Spontaneous Intracerebral Hemorrhage Research Articles

Genetic Variants ε2 and ε4 of APOE Predict Mortality and Poor Outcome Independently in Spontaneous Intracerebral Hemorrhage Within the Chinese Han Population.

The heightened mortality and disability rates, coupled with restricted neurological recovery post intracerebral hemorrhage (ICH), have sparked considerable attention toward its treatment and results. Simultaneously, the influence of the APOE gene on ICH prognosis has been well-documented. This research aimed to explore the relationship between specific APOE alleles in the present cohort and the incidences of mortality, recurrence, and adverse prognosis, as determined by neurological function assessments in ICH patients. Data on patients diagnosed with ICH and hospitalized in the Department of Neurology at our institution from October 2021 to March 2022 were collected, including determining their APOE genotypes. A 1-year follow-up was conducted to evaluate mortality, ICH recurrence, and modified Rankin Scale (mRS) scores at 3 and 12 months. Poor prognosis was defined as an mRS score of ≥ 3. Initially, we analyzed the relationships between different APOE alleles and mortality, recurrence, and poor prognosis. Subsequently, we explored additional factors influencing each prognostic outcome and conducted multivariate analysis to identify independent risk factors. An analysis was conducted on 289 patients diagnosed with ICH. The presence of the ε2 allele was found to be a significant independent predictor for unfavorable outcomes at both 3 months (p = 0.022, OR = 2.138, 95% CI [2.041, 3.470]) and 1 year (p = 0.020, OR = 5.116, 95% CI [5.044, 5.307]). Moreover, the ε4 allele was established as an independent risk factor for ICH recurrence within 1 year (p = 0.025, OR = 2.326, 95% CI [1.163, 2.652]), as well as for mortality at 3 months (p = 0.037, OR = 4.250, 95% CI [4.068, 4.920]) and 1 year (p = 0.023, OR = 4.109, 95% CI [4.016, 4.739]). In conclusions, Both APOE ε2 and ε4 variants independently heighten mortality risk, recurrence, and poor prognosis after ICH. The substantial influence underscores the need for additional investigation into the impact of APOE genotype on ICH prognosis.

Machine learning based classification of spontaneous intracranial hemorrhages using radiomics features.

To assess the efficacy of radiomics features extracted from non-contrast computed tomography (NCCT) scans in differentiating multiple etiologies of spontaneous intracerebral hemorrhage (ICH). CT images and clinical data from 141 ICH patients from 2010 to 2022 were collected. The cohort comprised primary (n = 57), tumorous (n = 46), and vascular malformation-related ICH (n = 38). Radiomics features were extracted from the initial brain NCCT scans and identified potential features using mutual information. A hierarchical classification with AdaBoost classifiers was employed to classify the multiple etiologies of ICH. Age of the patient and ICH's location were examined alongside radiomics features. The accuracy, area under the curve (AUC), sensitivity, and specificity were used to evaluate classification performance. The proposed method achieved an accuracy of 0.79. For identifying primary ICH, the model achieved a sensitivity of 0.86 and specificity of 0.87. Meanwhile, the sensitivity and specificity for identifying tumoral causes were 0.78 and 0.93, respectively. For vascular malformation, the model reached a sensitivity and specificity of 0.72 and 0.89, respectively. The AUCs for primary, tumorous, and vascular malformation were 0.86, 0.85, and 0.82, respectively. The findings further highlight the importance of texture-based variables in ICH classification. The age and location of the ICH can enhance the classification performance. The use of a machine learning model with radiomics features has the potential in classifying the three types of non-traumatic ICH. It may help the radiologist decide on an appropriate further examination plan to arrive at a correct diagnosis.

Predicting cerebral edema in patients with spontaneous intracerebral hemorrhage using machine learning.

The early prediction of cerebral edema changes in patients with spontaneous intracerebral hemorrhage (SICH) may facilitate earlier interventions and result in improved outcomes. This study aimed to develop and validate machine learning models to predict cerebral edema changes within 72 h, using readily available clinical parameters, and to identify relevant influencing factors. An observational study was conducted between April 2021 and October 2023 at the Quzhou Affiliated Hospital of Wenzhou Medical University. After preprocessing the data, the study population was randomly divided into training and internal validation cohorts in a 7:3 ratio (training: N = 150; validation: N = 65). The most relevant variables were selected using Support Vector Machine Recursive Feature Elimination (SVM-RFE) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms. The predictive performance of random forest (RF), GDBT, linear regression (LR), and XGBoost models was evaluated using the area under the receiver operating characteristic curve (AUROC), precision-recall curve (AUPRC), accuracy, F1-score, precision, recall, sensitivity, and specificity. Feature importance was calculated, and the SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) methods were employed to explain the top-performing model. A total of 84 (39.1%) patients developed cerebral edema changes. In the validation cohort, GDBT outperformed LR and RF, achieving an AUC of 0.654 (95% CI: 0.611-0.699) compared to LR of 0.578 (95% CI, 0.535-0.623, DeLong: p = 0.197) and RF of 0.624 (95% CI, 0.588-0.687, DeLong: p = 0.236). XGBoost also demonstrated similar performance with an AUC of 0.660 (95% CI, 0.611-0.711, DeLong: p = 0.963). However, in the training set, GDBT still outperformed XGBoost, with an AUC of 0.603 ± 0.100 compared to XGBoost of 0.575 ± 0.096. SHAP analysis revealed that serum sodium, HDL, subarachnoid hemorrhage volume, sex, and left basal ganglia hemorrhage volume were the top five most important features for predicting cerebral edema changes in the GDBT model. The GDBT model demonstrated the best performance in predicting 72-h changes in cerebral edema. It has the potential to assist clinicians in identifying high-risk patients and guiding clinical decision-making.

Neuroendoscopic surgery for brainstem hemorrhage: Technical notes and preliminary clinical results

BackgroundBrainstem hemorrhage accounts for a relatively small proportion of spontaneous intracerebral hemorrhages (∼10 %) but tends to occur earlier in life and has poorer prognosis. Numerous studies support the therapeutic potential of minimally invasive hematoma evacuation for intracerebral hemorrhage; however, there have been few assessments of the benefits for brainstem hemorrhage. MethodsWe evaluated the safety and efficacy of a minimally invasive approach under neuroendoscopic guidance with pneumatic arm fixation for removing the hematoma in severe brainstem hemorrhage patients. 14 patients diagnosed with primary brainstem hemorrhage and treated by neuroendoscopy-assisted evacuation at Suzhou Ninth Hospital affiliated to Soochow University were included in the study. Relevant clinical and prognostic date were collected and analyzed. ResultsHematoma volume ranged from 8 to 13 mL according to preoperative CT, while GCS at admission ranged from 4 to 6. The average operative time was 157 min and average intraoperative blood loss was 86 mL. All patients achieved satisfactory hematoma evacuation (over 90 %) according to immediate postoperative CT. Postoperative intensive care unit stay averaged 9.5 days and respiratory support averaged 7.5 days. 11 patients required tracheotomy due to pulmonary infection and absence of pharyngeal reflexes. 9 patients achieved satisfactory functional recovery (GOS score of 4 and 3), while 5 remained in a vegetative state (GOS score of 2). ConclusionNeuroendoscopy provides excellent direct visualization of brainstem hematomas for safe and reliable evacuation. Patients with a new PPH score of 2 or 3 are more likely to benefit from surgical treatment. Large-scale studies are required to identify patients most likely to benefit from this technique.

A machine learning model based on results of a comprehensive radiological evaluation can predict the prognosis of basal ganglia cerebral hemorrhage treated with neuroendoscopy.

Spontaneous intracerebral hemorrhage is the second most common subtype of stroke. Therefore, this study aimed to investigate the risk factors affecting the prognosis of patients with basal ganglia cerebral hemorrhage after neuroendoscopy. Between January 2020 and January 2024, 130 patients with basal ganglia cerebral hemorrhage who underwent neuroendoscopy were recruited from two independent centers. We split this dataset into training (n = 79), internal validation (n = 22), and external validation (n = 29) sets. The least absolute shrinkage and selection operator-regression algorithm was used to select the top 10 important radiomic features of different regions (perioperative hemorrhage area [PRH], perioperative surround area [PRS], postoperative hemorrhage area [PSH], and postoperative edema area [PSE]). The black hole, island, blend, and swirl signs were evaluated. The top 10 radiomic features and 4 radiological features were combined to construct the k-nearest neighbor classification (KNN), logistic regression (LR), and support vector machine (SVM) models. Finally, the performance of the perioperative hemorrhage and postoperative edema machine learning models was validated using another independent dataset (n = 29). The primary outcome is mRS at 6 months after discharge. The mRS score greater than 3 defined as functional independence. A total of 12 models were built: PRH-KNN, PRH-LR, PRH-SVM, PRS-KNN, PRS-LR, PRS-SVM, PSH-KNN, PSH-LR, PSH-SVM, PSE-KNN, PSE-LR, and PSE-SVM, with corresponding areas under the curve (AUC) values in the internal validation set of 0.95, 0.91, 0.94, 0.52, 0.91, 0.54, 0.67, 0.9, 0.72, 0.92, 0.92, and 0.95, respectively. The AUC values of the PRH-KNN, PRH-LR, PRH-SVM, PSE-KNN, PSE-LR, and PSE-SVM in the external validation were 0.9, 0.92, 0.89, 0.91, 0.92, and 0.88, respectively. The model built based on computed tomography images of different regions accurately predicted the prognosis of patients with basal ganglia cerebral hemorrhage treated with neuroendoscopy. The models built based on the preoperative hematoma area and postoperative edema area showed excellent predictive efficacy in external verification, which has important clinical significance.

Monocyte-to-Albumin Ratio Is Associated With Hematoma Expansion in Spontaneous Intracerebral Hemorrhage.

Hematoma expansion (HE) after spontaneous intracerebral hemorrhage (ICH) is a severe complication that independently predicts poor prognosis. In this study, we aimed to investigate whether monocyte-to-albumin ratio (MAR), a novel marker of systemic inflammation, could predict HE in patients with ICH. We retrospectively assessed the data of patients with ICH. The clinical, imaging, and laboratory test data including, the MAR on admission, were analyzed. A multivariate logistic regression analysis was carried out to explore the relationship between MAR and hematoma growth. The receiver operating characteristic (ROC) curve was employed to investigate the predictive value of MAR for HE after ICH. A total of 246 patients were included in the present study. Multivariate logistic regression analysis demonstrated that the MAR was associated with HE (odds ratio [OR]=1.179; 95% confidence interval, 1.093-1.272; p=0.000). ROC curve analysis showed that MAR could predict HE, with an area under the curve of 0.802 (95% CI: 0.744-0.859, p<0.001). The optimal predictive cutoff value of MAR for HE was 10.01 (sensitivity: 72.43%, specificity: 77.05%). Our results suggested that a high MAR on admission was associated with an increased risk of HE in ICH patients, and MAR can become an independent predictor of HE in ICH patients.

A comprehensive comparison of machine learning models for ICH prognostication: Retrospective review of 1501 intra-cerebral hemorrhage patients from the Qatar stroke database.

Multiple prognostic scores have been developed to predict morbidity and mortality in patients with spontaneous intracerebral hemorrhage(sICH). Since the advent of machine learning(ML), different ML models have also been developed for sICH prognostication. There is however a need to verify the validity of these ML models in diverse patient populations. We aim to create machine learning models for prognostication purposes in the Qatari population. By incorporating inpatient variables into model development, we aim to leverage more information. 1501 consecutive patients with acute sICH admitted to Hamad General Hospital(HGH) between 2013 and 2023 were included. We trained, evaluated, and compared several ML models to predict 90-day mortality and functional outcomes. For our dataset, we randomly selected 80% patients for model training and 20% for validation and used k-fold cross validation to train our models. The ML workflow included imbalanced class correction and dimensionality reduction in order to evaluate the effect of each. Evaluation metrics such as sensitivity, specificity, F-1 score were calculated for each prognostic model. Mean age was 50.8(SD 13.1) years and 1257(83.7%) were male. Median ICH volume was 7.5ml(IQR 12.6). 222(14.8%) died while 897(59.7%) achieved good functional outcome at 90 days. For 90-day mortality, random forest(RF) achieved highest AUC(0.906) whereas for 90-day functional outcomes, logistic regression(LR) achieved highest AUC(0.888). Ensembling provided similar results to the best performing models, namely RF and LR, obtaining an AUC of 0.904 for mortality and 0.883 for functional outcomes. Random Forest achieved the highest AUC for 90-day mortality, and LR achieved the highest AUC for 90-day functional outcomes. Comparing ML models, there is minimal difference between their performance. By creating an ensemble of our best performing individual models we maintained maximum accuracy and decreased variance of functional outcome and mortality prediction when compared with individual models.

Expanding Diagnostic Workup for hypertensive Intracerebral hemorrhage: a retrospective LATAM cerebrovascular registry comparison.

The leading cause of spontaneous intracerebral hemorrhage (ICH) is hypertensive arteriolopathy. In addition to age and hypertension history, patients usually present other comorbidities that potentially increase morbimortality. Ancillary studies other than non-contrast computerized tomography (NCCT) may help clarify the diagnosis and increase the detection of potentially modifiable vascular risk factors. Unfortunately, their use is not routinely performed. The study aimed to determine the frequency of ancillary studies performed in patients with hypertensive ICH. We performed a retrospective analysis of three Latin American cerebrovascular registries from academic medical centers, analyzing the results with descriptive statistics focusing on diagnosis and short-term outcomes. We analyzed a total of 1,324 patients (mean age 64 years). Hypertension and obesity were the most prevalent risk factors. Only 14% underwent MRI, 10.3% extracranial ultrasonography, and 6.7% echocardiography. Among the three registries, the Latin America Stroke Registry performed more ancillary studies. Most of the patients presented a poor clinical outcome and in-hospital death. The use of ancillary studies in the diagnostic workup of ICH was poor in the three registries, and mortality was high. The lack of ancillary studies performed may negatively impact outcomes.

Risk of spontaneous intracerebral hemorrhage associated with NOACs compared with aspirin and warfarin: A long-term single hospital follow-up study

BackgroundNon-vitamin K antagonist oral anticoagulants (NOACs) are currently the mainstay treatment for preventing thrombosis-induced ischemic stroke in patients with atrial fibrillation (AF), deep vein thrombosis (DVT), or previous infarction. However, such management may potentially induce antithrombotic-associated intracranial hemorrhage, leading to significantly adverse clinical outcomes. To investigate the risk of spontaneous intracranial hemorrhage (sICH) in patients under therapeutic anticoagulation. MethodsThis retrospective cohort study used a database established by Kaohsiung Veterans General Hospital to estimate the risk of first onset sICH in patients with AF, DVT or previous stroke who were 18 years old or older, and who had been on at least three months continuous long-term treatment with the oral anticoagulants aspirin, warfarin, or NOACs. In addition, we used propensity-score matching to minimize bias and Cox proportional hazards ratio to compare the risk of sICH among patients prescribed these anticoagulants. ResultsWe analyzed the data of 546 patients (182 aspirin users, 182 warfarin users, and 182 NOAC users). 180 (20 taking aspirin, 74 warfarin, and 86 NOACs) developed new onset sICH before seven years. No new onset cases were found after 7 years. Importantly, those taking NOACs were found to be at a higher risk of early onset hemorrhage (47.80 %) compared to the groups taking aspirin (11.10 %) and warfarin (47.80 %) with a median time-to-occurrence being 2.50, 4.00, and 4.40 years, respectively. ConclusionsThough NOACs prevented ischemic stroke, they were used with a higher risk of early onset spontaneous ICH at our large medical center.

Cerebral small vessel disease markers and long-term prognosis in spontaneous intracerebral hemorrhage: the HAGAKURE-ICH study

Cerebral small vessel disease markers and long-term prognosis in spontaneous intracerebral hemorrhage: the HAGAKURE-ICH study

Does stereotactic thrombolysis with alteplase for intracerebral haemorrhage alter intraventricular haematoma volume? A secondary analysis of the MISTIE-III trial

BackgroundStereotactic thrombolysis reduces intracerebral haemorrhage (ICH) volume in patients with spontaneous ICH. Whether intrahaematomal alteplase administration is associated with a change in intraventricular haemorrhage volume (deltaIVH) and functional outcomes is...

Influence of Hospital Type on Outcomes of Patients With Acute Spontaneous Intracerebral Hemorrhage: A Population-Based Study.

Influence of Hospital Type on Outcomes of Patients With Acute Spontaneous Intracerebral Hemorrhage: A Population-Based Study.

Development and validation of the nomogram model derived non-contrast CT score to predict hematoma expansion in patients with spontaneous intracerebral hemorrhage

Development and validation of the nomogram model derived non-contrast CT score to predict hematoma expansion in patients with spontaneous intracerebral hemorrhage

The effect of frailty on mortality and functional outcomes in spontaneous intracerebral haemorrhage

IntroductionLimited data in patients with spontaneous intracerebral haemorrhage (SICH) showed that frailty was associated with mortality; however, there was insufficient data on functional outcomes. This study aimed to investigate the effect of frailty on overall mortality and 90-day functional outcomes in SICH. Materials and methodsWe conducted a retrospective study of 1223 patients diagnosed with SICH from January 2014 to December 2020. Frailty was defined as a clinical frailty scale (CFS) score of 4–9. Binary cut-offs were defined using receiver operating curve analysis. 90-day poor functional outcomes (PFO) were defined as modified Rankin Scale (mRS) ≥3, and utility-weighted mRS (UW-mRS) were based on previous validated studies respectively. Regression analyses were conducted to investigate the association between frailty and outcomes. Confounders adjusted for included demographics, cardiovascular risk factors and haematoma characteristics. Results1091 patients met the inclusion criterion. 167 (15.3 %) had 30-day mortality and 730 (66.9 %) had 90-day PFO. Frailty was significantly associated with lower overall survival (HR: 1.54; 95 % CI: 1.11–2.14, p=0.010), 90-day PFO (OR: 1.90; 95 % CI: 1.32–2.74; p<0.001) and poorer UW-mRS (β: −0.06; 95 % CI: (-0.08 to −0.04); p<0.001) even after adjusting for confounders. ConclusionsFrailty was significantly associated with greater mortality and PFO after incident SICH, even after adjusting for a priori confounders. Frail male individuals may be predisposed to poorer outcomes from higher prevalence of cortical atrophy. The use of CFS in younger individuals may aid management by predicting outcomes after incident SICH. Identifying frail individuals with incident SICH could aid in decision-making and the surgical management of SICH.

Associations of serum Dickkopf-1 levels with disease severity and 90-day Prognosis after spontaneous intracerebral hemorrhage: results from the prospective cohort study.

Dickkopf-1 (DKK-1) may be involved in inflammatory response and secondary brain injury after acute brain injury. We gauged serum DKK-1 levels and further assessed its correlation with disease severity and investigated its predictive value for 90-day prognosis in patients with spontaneous intracerebral hemorrhage (sICH). Serum DKK-1 levels were measured in 128 sICH patients and 128 healthy controls. The severity of sICH was assessed using the Glasgow Coma Scale (GCS) scores and hematoma volumes. Poor prognosis was referred to as a Glasgow Outcome Scale (GOS) score of 1-3 at 90days after stroke. Multivariate analysis was performed to identify associations of serum DKK-1 levels with disease severity, early neurological deterioration (END) and poor prognosis. Receiver operating characteristic curve (ROC) was built to investigate the prognostic predictive capability. The serum DKK-1 levels of patients were significantly higher than those of controls (median, 4.74ng/mL versus 1.98ng/mL; P < 0.001), and were independently correlated with hematoma volumes (ρ = 0.567, P < 0.001; t = 3.444, P = 0.001) and GCS score (ρ = -0.612, P < 0.001; t = -2.048, P = 0.043). Serum DKK-1 significantly differentiated patients at risk of END (area under ROC curve (AUC), 0.850; 95% confidence interval (CI), 0.777-0.907; P < 0.001) and poor prognosis (AUC, 0.830; 95% CI, 0.753-0.890; P < 0.001), which had similar prognostic ability, as compared to GCS scores and hematoma volumes. Subsequent Logistic regression model affirmed that GCS score, hematoma volume, and serum DKK-1 levels were independently associated with END and poor prognosis at 90days after sICH. The models, which contained them, performed well using ROC curve analysis and calibration curve analysis. Serum DKK-1 levels are markedly associated with disease severity, END and 90-day poor prognosis in sICH. Hence, serum DKK-1 is presumed to be used as a potential prognostic biomarker of sICH.

Plasma Inflammation Markers Linked to Complications and Outcomes after Spontaneous Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) could trigger inflammatory responses. However, the specific role of inflammatory proteins in the pathological mechanism, complications, and prognosis of ICH remains unclear. In this study, we investigated the expression of 92 plasma inflammation-related proteins in patients with ICH (n = 55) and healthy controls (n = 20) using an Olink inflammation panel and discussed the relation to the severity of stroke, clinical complications, 30-day mortality, and 90-day outcomes. Our result showed that six proteins were upregulated in ICH patients compared with healthy controls, while seventy-four proteins were downregulated. In patients with ICH, seven proteins were increased in the severe stroke group compared with the moderate stroke group. In terms of complications, two proteins were downregulated in patients with pneumonia, while nine proteins were upregulated in patients with sepsis. Compared with the survival group, three proteins were upregulated, and one protein was downregulated in the death group. Compared with the good outcome group, eight proteins were upregulated, and four proteins were downregulated in the poor outcome group. In summary, an in-depth exploration of the differential inflammatory factors in the early stages of ICH could deepen our understanding of the pathogenesis of ICH, predict patient prognosis, and explore new treatment strategies.

Investigating recovery after a spontaneous intracerebral haemorrhage in zebrafish larvae.

Intracerebral haemorrhage is a debilitating stroke sub-type with high morbidity and mortality rates. For survivors, rehabilitation is a long process, and with no available therapeutics to limit the immediate pathophysiology of the haemorrhage, recovery is dependent on individual neuroplasticity. We have previously shown that zebrafish larvae can be used to model spontaneous brain haemorrhage. Zebrafish exhibit innate recovery mechanisms and are often used as a model system for investigation into regeneration after injury, including injury to the nervous system. Here, we investigate the spontaneous and immediate recovery in zebrafish larvae following an intracerebral haemorrhage at 2 days post-fertilisation, during pre-protected stages and over the first 3 weeks of life. We have shown that following the onset of bleed at ∼2 days post-fertilisation zebrafish are capable of clearing the haematoma through the ventricles. Brain cell damage associated with intracerebral haemorrhage is resolved within 48 h, and this recovery is associated with survival rates equal to wildtype and non-haemorrhaged sibling control animals. Larvae express more nestin-positive neural progenitor cells 24 h after injury when the most damage is observed, and through mass spectrometry analysis, we have determined that these cells are highly proliferative and may specially differentiate into oligodendrocytes. This study provides an insight into the haematoma resolution processes in a live, intact organism, and may suggest potential therapeutic approaches to support the recovery of intracerebral haemorrhage patients.

Association between the C-reactive protein to albumin ratio and poor clinical outcome in patients with spontaneous intracerebral hemorrhage

BackgroundThe C-reactive protein-to-albumin ratio (CAR) is a novel prognostic biomarker of systemic inflammation and nutritional status. The association between CAR and the long-term outcome of spontaneous intracerebral hemorrhage (ICH) remains unclear. MethodsFrom January 2014 to September 2016, 497 patients with spontaneous ICH were enrolled in our study from 13 hospitals in Beijing. According to the CAR quartiles, patients were classified into four groups (Q1-Q4). Logistic regression was applied to analyze the relationship between different CAR levels and main outcome (90-day and 1-year mRS 4-6). Restricted cubic splines and receiver operating characteristic (ROC) curves of CAR for poor clinical outcomes were assessed. ResultsIn the multivariate logistic regression model, compared with the lowest quartile of CAR, the adjusted odds ratios of the Q2, Q3, and Q4 group for 90-day mRS score of 4-6 were 3.64 (1.61–8.23), 3.83 (1.67–8.77), and 8.91 (3.85–20.64). In terms of 1-year mRS score of 4-6, compared with the lowest quartile of CAR, the adjusted odds ratios of the Q3 and Q4 group were 3.31 (1.33–8.22) and 6.87 (2.81–16.78). ConclusionsA high CAR level was associated with a high risk of long-term adverse prognosis in patients with ICH, and the risk of ICH poor outcome increased steadily with CAR rising in a certain range, and maintained in a high level thereafter.

Intracranial Pressure Variability Associates with 3-Month Outcomes in Spontaneous Intracerebral Hemorrhage: A Retrospective Analysis of 597 Patients

Background and ObjectiveSpontaneous intracerebral hemorrhage (ICH) is a devastating type of stroke but most favorable treatments to improve patients’ neurological outcomes are not clear. Invasive intracranial pressure (ICP) monitoring is a common treatment of ICH, but whether ICH patients could benefit from ICP monitoring is controversial. ICP variability (IPV) has been shown to correlate with poor outcomes in patients with subarachnoid hemorrhage (SAH) and traumatic brain injury (TBI), but this association has not been clearly elucidated in ICH patients. We hypothesized that 72 hour-IPV from time of ICP probe implantation is associated with outcomes in ICH patients. MethodsA retrospective chart review analysis of adult ICH patients, who received ICP monitoring at Huashan Hospital Fudan University between Jan. 2008 and Jan. 2023, was performed. We included ICH patients within 6 hours of signs or symptoms onset. Outcomes of ICH patients were assessed using 3-month mRS, and were dichotomized into poor (mRS 4 to 6) and good (mRS 0 to 3) outcome group. ICPs were recorded from the implantation of invasive ICP probe until it was removed. ICP was analyzed in the acute period, from 0 to 72 hours after ICP implantation. IPV was analyzed by SD (Standard deviation), CV (Coefficient of variation) and SV (Successive variation) of ICP. ResultsWe analyzed 597 patients’ charts. The 1st ICP assessment, immediately after ICP implantation, at median 117 minutes (interquartile range, 82-231 minutes) after admission was mean 20.5±7.8 mmHg. The 2nd ICP assessment, on NICU arrival after operation, was mean 14.6±8.3 mmHg. Poor outcomes occurred in 213 patients (35.68%). In univariate analysis, univariate quintile analysis or multivariate analysis, ICPSD, ICPCV and ICPSV were associated with poor outcomes. ConclusionsIPV during the first 72 hours after ICP implantation in patients with ICH was independently associated with poor functional outcome at 3-month. Stabilization of IPV during hyperacute and acute period maybe a potential therapeutic target to improve functional outcomes of these patients.

Hypomagnesemia is Associated with the Skull Computed Tomography Black Hole Sign in Patients with Spontaneous Intracerebral Hemorrhage

ObjectivesThe evaluation of hypomagnesemia's significance in predicting the presence of the black hole sign in patients with intracranial hemorrhage (ICH) is currently under investigation. MethodsThe study included 261 patients with cerebral hemorrhage who underwent initial skull computed tomography (CT) within 24 hours of admission.Sixty-nine patients (26.4%) exhibited hypomagnesemia in the initial laboratory examinations. The black hole sign was observed in 123 patients (referred to as the black hole sign group, which includes patients with and without hypomagnesemia), while the remaining 138 patients (non-black hole sign group) did not exhibit this feature. The values of hypomagnesemia were assessed through multivariable logistic regression analyses. ResultsThe black hole sign occurred in 45 of the 69 (65.2%) patients with hypomagnesemia, and in 78 of the 192 (40.6%) patients without hypomagnesemia.In the black hole sign group, hypomagnesemia was observed in 45 patients (36.6%). However, only 24 patients (19.5%) from the normal magnesium concentration group exhibited hypomagnesemia.The sensitivity, specificity, and positive and negative predictive values of hypomagnesemia for predicting the black hole sign were 69.9%, 82.5%, 36.6%, and 82.8% respectively.The odds ratios for hypomagnesemia, smoking history, and hypokalemia in predicting the presence of the black hole sign were 2.74, 1.971, and 1.629 correspondingly. ConclusionsThe presence of hypomagnesemia may serve as a predictive factor for the black hole sign and rebleeding in patients with intracerebral hemorrhage (ICH), thereby providing valuable guidance for clinical treatment.