The effectiveness of early systemic inflammatory indices in predicting advanced intraventricular hemorrhage in preterm infants.

Some systemic inflammatory indices have been reported to be associated with intracerebral hemorrhage in adults. However, the relationship between systemic inflammatory indices and intraventricular hemorrhage (IVH) in premature neonates is still not completely understood. OBJECTIVE: To evaluate the relationship between systemic inflammatory indices obtained on the first day of life in premature infants and the development of severe IVH. PATIENTS AND METHOD: Premature newborns < 32 weeks of gestational age were included. Eligible patients were divided into 2 groups: Group 1: without IVH or grade I and II hemorrhage, and Group 2: grade III and IV HIV. Demographic characteristics, clinical outcomes, monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII), pan-immune inflammation value (PIV), and Systemic inflammation response index (SIRI) were compared between groups. RESULTS: A total of 1176 newborns were included in the study, 1074 in Group 1 and 102 premature babies in Group 2. There was no difference between the groups in terms of the count of leukocytes, neutrophils, monocytes, lymphocytes and platelets (p > 0.05). The values of NLR, MLR, PLR, PIV, SII and SIRI were similar in both groups (p > 0.05). CONCLUSION: While the relationship between inflammation, hemodynamics and IVH is still under discussion, our results show that systemic inflammatory indices have no predictive value for IVH.

Clinical features and treatment of apoplectic intratumoral hemorrhage of glioma.

OBJECTIVE: The primary objective of this study was to explore the clinical characteristics of apoplectic intratumoral hemorrhage in gliomas and offer insights for improving the diagnosis and treatment of this disease. METHODS: We analyzed the clinical data of 35 patients with glioma and hemorrhage. There were eight cases of multiple cerebral lobe involvement, and 22 cases involved a single lobe. Twenty-one patients had a preoperative Glasgow Coma Scale (GCS) score of ≥ 9 and had a craniotomy with tumor resection and hematoma evacuation after undergoing preoperative preparation. A total of 14 patients with GCS < 9, including one with thalamic hemorrhage breaking into the ventricles and acute obstructive hydrocephalus, underwent craniotomy for tumor resection after external ventricular drainage (EVD). One patient had combined thrombocytopenia, which was surgically treated after platelet levels were normalized through transfusion. The remaining 12 patients received immediate intervention in the form of craniotomy hematoma evacuation and tumor resection. RESULTS: We performed subtotal resection on three tumors of thalamic origin and two tumors of corpus callosum origin, but we were able to successfully resect all the tumors in other locations that were gross total resection Pathology results showed that 71.43% of cases accounted for WHO-grade 4 tumors. Among the 21 patients with a GCS score of ≥ 9, two died perioperatively. Fourteen patients had a GCS score < 9, of which eight patients died perioperatively. CONCLUSIONS: Patients with a preoperative GCS score ≥ 9 who underwent subemergency surgery and received aggressive treatment showed a reasonable prognosis. We found their long-term outcomes to be correlated with the pathology findings. On the other hand, patients with a preoperative GCS score < 9 required emergency treatment and had a high perioperative mortality rate.

Serum secretoneurin as a promising biomarker for predicting poor prognosis in intracerebral hemorrhage: A prospective cohort study.

OBJECTIVE: Secretoneurin may play a brain-protective role. We aim to discover the relationship between serum secretoneurin levels and severity plus neurological outcome after intracerebral hemorrhage (ICH). METHODS: In this prospective cohort study, serum secretoneurin levels were measured in 110 ICH patients and 110 healthy controls. Glasgow Coma Scale (GCS) and hematoma volume were used to assess stroke severity. Poor prognosis was defined as Glasgow Outcome Scale (GOS) scores of 1-3 at 90 days after ICH. A multivariate logistic regression model was constructed to determine independent correlation of serum secretoneurin levels with severity and poor prognosis. Under receiver operating characteristic (ROC) curve, prognostic ability of serum secretoneurin levels was assessed. Restricted cubic spline (RCS) model and subgroups analysis were used for discovering association of serum secretoneurin levels with risk of poor prognosis. Calibration curve and decision curve were evaluated to confirm performance of nomogram. RESULTS: Serum secretoneurin levels of patients were significantly higher than those of healthy controls. Serum secretoneurin levels of patients were independently correlated with GCS scores and hematoma volume. There were 42 patients with poor prognosis at 90 days following ICH. Serum secretoneurin levels were significantly higher in patients with poor outcome than in those with good outcome. Under the ROC curve, serum secretoneurin levels significantly differentiated poor outcome. Serum secretoneurin levels ≥ 22.8 ng/mL distinguished patients at risk of poor prognosis at 90 days with a sensitivity of 66.2% and a specificity of 81.0%. Besides, serum secretoneurin levels independently predicted a 90-day poor prognosis. Subgroup analysis showed that serum secretoneurin levels had non-significant interactions with other variables. The nomogram, including independent prognostic predictors, showed reliable prognosis capability using calibration curve and decision curve. Area under the curve of the predictive model was significantly higher than those of GCS scores and hematoma volume. CONCLUSION: Serum secretoneurin levels are strongly related to ICH severity and poor prognosis at 90 days after ICH. Thus, serum secretoneurin may be a promising prognostic biomarker in ICH.

Precranial artery calcification burden: a potential indicator of the clinical outcome of reperfusion in patients with acute large artery occlusion.

OBJECTIVE: With mechanical thrombectomy (MT), we investigated the prognostic importance of aortic arch calcification (AoAC) and carotid sinus calcification (CaSC) for symptomatic intracerebral hemorrhage (sICH) and poor outcome in acute large artery occlusion (LAO). METHODS: In this retrospective observational study, we calculated pre-cranial artery calcification burden (PACB) scores (burden score of AoAC and CaSC) using the AoAC grading scale score plus Woodcock visual score. The outcome measure was sICH per the European Cooperative Acute Stroke Study III definition. A 3-month modified Rankin scale score 3-6 was designated as poor outcome. RESULTS: Compared with patients who had PACB <3, those with PACB ≥3 showed substantially higher risks of sICH (odds ratio [OR] = 2.567, 95% confidence interval [CI] = 1.187-5.550) and poor outcome (OR = 4.777, 95% CI = 1.659-13.756). According to receiver operating characteristic (ROC) curves, adding PACB to the regression model enhanced the predictive value for poor outcome (area under the ROC curve [AUC]: 0.718 vs. 0.519, Z = 2.340) and in patients receiving MT (AUC: 0.714 vs. 0.584, Z = 2.021), independently. CONCLUSIONS: Factors related to PACB were consistent with common risk factors of systemic atherosclerosis. Low PACB scores indicated better prognosis. In patients with LAO following MT, PACB was useful in predicting sICH and poor clinical outcome.

Advancements in prognostic markers and predictive models for intracerebral hemorrhage: from serum biomarkers to artificial intelligence models.

Intracerebral hemorrhage (ICH) is a severe form of stroke with high morbidity and mortality, accounting for 10-15% of all strokes globally. Recent advancements in prognostic biomarkers and predictive models have shown promise in enhancing the prediction and management of ICH outcomes. Serum sestrin2, a stress-responsive protein, has been identified as a significant prognostic marker, correlating with severity indicators such as NIHSS scores and hematoma volume. Its levels predict early neurological deterioration and poor prognosis, offering predictive capabilities comparable to traditional measures. Furthermore, a deep learning-based AI model demonstrated superior performance in predicting early hematoma enlargement, with higher sensitivity and specificity than conventional methods. Additionally, long-term outcome prediction models using CT radiomics and machine learning have achieved high accuracy, particularly with the Random Forest algorithm. These advancements underscore the potential of integrating novel biomarkers and advanced computational techniques to improve prognostication and management of ICH, aiming to enhance patient care and survival rates. The incorporation of serum sestrin2, AI, and machine learning in predictive models represents a significant step forward in the clinical management of ICH, offering new avenues for research and clinical application.

Anemia From Inflammation After Intracerebral Hemorrhage and Relationships With Outcome.

BACKGROUND: Baseline anemia is associated with poor intracerebral hemorrhage (ICH) outcomes. However, underlying drivers for anemia and whether anemia development after ICH impacts clinical outcomes are unknown. We hypothesized that inflammation drives anemia development after ICH and assessed their relationship to outcomes. METHODS AND RESULTS: Patients with serial hemoglobin and iron biomarker concentrations from the HIDEF (High-Dose Deferoxamine in Intracerebral Hemorrhage) trial were analyzed. Adjusted linear mixed models assessed laboratory changes over time. Of 42 patients, significant decrements in hemoglobin occurred with anemia increasing from 19% to 45% by day 5. Anemia of inflammation iron biomarker criteria was met in 88%. A separate cohort of 521 patients with ICH with more granular serial hemoglobin and long-term neurological outcome data was also investigated. Separate regression models assessed whether (1) systemic inflammatory response syndrome (SIRS) scores related to hemoglobin changes over time and (2) hemoglobin changes related to poor 90-day outcome. In this cohort, anemia prevalence increased from 30% to 71% within 2 days of admission yet persisted beyond this time. Elevated systemic inflammatory response syndrome was associated with greater hemoglobin decrements over time (adjusted parameter estimate: -0.27 [95% CI, -0.37 to -0.17]) and greater hemoglobin decrements were associated with poor outcomes (adjusted odds ratio per 1 g/dL increase, 0.76 [95% CI, 0.62-0.93]) independent to inflammation and ICH severity. CONCLUSIONS: We identified novel findings that acute anemia development after ICH is common, rapid, and related to inflammation. Because anemia development is associated with poor outcomes, further work is required to clarify if anemia, or its underlying drivers, are modifiable treatment targets that can improve ICH outcomes. REGISTRATION: https://www.clinicaltrials.gov Unique identifier: NCT01662895.

Prognostic biomarkers of intracerebral hemorrhage identified using targeted proteomics and machine learning algorithms.

Early prognostication of patient outcomes in intracerebral hemorrhage (ICH) is critical for patient care. We aim to investigate protein biomarkers' role in prognosticating outcomes in ICH patients. We assessed 22 protein biomarkers using targeted proteomics in serum samples obtained from the ICH patient dataset (N = 150). We defined poor outcomes as modified Rankin scale score of 3-6. We incorporated clinical variables and protein biomarkers in regression models and random forest-based machine learning algorithms to predict poor outcomes and mortality. We report Odds Ratio (OR) or Hazard Ratio (HR) with 95% Confidence Interval (CI). We used five-fold cross-validation and bootstrapping for internal validation of prediction models. We included 149 patients for 90-day and 144 patients with ICH for 180-day outcome analyses. In multivariable logistic regression, UCH-L1 (adjusted OR 9.23; 95%CI 2.41-35.33), alpha-2-macroglobulin (aOR 5.57; 95%CI 1.26-24.59), and Serpin-A11 (aOR 9.33; 95%CI 1.09-79.94) were independent predictors of 90-day poor outcome; MMP-2 (aOR 6.32; 95%CI 1.82-21.90) was independent predictor of 180-day poor outcome. In multivariable Cox regression models, IGFBP-3 (aHR 2.08; 95%CI 1.24-3.48) predicted 90-day and MMP-9 (aOR 1.98; 95%CI 1.19-3.32) predicted 180-day mortality. Machine learning identified additional predictors, including haptoglobin for poor outcomes and UCH-L1, APO-C1, and MMP-2 for mortality prediction. Overall, random forest models outperformed regression models for predicting 180-day poor outcomes (AUC 0.89), and 90-day (AUC 0.81) and 180-day mortality (AUC 0.81). Serum biomarkers independently predicted short-term poor outcomes and mortality after ICH. Further research utilizing a multi-omics platform and temporal profiling is needed to explore additional biomarkers and refine predictive models for ICH prognosis.

Advances and Future Trends in the Diagnosis and Management of Intracerebral Hemorrhage.

Spontaneous intracerebral hemorrhage accounts for approximately 10% to 15% of all strokes in the United States and remains one of the deadliest. Of concern is the increasing prevalence, especially in younger populations. This article reviews the following: epidemiology, risk factors, outcomes, imaging findings, medical management, and updates to surgical management.

Higher blood glucose is associated with the severity of hemorrhagic transformation after endovascular therapy for stroke.

OBJECTIVES: Hyperglycemia is associated with poor outcome in large vessel occlusion (LVO) stroke, with mechanism for this effect unknown. MATERIALS AND METHODS: We used our prospective, multicenter, observational study, Blood Pressure After Endovascular Stroke Therapy (BEST), of anterior circulation LVO stroke undergoing endovascular therapy (EVT) from 11/2017-7/2018 to determine association between increasing blood glucose (BG) and intracerebral hemorrhage (ICH). Our primary outcome was degree of ICH, classified as none, asymptomatic ICH, or symptomatic ICH (≥4-point increase in National Institutes of Health Stroke Scale [NIHSS] at 24 h with any hemorrhage on imaging). Secondary outcomes included 24 h NIHSS, early neurologic recovery (ENR, NIHSS 0-1 or NIHSS reduction by ≥8 within 24 h), and 90-day modified Rankin Scale (mRS) using univariate and multivariable regression. RESULTS: Of 485 enrolled patients, increasing BG was associated with increasing severity of ICH (adjusted OR, aOR 1.06, 95 % CI 1.02-1.1, p < 0.001), higher 24 h NIHSS (aOR 1.22, 95 % CI 1.11-1.34, p < 0.001), ENR (aOR 0.90, 95 % CI 0.82-1.00, p < 0.002), and 90-day mRS (aOR 1.06, 95 % CI 1.03-1.09, p < 0.001) when adjusted for age, presenting NIHSS, ASPECTS, 24-hour peak systolic blood pressure, time from last known well, and successful recanalization. CONCLUSIONS: In the BEST study, increasing BG was associated with greater odds of increasing ICH severity. Further study is warranted to determine whether treatment of will decrease ICH severity following EVT.

Can baseline serum calcium levels predict outcomes of intracerebral hemorrhage? A systematic review and meta-analysis.

OBJECTIVE: The prognostic role of baseline calcium levels in patients with intracerebral hemorrhage (ICH) is conflicting. We aimed to conduct the first meta-analysis in the literature to examine if baseline calcium levels can predict outcomes after ICH. METHODS: English-language studies listed on the databases of Embase, PubMed, ScienceDirect, and Web of Science were searched up to 20th November 2023. Meta-analysis was conducted for baseline hematoma volume, hematoma expansion, unfavorable functional outcome, and mortality. RESULTS: Ten studies were included. Meta-analysis showed that patients with hypocalcemia have significantly higher baseline hematoma volume (MD: 8.6 95 % CI: 3.30, 13.90 I2 = 88 %) but did not have a higher risk of hematoma expansion (OR: 1.82 95 % CI: 0.89, 3.73 I2 = 82 %). Meta-analysis of crude (OR: 1.86 95 % CI: 1.25, 2.78 I2 = 63 %) and adjusted data (OR: 2.05 95 % CI: 1.27, 3.28 I2 = 64 %) showed those with hypocalcemia had a significantly higher risk of unfavorable functional outcomes. Meta-analysis of both crude (OR: 2.09 95 % CI: 1.51, 2.88 I2 = 80 %) and adjusted data (OR: 1.38 95 % CI: 1.14, 1.69 I2 = 70 %) also demonstrated a significantly higher risk of mortality in patients with hypocalcemia. CONCLUSION: Baseline serum calcium may have a prognostic role in ICH. Hypocalcemia at baseline may lead to large hematoma volume and poor functional and survival outcomes. However, there seems to be no relation between hypocalcemia and the risk of hematoma expansion. Further studies examining the role of calcium on ICH prognosis are needed.

Outcome Trajectories after Intracerebral Hemorrhage.

Spontaneous intracerebral hemorrhage (ICH) is the most morbid of all stroke types with a high early mortality and significant early disability burden. Traditionally, outcome assessments after ICH have mirrored those of acute ischemic stroke, with 3 months post-ICH being considered a standard time point in most clinical trials, observational studies, and clinical practice. At this time point, the majority of ICH survivors remain with moderate to severe functional disability. However, emerging data suggest that recovery after ICH occurs over a more protracted course and requires longer periods of follow-up, with more than 40% of ICH survivors with initial severe disability improving to partial or complete functional independence over 1 year. Multiple other domains of recovery impact ICH survivors including cognition, mood, and health-related quality of life, all of which remain under studied in ICH. To further complicate the picture, the most important driver of mortality after ICH is early withdrawal of life-sustaining therapies, before initiation of treatment and evaluating effects of prolonged supportive care, influenced by early pessimistic prognostication based on baseline severity factors and prognostication biases. Thus, our understanding of the true natural history of ICH recovery remains limited. This review summarizes the existing literature on outcome trajectories in functional and nonfunctional domains, describes limitations in current prognostication practices, and highlights areas of uncertainty that warrant further research.

Development of a time-resolved immunochromatographic test strip for rapid and quantitative determination of GFAP in serum.

Glial fibrillary acidic protein (GFAP) in serum has been shown as a biomarker of traumatic brain injury (TBI) which is a significant global public health concern. Accurate and rapid detection of serum GFAP is critical for TBI diagnosis. In this study, a time-resolved fluorescence immunochromatographic test strip (TRFIS) was proposed for the quantitative detection of serum GFAP. This TRFIS possessed excellent linearity ranging from 0.05 to 2.5 ng/mL for the detection of serum GFAP and displayed good linearity (Y = 598723X + 797198, R2 = 0.99), with the lowest detection limit of 16 pg/mL. This TRFIS allowed for quantitative detection of serum GFAP within 15 min and showed high specificity. The intra-batch coefficient of variation (CV) and the inter-batch CV were both < 4.0%. Additionally, this TRFIS was applied to detect GFAP in the serum samples from healthy donors and patients with cerebral hemorrhage, and the results of TRFIS could efficiently discern the patients with cerebral hemorrhage from the healthy donors. Our developed TRFIS has the characteristics of high sensitivity, high accuracy, and a wide linear range and is suitable for rapid and quantitative determination of serum GFAP on-site.

The impact of sex on epidemiology, management, and outcome of spontaneous intracerebral hemorrhage (sICH).

OBJECTIVE: Data on sex differences in spontaneous intracerebral hemorrhages are limited. METHODS: An automated comprehensive scoping literature review was performed using PubMed and Scopus. Articles written in English about spontaneous intracerebral hemorrhage and sex were reviewed. RESULTS: Males experience spontaneous intracerebral hemorrhage more frequently than females, at younger ages, and have a higher prevalence of deep bleeds compared to females. Risk factors between sexes vary and may contribute to differing incidences and locations of spontaneous intracranial hemorrhage. Globally, females receive less aggressive care than males, likely impacting survival. CONCLUSIONS: Epidemiology, risk factors, and treatment of spontaneous intracranial hemorrhage vary by sex, with limited and oftentimes conflicting data available. Further research into the sex-based differences of spontaneous intracranial hemorrhage is necessary for clinicians to better understand how to evaluate and guide treatment in the future.

[Extremely preterm infants with severe intraventricular hemorrhage: neurological evolution and long term and educational status]. / Niños muy prematuros con hemorragia intraventricular extensa: evolución neurológica y escolaridad a largo plazo.

Extensive intraventricular hemorrhage (IVH) in very preterm newborns (VPNB) is associated with mortality and severe long-term neurological sequelae. OBJECTIVES: To know the most frequent neurological pathologies associated with extensive IVH, to determine the functional outcomes of mobility in the motor area and intellectual capacity in the cognitive area, to analyze the association between both areas and to know the schooling achieved. PATIENTS AND METHOD: Descriptive and longitudinal study in VPNB with extensive IVH born between 2001 and 2014. They underwent protocolized neurological follow-up until school age. The functional outcomes in mobility and intellectual capacity were categorized into 4 levels: level 1 corresponds to good functionality and autonomy; level 2, functionality that allows independence, with support in some tasks; level 3 requires constant external support; and level 4 where there is total dependence. The association was analyzed using Chi-square and Cramer's V coefficient. RESULTS: 74 children completed the follow-up; the most frequent associated neurological pathologies were neurodevelopmental disorders, hypertensive hydrocephalus, and epilepsy. Independent mobility (normal or with limitations) reached 74.4% while 24.3% used wheelchairs. 51.3% was categorized as normal to borderline intellectual range, 12.2% as mild intellectual disability (ID), 17.6% as moderate ID, and 19.9% as severe to profound ID. There was a strong statistical association between functional levels of mobility and intellectual capacity (p < 0.000 and V = 0.62). Schooling was proportional to intellectual capacity: 56.8% attended regular schools, 27.0% attended special schools, and 16.2% had no schooling. CONCLUSIONS: 2/3 VPNB with extensive IVH showed positive functional outcomes, from normal to mild limitations that allow an almost autonomous life; in 1/3 the outcomes were unfavorable in mobility and cognitive performance, and there was a strong statistical correlation between both areas studied. Schooling was consistent with the intellectual level.

Identifying potential (re)hemorrhage among sporadic cerebral cavernous malformations using machine learning.

The (re)hemorrhage in patients with sporadic cerebral cavernous malformations (CCM) was the primary aim for CCM management. However, accurately identifying the potential (re)hemorrhage among sporadic CCM patients in advance remains a challenge. This study aims to develop machine learning models to detect potential (re)hemorrhage in sporadic CCM patients. This study was based on a dataset of 731 sporadic CCM patients in open data platform Dryad. Sporadic CCM patients were followed up 5 years from January 2003 to December 2018. Support vector machine (SVM), stacked generalization, and extreme gradient boosting (XGBoost) were used to construct models. The performance of models was evaluated by area under receiver operating characteristic curves (AUROC), area under the precision-recall curve (PR-AUC) and other metrics. A total of 517 patients with sporadic CCM were included (330 female [63.8%], mean [SD] age at diagnosis, 42.1 [15.5] years). 76 (re)hemorrhage (14.7%) occurred during follow-up. Among 3 machine learning models, XGBoost model yielded the highest mean (SD) AUROC (0.87 [0.06]) in cross-validation. The top 4 features of XGBoost model were ranked with SHAP (SHapley Additive exPlanations). All-Elements XGBoost model achieved an AUROCs of 0.84 and PR-AUC of 0.49 in testing set, with a sensitivity of 0.86 and a specificity of 0.76. Importantly, 4-Elements XGBoost model developed using top 4 features got a AUROCs of 0.83 and PR-AUC of 0.40, a sensitivity of 0.79, and a specificity of 0.72 in testing set. Two machine learning-based models achieved accurate performance in identifying potential (re)hemorrhages within 5 years in sporadic CCM patients. These models may provide insights for clinical decision-making.

Predicting severe intraventricular hemorrhage or early death using machine learning algorithms in VLBWI of the Korean Neonatal Network Database.

Severe intraventricular hemorrhage (IVH) in premature infants can lead to serious neurological complications. This retrospective cohort study used the Korean Neonatal Network (KNN) dataset to develop prediction models for severe IVH or early death in very-low-birth-weight infants (VLBWIs) using machine-learning algorithms. The study included VLBWIs registered in the KNN database. The outcome was the diagnosis of IVH Grades 3-4 or death within one week of birth. Predictors were categorized into three groups based on their observed stage during the perinatal period. The dataset was divided into derivation and validation sets at an 8:2 ratio. Models were built using Logistic Regression with Ridge Regulation (LR), Random Forest, and eXtreme Gradient Boosting (XGB). Stage 1 models, based on predictors observed before birth, exhibited similar performance. Stage 2 models, based on predictors observed up to one hour after birth, showed improved performance in all models compared to Stage 1 models. Stage 3 models, based on predictors observed up to one week after birth, showed the best performance, particularly in the XGB model. Its integration into treatment and management protocols can potentially reduce the incidence of permanent brain injury caused by IVH during the early stages of birth.

Red cell distribution width to lymphocyte ratio could serve as a new inflammatory biomarker for predicting hematoma expansion in patients with intracerebral hemorrhage.

BACKGROUND: Hematoma expansion is a critical factor associated with increased mortality and adverse outcomes in patients with intracerebral hemorrhage (ICH). Identifying and preventing hematoma expansion early on is crucial for effective therapeutic intervention. This study aimed to investigate the potential association between the Red cell distribution width to lymphocyte ratio (RDWLR) and hematoma expansion in ICH patients. METHODS: We conducted a retrospective analysis of clinical data from 303 ICH patients treated at our department between May 2018 and May 2023. Demographic, clinical, radiological, and laboratory data, including RDWLR upon admission, were assessed. Binary logistic regression analysis was employed to determine independent associations between various variables and hematoma expansion. RESULTS: The study included 303 ICH patients, comprising 167 (55.1%) males and 136 (44.9%) females, with a mean age of 65.25 ± 7.32 years at admission. Hematoma expansion occurred in 73 (24.1%) cases. Multivariate analysis revealed correlations between hematoma volume at baseline (OR, 2.73; 95% CI: 1.45 -4,78; P < 0.001), admission systolic blood pressure (OR, 2.98 ; 95% CI: 1.54-4.98; P < 0.001), Glasgow Coma Scale (GCS) (OR, 1.58; 95% CI: 1.25-2.46; P = 0.017), and RDWLR (OR, 1.58; 95% CI: 1.13-2.85; P = 0.022) and hematoma expansion in these patients. CONCLUSIONS: Our findings suggest that RDWLR could serve as a new inflammatory biomarker for hematoma expansion in ICH patients. This cost-effective and readily available biomarker has the potential for early prediction of hematoma expansion in these patients.

Triglyceride-glucose index as a potential predictor for in-hospital mortality in critically ill patients with intracerebral hemorrhage: a multicenter, case-control study.

BACKGROUND: The correlation between the triglyceride-glucose index (TyG) and the prognosis of ischemic stroke has been well established. This study aims to assess the influence of the TyG index on the clinical outcomes of critically ill individuals suffering from intracerebral hemorrhage (ICH). METHODS: Patients diagnosed with ICH were retrospectively retrieved from the Medical Information Mart for Intensive Care (MIMIC-IV) and the eICU Collaborative Research Database (eICU-CRD). Various statistical methods, including restricted cubic spline (RCS) regression, multivariable logistic regression, subgroup analysis, and sensitivity analysis, were employed to examine the relationship between the TyG index and the primary outcomes of ICH. RESULTS: A total of 791 patients from MIMIC-IV and 1,113 ones from eICU-CRD were analyzed. In MIMIC-IV, the in-hospital and ICU mortality rates were 14% and 10%, respectively, while in eICU-CRD, they were 16% and 8%. Results of the RCS regression revealed a consistent linear relationship between the TyG index and the risk of in-hospital and ICU mortality across the entire study population of both databases. Logistic regression analysis revealed a significant positive association between the TyG index and the likelihood of in-hospital and ICU death among ICH patients in both databases. Subgroup and sensitivity analysis further revealed an interaction between patients' age and the TyG index in relation to in-hospital and ICU mortality among ICH patients. Notably, for patients over 60 years old, the association between the TyG index and the risk of in-hospital and ICU mortality was more pronounced compared to the overall study population in both MIMIC-IV and eICU-CRD databases, suggesting a synergistic effect between old age (over 60 years) and the TyG index on the in-hospital and ICU mortality of patients with ICH. CONCLUSIONS: This study established a positive correlation between the TyG index and the risk of in-hospital and ICU mortality in patients over 60 years who diagnosed with ICH, suggesting that the TyG index holds promise as an indicator for risk stratification in this patient population.

Case report: Non-EBV associated cerebral vasculitis and cerebral hemorrhage in X-linked lymphoproliferative disease.

X-linked lymphoproliferative disease (XLP) is a rare genetic disorder characterized by immune dysregulation. The three most common clinical phenotypes are EBV-associated infectious mononucleosis (FIM), abnormal gammaglobulinemia, and lymphoma. We present a rare case of XLP1 with neurovasculitis, which is non-EBV-related and involves multiple systems, a condition rarely seen in children. The patient initially presented with an unsteady gait, which progressively evolved into language and consciousness disorders. Additionally, CT scans revealed multiple nodules in the lungs. Subsequent genetic testing and brain tissue biopsy confirmed the diagnosis: XLP1-related cerebral vasculitis and cerebral hemorrhage. Tragically, during the diagnostic process, the child experienced a sudden cerebral hemorrhage and herniation, ultimately resulting in fatality. This case offers a comprehensive insight into XLP1-related cerebral vasculitis and cerebral hemorrhage, underscoring the significance of early diagnosis and prompt treatment, while also imparting valuable clinical experience and lessons to the medical community.

Circulating Blood Prognostic Biomarker Signatures for Hemorrhagic Cerebral Cavernous Malformations (CCMs).

Cerebral cavernous malformations (CCMs) are a neurological disorder characterized by enlarged intracranial capillaries in the brain, increasing the susceptibility to hemorrhagic strokes, a major cause of death and disability worldwide. The limited treatment options for CCMs underscore the importance of prognostic biomarkers to predict the likelihood of hemorrhagic events, aiding in treatment decisions and identifying potential pharmacological targets. This study aimed to identify blood biomarkers capable of diagnosing and predicting the risk of hemorrhage in CCM1 patients, establishing an initial set of circulating biomarker signatures. By analyzing proteomic profiles from both human and mouse CCM models and conducting pathway enrichment analyses, we compared groups to identify potential blood biomarkers with statistical significance. Specific candidate biomarkers primarily associated with metabolism and blood clotting pathways were identified. These biomarkers show promise as prognostic indicators for CCM1 deficiency and the risk of hemorrhagic stroke, strongly correlating with the likelihood of hemorrhagic cerebral cavernous malformations (CCMs). This lays the groundwork for further investigation into blood biomarkers to assess the risk of hemorrhagic CCMs.