Assessment and Comparison of the Four Most Extensively Validated Prognostic Scales for Intracerebral Hemorrhage: Systematic Review with Meta-analysis

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.

Evaluating the learning curve of endoscopic surgery for spontaneous intracerebral hemorrhage: A single-center experience in a county hospital

BACKGROUND

Endoscopic surgery has shown promise in treating Spontaneous Intracerebral Hemorrhage (sICH), but its adoption in county-level hospitals has been hindered by the high level of surgical expertise required.

METHODS

In this retrospective study at a county hospital, we utilized a Cumulative Sum (CUSUM) control chart to visualize the learning curve for two neurosurgeons. We compared patient outcomes in the learning and proficient phases, and compared them with expected outcomes based on ICH score and ICH functional outcome score, respectively.

RESULTS

The learning curve peaked at the 12th case for NS1 and the 8th case for NS2, signifying the transition to the proficient stage. This stage saw reductions in operation time, blood loss, rates of evacuation < 90 %, rebleeding rates, intensive care unit stay, hospital stay, and overall costs for both neurosurgeons. In the learning stage, 6 deaths occurred within 30 days, less than the 10.66 predicted by the ICH score. In the proficient stage, 3 deaths occurred, less than the 15.88 predicted. In intermediate and high-risk patients by the ICH functional outcome score, the proficient stage had fewer patients with an mRS ≥ 3 at three months than the learning stage (23.8 % vs. 69.2 %, P = 0.024; 40 % vs. 80 %, P = 0.360). Micromanipulating bipolar precision hemostasis and aspiration devices in the endoport's channels sped up the transition from learning to proficient.

CONCLUSION

The data shows a learning curve, with better surgical outcomes as surgeons gain proficiency. This suggests cost benefits of surgical proficiency and the need for ongoing surgical education and training in county hospitals.

Guidelines for Neuroprognostication in Critically Ill Adults with Intracerebral Hemorrhage

BACKGROUND

The objective of this document is to provide recommendations on the formal reliability of major clinical predictors often associated with intracerebral hemorrhage (ICH) neuroprognostication.

METHODS

A narrative systematic review was completed using the Grading of Recommendations Assessment, Development, and Evaluation methodology and the Population, Intervention, Comparator, Outcome, Timing, Setting questions. Predictors, which included both individual clinical variables and prediction models, were selected based on clinical relevance and attention in the literature. Following construction of the evidence profile and summary of findings, recommendations were based on Grading of Recommendations Assessment, Development, and Evaluation criteria. Good practice statements addressed essential principles of neuroprognostication that could not be framed in the Population, Intervention, Comparator, Outcome, Timing, Setting format.

RESULTS

Six candidate clinical variables and two clinical grading scales (the original ICH score and maximally treated ICH score) were selected for recommendation creation. A total of 347 articles out of 10,751 articles screened met our eligibility criteria. Consensus statements of good practice included deferring neuroprognostication-aside from the most clinically devastated patients-for at least the first 48-72 h of intensive care unit admission; understanding what outcomes would have been most valued by the patient; and counseling of patients and surrogates whose ultimate neurological recovery may occur over a variable period of time. Although many clinical variables and grading scales are associated with ICH poor outcome, no clinical variable alone or sole clinical grading scale was suggested by the panel as currently being reliable by itself for use in counseling patients with ICH and their surrogates, regarding functional outcome at 3 months and beyond or 30-day mortality.

CONCLUSIONS

These guidelines provide recommendations on the formal reliability of predictors of poor outcome in the context of counseling patients with ICH and surrogates and suggest broad principles of neuroprognostication. Clinicians formulating their judgments of prognosis for patients with ICH should avoid anchoring bias based solely on any one clinical variable or published clinical grading scale.

An artificial intelligence-based prognostic prediction model for hemorrhagic stroke

PURPOSE

The prognosis following a hemorrhagic stroke is usually extremely poor. Rating scales have been developed to predict the outcomes of patients with intracerebral hemorrhage (ICH). To date, however, the prognostic prediction models have not included the full range of relevant imaging features. We constructed a clinic-imaging fusion model based on convolutional neural networks (CNN) to predict the short-term prognosis of ICH patients.

MATERIALS AND METHODS

This was a multi-center retrospective study, which included 1990 patients with ICH. Two CNN-based deep learning models were constructed to predict the neurofunctional outcomes at discharge; these were validated using a nested 5-fold cross-validation approach. The models' predictive efficiency was compared with the original ICH scale and the ICH grading scale. Poor neurological outcome was defined as a Glasgow Outcome Scale (GOS) score of 1-3.

RESULTS

The training and test sets included 1599 and 391 patients, respectively. For the test set, the clinic-imaging fusion model had the highest area under the curve (AUC = 0.903), followed by the imaging-based model (AUC = 0.886), the ICH scale (AUC = 0.777), and finally the ICH grading scale (AUC = 0.747).

CONCLUSION

The CNN prognostic prediction model based on neuroimaging features was more effective than the ICH scales in predicting the neurological outcomes of ICH patients at discharge. The CNN model's predictive efficiency slightly improved when clinical data were included.

Whole-brain diffusion tensor imaging predicts 6-month functional outcome in acute intracerebral haemorrhage

INTRODUCTION

Small vessel disease (SVD) causes most spontaneous intracerebral haemorrhage (ICH) and is associated with widespread microstructural brain tissue disruption, which can be quantified via diffusion tensor imaging (DTI) metrics: mean diffusivity (MD) and fractional anisotropy (FA). Little is known about the impact of whole-brain microstructural alterations after SVD-related ICH. We aimed to investigate: (1) association between whole-brain DTI metrics and functional outcome after ICH; and (2) predictive ability of these metrics compared to the pre-existing ICH score.

METHODS

Sixty-eight patients (38.2% lobar) were retrospectively included. We assessed whole-brain DTI metrics (obtained within 5 days after ICH) in cortical and deep grey matter and white matter. We used univariable logistic regression to assess the associations between DTI and clinical-radiological variables and poor outcome (modified Rankin Scale > 2). We determined the optimal predictive variables (via LASSO estimation) in: model 1 (DTI variables only), model 2 (DTI plus non-DTI variables), model 3 (DTI plus ICH score). Optimism-adjusted C-statistics were calculated for each model and compared (likelihood ratio test) against the ICH score.

RESULTS

Deep grey matter MD (OR 1.04 [95% CI 1.01-1.07], p = 0.010) and white matter MD (OR 1.11 [95% CI 1.01-1.23], p = 0.044) were associated (univariate analysis) with poor outcome. Discrimination values for model 1 (0.67 [95% CI 0.52-0.83]), model 2 (0.71 [95% CI 0.57-0.85) and model 3 (0.66 [95% CI 0.52-0.82]) were all significantly higher than the ICH score (0.62 [95% CI 0.49-0.75]).

CONCLUSION

Our exploratory study suggests that whole-brain microstructural disruption measured by DTI is associated with poor 6-month functional outcome after SVD-related ICH. Whole-brain DTI metrics performed better at predicting recovery than the existing ICH score.

Impact of white matter hypodensities on outcome after intracerebral hemorrhage

OBJECTIVES

White matter hypodensities (WMH), a surrogate of small vessel disease, associate with cognitive decline and stroke risk. The impact of WMH on functional outcome after intracerebral hemorrhage (ICH) has differed between studies. We aimed to examine factors associated with the severity of WMH in ICH, and whether there is an independent association between the extent of WMH and outcome.

MATERIALS AND METHODS

This was a prospective study of consented patients with non-traumatic primary ICH, admitted to the Helsinki University Hospital between May 2014 and December 2018. To evaluate the extent of the WMH, modified van Swieten score of the side contralateral to the ICH was obtained. Patients were grouped into 3 categories of the scores. We performed univariate and multivariable analyses to find out factors associated with the severity of WMH, and whether WMH associate with functional outcome and mortality up to 12 months, adjusted for the known major outcome predictors.

RESULTS

In our cohort of 417 ICH patients, WMH severity associated with older age, female sex, admission National Institutes of Health Stroke Scale (NIHSS) points, and signs of previous ischemic stroke on CT. We found an independent association between WMH severity and poor functional outcome at 3 months (OR 1.72, 95% CI 1.27-2.33), and 1 year (OR 2.16, 95% CI 1.57-2.95), and mortality at 1 year (OR 1.91, 95% CI 1.29-2.85).

CONCLUSIONS

In our ICH patients, vascular comorbidities and older age associated with the presence of WMH, which, in turn, strongly associated with poor functional outcome.

Reappraisal of Intracerebral Hemorrhages and Intracerebral Hemorrhage Grading Scale Score in Surgically and Medically Managed Cerebellar Intracerebral Hemorrhage

BACKGROUND

As compared with supratentorial intracerebral hemorrhages (ICH), bleeds that occur within the cerebellum require special consideration given the nature of the posterior fossa.

OBJECTIVE

To validate ICH and ICH grading scale (ICH-GS) scores in patients with cerebellar hemorrhage and examine the outcomes of patients managed surgically as compared with those who underwent conservative treatment.

METHODS

This observational multicenter study included 475 patients with cerebellar hemorrhage from 9 different neurosurgical departments in Germany between 2005 and 2021. The prognostic accuracy of ICH and ICH-GS scores were calculated by the area under the curve of the receiver operating characteristic curves. Analyzed outcomes were the in-hospital mortality, mortality at 6 months, in-hospital outcome, and outcome at 6 months.

RESULTS

Of 403 patients, 252 patients (62.5%) underwent surgical treatment and 151 patients (37.5%) conservative treatment. Both ICH and ICH-GS scores demonstrated good prognostic accuracy regarding both overall mortality and functional outcomes. In those patients presenting with severe cerebellar hemorrhages, ie, ICH score >3 and ICH-GS score >11, overall mortality was significantly lower in surgically treated patients. Mortality was significantly higher in those patients managed surgically who presented with ICH scores ≤3; in such patients, improved outcomes were noted when the hematoma was treated conservatively.

CONCLUSION

ICH and ICH scores are useful tools for prediction of survival and outcome in patients with cerebellar ICH. Surgical management may be beneficial for those who present with severe cerebellar ICH as reflected by ICH scores >3, while conservative management seems reasonable in patients with lower ICH scores.

ANAID-ICH nomogram for predicting unfavorable outcome after intracerebral hemorrhage

OBJECTIVE

Diffusion-weighted imaging lesions (DWILs) are associated with unfavorable outcome in intracerebral hemorrhage (ICH). We proposed a novel predictive nomogram incorporating DWILs.

METHODS

A total of 738 patients with primary ICH in a tertiary hospital were prospectively enrolled as a training cohort. DWILs were defined as remote focal hyperintensities on DWI corresponding to low intensities on apparent diffusion coefficient images and remote from the focal hematoma. The outcome of interest was modified Rankin Scale scores of 4-6 at 90 days after onset. Multivariate logistic regression was used to construct a nomogram. Model performance was tested in the training cohort and externally validated with respect to discrimination, calibration, and clinical usefulness in another institute. Additionally, the nomogram was compared with the ICH score in terms of predictive ability.

RESULTS

Overall, 153 (20.73%) and 23 (15.54%) patients developed an unfavorable outcome in the training and validation cohorts, respectively. The multivariate analysis revealed that age, National Institutes of Health Stroke Scale (NIHSS) score, anemia, infratentorial location, presence of DWILs, and prior ICH were associated with unfavorable outcome. Our ANAID-ICH nomogram was constructed according to the aforementioned variables; the area under the receiver operating characteristic curve was 0.842 and 0.831 in the training and validation sets, respectively. With regard to the 90-day outcome, the nomogram showed a significantly higher predictive value than the ICH score in both cohorts.

CONCLUSIONS

The ANAID-ICH nomogram comprising age, NIHSS score, anemia, infratentorial location, presence of DWILs, and prior ICH may facilitate the identification of patients at higher risk for an unfavorable outcome.

Acute corticospinal tract diffusion tensor imaging predicts 6-month functional outcome after intracerebral haemorrhage

INTRODUCTION

Diffusion tensor imaging (DTI) can assess the structural integrity of the corticospinal tract (CST) in vivo. We aimed to investigate whether CST DTI metrics after intracerebral haemorrhage (ICH) are associated with 6-month functional outcome and can improve the predictive performance of the existing ICH score.

METHODS

We retrospectively included 42 patients with DTI performed within 5 days after deep supratentorial spontaneous ICH. Ipsilesional-to-contralesional ratios were calculated for fractional anisotropy (rFA) and mean diffusivity (rMD) in the pontine segment (PS) of the CST. We determined the most predictive variables for poor 6-month functional outcome [modified Rankin Scale (mRS) > 2] using the least absolute shrinkage and selection operator (LASSO) method. We calculated discrimination using optimism-adjusted estimation of the area under the curve (AUC).

RESULTS

Patients with 6-month mRS > 2 had lower rFA (0.945 [± 0.139] vs 1.045 [± 0.130]; OR 0.004 [95% CI 0.00-0.77]; p =  0.04) and higher rMD (1.233 [± 0.418] vs 0.963 [± 0.211]; OR 22.5 [95% CI 1.46-519.68]; p = 0.02). Discrimination (AUC) values were: 0.76 (95% CI 0.61-0.91) for the ICH score, 0.71 (95% CI 0.54-0.89) for rFA, and 0.72 (95% CI 0.61-0.91) for rMD. Combined models with DTI and non-DTI variables offer an improvement in discrimination: for the best model, the AUC was 0.82 ([95% CI 0.68-0.95]; p = 0.15).

CONCLUSION

In our exploratory study, PS-CST rFA and rMD had comparable predictive ability to the ICH score for 6-month functional outcome. Adding DTI metrics to clinical-radiological scores might improve discrimination, but this needs to be investigated in larger studies.

Prognostic value of glycemic gap in patients with spontaneous intracerebral hemorrhage

BACKGROUND

Glycemic gap (GG), as a novel biomarker showing the acute glycemic change after the onset of acute illness, has been found to be associated with adverse outcomes in many diseases. This study aimed to explore the prognostic value of GG on long-term outcomes of spontaneous intracerebral hemorrhage (sICH).

METHODS

The current study included 528 patients from a multi-center, prospective, consecutive, observational cohort study. Poor clinical outcome was defined as the modified Rankin Scale ≥ 3. GG was calculated using admission blood glucose minus hemoglobin A1c-derived average blood glucose. Logistic regression analyses were performed to determine the association between GG and poor clinical outcomes at 30-day, 90-day and 1-year.

RESULTS

GG was significantly associated with poor clinical outcomes at 30-day, 90-day, and 1-year (P < 0.05 for all models), where patients with higher GG were more likely to have poor clinical outcome. Restricted cubic splines revealed a positive association between GG and poor clinical outcome. In addition, patients with higher GG were more likely to have a higher 1-year mortality rate. The addition of GG to the intracerebral hemorrhage score improved the discrimination and calibration properties for the prediction of poor clinical outcome.

CONCLUSIONS

GG was independently associated with poor outcomes and may be a valuable prognostic factor in patients with sICH.

Hyperacute prediction of functional outcome in spontaneous intracerebral haemorrhage: systematic review and meta-analysis

Purpose

To describe the association between factors routinely available in hyperacute care of spontaneous intracerebral haemorrhage (ICH) patients and functional outcome.

Methods

We searched Medline, Embase and CINAHL in February 2020 for original studies reporting associations between markers available within six hours of arrival in hospital and modified Rankin Scale (mRS) at least 6 weeks post-ICH. A random-effects meta-analysis was performed where three or more studies were included.

Findings

Thirty studies were included describing 40 markers. Ten markers underwent meta-analysis and age (OR = 1.06; 95%CI = 1.05 to 1.06; p < 0.001), pre-morbid dependence (mRS, OR = 1.73; 95%CI = 1.52 to 1.96; p < 0.001), level of consciousness (Glasgow Coma Scale, OR = 0.82; 95%CI = 0.76 to 0.88; p < 0.001), stroke severity (National Institutes of Health Stroke Scale, OR=1.19; 95%CI = 1.13 to 1.25; p < 0.001), haematoma volume (OR = 1.12; 95%CI=1.07 to 1.16; p < 0.001), intraventricular haemorrhage (OR = 2.05; 95%CI = 1.68 to 2.51; p < 0.001) and deep (vs. lobar) location (OR = 2.64; 95%CI = 1.65 to 4.24; p < 0.001) were predictive of outcome but systolic blood pressure, CT hypodensities and infratentorial location were not. Of the remaining markers, sex, medical history (diabetes, hypertension, prior stroke), prior statin, prior antiplatelet, admission blood results (glucose, cholesterol, estimated glomerular filtration rate) and other imaging features (midline shift, spot sign, sedimentation level, irregular haematoma shape, ultraearly haematoma growth, Graeb score and onset to CT time) were associated with outcome.

Conclusion

Multiple demographic, pre-morbid, clinical, imaging and laboratory factors should all be considered when prognosticating in hyperacute ICH. Incorporating these in to accurate and precise models will help to ensure appropriate levels of care for individual patients.

Enhancing Robustness of Machine Learning Integration With Routine Laboratory Blood Tests to Predict Inpatient Mortality After Intracerebral Hemorrhage

Objective: The accurate evaluation of outcomes at a personalized level in patients with intracerebral hemorrhage (ICH) is critical clinical implications. This study aims to evaluate how machine learning integrates with routine laboratory tests and electronic health records (EHRs) data to predict inpatient mortality after ICH.

Methods: In this machine learning-based prognostic study, we included 1,835 consecutive patients with acute ICH between October 2010 and December 2018. The model building process incorporated five pre-implant ICH score variables (clinical features) and 13 out of 59 available routine laboratory parameters. We assessed model performance according to a range of learning metrics, such as the mean area under the receiver operating characteristic curve [AUROC]. We also used the Shapley additive explanation algorithm to explain the prediction model.

Results: Machine learning models using laboratory data achieved AUROCs of 0.71–0.82 in a split-by-year development/testing scheme. The non-linear eXtreme Gradient Boosting model yielded the highest prediction accuracy. In the held-out validation set of development cohort, the predictive model using comprehensive clinical and laboratory parameters outperformed those using clinical alone in predicting in-hospital mortality (AUROC [95% bootstrap confidence interval], 0.899 [0.897–0.901] vs. 0.875 [0.872–0.877]; P <0.001), with over 81% accuracy, sensitivity, and specificity. We observed similar performance in the testing set.

Conclusions: Machine learning integrated with routine laboratory tests and EHRs could significantly promote the accuracy of inpatient ICH mortality prediction. This multidimensional composite prediction strategy might become an intelligent assistive prediction for ICH risk reclassification and offer an example for precision medicine.

Validation of the ICH score and ICH-GS in a Peruvian surgical cohort: a retrospective study

The intracerebral hemorrhage (ICH) score and the ICH-grading scale (ICH-GS) are mortality predictor tools developed predominantly in conservatively treated ICH cohorts. We aimed to compare and evaluate the external validity of both models in predicting mortality in patients with ICH undergoing surgical intervention. A retrospective review of all patients presenting with spontaneous ICH admitted to a Peruvian national hospital between January 2018 and March 2020 was conducted. We compared the area under the receiver operating characteristic curve (AUC) for the ICH score and ICH-GS for in-hospital, 30-day, and 6-month mortality prediction. The research protocol was approved by the Institutional Review Board. A total of 73 patients (median age 62 years, 56.2% males) were included in the study. The mean ICH and ICH-GS scores were 2.5 and 8.7, respectively. In-hospital, 30-day, and 6-month mortality were 37%, 27.4%, and 37%, respectively. The AUC for in-hospital, 30-day, and 6-month mortality was 0.69, 0.71, and 0.69, respectively, for the ICH score and 0.64, 0.65, and 0.68, respectively, for the ICH-GS score. In this study, the ICH score and ICH-GS had moderate discrimination capacities to predict in-hospital, 30-day, and 6-month mortality in surgically treated patients. Additional studies should assess whether surgical intervention affects the discrimination of these prognostic models in order to develop predictive scores based on specific populations.

Postsurgical functional outcome prediction model using deep learning framework (Prediction One, Sony Network Communications Inc.) for hypertensive intracerebral hemorrhage

BACKGROUND

Reliable prediction models of intracerebral hemorrhage (ICH) outcomes are needed for decision-making of the treatment. Statistically making such prediction models needs a large number of samples and time-consuming statistical analysis. Deep learning (DL), one of the artificial intelligence, is attractive, but there were no reports on DL-based functional outcome prediction models for ICH outcomes after surgery. We herein made a functional outcome prediction model using DLframework, Prediction One (Sony Network Communications Inc., Tokyo, Japan), and compared it to original ICH score, ICH Grading Scale, and FUNC score.

METHODS

We used 140 consecutive hypertensive ICH patients' data in our hospital between 2012 and 2019. All patients were surgically treated. Modified Rankin Scale 0-3 at 6 months was defined as a favorable outcome. We randomly divided them into 100 patients training dataset and 40 patients validation dataset. Prediction One made the prediction model using the training dataset with 5-fold cross-validation. We calculated area under the curves (AUCs) regarding the outcome using the DL-based model, ICH score, ICH Grading Scale, and FUNC score. The AUCs were compared.

RESULTS

The model made by Prediction One using 64 variables had AUC of 0.997 in the training dataset and that of 0.884 in the validation dataset. These AUCs were superior to those derived from ICH score, ICH Grading Scale, and FUNC score.

CONCLUSION

We easily and quickly made prediction models using Prediction One, even with a small single-center dataset. The accuracy of the DL-based model was superior to those of previous statistically calculated models.

IL-33 as a Novel Serum Prognostic Marker of Intracerebral Hemorrhage

Objective

Interleukin 33 (IL-33) is a key cytokine involved in inflammation and oxidative stress. The significance of serum IL-33 levels on the prognosis of patients with intracerebral hemorrhage (ICH) has not been well studied. The purpose of this study is to determine whether there is a relationship between the serum IL-33 level and the prognosis of patients with ICH upon admission.

Methods

A total of 402 patients with confirmed ICH were included in this study. Their demographic data, medical history, laboratory data, imaging data, and clinical scores on admission were collected. At the same time, enzyme-linked immunoassay (ELISA) was used to detect the serum IL-33 levels of patients. The prognosis of patients was evaluated by mRS scale after 3 months, and mRS > 2 was defined as poor prognosis.

Results

Among 402 patients with ICH, the number of patients with good prognosis and poor prognosis after 3 months was 148 and 254, respectively. Compared with the ICH group with poor prognosis, the ICH group with good prognosis had lower baseline NHISS scores (p = 0.039) and hematoma volume (p = 0.025) and higher GCS scores (p < 0.001) and serum IL-33 levels (p < 0.001). The results of linear correlation analysis showed that serum IL-33 levels were significantly negatively correlated with baseline NHISS scores (r = −0.224, p = 0.033) and hematoma volume (r = −0.253, p = 0.046) but were significantly positively correlated with baseline GCS scores (r = 0.296, p = 0.020). The receiver operating characteristic curve (ROC) analysis showed that the sensitivity and specificity of serum IL-33 level in evaluating the prognosis of ICH were 72.1% and 74.3%, respectively. A cut-off value of serum IL-33 level < 109.3 pg/mL may indicate a poor prognosis for ICH.

Conclusions

Serum IL-33 level on admission may be a prognostic indicator of ICH, and its underlying mechanism needs further study.

Cerebral Small Vessel Disease and Functional Outcome Prediction After Intracerebral Hemorrhage

OBJECTIVE

To determine whether CT-based cerebral small vessel disease (SVD) biomarkers are associated with 6-month functional outcome after intracerebral hemorrhage (ICH) and whether these biomarkers improve the performance of the preexisting ICH prediction score.

METHODS

We included 864 patients with acute ICH from a multicenter, hospital-based prospective cohort study. We evaluated CT-based SVD biomarkers (white matter hypodensities [WMH], lacunes, brain atrophy, and a composite SVD burden score) and their associations with poor 6-month functional outcome (modified Rankin Scale score >2). The area under the receiver operating characteristic curve (AUROC) and Hosmer-Lemeshow test were used to assess discrimination and calibration of the ICH score with and without SVD biomarkers.

RESULTS

In multivariable models (adjusted for ICH score components), WMH presence (odds ratio [OR] 1.52, 95% confidence interval [CI] 1.12-2.06), cortical atrophy presence (OR 1.80, 95% CI 1.19-2.73), deep atrophy presence (OR 1.66, 95% CI 1.17-2.34), and severe atrophy (either deep or cortical) (OR 1.94, 95% CI 1.36-2.74) were independently associated with poor functional outcome. For the revised ICH score, the AUROC was 0.71 (95% CI 0.68-0.74). Adding SVD markers did not significantly improve ICH score discrimination; for the best model (adding severe atrophy), the AUROC was 0.73 (95% CI 0.69-0.76). These results were confirmed when lobar and nonlobar ICH were considered separately.

CONCLUSIONS

The ICH score has acceptable discrimination for predicting 6-month functional outcome after ICH. CT biomarkers of SVD are associated with functional outcome, but adding them does not significantly improve ICH score discrimination.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT02513316.

Neck Circumference Is Associated With Poor Outcome in Patients With Spontaneous Intracerebral Hemorrhage

Objective: This study aimed to assess the association between neck circumference (NC) and functional outcome in intracerebral hemorrhage (ICH) patients.

Methods: We prospectively analyzed data from ICH patients who received treatment at our institution from January 2018 to November 2019. Patients were categorized into two groups according to 180-day modified Rankin scale (MRS) scores. Univariate and multivariate analyses were performed to assess whether NC was associated with poor outcome in ICH patients. Receiver operating characteristic (ROC) curve analysis was performed to determine the significance of NC in predicting the functional outcome of ICH patients.

Results: A total of 312 patients were enrolled in our study. Multivariate logistic regression analysis indicated that NC was an independent predictor of poor 180-day functional outcome [odds ratio (OR) = 1.205, 95% confidence interval (CI): 1.075–1.350, p = 0.001]. ROC analysis revealed that NC could predict poor functional outcome at 6 months.

Conclusions: NC is an independent predictor of unfavorable functional outcome at 6 months in ICH patients.

Validation of the newly conceived Surgical Swedish ICH grading scale for surgically treated patients with intracerebral hemorrhage: patient series

BACKGROUND

The authors sought to externally validate a newly developed clinical grading scale, the Surgical Swedish ICH (SwICH) score. Patients surgically treated for spontaneous supratentorial intracerebral hemorrhage (ICH) from 2009 to 2019 in a single center in Denmark were identified. Data were retrospectively collected from patient records and neuroimaging. Surgical SwICH and ICH scores were calculated for each patient, and the validity of the Surgical SwICH was assessed and compared.

OBSERVATIONS

The 126 patients included had an overall 30-day mortality rate of 23%. All patients with a Surgical SwICH score of 0 survived past one year. No patient scored the maximum Surgical SwICH score of 6. The 30-day mortality rates for Surgical SwICH scores 1, 2, 3, and 4 were 0%, 20%, 53%, and 25%, respectively (p <0.0001 for trend). Mortality rates for ICH scores 1, 2, 3, and 4 were 0%, 11%, 33%, and 76%, respectively (p <0.001 for trend). Receiver operator characteristics showed an area under curve of 0.78 for the Surgical SwICH score and 0.80 for the ICH score (p = 0.21 difference).

LESSONS

The Surgical SwICH score was a good predictor of 30-day mortality in patients surgically treated for spontaneous supratentorial ICH. However, the Surgical SwICH score did not outperform the previously established ICH score in predicting 30-day mortality.

Treatment of intracerebral hemorrhage: From specific interventions to bundles of care

Intracerebral hemorrhage (ICH) represents a major, global, unmet health need with few treatments. A significant minority of ICH patients present taking an anticoagulant; both vitamin-K antagonists and increasingly direct oral anticoagulants. Anticoagulants are associated with an increased risk of hematoma expansion, and rapid reversal reduces this risk and may improve outcome. Vitamin-K antagonists are reversed with prothrombin complex concentrate, dabigatran with idarucizumab, and anti-Xa agents with PCC or andexanet alfa, where available. Blood pressure lowering may reduce hematoma growth and improve clinical outcomes and careful (avoiding reductions ≥60 mm Hg within 1 h), targeted (as low as 120–130 mm Hg), and sustained (minimizing variability) treatment during the first 24 h may be optimal for achieving better functional outcomes in mild-to-moderate severity acute ICH. Surgery for ICH may include hematoma evacuation and external ventricular drainage to treat hydrocephalus. No large, well-conducted phase III trial of surgery in ICH has so far shown overall benefit, but meta-analyses report an increased likelihood of good functional outcome and lower risk of death with surgery, compared to medical treatment only. Expert supportive care on a stroke unit or critical care unit improves outcomes. Early prognostication is difficult, and early do-not-resuscitate orders or withdrawal of active care should be used judiciously in the first 24–48 h of care. Implementation of acute ICH care can be challenging, and using a care bundle approach, with regular monitoring of data and improvement of care processes can ensure consistent and optimal care for all patients.

Reliability of the intracerebral hemorrhage score for predicting outcome in patients with intracerebral hemorrhage using oral anticoagulants

BACKGROUND AND PURPOSE

The intracerebral hemorrhage (ICH) score is the most widely used and validated prognostic model for estimating 30-day mortality in ICH. However, the score was developed and validated in an ICH population probably not using oral anticoagulants (OACs). The aim of this study was to determine the performance of the ICH score for predicting the 30-day mortality rate in the full range of ICH scores in patients using OACs.

METHODS

Data from admitted patients with ICH were collected retrospectively in two Dutch comprehensive stroke centers. The validity of the ICH score was evaluated by assessing both discrimination and calibration in OAC and OAC-naive patient groups.

RESULTS

A total of 1752 patients were included of which 462 (26%) patients were on OAC. The 30-day mortality was 54% for the OAC cohort and 34% for the OAC-naive cohort. The 30-day mortality was higher in the OAC cohort for ICH score 1 (33% vs. 12.5%; odds ratio, 3.4; 95% confidence intervals, 1.1-10.4) and ICH score 2 (53% vs. 26%; odds ratio, 3.2; 95% confidence intervals, 1.2-8.2) compared with the predicted mortality rate of the original ICH score. Overall, the discriminative ability of the ICH score was equally good in both cohorts (area under the curve 0.83 vs. 0.87, respectively).

CONCLUSIONS

The ICH score underestimated the 30-day mortality rate for lower ICH scores in OAC-ICH. When estimating the prognosis of ICH in patients using OAC, this underestimation of mortality must be taken into account.

Early Predictors for Infectious Complications in Patients With Spontaneous Intracerebral Hemorrhage and Their Impact on Outcome

Background: Infectious complications (IC) commonly occur in patients with intracerebral hemorrhage (ICH) and are associated with increased length of hospitalization (LOS) and poor long-term outcome. Little is known about early ICH-related predictors for the development of IC to allow appropriate allocation of resources and timely initiation of preventive measures.

Methods: We prospectively enrolled 229 consecutive patients with non-traumatic ICH admitted to the neurocritical care unit (NICU) of a tertiary care hospital. Patients were screened daily for IC. Multivariable regression models using generalized linear models were used to identify associated factors with the occurrence of IC and to study their impact on functional outcome, which was assessed using the modified Rankin Scale Score (mRS) after 3 months. Unfavorable outcome was defined as mRS ≥3.

Results: The most common IC were pneumonia (n = 64, 28%) and urinary tract infection (n = 54, 24%), followed by sepsis (n = 9, 4%) and ventriculitis (n = 4, 2%). Patients with a higher admission ICH Score (>2) had higher odds to develop any IC during NICU stay (OR = 1.7, 95% CI 1.2–2.3, p = 0.02). Moreover, early-onset pneumonia (≤48 h after admission) was predictive of sepsis occurring at a later time-point (median at day 11 [IQR = 6–34 days], adjOR = 22.5, 95% CI 4.88–103.6, p < 0.001). Having at least one IC and pneumonia itself were independently associated with unfavorable 3-months outcome (adjOR = 3.0, 95% CI 1.41–6.54, p = 0.005; adjOR = 4.2, 95% CI 1.33–13.19, p = 0.015, respectively). All patients with sepsis died or had poor functional outcome.

Conclusions: Infectious complications are common in ICH patients and independently associated with unfavorable outcome. An ICH Score >2 on admission and early pneumonia may help to early identify patients at high risk of IC to allocate resources and start careful surveillance.

Identification and Validation of Hematoma Volume Cutoffs in Spontaneous, Supratentorial Deep Intracerebral Hemorrhage

Background and Purpose- Clinical trials in spontaneous intracerebral hemorrhage (ICH) have used volume cutoffs as inclusion criteria to select populations in which the effects of interventions are likely to be the greatest. However, optimal volume cutoffs for predicting poor outcome in deep locations (thalamus versus basal ganglia) are unknown. Methods- We conducted a 2-phase study to determine ICH volume cutoffs for poor outcome (modified Rankin Scale score of 4-6) in the thalamus and basal ganglia. Cutoffs with optimal sensitivity and specificity for poor outcome were identified in the ERICH ([Ethnic/Racial Variations of ICH] study; derivation cohort) using receiver operating characteristic curves. The cutoffs were then validated in the ATACH-2 trial (Antihypertensive Treatment of Acute Cerebral Hemorrhage-2) by comparing the c-statistic of regression models for outcome (including dichotomized volume) in the validation cohort. Results- Of the 3000 patients enrolled in ERICH, 1564 (52%) had deep ICH, of whom 1305 (84%) had complete neuroimaging and outcome data (660 thalamic and 645 basal ganglia hemorrhages). Receiver operating characteristic curve analysis identified 8 mL in thalamic (area under the curve, 0.79; sensitivity, 73%; specificity, 78%) and 18 mL in basal ganglia ICH (area under the curve, 0.79; sensitivity, 70%; specificity, 83%) as optimal cutoffs for predicting poor outcome. The validation cohort included 834 (84%) patients with deep ICH and complete neuroimaging data enrolled in ATACH-2 (353 thalamic and 431 basal ganglia hemorrhages). In thalamic ICH, the c-statistic of the multivariable outcome model including dichotomized ICH volume was 0.80 (95% CI, 0.75-0.85) in the validation cohort. For basal ganglia ICH, the c-statistic was 0.81 (95% CI, 0.76-0.85) in the validation cohort. Conclusions- Optimal hematoma volume cutoffs for predicting poor outcome in deep ICH vary by the specific deep brain nucleus involved. Utilization of location-specific volume cutoffs may improve clinical trial design by targeting deep ICH patients that will obtain maximal benefit from candidate therapies.