of white blood cells, total cholesterol, and estimated glomerular filtration rate, but higher levels of high-sensitivity C-reactive protein and potassium. The Cox proportional hazards model revealed that hemoglobin< 12 g/dL was associated with higher risk of all-cause mortality (hazard ratio (HR) 1.99, 95 % confidence interval (CI) 1.20-3.32, P = 0.008) and lower risk of stroke recurrence over 5 years in IS patients with high-grade CAS (HR 0.50, 95 % CI 0.26-0.95; P = 0.033).

CONCLUSIONS

Hemoglobin< 12 g/dL was associated with higher mortality and lower stroke recurrence risk over 5 years in IS patients with high-grade CAS. Further studies are warranted to determine the optimal hemoglobin level for improving outcomes in these patients.

Efficacy and safety of Ferrous iron on the prevention of Vascular cOgnitive impaiRment among patients with cerebral Infarction/TIA (FAVORITE): rationale and design of a multicentre randomised trial

BACKGROUND

The incidence of vascular cognitive impairment (VCI) is high in patients suffering from ischaemic stroke or transient ischaemic attack (TIA) or with vascular risk factors. Effective prevention strategies for VCI remain limited. Anaemia or low haemoglobin was found as an independent risk factor for adverse outcomes after acute stroke. Anaemia or low haemoglobin was possibly associated with an increased risk of poststroke cognitive impairment. Whether supplement of ferrous iron to correct anaemia reduces the risk of VCI and improves adverse outcomes in patients with ischaemic cerebrovascular disease remains uncertain.

AIM

We aim to introduce the design and rationale of the safety and efficacy of Ferrous iron on the prevention of Vascular cOgnitive impaiRment in patients with cerebral Infarction or TIA (FAVORITE) trial.

DESIGN

FAVORITE is a randomised, placebo-controlled, double-blind, multicentre trial that compares supplement of ferrous iron with placebo for recent minor stroke/TIA patients complicated with mild anaemia or iron deficiency: Ferrous succinate sustained-release tablet 0.2 g (corresponding to 70 mg of elemental iron) once daily after or during breakfast for 12 weeks or placebo with much the same colour, smell and size as ferrous iron once daily during or after breakfast for 12 weeks. All paticipants will be followed within the next year.

STUDY OUTCOMES

The primary effective outcome is the incidence of VCI at 3 months after randomisation and the primary safety outcome includes any gastrointestinal adverse event during 3 months.

DISCUSSION

The FAVORITE trial will clarify whether supplement of ferrous iron to correct low haemoglobin reduces the risk of VCI in patients with recent ischaemic stroke or TIA complicated with mild anaemia or iron deficiency compared with placebo.

TRIAL REGISTRATION NUMBER

NCT03891277.

The hemoglobin, albumin, lymphocyte, and platelet score as a useful predictor for mortality in older patients with hip fracture

Objective

With a rapidly aging population, identifying effective prognostic predictors has always been a research hotspot in older patients with hip fracture. Recently, the score combining hemoglobin, albumin, lymphocyte and platelet (HALP) has been proposed as a novel biomarker for reflecting systemic inflammation and nutritional status. However, it is unclear whether the HALP score could be a potential prognostic indicator for mortality following hip fracture. Thus, the objective of this study was to explore the relationship between the HALP score and mortality risk in older patients with hip fracture, and further evaluate its predictive value.

Methods

Consecutive patients were identified from our institutional hip fracture database over the period from January 1, 2013 to December 31, 2022. Outcomes were 90-day all-cause mortality and overall mortality at the longest follow-up. Multivariate Cox proportional hazard models and restricted cubic spline (RCS) models were employed to assess this relationship. The incremental predictive performance of the HALP score was assessed using the c statistic, net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

Results

In total, 1707 patients were included with a median follow-up duration of 44.4 months, of whom 174 cases (10.2%) died within 90 days and 667 cases (39.1%) died at the longest follow-up. After multivariate adjustment, compared to tertile 1 group, tertile 2 and tertile 3 groups exhibited 0.676-fold (95% confidence interval [CI]: 0.471-0.972, p = 0.035) and 0.598-fold (95% CI: 0.390-0.918, p = 0.019) lower risks of 90-day mortality, as well as 0.681-fold (95% CI: 0.566-0.820, p < 0.001) and 0.618-fold (95% CI: 0.504-0.759, p < 0.001) decreased risks of overall mortality, respectively. For each unit increase in the HALP score, there was a significant decrease in 90-day mortality by 1.1% and in overall mortality by 1.0% (all p < 0.05). RCS analyses indicated nonlinear relationships between the HALP score and 90-day and overall mortality (all P for nonlinear <0.01). Moreover, adding the HALP score significantly improved the predictive ability for 90-day and overall mortality (all p < 0.05).

Conclusion

The HALP score was independently associated with mortality risk, highlighting its potential as a useful prognostic indicator for predicting mortality in older patients with hip fracture.

Effect of Hemoglobin and Blood Glucose Levels on CT Perfusion Ischemic Core Estimation: A Post Hoc Analysis of the ESCAPE-NA1 Trial

BACKGROUND AND OBJECTIVES

CT perfusion (CTP) maps can estimate the ischemic core in acute ischemic stroke based on distinctive cerebral blood flow thresholds. However, metabolic factors beyond perfusion influence the tissue tolerance to ischemia and the infarct growth rate. Underestimating the ischemic core volume (ICV) might result in overestimating the salvageable cerebral tissue and, consequently, overestimating the potential clinical benefits of reperfusion therapies. We aim to evaluate whether baseline hemoglobin and blood glucose levels influence the accuracy of baseline CTP ICV estimations.

METHODS

Large vessel occlusion stroke patients investigated with baseline CTP undergoing thrombectomy with near-complete reperfusion and without parenchymal hemorrhage from the ESCAPE-NA1 trial were included. Patients were subdivided into anemic (hemoglobin <130 g/L for men and <120 g/L for women) and nonanemic groups, and hyperglycemic (blood glucose level >7 mmol/L) and normoglycemic groups. Ischemic core underestimated volume (ICuV) was calculated: final infarct volume minus CTP-based ICV. The primary outcome was the presence of "perfusion scotoma" defined as ICuV ≥10 mL. Presence of "perfusion scotoma" and median ICuV were compared between anemic vs nonanemic and hyperglycemic vs normoglycemic patients using nonparametric tests and multivariable binary logistic regression with adjustment for baseline variables.

RESULTS

One hundred sixty-two of 1,105 (15%) patients were included (median age 70.5 [interquartile range (IQR) 61-80.4], 50.6% women). The median ICuV was 7.26 mL (IQR 0-25.63). Seventy-eight (48%) patients demonstrated perfusion scotoma. Forty-two (25.7%) patients were anemic, and 65 (40.1%) were hyperglycemic. In univariable analysis, the hyperglycemic group had a higher prevalence of perfusion scotoma (65% [n = 40] vs 39% [n = 38], p = 0.006) and larger ICuV (17.79 mL [IQR 1.57-42.75] vs 6 mL [-0.31 to 12.51], p = 0.003) compared to normoglycemic patients. No significant ICuV differences between patients with and without anemia were seen. Multivariable regression analysis revealed an association between perfusion scotoma and hyperglycemia, adjusted odds ratio (OR) 2.48 (95% CI 1.25-4.92), and between perfusion scotoma and blood glucose levels, adjusted OR 1.19 (95% CI 1.03-1.39) per 1 mmol/L increase.

DISCUSSION

In our study, CTP-based ischemic core underestimation was common and associated with higher baseline blood glucose levels. Individual metabolic factors beyond perfusion that critically influence the infarct growth rate should be considered when interpreting baseline CTP estimations of ischemic core.

Nutritional management for post-stroke sarcopenia risk and multi-comorbidities patient via percutaneous endoscopic gastrotomy: a case report and review of the literature

Stroke is a major cause of morbidity and mortality worldwide, often leading to complications such as malnutrition, dysphagia, and sarcopenia. We present the case of a 78-year-old male with a history of ischemic stroke and multiple comorbidities, who was underweight and weakened. Over a 10-month follow-up period, a percutaneous endoscopic gastrostomy (PEG) tube was placed, and nutritional management was carried out based on biochemical and nutritional status assessments. Anthropometric and blood biochemical parameters confirmed the need to adjust protein and energy intake to the patient's requirements. Personalized nutritional intervention, including a caloric surplus and dietary adjustments, resulted in weight gain, improved muscle mass and biochemical blood parameters. This case report highlights the comprehensive nutritional management of a post-stroke patient to improve outcomes and quality of life.

"The association between HALP score and infection in acute ischemic stroke patients"

BACKGROUND AND PURPOSE

Stroke-associated infection (SAI) is related to increased mortality in acute ischemic stroke (AIS) cases. The HALP index is used to evaluate nutrition and inflammation. Our research aimed to assess the relation between HALP scores and infection risk in AIS cases.

MATERIALS AND METHODS

132 cases of acute ischemic stroke were registered. 77 cases were male and 55 cases were female. The median age of the attending cases was 66 (35-104) years. Laboratory variables were assessed within 24 h after hospitalization in the neurology care unit. The HALP score is evaluated utilizing the formula "Hemoglobin (g/dL) × Albumin (g/dL) × Lymphocyte (/10^3/uL) / Platelet (/10^3/uL)".

RESULTS

Cases were separated into two groups according to their corresponding HALP score. Group-1 cases have a low HALP score (HALP score ≤ 18227,93). Group-2 cases have a high HALP score (HALP score > 18227,93). 26 (19.6 %) cases were diagnosed with various infections after hospitalization in the neurology care unit. Urinary tract infections were frequent infection causes in AIS cases (13 cases, 50 %). Pneumonia was observed in 8 cases, making up 30 % of the total cases. Another infection was seen in 5 (20 %) of the cases. The frequently encountered bacteria were Escherichia coli ESBL + (n = 7, 27 %) and Staphylococcus aureus (n = 6, 23 %). The mortality ratio was higher in Group-1 cases than in Group-2 cases (34 % vs 7 %).

CONCLUSIONS

This investigation has suggested a relationship between infection and HALP score in AIS patients.

Age affects the association of red blood cell indices with efficacy of remote ischemic conditioning in patients with acute moderate ischemic stroke

We conducted a post hoc analysis of Remote Ischemic Conditioning for Acute Moderate Ischemic Stroke (RICAMIS) to investigate whether red blood cell (RBC) indices are associated with efficacy of remote ischemic conditioning (RIC), and whether the association is affected by age. In this post hoc analysis, patients with RBC indices at admission were enrolled. RBC indices including RBC count, hematocrit (HCT), mean corpuscular volume (MCV), hemoglobin (HB), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were analyzed. According to the median of these RBC indices, eligible patients were divided into high and low groups, which were further subdivided into RIC and control subgroups. Primary endpoint was excellent functional outcome defined as a modified Rankin Scale score of 0-1 at 90 days, which was used to evaluate RIC efficacy. RIC efficacy as well as effect of age on RIC efficacy were analyzed across the high and low groups of different RBC indices, and the interaction effects of RBC indices on RIC efficacy were evaluated. A total of 1640 patients were enrolled in the final analysis. In overall patients, no significant interaction effects of RIC intervention by all RBC indices were found, although there was a trend in interaction effect of RIC intervention by MCH (p = 0.116). However, we found an effect of age on the association of MCH with RIC efficacy. In patients over 60 years old, MCH significantly affected RIC efficacy (p = 0.006) and RIC significantly produced a higher proportion of primary outcome in high MCH (72.6% vs. 59.1%, P < 0.001) vs. low MCH group (61.2% vs. 62%, P = 0.829), which was not identified in patients under 60 years old. Furthermore, RIC efficacy decreased with increasing age in patients with low MCH with significant interaction effect (p = 0.012), while RIC efficacy increased with increasing age in patients with high MCH although no significant interaction (p = 0.126). No significant interaction effects of RIC intervention by RBC count, HCT, MCV, HB, and MCHC were found regardless of age. This secondary analysis of RICAMIS suggested that RIC exhibited more obvious benefit in AIS patients over 60 years old with high MCH compared with those with low MCH group, but RBC count, HCT, MCV, HB, and MCHC were not associated with the efficacy of RIC treatment regardless of age.

Development and Validation of a Predictive Score for Three-Year Mortality in Acute Ischemic Stroke Patients

Background and Objectives: Acute ischemic stroke (AIS) is a leading cause of death and disability with poor long-term outcomes. Creating a predictive score for long-term mortality in AIS might be important for optimizing treatment strategies. The aim of this study is to develop and validate a predictive score for three-year mortality in patients with AIS using several demographic, clinical, laboratory and imaging parameters. Materials and Methods: This study included 244 AIS patients admitted to a tertiary center and followed up for three years. The patients' data included demographics, clinical features, laboratory tests (including resistin and leptin levels) and imaging parameters. The patients were randomly divided into a predictive group (n = 164) and a validation group (n = 80). Results: Advanced age, a high NIHSS score, low levels of hemoglobin, elevated resistin levels and the presence of carotid plaques were independently associated with three-year mortality. The predictive model incorporated these variables, and it was validated in a separate cohort. Leptin levels did not significantly predict mortality. Conclusions: This study developed and validated a promising predictive score for three-year mortality in patients with AIS. Advanced age, high NIHSS scores, low hemoglobin levels, elevated resistin levels and the presence of carotid plaques were the independent predictors of long-term mortality.

Inflammation-Derived and Clinical Indicator-Based Predictive Model for Ischemic Stroke Recovery

BACKGROUND

Neuroinflammatory responses are closely associated with poststroke prognosis severity. This study aimed to develop a predictive model, combining inflammation-derived markers and clinical indicators, for distinguishing functional outcomes in patients with subacute ischemic stroke.

METHODS AND RESULTS

Based on activities of daily living assessments, ischemic stroke participants were categorized into groups with little effective (LE) recovery and obvious effective (OE) recovery. Initial biocandidates were identified by overlapping differentially expressed proteins from proteomics of clinical serum samples (5 LE, 5 OE, and 6 healthy controls) and differentially expressed genes from an RNA sequence of the ischemic cortex in middle cerebral artery occlusion mice (n=3). Multidimensional validations were conducted in ischemia-reperfusion models and a clinical cohort (15 LE, 11 OE, and 18 healthy controls). Models of robust biocandidates combined with clinical indicators were developed with machine learning in the training data set and prediction in another test data set (15 LE and 11 OE). We identified 194 differentially expressed proteins (LE versus healthy controls) and 174 differentially expressed proteins (OE versus healthy controls) in human serum, and 5121 differentially expressed genes (day 3) and 5906 differentially expressed genes (day 7) in middle cerebral artery occlusion mice cortex. Inflammation-derived biomarkers TIMP1 (tissue inhibitor metalloproteinase-1) and galactosidase-binding protein LGLAS3 (galectin-3) exhibited robust increases under ischemic injury in mice and humans. TIMP1 and LGALS3 coupled with clinical indicators (hemoglobin, low-density lipoprotein cholesterol, and uric acid) were developed into a combined model for differentiating functional outcome with high accuracy (area under the curve, 0.8).

CONCLUSIONS

The combined model is a valuable tool for evaluating prognostic outcomes, and the predictive factors can facilitate development of better treatment strategies.

Exploring Relationships of Heart Rate Variability, Neurological Function, and Clinical Factors with Mortality and Behavioral Functional Outcome in Patients with Ischemic Stroke

Ischemic stroke is a leading cause of mortality and disability. The relationships of heart rate variability (HRV) and stroke-related factors with mortality and functional outcome are complex and not fully understood. Understanding these relationships is crucial for providing better insights regarding ischemic stroke prognosis. The objective of this study is to examine the relationship between HRV, neurological function, and clinical factors with mortality and 3-month behavioral functional outcome in ischemic stroke. We prospectively collected the HRV data and monitored the behavioral functional outcome of patients with ischemic stroke. The behavioral functional outcome was represented by a modified Rankin Scale (mRS) score. This study population consisted of 58 ischemic stroke patients (56.9% male; mean age 70) with favorable (mRS score ≤ 2) and unfavorable (mRS score ≥ 3) outcome. The analysis indicated that the median of the mean RR interval (RR mean) showed no statistical difference between mortality groups. Conversely, the median of the RR mean had significant association with unfavorable outcome (OR = 0.989, p = 0.007). Lower hemoglobin levels had significant association with unfavorable outcome (OR = 0.411, p = 0.010). Higher National Institute of Health Stroke Scale (NIHSS) score at admission had significant association with unfavorable outcome (OR = 1.396, p = 0.002). In contrast, age, stroke history, NIHSS score at admission, and hemoglobin showed no significant association with mortality in ischemic stroke. These results imply that HRV, as indicated by the median of RR mean, alongside specific clinical factors and neurological function at admission (measured by NIHSS score), may serve as potential prognostic indicators for 3-month behavioral functional outcome in ischemic stroke.

Anemia and Optimal Transfusion Thresholds in Brain-Injured Patients: A Narrative Review of the Literature

Anemia is a highly prevalent condition that may compromise oxygen delivery to vital organs, especially among the critically ill. Although current evidence supports the adoption of a restrictive transfusion strategy and threshold among the nonbleeding critically ill patient, it remains unclear whether this practice should apply to the brain-injured patient, given the predisposition to cerebral ischemia in this patient population, in which even nonprofound anemia may exert a detrimental effect on clinical outcomes. The purpose of this review is to provide an overview of the pathophysiological changes related to impaired cerebral oxygenation in the brain-injured patient and to present the available evidence on the effect of anemia and varying transfusion thresholds on the clinical outcomes of patients with acute brain injury.

Association of red blood cell distribution width to albumin ratio with prognosis in stroke patients

Aim: The authors investigated the association of red blood cell distribution width to albumin ratio (RAR) with prognosis and severity in acute ischemic stroke (AIS). Methods: One hundred twenty-seven patients with AIS were prospectively analyzed. The NIH Stroke Scale was used to determine stroke severity. RAR was compared between severe and nonsevere patients. Results: RAR was significantly higher in severe compared with nonsevere patients (p < 0.001). According to receiver operating characteristic analysis, RAR alone predicted mortality better than red blood cell distribution width and albumin (area under the curve: 0.933, 0.911, 0.870, respectively). Additionally, RAR was significantly correlated with NIH Stroke Scale score (p < 0.001). Conclusion: High RAR measured at presentation is a feasible index for prognosis and severity stratification in AIS.

The association between hemoglobin concentration and clinical outcomes after aneurysmal subarachnoid hemorrhage: Insights from the LongTEAM registry

OBJECTIVE

The aim of this study is to explore whether preoperative hemoglobin levels could serve as a prospective biomarker for early brain injury in patients with aneurysmal subarachnoid hemorrhage (aSAH). This investigation seeks to discern its association with postoperative complications and unfavorable clinical outcomes.

METHODS

We conducted a comprehensive analysis of data derived from the LongTeam registry, including patients with aSAH diagnosed between January 2015 and September 2021. These patients were stratified into three distinct groups based on their hemoglobin levels: anemic, standard, and elevated HGB. We employed logistic models featuring spline transformations to assess the relationship between HGB levels and in-hospital complications. Furthermore, a multivariate Cox proportional hazard model was employed to estimate the impact of elevated hemoglobin levels on the hazard function, which was elucidated through Kaplan-Meier curves.

RESULTS

Our study comprised a total of 988 patients, among whom 115 (11.6%) presented preoperative anemia, and 63 (6.4%) exhibited elevated preoperative HGB levels. Following adjustments for potential confounding factors, no significant disparity in risk was evident between anemic patients and those with standard HGB levels. However, individuals with elevated HGB levels displayed a heightened incidence and an increased risk of developing deep vein thrombosis (DVT, odds ratio [OR] = 2.39, 95% confidence interval [CI] = 1.16-4.91, p = 0.018; hazard ratio [HR] = 2.05, 95% CI 1.08-3.92, p = 0.015). Aberrant HGB concentrations did not demonstrate an association with other clinical outcomes.

CONCLUSION

Our findings emphasize that abnormal HGB levels show no association with adverse outcomes at the 90 days mark after accounting for clinical confounding factors in patients with aSAH. Simultaneously, the study illuminates the potential of HGB as an early indicator for identifying patients at a heightened risk of developing DVT.

Mechanisms and treatment of anemia related to cardiac arrest

Cardiac arrest is a common and fatal emergency situation. Recently, an increasing number of studies have shown that anemia in patients with cardiac arrest is closely related to high mortality rates and poor neurological outcomes. Anemia is prevalent among patients with post-cardiac arrest syndrome (PCAS), but its specific pathogenesis remains unclear. The mechanisms may involve various factors, including reduced production of erythropoietin, oxidative stress/inflammatory responses, gastrointestinal ischemic injury, hepcidin abnormalities, iatrogenic blood loss, and malnutrition. Measures to improve anemia related to cardiac arrest may include blood transfusions, administration of erythropoietin, anti-inflammation and antioxidant therapies, supplementation of hematopoietic materials, protection of gastrointestinal mucosa, and use of hepcidin antibodies and antagonists. Therefore, exploring the latest research progress on the mechanisms and treatment of anemia related to cardiac arrest is of significant guiding importance for improving secondary brain injury caused by anemia and the prognosis of patients with cardiac arrest.

Beyond diagnosis: Leveraging routine blood and urine biomarkers to predict severity and functional outcome in acute ischemic stroke

Background

The initial severity of acute ischemic stroke (AIS) is a crucial predictor of the disease outcome. In this study, blood and urine biomarkers from patients with AIS were measured to estimate stroke severity and predict long-term stroke outcomes.

Methods

The medical records of patients with AIS between October 2016 and May 2020 were retrospectively analyzed. The relationships of blood and urine biomarkers with stroke severity at admission were evaluated in patients with AIS. Predictive models for initial stroke severity and long-term prognosis were then developed using a panel of identified biomarkers.

Results

A total of 2229 patients were enrolled. Univariate analysis revealed 12 biomarkers associated with the National Institutes of Health Stroke Scale scores at admission. The area under the curve values for predicting initial stroke severity and long-term prognosis on the basis of these biomarkers were 0.7465, 0.7470, and 0.8061, respectively. Among multiple tested machine-learning, eXtreme gradient boosting exhibited the highest effectiveness in predicting 90-day modified Rankin Scale scores. SHapley Additive exPlanations revealed fasting glucose, albumin, hemoglobin, prothrombin time, and urine-specific gravity to be the top five most crucial biomarkers.

Conclusion

These findings demonstrate that clinically available blood and urine biomarkers can effectively estimate initial stroke severity and predict long-term prognosis in patients with AIS. Our results provide a scientific basis for developing tailored clinical treatment and management strategies for AIS, through incorporating liquid biomarkers into stroke risk assessment and patient care protocols for patients with AIS.

Interpretable machine learning for prediction of clinical outcomes in acute ischemic stroke

Background and aims

Predicting the prognosis of acute ischemic stroke (AIS) is crucial in a clinical setting for establishing suitable treatment plans. This study aimed to develop and validate a machine learning (ML) model that predicts the functional outcome of AIS patients and provides interpretable insights.

Methods

We included AIS patients from a multicenter stroke registry in this prognostic study. ML-based methods were utilized to predict 3-month functional outcomes, which were categorized as either favorable [modified Rankin Scale (mRS) ≤ 2] or unfavorable (mRS ≥ 3). The SHapley Additive exPlanations (SHAP) method was employed to identify significant features and interpret their contributions to the predictions of the model.

Results

The dataset comprised a derivation set of 3,687 patients and two external validation sets totaling 250 and 110 patients each. Among them, the number of unfavorable outcomes was 1,123 (30.4%) in the derivation set, and 93 (37.2%) and 32 (29.1%) in external sets A and B, respectively. Among the ML models used, the eXtreme Gradient Boosting model demonstrated the best performance. It achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.790 (95% CI: 0.775-0.806) on the internal test set and 0.791 (95% CI: 0.733-0.848) and 0.873 (95% CI: 0.798-0.948) on the two external test sets, respectively. The key features for predicting functional outcomes were the initial NIHSS, early neurologic deterioration (END), age, and white blood cell count. The END displayed noticeable interactions with several other features.

Conclusion

ML algorithms demonstrated proficient prediction for the 3-month functional outcome in AIS patients. With the aid of the SHAP method, we can attain an in-depth understanding of how critical features contribute to model predictions and how changes in these features influence such predictions.

Development of machine learning models for predicting outcome in patients with distal medium vessel occlusions: a retrospective study

Background

While numerous prognostic factors have been reported for large vessel occlusion (LVO)-acute ischemic stroke (AIS) patients, the same cannot be said for distal medium vessel occlusions (DMVOs). We used machine learning (ML) algorithms to develop a model predicting the short-term outcome of AIS patients with DMVOs using demographic, clinical, and laboratory variables and baseline computed tomography (CT) perfusion (CTP) postprocessing quantitative parameters.

Methods

In this retrospective cohort study, consecutive patients with AIS admitted to two comprehensive stroke centers between January 1, 2017, and September 1, 2022, were screened. Demographic, clinical, and radiological data were extracted from electronic medical records. The clinical outcome was divided into two categories, with a cut-off defined by the median National Institutes of Health Stroke Scale (NIHSS) shift score. Data preprocessing involved addressing missing values through imputation, scaling with a robust scaler, normalization using min-max normalization, and encoding of categorical variables. The data were split into training and test sets (70:30), and recursive feature elimination (RFE) was employed for feature selection. For ML analyses, XGBoost, LightGBM, CatBoost, multi-layer perceptron, random forest, and logistic regression algorithms were utilized. Performance evaluation involved the receiver operating characteristic (ROC) curve, precision-recall curve (PRC), the area under these curves, accuracy, precision, recall, and Matthews correlation coefficient (MCC). The relative weights of predictor variables were examined using Shapley additive explanations (SHAP).

Results

Sixty-nine patients were included and divided into two groups: 35 patients with favorable outcomes and 34 patients with unfavorable outcomes. Utilizing ten selected features, the XGBoost algorithm achieved the best performance in predicting unfavorable outcomes, with an area under the ROC curve (AUROC) of 0.894 and an area under the PRC curve (AUPRC) of 0.756. The SHAP analysis ranked the following features in order of importance for the XGBoost model: mismatch volume, time-to-maximum of the tissue residue function (Tmax) >6 s, diffusion-weighted imaging (DWI) volume, neutrophil-to-platelet ratio (NPR), mean corpuscular volume (MCV), Tmax >10 s, hemoglobin, potassium, hypoperfusion index (HI), and Tmax >8 s.

Conclusions

Our ML models, trained on baseline quantitative laboratory and CT parameters, accurately predicted the short-term outcome in patients with DMVOs. These findings may aid clinicians in predicting prognosis and may be helpful for future research.

Causal Association Between Anemia and Cardiovascular Disease: A 2-Sample Bidirectional Mendelian Randomization Study

Background Although previous observational studies have shown an association between anemia and cardiovascular disease (CVD), the underlying causal relationship between anemia and CVD remains uncertain. Methods and Results We conducted a 2-sample bidirectional Mendelian randomization (MR) study to assess the causal association between anemia and CVD. We extracted summary statistics data for anemia, heart failure (HF), coronary artery disease (CAD), atrial fibrillation, any stroke, and any ischemic stroke (AIS) from relevant published genome-wide association studies. After rigorous quality control steps, independent single-nucleotide polymorphisms for each disease were selected as instrumental variables. Inverse-variance weighting was used as the primary method to estimate the causal association between anemia and CVD in the 2-sample MR analysis. Simultaneously, we performed a series of multiple methods analyses (median weighting, maximum likelihood [MR robust adjusted profile score]), sensitivity analyses (Cochran's Q test and MR-Egger intercept, leave-one-out test [MR pleiotropy residual sum and outlier]), instrumental variable strength evaluations (F statistic), and statistic power estimates to verify the robustness and reliability of our results. Furthermore, the associations between anemia and CVD from different studies, including the UK Biobank and FinnGen studies, were combined by meta-analysis. The MR analysis showed that genetically predicted anemia was significantly associated with HF risk at the Bonferroni-corrected significance level (odds ratio [OR], 1.11 [95% CI, 1.04-1.18]; P=0.002) and was suggestively associated with CAD risk (OR, 1.11 [95% CI, 1.02-1.22]; P=0.020). However, the associations between anemia and atrial fibrillation, any stroke, or AIS were not statistically significant. In the reverse MR analysis, we found that genetic susceptibility to HF, CAD, and AIS was significantly associated with anemia risk. The ORs of HF, CAD, and AIS were 1.64 (95% CI, 1.39-1.94; P=7.60E-09), 1.16 (95% CI, 1.08-1.24; P=2.32E-05), and 1.30 (95% CI, 1.11-1.52; P=0.001), respectively. Genetically predicted atrial fibrillation was suggestively associated with anemia (OR, 1.06 [95% CI, 1.01-1.12]; P=0.015). Sensitivity analyses found weak evidence of horizontal pleiotropy and heterogeneity, which ensured the robustness and reliability of the results. Meta-analysis also showed the statistically significant association between anemia and HF risk. Conclusions Our study supports bidirectional causality between anemia and HF and significant associations between genetic predisposition to CAD and AIS with anemia, which contributes to the clinical management of both diseases.