Combining Transcranial Doppler and EEG Data to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage

Quantitative electroencephalography predicts delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: a retrospective study

PURPOSE

Delayed cerebral ischemia (DCI) is a common complication that occurs in aneurysmal subarachnoid hemorrhage (aSAH). This complication can lead to clinical deterioration and poor prognosis. The aim of this study is to explore the risk factors for DCI in aSAH patients in neurological ICU, develop a nomogram including quantitative electroencephalography (qEEG) parameters, and evaluate its performance.

METHODS

We retrospectively analyzed and processed Severe aneurysmal subarachnoid hemorrhage (SaSAH) patients from June 2022 to May 2024 who underwent bedside qEEG monitoring and analyzed the qEEG indices, brain CT, and clinical data of these patients. Logistic multivariate regression analysis was employed to identify the independent risk factors of DCI. A clinical prediction model in the form of a nomogram for DCI was developed using the R programming language and subsequently evaluated for its performance and quality.

RESULTS

A total of 145 patients with SaSAH were included in the analysis, comprising 101 patients in the training set and 44 patients in the validation set. 77 patients (53.10 %) developed DCI. Multivariate regression analysis revealed that GCS, modified Fisher grade, hypothermia, alpha/delta ratio (ADR) and PAV grade were independent risk factors for DCI. The nomogram exhibited excellent discriminative performance in both the training set (AUC = 0.84) and the validation set (AUC = 0.80).

CONCLUSION

Quantitative EEG can predict DCI following SaSAH, the resulting nomogram demonstrated substantial predictive value and may help target therapies to patients at highest risk of secondary brain injury. It needs to be further confirmed in the future by multi-center large sample studies.

The value of fetal growth trajectory during pregnancy in predicting small for gestational age neonates at term

BACKGROUND

The predictive value of trajectory identified by group-based trajectory modeling (GBTM) has been discussed but its value in predicting small for gestational age (SGA) neonates is still unclear. This study aims to describe the trajectory of fetal growth of estimated fetal weight (EFW) during pregnancy and compare its performance to growth velocity of EFW and EFW z-scores at each scan in predicting SGA neonates at term.

METHODS

The growth trajectory for EFW obtained from ultrasound scan at around 23-24, 31-32, 37-39 weeks of gestation of 1699 women from Shenzhen Birth Cohort Study was identified using GBTM. The area under receiver operating characteristics curve (AUC), Brier scores and Decision curve analysis (DCA) was used to evaluate the discrimination, calibration performance and clinical usefulness of EFW growth trajectory, EFW growth velocity between each stage and EFW z-scores at each scan.

RESULTS

Four trajectory groups of EFW which described as "very low-stable", "low-stable", "average-stable", "rising-falling" were identified. The growth trajectory performed better in discrimination and calibration than growth velocity, with AUC of 0.76 (95%CI: 0.73-0.80) and Brier score of 0.067 in predicting SGA neonates at term. When compared to the EFW z-scores, growth trajectory performed better than EFW z-scores of 23-24 weeks (AUC = 0.72, 95%CI: 0.68-0.76, Brier score = 0.073), but not as well as EFW z-scores of 37-39 weeks of gestation (AUC = 0.88, 95%CI: 0.86-0.91, Brier score = 0.060).

CONCLUSIONS

EFW z-scores of 37-39 weeks of gestation outperformed in predicting SGA neonates at term than growth trajectory and velocity. Growth trajectory has better potential for serial ultrasound examinations to describe the process of fetal growth and to predict SGA neonates at term than fetal growth velocity.

Prognostic factors in aneurysmal subarachnoid hemorrhage with poor initial clinical grade

Introduction

Aneurysmal subarachnoid hemorrhage (aSAH) is a rare cause of stroke that poses significant morbidity and mortality, as it affects patients around the age of 50 years. While advances in early aneurysm intervention have reduced mortality rates, many patients still experience poor outcomes due to early brain injury (EBI) and delayed cerebral ischemia (DCI). This study aims to explore the characteristics of patients with poor neurological outcomes among patients with poor neurological status at admission, using comprehensive clinical and neuroimaging data.

Methods

We analyzed 377 aSAH patients (WFNS 4-5) admitted between 2013 and 2020, focusing on demographics, clinical assessments, imaging, treatments, and outcomes at discharge and 3 months later.

Results

Among the cohort, which predominantly consisted of females, the mortality rate was 49%. Our findings indicate that older patients had poorer functional outcomes; notably, 59% of patients aged 75 and older had limitations on therapeutic efforts, leading to a 100% mortality rate in that subgroup. There was no difference in outcomes between endovascular and surgical treatments. However, patients undergoing multimodal monitoring had better functional outcomes at discharge. Angiographic vasospasm was found in 31% of patients and was linked to poorer outcomes at discharge (p = 0.016). Though DCI did not directly correlate with functional outcomes, it correlated strongly with new cerebral infarcts (90% incidence).

Conclusion

The prognosis of patients with aSAH and poor neurological status on admission is generally poor. Multimodal monitoring and tailored treatment appear to be beneficial in achieving favorable results in these patients. Despite the initial severity, up to 20% of patients achieve a good functional result on discharge and up to 35% do so at 3 months. These should be considered in the initial prognostic assessment with the families of these patients.

Analysis of endovascular treatment for cerebral vasospasms after subarachnoid hemorrhage in the Japanese Registry of Neuroendovascular Therapy 4

BACKGROUND

This study aimed to evaluate the periprocedural and postprocedural outcomes of endovascular treatments for cerebral vasospasm after subarachnoid hemorrhage using data from the Japan Registry of Neuroendovascular Therapy 4 (JR-NET4) (2015-2019).

METHODS

In this retrospective multicenter study, procedures of endovascular treatment for cerebral vasospasms registered in JR-NET4 were analyzed. The procedure outcomes and complications for percutaneous transluminal angioplasty (PTA) and intra-arterial administration of vasodilators (IA-vasodilator) were compared. The factors associated with imaging and symptom improvement were assessed.

RESULTS

Analysis of 1549 procedures revealed that 83.5% of procedures were IA-vasodilator and 16.5% of procedures were PTA. Postprocedural imaging improvement was achieved in 97.0% of patients, and 50.1% of patients experienced symptomatic improvement. The overall complication rate was 1.6%. No significant differences were detected in overall complication rates between patients who underwent PTA and intra-arterial administration of vasodilators; however, hemorrhagic complications were significantly more frequent in patients who underwent PTA. Shorter intervals from symptom onset and the absence of periprocedural complications were associated with improved imaging and neurological outcomes. Local anesthesia and prior treatment with endovascular embolization for ruptured aneurysms were associated with enhanced neurological improvements.

CONCLUSION

Endovascular treatment for cerebral vasospasm is safe and effective. Factors such as early intervention and treatment under local anesthesia may contribute to neurological improvements. However, caution is warranted for PTA due to the slightly higher incidence of hemorrhagic complications.

Machine Learning for the Early Prediction of Delayed Cerebral Ischemia in Patients With Subarachnoid Hemorrhage: Systematic Review and Meta-Analysis

BACKGROUND

Delayed cerebral ischemia (DCI) is a primary contributor to death after subarachnoid hemorrhage (SAH), with significant incidence. Therefore, early determination of the risk of DCI is an urgent need. Machine learning (ML) has received much attention in clinical practice. Recently, some studies have attempted to apply ML models for early noninvasive prediction of DCI. However, systematic evidence for its predictive accuracy is still lacking.

OBJECTIVE

The aim of this study was to synthesize the prediction accuracy of ML models for DCI to provide evidence for the development or updating of intelligent detection tools.

METHODS

PubMed, Cochrane, Embase, and Web of Science databases were systematically searched up to May 18, 2023. The risk of bias in the included studies was assessed using PROBAST (Prediction Model Risk of Bias Assessment Tool). During the analysis, we discussed the performance of different models in the training and validation sets.

RESULTS

We finally included 48 studies containing 16,294 patients with SAH and 71 ML models with logistic regression as the main model type. In the training set, the pooled concordance index (C index), sensitivity, and specificity of all the models were 0.786 (95% CI 0.737-0.835), 0.77 (95% CI 0.69-0.84), and 0.83 (95% CI 0.75-0.89), respectively, while those of the logistic regression models were 0.770 (95% CI 0.724-0.817), 0.75 (95% CI 0.67-0.82), and 0.71 (95% CI 0.63-0.78), respectively. In the validation set, the pooled C index, sensitivity, and specificity of all the models were 0.767 (95% CI 0.741-0.793), 0.66 (95% CI 0.53-0.77), and 0.78 (95% CI 0.71-0.84), respectively, while those of the logistic regression models were 0.757 (95% CI 0.715-0.800), 0.59 (95% CI 0.57-0.80), and 0.80 (95% CI 0.71-0.87), respectively.

CONCLUSIONS

ML models appear to have relatively desirable power for early noninvasive prediction of DCI after SAH. However, enhancing the prediction sensitivity of these models is challenging. Therefore, efficient, noninvasive, or minimally invasive low-cost predictors should be further explored in future studies to improve the prediction accuracy of ML models.

TRIAL REGISTRATION

PROSPERO (CRD42023438399); https://tinyurl.com/yfuuudde.

Leveraging machine learning algorithms to forecast delayed cerebral ischemia following subarachnoid hemorrhage: a systematic review and meta-analysis of 5,115 participants

It is feasible to predict delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH) using Artificial intelligence (AI) algorithms, which may offer significant improvements in early diagnosis and patient management. This systematic review and meta-analysis evaluate the efficacy of machine learning (ML) in predicting DCI, aiming to integrate complex clinical data to enhance diagnostic accuracy. We searched PubMed, Scopus, Web of science, and Embase databases without restrictions until June 2024, applying PRISMA guidelines. Out of 1498 studies screened, 10 met our eligibility criteria involving ML approaches in patients with confirmed aSAH. The studies employed various ML algorithms and reported differential ML metrics outcomes. Meta-analysis was performed on eight studies, which resulted in a pooled sensitivity of 0.79 [95% CI: 0.63-0.89], specificity of 0.78[95% CI: 0.68-0.85], positive DLR of 3.54 [95% CI: 2.22-5.64] and the negative DLR of 0.28 [95% CI: 0.15-0.52], diagnostic odds ratio of 12.82 [95% CI: 4.66-35.28], the diagnostic score of 2.55 [95% CI: 1.54-3.56], and the area under the curve (AUC) of 0.85. These findings show significant diagnostic accuracy and demonstrate the potential of ML algorithms to significantly improve the predictability of DCI, implying that ML could impart a significant role on improving clinical decision making. However, variability in methodological approaches across studies shows a need for standardization to realize the full benefits of ML in clinical settings.

Using artificial intelligence to optimize anti-seizure treatment and EEG-guided decisions in severe brain injury

Electroencephalography (EEG) is invaluable in the management of acute neurological emergencies. Characteristic EEG changes have been identified in diverse neurologic conditions including stroke, trauma, and anoxia, and the increased utilization of continuous EEG (cEEG) has identified potentially harmful activity even in patients without overt clinical signs or neurologic diagnoses. Manual annotation by expert neurophysiologists is a major resource limitation in investigating the prognostic and therapeutic implications of these EEG patterns and in expanding EEG use to a broader set of patients who are likely to benefit. Artificial intelligence (AI) has already demonstrated clinical success in guiding cEEG allocation for patients at risk for seizures, and its potential uses in neurocritical care are expanding alongside improvements in AI itself. We review both current clinical uses of AI for EEG-guided management as well as ongoing research directions in automated seizure and ischemia detection, neurologic prognostication, and guidance of medical and surgical treatment.

Comparative Analysis of Somatosensory-Evoked Potentials and Transcranial Doppler Ultrasound for Cerebral Ischemia Detection in Carotid Endarterectomy: Insights from Network Meta-Analysis and Clinical Data

OBJECTIVE

This study aims to compare the diagnostic efficacy of somatosensory-evoked potentials (SEPs) and transcranial Doppler sonography (TCD) for monitoring cerebral tissue ischemia during carotid endarterectomy (CEA) using network meta-analysis and retrospective analysis of clinical data.

METHODS

For the meta-analysis, we conducted a comprehensive search of 4 electronic databases (PubMed, EMBASE, Cochrane, and Web of Science) from inception to September 2023, resulting in the inclusion of 52 relevant articles. Additionally, a retrospective study was conducted at our hospital, involving patients who underwent CEA surgery from July 2019 to July 2021.

RESULTS

The network meta-analysis incorporated 52 articles, with ranking results indicating that SEP demonstrated superior performance in specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy with surface under the cumulative ranking curve values of 99.9%, 93.8%, 96.6%, and 99.9%, respectively. Furthermore, TCD exhibited the highest sensitivity with a surface under the cumulative ranking value of 92.0%. A total of 190 patients meeting inclusion criteria were included in the retrospective study. The area under the curve for SEP's receiver operating characteristic curve was 0.787, compared to TCD's area under the curve of 0.606. SEP demonstrated a sensitivity of 66.67%, with a specificity of 90.76%, PPV of 19.05%, NPV of 98.82%, and accuracy of 90%. For TCD, the diagnostic performance measures included a sensitivity of 50.00%, specificity of 71.19%, PPV of 5.35%, NPV of 97.76%, and accuracy of 70.53%. The Fisher's exact test for sensitivity yielded a result of P = 1.000. The χˆ2 test for specificity resulted in χˆ2 = 22.863, with P < 0.001. Continuous correction χˆ2 tests for PPV and NPV showed χˆ2 = 2.005 (P = 0.157) and χˆ2 = 0.069 (P = 0.793), respectively. Additionally, the χˆ2 test for accuracy showed χˆ2 = 22.742, with P < 0.001.

CONCLUSIONS

During CEA, SEP appears to provide a slightly more reliable indication of the ischemic condition in cerebral tissues compared to TCD.

Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT

BACKGROUND AND PURPOSE

Delayed cerebral ischemia is hard to diagnose early due to gradual, symptomless development. This study aimed to develop an automated model for predicting delayed cerebral ischemia following aneurysmal SAH on NCCT.

MATERIALS AND METHODS

This retrospective study included 400 patients with aneurysmal SAH (156 with delayed cerebral ischemia) who underwent NCCT. The study used ATT-Deeplabv3+ for automatically segmenting hemorrhagic regions using semisupervised learning. Principal component analysis was used for reducing the dimensionality of deep learning features extracted from the average pooling layer of ATT-DeepLabv3+. The classification model integrated clinical data, radiomics, and deep learning features to predict delayed cerebral ischemia. Feature selection involved Pearson correlation coefficients, least absolute shrinkage, and selection operator regression. We developed models based on clinical features, clinical-radiomics, and a combination of clinical, radiomics, and deep learning. The study selected logistic regression, Naive Bayes, Adaptive Boosting (AdaBoost), and multilayer perceptron as classifiers. The performance of segmentation and classification models was evaluated on their testing sets using the Dice similarity coefficient for segmentation, and the area under the receiver operating characteristic curve (AUC) and calibration curves for classification.

RESULTS

The segmentation process achieved a Dice similarity coefficient of 0.91 and the average time of 0.037 s/image. Seventeen features were selected to calculate the radiomics score. The clinical-radiomics-deep learning model with multilayer perceptron achieved the highest AUC of 0.84 (95% CI, 0.72-0.97), which outperformed the clinical-radiomics model (P = .002) and the clinical features model (P = .001) with multilayer perceptron. The performance of clinical-radiomics-deep learning model using AdaBoost was significantly superior to its clinical-radiomics model (P = .027). The performance of the clinical-radiomics-deep learning model and the clinical-radiomics model with logistic regression notably exceeded that of the model based solely on clinical features (P = .028; P = .046). The AUC of the clinical-radiomics-deep learning model with multilayer perceptron (P < .001) and the clinical-radiomics model with logistic regression (P = .046) were significantly higher than the clinical model with logistic regression. Of all models, the clinical-radiomics-deep learning model with multilayer perceptron showed best calibration.

CONCLUSIONS

The proposed 2-stage end-to-end model not only achieves rapid and accurate segmentation but also demonstrates superior diagnostic performance with high AUC values and good calibration in the clinical-radiomics-deep learning model, suggesting its potential to enhance delayed cerebral ischemia detection and treatment strategies.

Novel cortisol trajectory sub-phenotypes in sepsis

BACKGROUND

Sepsis is a heterogeneous syndrome. This study aimed to identify new sepsis sub-phenotypes using plasma cortisol trajectory.

METHODS

This retrospective study included patients with sepsis admitted to the intensive care unit of Zhongshan Hospital Fudan University between March 2020 and July 2022. A group-based cortisol trajectory model was used to classify septic patients into different sub-phenotypes. The clinical characteristics, biomarkers, and outcomes were compared between sub-phenotypes.

RESULTS

A total of 258 patients with sepsis were included, of whom 186 were male. Patients were divided into two trajectory groups: the lower-cortisol group (n = 217) exhibited consistently low and slowly declining cortisol levels, while the higher-cortisol group (n = 41) showed relatively higher levels in comparison. The 28-day mortality (65.9% vs.16.1%, P < 0.001) and 90-day mortality (65.9% vs. 19.8%, P < 0.001) of the higher-cortisol group were significantly higher than the lower-cortisol group. Multivariable Cox regression analysis showed that the trajectory sub-phenotype (HR = 5.292; 95% CI 2.218-12.626; P < 0.001), APACHE II (HR = 1.109; 95% CI 1.030-1.193; P = 0.006), SOFA (HR = 1.161; 95% CI 1.045-1.291; P = 0.006), and IL-1β (HR = 1.001; 95% CI 1.000-1.002; P = 0.007) were independent risk factors for 28-day mortality. Besides, the trajectory sub-phenotype (HR = 4.571; 95% CI 1.980-10.551; P < 0.001), APACHE II (HR = 1.108; 95% CI 1.043-1.177; P = 0.001), SOFA (HR = 1.270; 95% CI 1.130-1.428; P < 0.001), and IL-1β (HR = 1.001; 95% CI 1.000-1.001; P = 0.015) were also independent risk factors for 90-day mortality.

CONCLUSION

This study identified two novel cortisol trajectory sub-phenotypes in patients with sepsis. The trajectories were associated with mortality, providing new insights into sepsis classification.

Value of Glycemic Indices for Delayed Cerebral Ischemia after Aneurysmal Subarachnoid Hemorrhage: A Retrospective Single-Center Study

Delayed cerebral ischemia (DCI) is a severe complication following aneurysmal subarachnoid hemorrhage (aSAH), linked to poor functional outcomes and prolonged intensive care unit (ICU) stays. Timely DCI diagnosis is crucial but remains challenging. Dysregulated blood glucose, commonly observed after aSAH, may impair the constant glucose supply that is vital for brain function, potentially contributing to DCI. This study aimed to assess whether glucose indices could help identify at-risk patients and improve DCI detection. This retrospective, single-center observational study examined 151 aSAH patients between 2016 and 2019. Additionally, 70 of these (46.4%) developed DCI and 81 did not (no-DCI). To determine the value of glycemic indices for DCI, they were analyzed separately in patients in the period before (pre-DCI) and after DCI (post-DCI). The time-weighted average glucose (TWAG, p = 0.024), mean blood glucose (p = 0.033), and novel time-unified dysglycemic rate (TUDR140, calculated as the ratio of dysglycemic to total periods within a glucose target range of 70-140 mg/dL, p = 0.042), showed significantly higher values in the pre-DCI period of the DCI group than in the no-DCI group. In the time-series analysis, significant increases in TWAG and TUDR140 were observed at the DCI onset. In conclusion, DCI patients showed elevated blood glucose levels before and a further increase at the DCI onset. Prospective studies are needed to confirm these findings, as this retrospective, single-center study cannot completely exclude confounders and limitations. In the future blood glucose indices might become valuable parameters in multiparametric models to identify patients at risk and detect DCI onset earlier.

Risk Factors and Clinical Significance of Ultra-Long-Term Microischemia After Intracranial Aneurysm Embolization

INTRODUCTION

This study aimed to explore influencing factors and clinical significance of ultra-long-term microischemia following intracranial aneurysm (IA) embolization and establish a theoretical foundation for reducing both the incidence of ultra-long-term microischemia and cognitive dysfunction in patients post embolization.

METHODS

A retrospective analysis was conducted on data from 147 patients who received endovascular treatment for IAs. Patients were categorized into microischemic and control (non-microischemic) groups on the based on the findings of high-resolution magnetic resonance vessel wall imaging (HR-VWI) examinations performed 3 days postoperatively and 6 months postoperatively. Risk factors for the occurrence of ultra-long-term microischemia were determined by univariate analysis and multivariate logistic regression analysis.

RESULTS

Out of 147 patients included in the study, 51 (34.69%) developed microischemia while the remaining 96 (65.31%) did not experience this condition. Analysis revealed that factors such as sex, age, history of underlying diseases (hypertension, diabetes mellitus), aneurysmal site characteristics, the presence or absence of stenosis in the aneurysm-bearing artery, modified Fisher score at admission, Barthel's index at discharge, immunoinflammatory index at 3 days postoperatively and at the 6-month follow-up, the presence or absence of aneurysmal wall enhancement, and the presence or absence of aneurysmal lumen showed no statistically significant differences between the two groups (all P > 0.05). By contrast, variables like in operative time, rupture status of the aneurysm before surgery according to World Federation of Neurologic Surgeons (WFNS) grade, aneurysm size, number of stents used, number of guidewires and catheters used, and Evans index between the two groups were found to have statistically significant disparities between those who developed microischemia and those who did not (P < 0.05). A subsequent multivariate analysis revealed that aneurysm size, Evans index, and the number of stents used were independent risk factors for the occurrence of ultra-long-term microischemia after surgical intervention of aneurysms (P < 0.05). The receiver operating characteristic (ROC) curves of the patients were constructed on the basis of risk factors determined through multivariate logistic regression analysis. Results indicated that aneurysm size (area under ROC curve (AUC) 0.619, sensitivity 94.7%, specificity 17.1%, P = 0.049), Evans index (AUC 0.670, sensitivity 96.4%, specificity 26.8%, P = 0.004), and number of stents (AUC 0.639, sensitivity 44.6%, specificity 90.2%, P < 0.001) effectively predicted the occurrence of microischemia. The incidence of cognitive dysfunction was higher in the microischemic group than in the control group (P < 0.05), and a greater number of microischemic foci was associated with a higher incidence of cognitive dysfunction. The proportion of microschemia foci in the thalamus and basal ganglia in patients with cognitive dysfunction (60.87%) was significantly higher than that in patients without cognitive dysfunction (34.55%) (P < 0.05).

CONCLUSION

Aneurysm size, Evans index > 0.3, and the quantity of stents were independent risk factors for the occurrence of ultra-long-term microischemia after aneurysm embolization and provided good predictive performance. Cognitive dysfunction was closely associated with microischemia, with its severity increasing with an increase in the number of ischemic foci.

CT perfusion-guided administration of IV milrinone is associated with a reduction in delayed cerebral infarction after subarachnoid hemorrhage

Delayed cerebral ischemia (DCI) after aneurysmal subarachnoid haemorrhage (aSAH) is a singular pathological entity necessitating early diagnostic approaches and both prophylactic and curative interventions. This retrospective before-after study investigates the effects of a management strategy integrating perfusion computed tomography (CTP), vigilant clinical monitoring and standardized systemic administration of milrinone on the occurrence of delayed cerebral infarction (DCIn). The "before" period included 277 patients, and the "after" one 453. There was a higher prevalence of Modified Fisher score III/IV and more frequent diagnosis of vasospasm in the "after" period. Conversely, the occurrence of DCIn was reduced with the "after" management strategy (adjusted OR 0.48, 95% CI [0.26; 0.84]). Notably, delayed ischemic neurologic deficits were less prevalent at the time of vasospasm diagnosis (24 vs 11%, p = 0.001 ), suggesting that CTP facilitated early detection. In patients diagnosed with vasospasm, intravenous milrinone was more frequently administered (80 vs 54%, p < 0.001 ) and associated with superior hemodynamics. The present study from a large cohort of aSAH patients suggests, for one part, the interest of CTP in early diagnosis of vasospasm and DCI, and for the other the efficacy of CT perfusion-guided systemic administration of milrinone in both preventing and treating DCIn.

Emergent Management of Spontaneous Subarachnoid Hemorrhage

OBJECTIVE

Spontaneous subarachnoid hemorrhage (SAH) carries high morbidity and mortality rates, and the emergent management of this disease can make a large impact on patient outcome. The purpose of this article is to provide a pragmatic overview of the emergent management of SAH.

LATEST DEVELOPMENTS

Recent trials have influenced practice around the use of antifibrinolytics, the timing of aneurysm securement, the recognition of cerebral edema and focus on avoiding a lower limit of perfusion, and the detection and prevention of delayed cerebral ischemia. Much of the acute management of SAH can be protocolized, as demonstrated by two updated guidelines published by the American Heart Association/American Stroke Association and the Neurocritical Care Society in 2023. However, the gaps in evidence lead to clinical equipoise in some aspects of critical care management.

ESSENTIAL POINTS

In acute management, there is an urgency to differentiate the etiology of SAH and take key emergent actions including blood pressure management and coagulopathy reversal. The critical care management of SAH is similar to that of other acute brain injuries, with the addition of detecting and treating delayed cerebral ischemia. Strategies for the detection and treatment of delayed cerebral ischemia are limited by disordered consciousness and may be augmented by monitoring and imaging technology.

Machine Learning Algorithms to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Systematic Review and Meta-analysis

Delayed cerebral ischemia (DCI) is a common and severe complication after subarachnoid hemorrhage (SAH). Logistic regression (LR) is the primary method to predict DCI, but it has low accuracy. This study assessed whether other machine learning (ML) models can predict DCI after SAH more accurately than conventional LR. PubMed, Embase, and Web of Science were systematically searched for studies directly comparing LR and other ML algorithms to forecast DCI in patients with SAH. Our main outcome was the accuracy measurement, represented by sensitivity, specificity, and area under the receiver operating characteristic. In the six studies included, comprising 1828 patients, about 28% (519) developed DCI. For LR models, the pooled sensitivity was 0.71 (95% confidence interval [CI] 0.57-0.84; p < 0.01) and the pooled specificity was 0.63 (95% CI 0.42-0.85; p < 0.01). For ML models, the pooled sensitivity was 0.74 (95% CI 0.61-0.86; p < 0.01) and the pooled specificity was 0.78 (95% CI 0.71-0.86; p = 0.02). Our results suggest that ML algorithms performed better than conventional LR at predicting DCI.Trial Registration: PROSPERO (International Prospective Register of Systematic Reviews) CRD42023441586; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=441586.

Intrahospital Transport of Critically Ill Patients with Subarachnoid Hemorrhage-Frequency, Timing, Complications, and Clinical Consequences

BACKGROUND

Patients with subarachnoid hemorrhage (SAH) often necessitate intra-hospital transport (IHT) during intensive care treatment. These transfers to facilities outside of the neurointensive care unit (NICU) pose challenges due to the inherent instability of the hemodynamic, respiratory, and neurological parameters that are typical in these patients.

METHODS

In this retrospective, single-center cohort study, a total of 108 IHTs were analyzed for demographics, transport rationale, clinical outcomes, and pre/post-IHT monitoring parameters. After establishing clinical thresholds, the frequency of complications was calculated, and predictors of thresholds violations were determined.

RESULTS

The mean age was 55.7 (+/-15.3) years, with 68.0% showing severe SAH (World Federation of Neurosurgical Societies Scale 5). IHTs with an emergency indication made up 30.8% of all transports. Direct therapeutic consequences from IHT were observed in 38.5%. On average, the first IHT occurred 1.5 (+/-2.0) days post-admission and patients were transported 4.3 (+/-1.8) times during their stay in the NICU. Significant parameter changes from pre- to post-IHT included mean arterial pressure, systolic blood pressure, oxygen saturation, blood glucose levels, temperature, dosages of propofol and ketamine, tidal volume, inspired oxygen concentration, Horovitz index, glucose, pH, intracranial pressure, and cerebral perfusion pressure. Relevant hemodynamic thresholds were violated in 31.5% of cases, while respiratory complications occurred in 63.9%, and neurological complications in 20.4%. For hemodynamic complications, a low heart rate with a threshold of 61/min (OR 0.96, 95% CI 0.93-0.99, p = 0.0165) and low doses of midazolam with a threshold of 17.5 mg/h (OR 0.97, 95% CI 0.95-1.00, p = 0.0232) significantly predicted adverse events. However, the model did not identify significant predictors for respiratory and neurological outcomes.

CONCLUSIONS

Conclusively, IHTs in SAH patients are associated with relevant changes in hemodynamic, respiratory, and neurological monitoring parameters, with direct therapeutic consequences in 4/10 IHTs. These findings underscore the importance of further studies on the clinical impact of IHTs.

Diagnosis of Delayed Cerebral Ischemia in Patients with Aneurysmal Subarachnoid Hemorrhage and Triggers for Intervention

INTRODUCTION

Delayed cerebral ischemia (DCI) is a major determinant for poor neurological outcome after aneurysmal subarachnoid hemorrhage (aSAH). Detection and treatment of DCI is a key component in the neurocritical care of patients with aSAH after initial aneurysm repair.

METHODS

Narrative review of the literature.

RESULTS

Over the past 2 decades, there has been a paradigm shift away from macrovascular (angiographic) vasospasm as a main diagnostic and therapeutic target. Instead, the pathophysiology of DCI is hypothesized to derive from several proischemic pathomechanisms. Clinical examination remains the most reliable means for monitoring and treatment of DCI, but its value is limited in comatose patients. In such patients, monitoring of DCI is usually based on numerous neurophysiological and/or radiological diagnostic modalities. Catheter angiography remains the gold standard for the detection of macrovascular spasm. Computed tomography (CT) angiography is increasingly used instead of catheter angiography because it is less invasive and may be combined with CT perfusion imaging. CT perfusion permits semiquantitative cerebral blood flow measurements, including the evaluation of the microcirculation. It may be used for prediction, early detection, and diagnosis of DCI, with yet-to-prove benefit on clinical outcome when used as a screening modality. Transcranial Doppler may be considered as an additional noninvasive screening tool for flow velocities in the middle cerebral artery, with limited accuracy in other cerebral arteries. Continuous electroencephalography enables detection of early signs of ischemia at a reversible stage prior to clinical manifestation. However, its widespread use is still limited because of the required infrastructure and expertise in data interpretation. Near-infrared spectroscopy, a noninvasive and continuous modality for evaluation of cerebral blood flow dynamics, has shown conflicting results and needs further validation. Monitoring techniques beyond neurological examinations may help in the detection of DCI, especially in comatose patients. However, these techniques are limited because of their invasive nature and/or restriction of measurements to focal brain areas.

CONCLUSION

The current literature review underscores the need for incorporating existing modalities and developing new methods to evaluate brain perfusion, brain metabolism, and overall brain function more accurately and more globally.

2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage: A Guideline From the American Heart Association/American Stroke Association

AIM

The "2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage" replaces the 2012 "Guidelines for the Management of Aneurysmal Subarachnoid Hemorrhage." The 2023 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with aneurysmal subarachnoid hemorrhage.

METHODS

A comprehensive search for literature published since the 2012 guideline, derived from research principally involving human subjects, published in English, and indexed in MEDLINE, PubMed, Cochrane Library, and other selected databases relevant to this guideline, was conducted between March 2022 and June 2022. In addition, the guideline writing group reviewed documents on related subject matter previously published by the American Heart Association. Newer studies published between July 2022 and November 2022 that affected recommendation content, Class of Recommendation, or Level of Evidence were included if appropriate. Structure: Aneurysmal subarachnoid hemorrhage is a significant global public health threat and a severely morbid and often deadly condition. The 2023 aneurysmal subarachnoid hemorrhage guideline provides recommendations based on current evidence for the treatment of these patients. The recommendations present an evidence-based approach to preventing, diagnosing, and managing patients with aneurysmal subarachnoid hemorrhage, with the intent to improve quality of care and align with patients' and their families' and caregivers' interests. Many recommendations from the previous aneurysmal subarachnoid hemorrhage guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.

Ultrasound-guided puncture into newborn rat brain

Since the brain structure of neonatal rats was not fully formed during the first 4 days, it cannot be detected using ultrasound. The objective of this study was to investigate the use of ultrasound to guide puncture in the normal coronal brain structure and determine the puncture depth of the location of the cortex, hippocampus, lateral ventricle, and striatum of newborn rats of 5-15 days. The animal was placed in a prone position. The specific positions of the cortex, hippocampus, lateral ventricle, and striatum were measured under ultrasound. Then, the rats were punctured with a stereotaxic instrument, and dye was injected. Finally, the brains of rats were taken to make frozen sections to observe the puncture results. By ultrasound, the image of the cortex, hippocampus, lateral ventricle, and striatum of the rat can be obtained and the puncture depth of the cortex (8 days: 1.02 ± 0.12, 10 days: 1.02 ± 0.08, 13 days: 1.43 ± 0.05), hippocampus (8 days: 2.63 ± 0.07, 10 days: 2.77 ± 0.14, 13 days: 2.82 ± 0.09), lateral ventricle (8 days: 2.08 ± 0.04, 10 days: 2.26 ± 0.03, 13 days: 2.40 ± 0.06), and corpus striatum (8 days: 4.57 ± 0.09, 10 days: 4.94 ± 0.31, 13 days: 5.13 ± 0.10) can be accurately measured. The rat brain structure and puncture depth changed with the age of the rats. Ultrasound technology can not only clarify the brain structure characteristics of 5-15-day-old rats but also guide the puncture and injection of the rat brain structure. The results of this study laid the foundation for the future use of ultrasound in experimental animal models of neurological diseases.

Precision Medicine in Neurocritical Care for Cerebrovascular Disease Cases

Scientific advances have informed many aspects of acute stroke care but have also highlighted the complexity and heterogeneity of cerebrovascular diseases. While practice guidelines are essential in supporting the clinical decision-making process, they may not capture the nuances of individual cases. Personalized stroke care in ICU has traditionally relied on integrating clinical examinations, neuroimaging studies, and physiologic monitoring to develop a treatment plan tailored to the individual patient. However, to realize the potential of precision medicine in stroke, we need advances and evidence in several critical areas, including data capture, clinical phenotyping, serum biomarker development, neuromonitoring, and physiology-based treatment targets. Mathematical tools are being developed to analyze the multitude of data and provide clinicians with real-time information and personalized treatment targets for the critical care management of patients with cerebrovascular diseases. This review summarizes research advances in these areas and outlines principles for translating precision medicine into clinical practice.

Bispectral index monitoring to detect delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage

PURPOSE

Evaluate the bispectral index (BIS) monitoring to detect delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH).

MATERIALS AND METHODS

A single-center prospective study in patients with aSAH. BIS monitoring was recorded during 25-120 min in two periods, within the initial 72 h (BIS1) and between days 4 and 6 (BIS2) from admission. The median for each exported BIS parameter was analyzed. Transcranial Doppler (TCD) sonography was simultaneously performed with BIS1 (TCD1) and BIS2 (TCD2) monitoring. A multivariate logistic regression model was built to identify the variables associated with DCI.

RESULTS

Sixty-four patients were included and 16 (25%) developed DCI. During BIS2 monitoring, significant differences were found in BIS value (left, p = 0.01; right, p = 0.009), 95% spectral edge frequency (left and right, p = 0.04), and total power (left and right, p = 0.04). In multivariable analysis, vasospasm on TCD2 (OR 42.8 [95% CI 3.1-573]; p = 0.005), a median BIS2 value <85 in one or both sides (OR 6.2 [95% CI 1.28-30]; p = 0.023), and age (OR 1.08 [95% CI 1.00-1.17]; p = 0.04) were associated with the development of DCI.

CONCLUSIONS

BIS value is the most useful BIS parameter for detecting DCI after aSAH. Pending further validation, BIS monitoring might be even more accurate than TCD.

Electroencephalogram in the intensive care unit: a focused look at acute brain injury

Over the past decades, electroencephalography (EEG) has become a widely applied and highly sophisticated brain monitoring tool in a variety of intensive care unit (ICU) settings. The most common indication for EEG monitoring currently is the management of refractory status epilepticus. In addition, a number of studies have associated frequent seizures, including nonconvulsive status epilepticus (NCSE), with worsening secondary brain injury and with worse outcomes. With the widespread utilization of EEG (spot and continuous EEG), rhythmic and periodic patterns that do not fulfill strict seizure criteria have been identified, epidemiologically quantified, and linked to pathophysiological events across a wide spectrum of critical and acute illnesses, including acute brain injury. Increasingly, EEG is not just qualitatively described, but also quantitatively analyzed together with other modalities to generate innovative measurements with possible clinical relevance. In this review, we discuss the current knowledge and emerging applications of EEG in the ICU, including seizure detection, ischemia monitoring, detection of cortical spreading depolarizations, assessment of consciousness and prognostication. We also review some technical aspects and challenges of using EEG in the ICU including the logistics of setting up ICU EEG monitoring in resource-limited settings.

Neutrophil Extracellular Traps and Delayed Cerebral Ischemia in Aneurysmal Subarachnoid Hemorrhage

IMPORTANCE

Myeloperoxidase (MPO)-DNA complexes, biomarkers of neutrophil extracellular traps (NETs), have been associated with arterial and venous thrombosis. Their role in aneurysmal subarachnoid hemorrhage (aSAH) is unknown.

OBJECTIVES

To assess whether serum MPO-DNA complexes are present in patients with aSAH and whether they are associated with delayed cerebral ischemia (DCI).

DESIGN SETTING AND PARTICIPANTS

Post-hoc analysis of a prospective, observational single-center study, with de novo serum biomarker measurements in consecutive patients with aSAH between July 2018 and September 2020, admitted to a tertiary care neuroscience ICU.

MAIN OUTCOMES AND MEASURES

We analyzed serum obtained at admission and hospital day 4 for concentrations of MPO-DNA complexes. The primary outcome was DCI, defined as new infarction on brain CT. The secondary outcome was clinical vasospasm, a composite of clinical and transcranial Doppler parameters. We used Wilcoxon signed-rank-test to assess for differences between paired measures.

RESULTS

Among 100 patients with spontaneous subarachnoid hemorrhage, mean age 59 years (sd ± 13 yr), 55% women, 78 had confirmed aSAH. Among these, 29 (37%) developed DCI. MPO-DNA complexes were detected in all samples. The median MPO-DNA level was 33 ng/mL (interquartile range [IQR], 18-43 ng/mL) at admission, and 22 ng/mL (IQR, 11-31 ng/mL) on day 4 (unpaired test; p = 0.015). We found a significant reduction in MPO-DNA levels from admission to day 4 in patients with DCI (paired test; p = 0.036) but not in those without DCI (p = 0.17). There was a similar reduction in MPO-DNA levels between admission and day 4 in patients with (p = 0.006) but not in those without clinical vasospasm (p = 0.47).

CONCLUSIONS AND RELEVANCE

This is the first study to detect the NET biomarkers MPO-DNA complexes in peripheral serum of patients with aSAH and to associate them with DCI. A pronounced reduction in MPO-DNA levels might serve as an early marker of DCI. This diagnostic potential of MPO-DNA complexes and their role as potential therapeutic targets in aSAH should be explored further.

Multimodality Monitoring for Delayed Cerebral Ischemia in Subarachnoid Hemorrhage: A Mini Review

Aneurysmal subarachnoid hemorrhage is a disease with high mortality and morbidity due in large part to delayed effects of the hemorrhage, including vasospasm, and delayed cerebral ischemia. These two are now recognized as overlapping yet distinct entities, and supportive therapies for delayed cerebral ischemia are predicated on identifying DCI as quickly as possible. The purpose of this overview is to highlight diagnostic tools that are being used in the identification of DCI in the neurocritical care settings.