Prediction and observation of post-admission hematoma expansion in patients with intracerebral hemorrhage

Time-Dependent Changes in Hematoma Expansion Rate after Supratentorial Intracerebral Hemorrhage and Its Relationship with Neurological Deterioration and Functional Outcome

BACKGROUND

Hematoma expansion (HE) following an intracerebral hemorrhage (ICH) is a modifiable risk factor and a treatment target. We examined the association of HE with neurological deterioration (ND), functional outcome, and mortality based on the time gap from onset to baseline CT.

METHODS

We included 567 consecutive patients with supratentorial ICH and baseline head CT within 24 h of onset. ND was defined as a ≥4-point increase on the NIH stroke scale (NIHSS) or a ≥2-point drop on the Glasgow coma scale. Poor outcome was defined as a modified Rankin score of 4 to 6 at 3-month follow-up.

RESULTS

The rate of HE was higher among those scanned within 3 h (124/304, 40.8%) versus 3 to 24 h post-ICH onset (53/263, 20.2%) (p < 0.001). However, HE was an independent predictor of ND (p < 0.001), poor outcome (p = 0.010), and mortality (p = 0.003) among those scanned within 3 h, as well as those scanned 3-24 h post-ICH (p = 0.043, p = 0.037, and p = 0.004, respectively). Also, in a subset of 180/567 (31.7%) patients presenting with mild symptoms (NIHSS ≤ 5), hematoma growth was an independent predictor of ND (p = 0.026), poor outcome (p = 0.037), and mortality (p = 0.027).

CONCLUSION

Despite decreasing rates over time after ICH onset, HE remains an independent predictor of ND, functional outcome, and mortality among those presenting >3 h after onset or with mild symptoms.

Revisiting the role of the complement system in intracerebral hemorrhage and therapeutic prospects

Intracerebral hemorrhage (ICH) is a stroke subtype characterized by non-traumatic rupture of blood vessels in the brain, resulting in blood pooling in the brain parenchyma. Despite its lower incidence than ischemic stroke, ICH remains a significant contributor to stroke-related mortality, and most survivors experience poor outcomes that significantly impact their quality of life. ICH has been accompanied by various complex pathological damage, including mechanical damage of brain tissue, hematoma mass effect, and then leads to inflammatory response, thrombin activation, erythrocyte lysis, excitatory amino acid toxicity, complement activation, and other pathological changes. Accumulating evidence has demonstrated that activation of complement cascade occurs in the early stage of brain injury, and the excessive complement activation after ICH will affect the occurrence of secondary brain injury (SBI) through multiple complex pathological processes, aggravating brain edema, and pathological brain injury. Therefore, the review summarized the pathological mechanisms of brain injury after ICH, specifically the complement role in ICH, and its related pathological mechanisms, to comprehensively understand the specific mechanism of different complements at different stages after ICH. Furthermore, we systematically reviewed the current state of complement-targeted therapies for ICH, providing a reference and basis for future clinical transformation of complement-targeted therapy for ICH.

Current Evaluation of Intracerebral Hemorrhage

Advanced imaging is currently critical in diagnosing, predicting, and managing intracerebral hemorrhage. MD CT angiography has occupied the first line of evaluating patients with a clinical diagnosis of a stroke, given its rapid acquisition time, high resolution of vascular structures, and sensitivity for secondary causes of ICH.

Deep Learning-Based Prediction of Hematoma Expansion Using a Single Brain Computed Tomographic Slice in Patients With Spontaneous Intracerebral Hemorrhages

OBJECTIVES

We aimed to predict hematoma expansion in intracerebral hemorrhage (ICH) patients by using the deep learning technique.

METHODS

We retrospectively collected data from ICH patients treated between May 2015 and May 2019. Head computed tomography (CT) scans were performed at admission, and 6 hours, 24 hours, and 72 hours after admission. CT scans were mandatory when neurologic deficits occurred. Univariate and multivariate analyses were conducted to illustrate the association between clinical variables and hematoma expansion. Convolutional neural network (CNN) was adopted to predict hematoma expansion based on brain CT slices. In addition, 5 machine learning methods, including support vector machine, multi-layer perceptron, naive Bayes, decision tree, and random forest, were also performed to predict hematoma expansion based on clinical variables for comparisons.

RESULTS

A total of 223 patients were included. It was revealed that patients' older age (odds ratio [95% confidence interval]: 1.783 [1.417-1.924]), cerebral hemorrhage and breaking into the ventricle (2.524 [1.291-1.778]), coagulopathy (2.341 [1.677-3.454]), and baseline National Institutes of Health Stroke Scale (1.545 [1.132-3.203]) and Glasgow Coma Scale scores (0.782 [0.432-0.918]) independently associated with hematoma expanding. After 4-5 epochs, the CNN framework was well trained. The average sensitivity, specificity, and accuracy of CNN prediction are 0.9197, 0.8837, and 0.9058, respectively. Compared with 5 machine learning methods based on clinical variables, CNN can also achieve better performance.

CONCLUSIONS

More than 90% of hematomas with or without expansion can be precisely classified by deep learning technology within this study, which is better than other methods based on clinical variables only. Deep learning technology could favorably predict hematoma expansion from non-contrast CT scan images.

Increased Prognostic Yield by Combined Assessment of Non-Contrast Computed Tomography Markers of Antithrombotic-Related Spontaneous Intracerebral Hemorrhage Expansion

Background and aims: The utility of proposed non-contrast computed tomography (NCCT) markers for the prediction of hematoma expansion in patients with antithrombotic-related spontaneous intracerebral hemorrhage (ICH) is limited. Additionally, there is significant overlap between different suggested ICH shape and density markers. Methods: We assessed the prognostic yield for hematoma expansion of a combined score incorporating features of ICH shape irregularity (satellite sign and/or Barras score ≥ 3), heterogeneous ICH density (swirl sign and/or Barras score ≥ 3) on baseline NCCT and timing from ICH onset to NCCT. Results: We evaluated data from 79 patients with antithrombotic-related spontaneous ICH (32% with hematoma expansion). Swirl (84% vs. 39%) and satellite signs (20% vs. 7%) on baseline NCCT were significantly more prevalent (p < 0.001) in patients with hematoma expansion. Patients with hematoma expansion had more irregular and heterogeneous bleeds on baseline NCCT scans, as quantified by higher (p < 0.001) Barras shape (4 (4−5) vs. 3 (2−4)) and density scores (4 (3−5) vs. 2 (1−3)), respectively. The overall diagnostic yield of the combined score (area under the curve: 0.86, 95%CI: 0.78−0.94) significantly outperformed (p < 0.001) the diagnostic yield of each individual marker. Scores of 4 or 5 in the combined score were associated with a sensitivity of 60.0%, specificity of 90.7%, overall diagnostic accuracy of 81.0%, positive likelihood ratio (LR) of 6.48, negative LR of 0.44, positive predictive value (PV) of 0.76 and negative PV of 0.83. Conclusion: Combined NCCT marker assessment seems to increase the prognostic accuracy for hematoma expansion in antithrombotic-related spontaneous ICH patients.

Predicting Hematoma Expansion after Spontaneous Intracranial Hemorrhage Through a Radiomics Based Model

PURPOSE

Intracranial hemorrhage (ICH) is characterized as bleeding into the brain tissue, intracranial space, and ventricles and is the second most disabling form of stroke. Hematoma expansion (HE) following ICH has been correlated with significant neurological decline and death. For early detection of patients at risk, deep learning prediction models were developed to predict whether hematoma due to ICH will expand. This study aimed to explore the feasibility of HE prediction using a radiomic approach to help clinicians better stratify HE patients and tailor intensive therapies timely and effectively.

MATERIALS AND METHODS

Two hundred ICH patients with known hematoma evolution, were enrolled in this study. An open-source python package was utilized for the extraction of radiomic features from both non-contrast computed tomography (NCCT) and magnetic resonance imaging (MRI) scans through characterization algorithms. A total of 99 radiomic features were extracted and different features were selected for network inputs for the NCCT and MR models. Seven supervised classifiers: Support Vector Machine, Naïve Bayes, Decision Tree, Random Forest, Logistic Regression, K-Nearest Neighbor and Multilayer Perceptron were used to build the models. A training:testing split of 80:20 and 20 iterations of Monte Carlo cross validation were performed to prevent overfitting and assess the variability of the networks, respectively. The models were fed training datasets from which they learned to classify the data based on pre-determined radiomic categories.

RESULTS

The highest sensitivity among the NCCT classifier models was seen with the support vector machine (SVM) and logistic regression (LR) of 72 ± 0.3% and 73 ± 0.5%, respectively. The MRI classifier models had the highest sensitivity of 68 ± 0.5% and 72 ± 0.5% for the SVM and LR models, respectively.

CONCLUSIONS

This study indicates that the NCCT radiomics model is a better predictor of HE and that SVM and LR classifiers are better predictors of HE due to their more cautious approach indicated by a higher sensitivity metric.

MicroRNA Transcriptomics Analysis Identifies Dysregulated Hedgehog Signaling Pathway in a Mouse Model of Acute Intracerebral Hemorrhage Exposed to Hyperglycemia

OBJECTIVE

Hyperglycemia is often observed in the patients after acute stroke. This study aims to elucidate the potential effect and mechanism of hyperglycemia by screening microRNAs expression in intracerebral hemorrhage mice.

METHODS

We employed the collagenase model of intracerebral hemorrhage. Twenty male C57BL/6 mice were used and randomly divided in normo- and hyperglycemic. The hyperglycemia was induced by intraperitoneally injection of 50% of Dextrose (8 mL/kg) 3 hours after intracerebral hemorrhage. The neurologic impairment was investigated by neurologic deficit scale. To study the specific mechanisms of hyperglycemia, microRNAs expression in perihematomal area was investigated by RNA sequencing. MicroRNAs expression in hyperglycemic intracerebral hemorrhage animals were compared normoglycemic mice. Functional annotation analysis was used to indicate potential pathological pathway, underlying observed effects. Finally, polymerase chain reaction validation was administered.

RESULTS

Intraperitoneal injection of dextrose significantly increased blood glucose level. That was associated with aggravation of neurological deficits in hyperglycemic compared to normoglycemic animals. A total of 73 differentially expressed microRNAs were identified via transcriptomics analysis. Bioinformatics analyses showed that these microRNAs were significantly altered in several signaling pathways, of which the hedgehog signaling pathway was regarded as the most potential pathway associated with the effect of hyperglycemia on acute intracerebral hemorrhage. Furthermore, polymerase chain reaction results validated the correlation between microRNAs and hedgehog signaling pathway.

CONCLUSIONS

MicroRNA elevated in hyperglycemia group may be involved in worsening the neurological function via inhibiting the hedgehog signaling, which provides a novel molecular physiological mechanism and lays the foundation for treatment of intracerebral hemorrhage.

A Novel CT-based Radiomics-Clinical Nomogram for the Prediction of Short-Term Prognosis in Deep Intracerebral Hemorrhage

OBJECTIVE

To develop and validate a radiomics-clinical nomogram for the prediction of short-term prognosis in patients with deep intracerebral hemorrhage (DICH) on admission.

METHODS

A total of 326 patients with DICH (development cohort = 187; testing cohort = 81; validation cohort = 58) were retrospectively included. Radiomics features were extracted from computed tomography (CT) images and optimal features were selected using least absolute shrinkage and selection operator regression. A radiomics score (R-score) was developed using the optimal features. Univariate and multivariate analyses were used to determine independent risk factors for poor outcomes at 30 days. A radiomics-clinical (R-C) nomogram was developed and validated in the three cohorts. Receiver operating characteristic curve (ROC), calibration curve and decision curve analyses were conducted to evaluate the performances of the R-C nomogram.

RESULTS

Only 4 of 396 radiomics features were selected to develop R-scores. Age, onset-to-CT time, Glasgow Coma Scale score, midline shift, and R-score were detected as independent predictors of poor prognosis of DICH. The R-C nomogram was developed by the independent predictors and showed acceptable discrimination with areas under ROCs of 0.80, 0.79, and 0.70 in the development, testing and validation cohorts, respectively. The R-C nomogram showed good agreement between the predicted probability and the actual probability (all P > 0.05) and clinical applicability in each cohort.

CONCLUSIONS

The R-C nomogram is a stable and effective tool for predicting the short-term prognosis of DICH, which may help clinicians perform individual risk assessments and make decisions for patients with DICH.

Systematic Analysis of Combined Thrombolysis Using Ultrasound and Different Fibrinolytic Drugs in an in Vitro Clot Model of Intracerebral Hemorrhage

Adequate removal of blood clots by minimally invasive surgery seems to correlate with a better clinical outcome in patients with intracerebral hemorrhages (ICHs). Moreover, neurotoxic effects of recombinant tissue plasminogen activator have been reported. The aim of this study was to improve fibrinolysis using an intra-clot ultrasound application with tenecteplase and urokinase in our established ICH clot model. One hundred thirty clots were produced from 25 or 50 mL of human blood, incubated for different periods and equipped with drainage, through which an ultrasound catheter was placed in 65 treatment clots for 1 h, randomly allocated into three groups: administration of ultrasound, administration of 60 IU of tenecteplase or administration of 30,000 IU urokinase. Relative end weights were compared. This study found a significant increase in thrombolysis caused by a combination of ultrasound and fibrinolytic drugs, whereas ultrasound and tenecteplase are significantly more effective in the treatment of larger and aged clots.

Imaging of Spontaneous Intracerebral Hemorrhage

Primary or nontraumatic spontaneous intracerebral hemorrhage (ICH) comprises approximately 15% to 20% of all stroke. ICH has a mortality of approximately 40% within the first month, and 75% mortality and morbidity rate within the first year. Despite reduction in overall stroke incidence, hemorrhagic stroke incidence has remained steady since 1980. Neuroimaging is critical in detection of ICH, determining the underlying cause, identification of patients at risk of hematoma expansion, and directing the treatment strategy. This article discusses the neuroimaging methods of ICH, imaging markers for clinical outcome prediction, and future research directions with attention to the latest evidence-based guidelines.

Clinical-radiomics Nomogram for Risk Estimation of Early Hematoma Expansion after Acute Intracerebral Hemorrhage

RATIONALE AND OBJECTIVES

Noncontrast CT-based radiomics signature has shown ability for detecting hematoma expansion (HE) in spontaneous intracerebral hemorrhage (ICH). We sought to compare its predictive performance with clinical risk factors and develop a clinical-radiomics nomogram to assess the risk of early HE.

MATERIALS AND METHODS

In total, 1153 patients with ICH who underwent baseline cranial CT within 6 hours and follow-up scans within 72 hours of stroke onset were enrolled, of whom 864 (75%) were assigned to the derivation cohort and 289 (25%) to the validation cohort. Based on LASSO algorithm or stepwise logistic regression analysis, three models (clinical model, radiomics model, and hybrid model) were constructed to predict HE. The Akaike information criterion (AIC) and likelihood ratio test (LRT) were used for comparing the goodness of fit of the three models, and the AUC was used to evaluate their discrimination ability for HE.

RESULTS

The hybrid model (AIC = 681.426; χ²= 128.779) was the optimal model with the lowest AIC and highest chi-square values compared to the radiomics model (AIC = 767.979; χ² = 110.234) or the clinical model (AIC = 753.757; χ² = 56.448). The radiomics model was superior in the prediction of HE to the clinical model in both derivation (p = 0.009) and validation (p = 0.022) cohorts. In both datasets, the clinical-radiomics nomogram showed satisfactory discrimination and calibration for detecting HE (AUC = 0.771, Sensitivity = 87.0%; AUC = 0.820, Sensitivity = 88.1%; respectively).

CONCLUSION

Among patients with acute ICH, noncontrast CT-based radiomics model outperformed the clinical-only model in the prediction of HE, and the established clinical-radiomics nomogram with favorable performance can offer a noninvasive tool for the risk stratification of HE.

Smoking Status Affects the Association Between Hematoma Heterogeneity and Hematoma Expansion

Objective

The purpose of this study was to verify the relationship between hematoma heterogeneity and hematoma expansion and explore any effect modifiers through subgroup analyses.

Methods

Clinical records of 357 patients with spontaneous cerebral hemorrhage at Shenzhen Second People’s Hospital from March 2016 to October 2018 were included in the study. Hematoma heterogeneity was measured on the first noncontrast computed tomography image according to the Barras scale. Hematoma expansion was defined as an absolute hematoma volume increase of 6 mL, or a 33% increase. We performed univariate and multivariate logistic regression analyses, as well as subgroup analyses, to assess the relationship between the presence of heterogeneity on noncontrast computed tomography and hematoma expansion.

Results

Hematoma expansion occurred in 79 (22.13%) of the 357 patients with intracerebral hemorrhage (ICH). Among the patients with ICH, there were 83 smokers, accounting for 23.24%. The average patient age was 56.21 ± 13.75 years, and 74.51% were male. Compared with the absence of heterogeneity, the risk of hematoma expansion increased by 1.06 times (odds ratio, 2.06; 95% confidence interval, 1.10–3.86). Based on the subgroup analysis, smoking status was found to modify the association between heterogeneity and hematoma expansion; the association was stronger in smokers than in nonsmokers (odds ratio, 10.23; 95% confidence interval, 2.15–48.65).

Conclusions

Heterogeneity independently predicts hematoma expansion, especially in smoking patients.

Methyltransferase 3 Mediated miRNA m6A Methylation Promotes Stress Granule Formation in the Early Stage of Acute Ischemic Stroke

The modification of methyltransferase-like (METTL) enzymes plays important roles in various cellular responses by regulating microRNA expression. However, how m6A modification is involved in stress granule (SG) formation in the early stage of acute ischemic stroke by affecting the biogenesis processing of microRNAs remains unclear. Here, we established a middle cerebral artery occlusion (MCAO) model in rats and an oxygen-glucose deprivation/reperfusion (OGD/R) model in primary cortical neurons and PC12 cells to explore the potential mechanism between m6A modification and SG formation. The in vivo results showed that the level of infarction and apoptosis increased while SG formation decreased significantly within the ischemic cortex with improved reperfusion time after 2 h of ischemia. Consistent with the in vivo data, an inverse association between the apoptosis level and SG formation was observed in PC12 cells during the reperfusion period after 6 h of OGD stimulation. Both in vivo and in vitro results showed that the expression of METTL3 protein, m6A and miR-335 was significantly decreased with the reperfusion period. Overexpression of the METTL3 and METTL3 gene-knockdown in PC12 cells were achieved via plasmid transfection and CRISPR-Cas9 technology, respectively. Overexpression or knockdown of METTL3 in oxygen-glucose deprivation of PC12 cells resulted in functional maturation of miR-335, SG formation and apoptosis levels. In addition, we found that miR-335 enhanced SG formation through degradation of the mRNA of the eukaryotic translation termination factor (Erf1). In conclusion, we found that METTL3-mediated m6A methylation increases the maturation of miR-335, which promotes SG formation and reduces the apoptosis level of injury neurons and cells, and provides a potential therapeutic strategy for AIS.

Imaging-based outcome prediction in patients with intracerebral hemorrhage

Besides the established spot sign in computed tomography angiography (CTA), recently investigated imaging predictors of hematoma growth in noncontrast computed tomography (NCCT) suggest great potential for outcome prediction in patients with intracerebral hemorrhage (ICH). Secondary hematoma growth is an appealing target for therapeutic interventions because in contrast to other determined factors, it is potentially modifiable. Even more initial therapy studies failed to demonstrate clear therapeutic benefits, there is a need for an effective patient selection using imaging markers to identify patients at risk for poor outcome and thereby tailor individual treatments for every patient. Hence, this review gives an overview about the current literature on NCCT imaging markers for neurological outcome prediction and aims to clarify the association with the established spot sign. Moreover, it demonstrates the clinical impact of these parameters and gives a roadmap for future imaging research in patients with intracerebral hemorrhage.

Association of Short- and Medium-Term Particulate Matter Exposure with Risk of Mortality after Spontaneous Intracerebral Hemorrhage

OBJECTIVE

We investigated the association of short- and medium-term particulate matter (PM) exposure with risk of mortality in patients with spontaneous intracerebral hemorrhage (ICH) identified according to strict etiologic criteria.

METHODS

We conducted a retrospective analysis of prospectively collected data from consecutive patients with spontaneous ICH admitted to the emergency department of the University Hospital of Verona from March 2011 to December 2014. Outcome measures were mortality within 1 month after ICH and significant hematoma expansion (HE) defined as an absolute growth of more than 12.5 mL or a relative increase of more than 50% from baseline to follow-up computed tomography scan.

RESULTS

A final number of 308 patients were included. In the adjusted model, higher PM_2.5 and PM₁₀ values in the last 3 days (odds ratio [OR] 1.827, 95% confidence interval [CI] 1.057-3.159, P = .031 and OR 1.949, 95% CI 1.025-3.704, P = .042, respectively) and in the last 4 weeks (OR 4.975, 95% CI 2.174-11.381, P < .001 and OR 9.781, 95% CI 3.425-27.932, P < .001, respectively) before ICH were associated with higher mortality rate. No association was found between PM exposure and significant HE.

CONCLUSIONS

PM exposure in the short- and medium-term before spontaneous ICH was associated with risk of 1-month mortality, independent of predictors such as age, sex, stroke severity, intraventricular hemorrhage, ICH volume, ICH location, ICH etiologic subtype, significant HE, antithrombotic therapy, atrial fibrillation, and blood glucose levels.

Intracerebral Hemorrhagic Expansion Occurs in Patients Using Non-Vitamin K Antagonist Oral Anticoagulants Comparable with Patients Using Warfarin

BACKGROUND

Non-vitamin K antagonist oral anticoagulant (NOAC) use has significantly reduced intracerebral hemorrhagic (ICH) risk compared with standard anticoagulant treatment. Hematoma expansion (HE) is a known predictor of mortality in warfarin-associated ICH. Little is known about HE in patients using NOACs.

METHODS

We conducted a retrospective chart review of patients with ICH admitted to Cedars-Sinai Medical Center from October 2010 to June 2016. We identified patients with concomitant administration of an oral anticoagulant and collected data including evidence of HE on imaging and modified Rankin Scale (mRS) at discharge. We defined HE as relative (≥33% increase) or absolute expansion (≥12 mL). We compared outcomes of patients with and without HE.

RESULTS

Out of 814 patients with ICH who were admitted, we identified 9 patients with recent NOAC use and 18 intentionally matched controls on warfarin. We found no significant differences in National Institutes of Health Stroke Scale or ICH score on presentation (median [interquartile range] 15 [5,21] versus 7 [1.25,19.5] [P = .41] and 2 [1,4] versus 1 [1,3] [P = .33]) between patients on NOACs and those on warfarin. Four out of the 9 patients on NOAC and 5 of the 18 patients on warfarin demonstrated HE, with no significant difference (P = .42). There were no significant differences in mRS on discharge between groups (P = .52).

CONCLUSIONS

In our coagulopathic NOAC patient population, HE occurs within 6 hours in 44% of patients. This case series did not have sufficient statistical power to detect significant differences between the groups. To our knowledge, this is one of the largest case series reporting on HE with concomitant NOAC use.

Quantitative assessment on blood-brain barrier permeability of acute spontaneous intracerebral hemorrhage in basal ganglia: a CT perfusion study

PURPOSE

Blood-brain barrier (BBB) damage aggravates perihematomal edema, and edema volume predicts prognosis independently. But the BBB permeability at the late stage of acute intracerebral hemorrhage (ICH) patients is uncertain. We aimed to assess the BBB permeability of spontaneous basal ganglia ICH using computed tomographic perfusion (CTP) and investigates its relationship with hematoma and perihematomal edema volume.

METHODS

We performed CTP on 54 consecutive ICH patients within 24 to 72 h after symptom onset. Permeability-surface area product (PS) derived from CTP imaging was measured in hematoma, "high-PS spot," perihematoma, normal-appearing, hemispheric, and contralateral regions. Hematoma and edema volumes were calculated from non-contrast CT.

RESULTS

"High-PS spot" and perihematoma regions had higher PS than the contralateral regions (p < 0.001). Hematoma PS was lower than that in the contralateral regions (p < 0.001). Perihematoma PS of the large-hematoma group was higher than that of the small-hematoma group (p = 0.011). Perihematomal edema volume correlated positively with hematoma volume (β = 0.864, p < 0.001) and perihematoma PS (β = 0.478, p < 0.001). Perihematoma PS correlated positively with hematoma volume (β = 0.373, p = 0.005).

CONCLUSIONS

Locally elevated perihematoma PS was found in most spontaneous basal ganglia ICH patients within 24 to 72 h after symptom onset. Perihematoma PS was higher in larger hematomas and was associated with larger edema volume. At this period, BBB leakage is likely to be an important factor in edema formation.

Association Between Circulating Copeptin Level and Mortality Risk in Patients with Intracerebral Hemorrhage: a Systemic Review and Meta-Analysis

Copeptin has been identified as a biomarker of disease severity and is associated with mortality risk in several common diseases. This study sought to determine the association between circulating copeptin level and mortality risk in patients with intracerebral hemorrhage. PubMed, Web of Science, and Wanfang Medicine Database were searched for studies assessing the association between circulating copeptin level and mortality risk in patients with intracerebral hemorrhage. The pooled hazard ratio (HR) of mortality was calculated and presented with 95 % confidence interval (95 % CI). Data from 1332 intracerebral hemorrhage patients were derived from 9 studies. Meta-analysis showed that intracerebral hemorrhage patients with poor prognosis had much higher copeptin levels than those survivors (standardized mean difference = 1.68, 95 % CI 1.26-2.11, P < 0.00001). Meta-analysis of 8 studies with HRs showed that high circulating copeptin level was associated with higher risk of mortality in patients with intracerebral hemorrhage (HR = 2.42, 95 % CI 1.60-3.65, P < 0.0001). Meta-analysis of 6 studies with adjusted HRs showed that high circulating copeptin level was independently associated with higher risk of mortality in patients with intracerebral hemorrhage (HR = 1.67, 95 % CI 1.26-2.22, P = 0.0003). Our study suggests that there is an obvious association between circulating copeptin level and mortality in patients with intracerebral hemorrhage. High circulating copeptin level is independently associated with higher risk of mortality in patients with intracerebral hemorrhage.

Imaging of cerebrovascular disorders: precision medicine and the collaterome

Imaging of stroke and neurovascular disorders has profoundly enhanced clinical practice and related research during the last 40 years since the introduction of computed tomography (CT) and magnetic resonance imaging (MRI) enabled mapping of the brain. We highlight recent advances in neurovascular imaging. We describe how the convergence of readily available data and new clinical trial paradigms will recast our methods for studying the neurovascular patient. The application of a precision medicine approach to the collaterome, a comprehensive synthesis of neurovascular pathophysiology, will entail novel methods for clinical trial randomization, collection of routine and clinical trial imaging results, data archiving, and analysis.