The SAH Score: a comprehensive communication tool

Accurately predicting the risk of unfavorable outcomes after endovascular coil therapy in patients with aneurysmal subarachnoid hemorrhage: an interpretable machine learning model

BACKGROUND

Despite endovascular coiling as a valid modality in treatment of aneurysmal subarachnoid hemorrhage (aSAH), there is a risk of poor prognosis. However, the clinical utility of previously proposed early prediction tools remains limited. We aimed to develop a clinically generalizable machine learning (ML) models for accurately predicting unfavorable outcomes in aSAH patients after endovascular coiling.

METHODS

Functional outcomes at 6 months after endovascular coiling were assessed via the modified Rankin Scale (mRS) and unfavorable outcomes were defined as mRS 3-6. Five ML algorithms (logistic regression, random forest, support vector machine, deep neural network, and extreme gradient boosting) were used for model development. The area under precision-recall curve (AUPRC) and receiver operating characteristic curve (AUROC) was used as main indices of model evaluation. SHapley Additive exPlanations (SHAP) method was applied to interpret the best-performing ML model.

RESULTS

A total of 371 patients were eventually included into this study, and 85.4% of them had favorable outcomes. Among the five models, the DNN model had a better performance with AUPRC of 0.645 (AUROC of 0.905). Postoperative GCS score, size of aneurysm, and age were the top three powerful predictors. The further analysis of five random cases presented the good interpretability of the DNN model.

CONCLUSION

Interpretable clinical prediction models based on different ML algorithms have been successfully constructed and validated, which would serve as reliable tools in optimizing the treatment decision-making of aSAH. Our DNN model had better performance to predict the unfavorable outcomes at 6 months in aSAH patients compared with Yan's nomogram model.

Comparison of Prognostic Models for Functional Outcome in Aneurysmal Subarachnoid Hemorrhage Based on Machine Learning

BACKGROUND

Controversy exists regarding the superiority of the performance of prognostic tools based on advanced machine learning (ML) algorithms for patients with aneurysmal subarachnoid hemorrhage (aSAH). However, it is unclear whether ML prognostic models will benefit patients due to the lack of a comprehensive assessment. We aimed to develop and evaluate ML models for predicting unfavorable functional outcomes for aSAH patients and identify the model with the greatest performance.

METHODS

In this retrospective study, a dataset of 955 patients with aSAH was used to construct and validate prognostic models for functional outcomes assessed using the modified Rankin scale during a follow-up period of 3-6 months. Clinical scores and clinical and radiological features on admission and secondary complications were used to construct models based on 5 ML algorithms (i.e., logistic regression [LR], k-nearest neighbor, extreme gradient boosting, random forest, and artificial neural network). For evaluation among the models, the area under the receiver operating characteristic curve, area under the precision-recall curve, calibration curve, and decision curve analysis were used.

RESULTS

Composite models had significantly higher area under the receiver operating characteristic curves than did simple models in predicting unfavorable functional outcomes. Compared with other composite models (random forest and extreme gradient boosting) with good calibration, LR had the highest area under the precision-recall score and showed the greatest benefit in decision curve analysis.

CONCLUSIONS

Of the 5 studied ML models, the conventional LR model outperformed the advanced algorithms in predicting the prognosis and could be a useful tool for health care professionals.

Predicting the Outcome of Patients with Aneurysmal Subarachnoid Hemorrhage: A Machine-Learning-Guided Scorecard

Aneurysmal subarachnoid hemorrhage (aSAH) frequently causes long-term disability, but predicting outcomes remains challenging. Routine parameters such as demographics, admission status, CT findings, and blood tests can be used to predict aSAH outcomes. The aim of this study was to compare the performance of traditional logistic regression with several machine learning algorithms using readily available indicators and to generate a practical prognostic scorecard based on machine learning. Eighteen routinely available indicators were collected as outcome predictors for individuals with aSAH. Logistic regression (LR), random forest (RF), support vector machines (SVMs), and fully connected neural networks (FCNNs) were compared. A scorecard system was established based on predictor weights. The results show that machine learning models and a scorecard achieved 0.75~0.8 area under the curve (AUC) predicting aSAH outcomes (LR 0.739, RF 0.749, SVM 0.762~0.793, scorecard 0.794). FCNNs performed best (~0.95) but lacked interpretability. The scorecard model used only five factors, generating a clinically useful tool with a total cutoff score of ≥5, indicating poor prognosis. We developed and validated machine learning models proven to predict outcomes more accurately in individuals with aSAH. The parameters found to be the most strongly predictive of outcomes were NLR, lymphocyte count, monocyte count, hypertension status, and SEBES. The scorecard system provides a simplified means of applying predictive analytics at the bedside using a few key indicators.

A visualized MAC nomogram online predicts the risk of three-month mortality in Chinese elderly aneurysmal subarachnoid hemorrhage patients undergoing endovascular coiling

OBJECTIVE

Aneurysmal subarachnoid hemorrhage (aSAH) is an aggressive disease with higher mortality rate in the elderly population. Unfortunately, the previous models for predicting clinical prognosis are still not accurate enough. Therefore, we aimed to construct and validate a visualized nomogram model to predict online the 3-month mortality in elderly aSAH patients undergoing endovascular coiling.

METHOD

We conducted a retrospective analysis of 209 elderly aSAH patients at People's Hospital of Hunan Province, China. A nomogram was developed based on multivariate logistic regression and forward stepwise regression analysis, then validated using the bootstrap validation method (n = 1000). In addition, the performance of the nomogram was evaluated by various indicators to prove its clinical value.

RESULT

Morbid pupillary reflex, age, and using a breathing machine were independent predictors of 3-month mortality. The AUC of the nomogram was 0.901 (95% CI: 0.853-0.950), and the Hosmer-Lemeshow goodness-of-fit test showed good calibration of the nomogram (p = 0.4328). Besides, the bootstrap validation method internally validated the nomogram with an area under the curve of the receiver operator characteristic (AUROC) of 0.896 (95% CI: 0.846-0.945). Decision curve analysis (DCA) and clinical impact curve (CIC) indicated the nomogram's excellent clinical utility and applicability.

CONCLUSION

An easily applied visualized nomogram model named MAC (morbid pupillary reflex-age-breathing machine) based on three accessible factors has been successfully developed. The MAC nomogram is an accurate and complementary tool to support individualized decision-making and emphasizes that patients with higher risk of mortality may require closer monitoring. Furthermore, a web-based online version of the risk calculator would greatly contribute to the spread of the model in this field.

Additive prognostic impact of the cerebrospinal fluid arginine/ornithine ratio to established clinical scores in aneurysmal subarachnoid hemorrhage

Cerebrospinal fluid (CSF) metabolites are increasingly recognized as prognostic factors in aneurysmal subarachnoid hemorrhage (SAH). The CSF arginine/ornithine ratio (Arg/Orn) was shown to predict cerebral vasospasms and clinical outcome in SAH. The additive prognostic value of Arg/Orn over established prognostic scores has not been investigated. CSF Arg/Orn and the established prognostic scores SAH, FRESH, SAH-PDS, HAIR, Rosen-McDonald, Hunt and Hess, WFNS and modified Fisher scale were determined in a prospective cohort of patients with aneurysmal SAH. Logistic regression models to predict a favorable outcome, defined as a modified Rankin Scale score of 0-3 at 3  months follow-up, were constructed for each score, both with and without the addition of Arg/Orn. The impact of Arg/Orn was assessed comparing logistic regression models containing the respective score with and without Arg/Orn with the likelihood ratio chi-squared test. CSF Arg/Orn and clinical scores were determined in 38 SAH patients. Arg/Orn was an independent predictor of clinical outcome when added to established prognostic scores (p < 0.05) with the exception of HAIR (p = 0.078). All models were significantly improved if Arg/Orn was added as a covariable (p < 0.05). The results of this study confirm Arg/Orn as an independent prognostic factor and its addition improves established prognostic models in SAH.

Activated protein C overexpression suppresses the pyroptosis of subarachnoid hemorrhage model cells by regulating the NLRP3 inflammasome pathway

Subarachnoid hemorrhage (SAH) is a condition with a high associated mortality rate that is caused by hemorrhagic stroke. Activated protein C (APC) serves a neuroprotective role in central nervous system diseases. However, its role in SAH remains unclear. The present study aimed to investigate the role of APC and its regulatory mechanism in SAH. The SAH rat model was constructed through internal carotid artery puncture, while the SAH cell model was established via the application of oxygenated hemoglobin. ELISA was performed to detect the level of cytokines, and flow cytometry was used to determine the population of pyroptotic cells. Reverse transcription-quantitative PCR and western blotting were used to examine the relative mRNA and protein levels of APC. APC was silenced using specific APC short hairpin RNA. Neurological functions of rats were estimated using modified Garcia scoring and the balance beam test, while SAH was estimated using modified Sugawara's scoring. The results demonstrated that the expression of APC was significantly decreased, whereas the expression of NLR family pyrin domain-containing 3 (NLRP3) was increased in the SAH rat model in a time-dependent manner. The application of APC recombinant protein 3K3A-APC could significantly ameliorate SAH and improve neurological functions. In addition, 3K3A-APC could inhibit pyroptosis in a dose-dependent manner in the SAH cell model. Moreover, the NLRP3 inhibitor BAY11-7082 could reverse the upregulation of pyroptosis induced by APC-knockdown. Overall, the present study revealed that APC could ameliorate SAH-induced early brain injury by suppressing pyroptosis via inhibition of the NLRP3 inflammasome, which could provide a novel strategy for the treatment of SAH.

Comorbidities and Medical Complications in Hospitalized Subarachnoid Hemorrhage Patients

BACKGROUND

Aneurysmal subarachnoid hemorrhage (SAH) remains a devastating condition with a case fatality of 36% at 30 days. Risk factors for mortality in SAH patients include patient demographics and the severity of the neurological injury. Pre-existing conditions and non-neurological medical complications occurring during the index hospitalization are also risk factors for mortality in SAH. The magnitude of the effect on mortality of pre-existing conditions and medical complications, however, is less well understood. In this study, we aim to determine the effect of pre-existing conditions and medical complications on SAH mortality.

METHODS

For a 25% random sample of the Greater Montreal Region, we used discharge abstracts, physician billings, and death certificate records, to identify adult patients with a new diagnosis of non-traumatic SAH who underwent cerebral angiography or surgical clipping of an aneurysm between 1997 and 2014.

RESULTS

The one-year mortality rate was 14.76% (94/637). Having ≥3 pre-existing conditions was associated with increased one-year mortality OR 3.74, 95% CI [1.25, 9.57]. Having 2, or ≥3 medical complications was associated with increased one-year mortality OR, 2.42 [95% CI 1.25-4.69] and OR, 2.69 [95% CI 1.43-5.07], respectively. Sepsis, respiratory failure, and cardiac arrhythmias were associated with increased one-year mortality. Having 1, 2, or ≥3 pre-existing conditions was associated with increased odds of having medical complications in hospital.

CONCLUSIONS

Pre-existing conditions and in-hospital non-neurological medical complications are associated with increased one-year mortality in SAH. Pre-existing conditions are associated with increased medical complications.

Nitric Oxide-Based Treatment of Poor-Grade Patients After Severe Aneurysmal Subarachnoid Hemorrhage

Background

Patients with aneurysmal subarachnoid hemorrhage (aSAH) require close treatment in neuro intensive care units (NICUs). The treatments available to counteract secondary deterioration and delayed ischemic events remain restricted; moreover, available neuro-monitoring of comatose patients is undependable. In comatose patients, clinical signs are hidden, and timing interventions to prevent the evolution of a perfusion disorder in response to fixed ischemic brain damage remain a challenge for NICU teams. Consequently, comatose patients often suffer secondary brain infarctions. The outcomes for long-term intubated patients w/wo pupil dilatation are the worst, with only 10% surviving. We previously added two nitroxide (NO) donors to the standard treatment: continuous intravenous administration of Molsidomine in patients with mild-to-moderate aSAH and, if required as a supplement, intraventricular boluses of sodium nitroprusside (SNP) in high-risk patients to overcome the so-called NO-sink effect, which leads to vasospasm and perfusion disorders. NO boluses were guided by clinical status and promptly reversed recurrent episodes of delayed ischemic neurological deficit. In this study, we tried to translate this concept, the initiation of intraventricular NO application on top of continuous Molsidomine infusion, from awake to comatose patients who lack neurological–clinical monitoring but are primarily monitored using frequently applied transcranial Doppler (TCD).

Methods

In this observational, retrospective, nonrandomized feasibility study, 18 consecutive aSAH comatose/intubated patients (Hunt and Hess IV/V with/without pupil dilatation) whose poor clinical status precluded clinical monitoring received standard neuro-intensive care, frequent TCD monitoring, continuous intravenous Molsidomine plus intraventricular SNP boluses after TCD-confirmed macrospasm during the daytime and on a fixed nighttime schedule.

Results

Very likely associated with the application of SNP, which is a matter of further investigation, vasospasm-related TCD findings promptly and reliably reversed or substantially weakened (p < 0.0001) afterward. Delayed cerebral ischemia (DCI) occurred only during loose, low-dose or interrupted treatment (17% vs. an estimated 65% with secondary infarctions) in 17 responders. However, despite their worse initial condition, 29.4% of the responders survived (expected 10%) and four achieved Glasgow Outcome Scale Extended (GOSE) 8–6, modified Rankin Scale (mRS) 0–1 or National Institutes of Health Stroke Scale (NIHSS) 0–2.

Conclusions

Even in comatose/intubated patients, TCD-guided dual-compartment administration of NO donors probably could reverse macrospasm and seems to be feasible. The number of DCI was much lower than expected in this specific subgroup, indicating that this treatment possibly provides a positive impact on outcomes. A randomized trial should verify or falsify our results.

Development of a Complication- and Treatment-Aware Prediction Model for Favorable Functional Outcome in Aneurysmal Subarachnoid Hemorrhage Based on Machine Learning

BACKGROUND

Current prognostic tools in aneurysmal subarachnoid hemorrhage (aSAH) are constrained by being primarily based on patient and disease characteristics on admission.

OBJECTIVE

To develop and validate a complication- and treatment-aware outcome prediction tool in aSAH.

METHODS

This cohort study included data from an ongoing prospective nationwide multicenter registry on all aSAH patients in Switzerland (Swiss SOS [Swiss Study on aSAH]; 2009-2015). We trained supervised machine learning algorithms to predict a binary outcome at discharge (modified Rankin scale [mRS] ≤ 3: favorable; mRS 4-6: unfavorable). Clinical and radiological variables on admission ("Early" Model) as well as additional variables regarding secondary complications and disease management ("Late" Model) were used. Performance of both models was assessed by classification performance metrics on an out-of-sample test dataset.

RESULTS

Favorable functional outcome at discharge was observed in 1156 (62.0%) of 1866 patients. Both models scored a high accuracy of 75% to 76% on the test set. The "Late" outcome model outperformed the "Early" model with an area under the receiver operator characteristics curve (AUC) of 0.85 vs 0.79, corresponding to a specificity of 0.81 vs 0.70 and a sensitivity of 0.71 vs 0.79, respectively.

CONCLUSION

Both machine learning models show good discrimination and calibration confirmed on application to an internal test dataset of patients with a wide range of disease severity treated in different institutions within a nationwide registry. Our study indicates that the inclusion of variables reflecting the clinical course of the patient may lead to outcome predictions with superior predictive power compared to a model based on admission data only.

Monocyte-based inflammatory indices predict outcomes following aneurysmal subarachnoid hemorrhage

The contribution of specific immune cell populations to the post-hemorrhagic inflammatory response in aneurysmal subarachnoid hemorrhage (aSAH) and correlations with clinical outcomes, such as vasospasm and functional status, remains unclear. We aimed to compare the predictive value of leukocyte ratios that include monocytes as compared to the neutrophil-to-lymphocyte ratio (NLR) in aSAH. A prospectively accrued database of consecutive patients presenting to our institution with aSAH between January 2013 and December 2018 was used. Patients with signs and symptoms of infection (day 1-3) were excluded. Admission values of the NLR, monocyte-neutrophil-to-lymphocyte ratio (M-NLR), and lymphocyte-to-monocyte ratio (LMR) were calculated. Associations with functional status, the primary outcome, and vasospasm were evaluated using univariable and multivariable logistic regression analyses. In the cohort of 234 patients with aSAH, the M-NLR and LMR, but not the NLR, were significantly associated with poor functional status (modified Rankin scale > 2) at 12-18 months following discharge (p = 0.001, p = 0.023, p = 0.161, respectively). The area under the curve for predicting poor functional status was significantly lower for the NLR (0.543) compared with the M-NLR (0.603, p = 0.024) and LMR (0.608, p = 0.040). The M-NLR (OR = 1.01 [1.01-1.02]) and LMR (OR = 0.88 [0.78-0.99]) were independently associated with poor functional status while controlling for age, hypertension, Fisher grade, and baseline clinical status. The LMR was significantly associated with vasospasm (OR = 0.84 [0.70-0.99]) while adjusting for age, hypertension, Fisher grade, aneurysm size, and current smoking. Inflammatory indices that incorporate monocytes (e.g., M-NLR and LMR), but not those that include only neutrophils, predict outcomes after aSAH.

Validation and Optimization of Barrow Neurological Institute Score in Prediction of Adverse Events and Functional Outcome After Subarachnoid Hemorrhage-Creation of the HATCH (Hemorrhage, Age, Treatment, Clinical State, Hydrocephalus) Score

BACKGROUND

The Barrow Neurological Institute (BNI) score, measuring maximal thickness of aneurysmal subarachnoid hemorrhage (aSAH), has previously shown to predict symptomatic cerebral vasospasms (CVSs), delayed cerebral ischemia (DCI), and functional outcome.

OBJECTIVE

To validate the BNI score for prediction of above-mentioned variables and cerebral infarct and evaluate its improvement by integrating further variables which are available within the first 24 h after hemorrhage.

METHODS

We included patients from a single center. The BNI score for prediction of CVS, DCI, infarct, and functional outcome was validated in our cohort using measurements of calibration and discrimination (area under the curve [AUC]). We improved it by adding additional variables, creating a novel risk score (measure by the dichotomized Glasgow Outcome Scale) and validated it in a small independent cohort.

RESULTS

Of 646 patients, 41.5% developed symptomatic CVS, 22.9% DCI, 23.5% cerebral infarct, and 29% had an unfavorable outcome. The BNI score was associated with all outcome measurements. We improved functional outcome prediction accuracy by including age, BNI score, World Federation of Neurologic Surgeons, rebleeding, clipping, and hydrocephalus (AUC 0.84, 95% CI 0.8-0.87). Based on this model we created a risk score (HATCH-Hemorrhage, Age, Treatment, Clinical State, Hydrocephalus), ranging 0 to 13 points. We validated it in a small independent cohort. The validated score demonstrated very good discriminative ability (AUC 0.84 [95% CI 0.72-0.96]).

CONCLUSION

We developed the HATCH score, which is a moderate predictor of DCI, but excellent predictor of functional outcome at 1 yr after aSAH.

Machine Learning to Predict Delayed Cerebral Ischemia and Outcomes in Subarachnoid Hemorrhage

OBJECTIVE

To determine whether machine learning (ML) algorithms can improve the prediction of delayed cerebral ischemia (DCI) and functional outcomes after subarachnoid hemorrhage (SAH).

METHODS

ML models and standard models (SMs) were trained to predict DCI and functional outcomes with data collected within 3 days of admission. Functional outcomes at discharge and at 3 months were quantified using the modified Rankin Scale (mRS) for neurologic disability (dichotomized as good [mRS ≤ 3] vs poor [mRS ≥ 4] outcomes). Concurrently, clinicians prospectively prognosticated 3-month outcomes of patients. The performance of ML, SMs, and clinicians were retrospectively compared.

RESULTS

DCI status, discharge, and 3-month outcomes were available for 399, 393, and 240 participants, respectively. Prospective clinician (an attending, a fellow, and a nurse) prognostication of 3-month outcomes was available for 90 participants. ML models yielded predictions with the following area under the receiver operating characteristic curve (AUC) scores: 0.75 ± 0.07 (95% confidence interval [CI] 0.64-0.84) for DCI, 0.85 ± 0.05 (95% CI 0.75-0.92) for discharge outcome, and 0.89 ± 0.03 (95% CI 0.81-0.94) for 3-month outcome. ML outperformed SMs, improving AUC by 0.20 (95% CI -0.02 to 0.4) for DCI, by 0.07 ± 0.03 (95% CI -0.0018 to 0.14) for discharge outcomes, and by 0.14 (95% CI 0.03-0.24) for 3-month outcomes and matched physician's performance in predicting 3-month outcomes.

CONCLUSION

ML models significantly outperform SMs in predicting DCI and functional outcomes and has the potential to improve SAH management.

Unfavorable Outcome After Good Grade Aneurysmal Subarachnoid Hemorrhage: Exploratory Analysis

OBJECTIVE

Patients with good-grade aneurysmal subarachnoid hemorrhage (aSAH) are thought to recover well, yet some do not. This work sought to identify predictors of unfavorable functional outcome after good-grade aSAH.

METHODS

We performed a post-hoc analysis of the CONSCIOUS-1 trial. Patients with World Federation of Neurosurgical Societies grades I or II aSAH were included. The primary outcome was unfavorable functional outcome (defined as a modified Rankin Scale score >2) at 12 weeks. Parametric and nonparametric testing were used as appropriate. Variables were classified as modifiable or nonmodifiable, depending on whether they were present at patient admission. Stepwise logistic regression models were created for modifiable and nonmodifiable predictors of outcome. Independent predictors in the respective multivariate analyses were combined into a final multivariate regression model.

RESULTS

We included 301 patients, 67 of whom (22%) had an unfavorable outcome. Of the nonmodifiable predictors, higher admission systolic blood pressure (P = 0.002) and female sex (P = 0.011) were independently associated with unfavorable outcome. Potentially modifiable independent predictors of outcome were delayed cerebral ischemia (P = 0.039), higher maximum temperature (0.036), suffering a respiratory system complication (P = 0.004), and suffering an intracranial hemorrhagic complication (P = 0.022). All variables found to be independently predictive of poor outcome in their respective models retained statistical significance in the combined multivariate analysis.

CONCLUSIONS

About 1 in 5 good-grade aSAH patients enrolled in CONSCIOUS-1 suffered an unfavorable functional outcome. Admission systolic blood pressure, female sex, hyperthermia, delayed cerebral ischemia, respiratory complications, and intracranial hemorrhagic complications may be predictive of outcome.

Multimorbidity and Critical Care Neurosurgery: Minimizing Major Perioperative Cardiopulmonary Complications

With increasing prevalence of chronic diseases, multimorbid patients have become commonplace in the neurosurgical intensive care unit (neuro-ICU), offering unique management challenges. By reducing physiological reserve and interacting with one another, chronic comorbidities pose a greatly enhanced risk of major postoperative medical complications, especially cardiopulmonary complications, which ultimately exert a negative impact on neurosurgical outcomes. These premises underscore the importance of perioperative optimization, in turn requiring a thorough preoperative risk stratification, a basic understanding of a multimorbid patient’s deranged physiology and a proper appreciation of the potential of surgery, anesthesia and neurocritical care interventions to exacerbate comorbid pathophysiologies. This knowledge enables neurosurgeons, neuroanesthesiologists and neurointensivists to function with a heightened level of vigilance in the care of these high-risk patients and can inform the perioperative neuro-ICU management with individualized strategies able to minimize the risk of untoward outcomes. This review highlights potential pitfalls in the intra- and postoperative neuro-ICU period, describes common preoperative risk stratification tools and discusses tailored perioperative ICU management strategies in multimorbid neurosurgical patients, with a special focus on approaches geared toward the minimization of postoperative cardiopulmonary complications and unplanned reintubation.

Gap Analysis Regarding Prognostication in Neurocritical Care: A Joint Statement from the German Neurocritical Care Society and the Neurocritical Care Society

Background/Objective

Prognostication is a routine part of the delivery of neurocritical care for most patients with acute neurocritical illnesses. Numerous prognostic models exist for many different conditions. However, there are concerns about significant gaps in knowledge regarding optimal methods of prognostication.

Methods

As part of the Arbeitstagung NeuroIntensivMedizin meeting in February 2018 in Würzburg, Germany, a joint session on prognostication was held between the German NeuroIntensive Care Society and the Neurocritical Care Society. The purpose of this session was to provide presentations and open discussion regarding existing prognostic models for eight common neurocritical care conditions (aneurysmal subarachnoid hemorrhage, intracerebral hemorrhage, acute ischemic stroke, traumatic brain injury, traumatic spinal cord injury, status epilepticus, Guillain–Barré Syndrome, and global cerebral ischemia from cardiac arrest). The goal was to develop a qualitative gap analysis regarding prognostication that could help inform a future framework for clinical studies and guidelines.

Results

Prognostic models exist for all of the conditions presented. However, there are significant gaps in prognostication in each condition. Furthermore, several themes emerged that crossed across several or all diseases presented. Specifically, the self-fulfilling prophecy, lack of accounting for medical comorbidities, and absence of integration of in-hospital care parameters were identified as major gaps in most prognostic models.

Conclusions

Prognostication in neurocritical care is important, and current prognostic models are limited. This gap analysis provides a summary assessment of issues that could be addressed in future studies and evidence-based guidelines in order to improve the process of prognostication.

Comparison of aneurysmal subarachnoid hemorrhage grading scores in patients with aneurysm clipping and coiling

Past studies revealed the prognosis differed between aneurysmal subarachnoid hemorrhage (aSAH) patients with surgical clipping and endovascular coiling. We retrospectively reviewed aSAH patients in our institution to investigate the effectiveness of grading scores between two groups. In the surgical clipping group (n = 349), VASOGRADE had a favorable performance for predicting delayed cerebral ischemia (DCI) (area under curve (AUC) > 0.750), and had better results than clinical (World Federation of Neurosurgical Societies (WFNS), Hunt & Hess (HH) and radiological scores (modified Fisher Scale (mFS), Subarachnoid Hemorrhage Early Brain Edema Score) (P < 0.05). Clinical and combined scores (VASOGRADE, HAIR) had favorable performance for predicting poor outcome (AUC > 0.750), and had better results than radiological scores (P < 0.05). In the coiling group (n = 320), none of the grading scores demonstrated favorable predictive accuracy for DCI (AUC < 0.750). Only WFNS and VASOGRADE had AUC > 0.700, with better performance than mFS (P < 0.05). The clinical and combined scores showed favorable performance for predicting a poor outcome (AUC > 0.750), and were better than the radiological scores (P < 0.05). Radiological scores appeared inferior to the clinical and combined scores in clipping and coiling groups. VASOGRADE can be an effective grading score in patients with clipping or coiling for predicting DCI and poor outcome.

Initial pupil status is a strong predictor for in-hospital mortality after aneurysmal subarachnoid hemorrhage

Prognosis of patients with high-grade aneurysmal subarachnoid hemorrhage (aSAH) is only insufficiently displayed by current standard prognostic scores. This study aims to evaluate the role of pupil status for mortality prediction and provide improved prognostic models. Anonymized data of 477 aSAH patients admitted to our medical center from November 2010 to August 2018 were retrospectively analyzed. Identification of variables independently predicting in-hospital mortality was performed by multivariable logistic regression analysis. Final regression models included Hunt & Hess scale (H&H), pupil status and age or in a simplified variation only H&H and pupil status, leading to the design of novel H&H-Pupil-Age score (HHPA) and simplified H&H-Pupil score (sHHP), respectively. In an external validation cohort of 402 patients, areas under the receiver operating characteristic curves (AUROC) of HHPA (0.841) and sHHP (0.821) were significantly higher than areas of H&H (0.794; p < 0.001) or World Federation of Neurosurgical Societies (WFNS) scale (0.775; p < 0.01). Accordingly, including information about pupil status improves the predictive performance of prognostic scores for in-hospital mortality in patients with aSAH. HHPA and sHHP allow simple, early and detailed prognosis assessment while predictive performance remained strong in an external validation cohort suggesting adequate generalizability and low interrater variability.

Validation and Comparison of Aneurysmal Subarachnoid Hemorrhage Grading Scales in Angiogram-Negative Subarachnoid Hemorrhage Patients

Numerous grading scales have been proposed to predict the outcome of aneurysmal subarachnoid hemorrhage (SAH); however, these have not been validated in angiogram-negative SAH patients. In this study, we aim to validate and compare the aneurysmal SAH grading scales in angiogram-negative SAH patients. There were 190 angiogram-negative SAH patients analyzed from January 2014 to December 2015. The outcomes were measured by delayed cerebral ischemia (DCI) and poor outcome (defined as modified Rankin Scale (mRS) 3-6 or 4-6). The predictive performance of the grading scales was assessed via evaluation of distribution, trend, association, and discrimination. In regard to the distribution, none of the patients were categorized as HAIR 8 and SAH score 8. Both grading scales indicated a significant trend between scores and outcome (P < 0.05), and association with the outcome (OR > 1). The modified Fisher Scale (mFS), World Federation of Neurosurgical Societies scale (WFNS), and combined scores VASOGRADE and HAIR showed good predictive accuracy (area under the curve (AUC) > 0.750) for DCI. The predictive accuracy in each scale performed well in predicting poor outcome, with the exception of mFS and the Subarachnoid hemorrhage Early Brain Edema Score (SEBES). However, the mFS performed with increased accuracy when predicting mRS 4-6. The VASOGRADE, HAIR, and WFNS may be valuable prognostic tools for predicting both DCI and poor outcome. The mFS can be applicable for predicting DCI and mRS 4-6. The SAH score and the Hunt-Hess were also optimal for predicting poor outcome. The predictive performance of SEBES was relatively poor compared to the other scales.

Warning headache correlates survival rate in aneurysmal subarachnoid hemorrhage

Background

Severe headaches, projectile vomiting, focal neurological deficits and early onset seizure are regarded as early warning symptoms of subarachnoid hemorrhage (SAH). Earlier diagnosis based on such warning symptoms theoretically would improve the clinical prognosis. However, it is still not clear whether the prognosis is correlated with early warning symptoms. Here, we reviewed warning symptoms and other predictive factors in the emergency room (ER) setting and examined their correlations with mortality.

Methods

Ninety saccular aneurysmal SAH cases were reviewed in a single medical center between January 2011 and December 2013. We examined differences in mortality rate related to warning symptoms, SAH scales, onset-to-ER time, hydrocephalus, and aneurysm size, location, and complexity. Logistic regression analyses were performed to determine the correlations of warning symptoms and other predictive factors with mortality. Receiver operating characteristic (ROC) curve analysis was used to calculate the area the under curve (AUC) of SAH mortality prediction tools.

Results

Warning headache, projectile vomiting, the Hunt and Hess scale, Fisher scale, World Federation of Neurological Surgeons (WFNS) grading scale, and modified WFNS (m-WFNS) scale, body mass index, aneurysm complexity and hydrocephalus were significantly different between the survivors and the decedents. The warning headache and WFNS grade were strongly correlated with mortality. The rate of prognostic prediction improved from 90.4% to 94.6% when warning headache was additionally evaluated.

Conclusions

With growing healthcare costs and recognition of the value of palliative care, early identification via warning headache and a detailed clinical history review is necessary for cases of aSAH.

Development and external validation of new nomograms by adding ECG changes (ST depression or tall T wave) and age to conventional scoring systems to improve the predictive capacity in patients with subarachnoid haemorrhage: a retrospective, observational study in Korea

OBJECTIVES

To develop new nomograms by adding ECG changes (ST depression or tall T wave) and age to three conventional scoring systems, namely, World Federation of Neurosurgical Societies (WFNS) scale, Hunt and Hess (HH) system and Fisher scale, that can predict prognosis in patients with subarachnoid haemorrhage (SAH) using our preliminary research results and to perform external validation of the three new nomograms.

DESIGN

Retrospective, observational study SETTING: Emergency departments (ED) of two university-affiliated tertiary hospital between January 2009 and March 2015.

PARTICIPANTS

Adult patients with SAH were enrolled. Exclusion criteria were age <19 years, no baseline ECG, cardiac arrest on arrival, traumatic SAH, referral from other hospital and referral to other hospitals from the ED.

PRIMARY OUTCOME MEASURES

The 6 month prognosis was assessed using the Glasgow Outcome Scale (GOS). We defined a poor outcome as a GOS score of 1, 2 or 3.

RESULTS

A total of 202 patients were included for analysis. From the preliminary study, age, ECG changes (ST depression or tall T wave), and three conventional scoring systems were selected to predict prognosis in patients with SAH using multi-variable logistic regression. We developed simplified nomograms using these variables. Discrimination of the developed nomograms including WFNS scale, HH system and Fisher scale was superior to those of WFNS scale, HH system and Fisher scale (0.912 vs 0.813; p<0.001, 0.913 vs 0.826; p<0.001, and 0.885 vs 0.746; p<0.001, respectively). The calibration plots showed excellent agreement. In the external validation, the discrimination of the newly developed nomograms incorporating the three scoring systems was also good, with an area under the receiver-operating characteristic curve value of 0.809, 0.812 and 0.772, respectively.

CONCLUSIONS

We developed and externally validated new nomograms using only three independent variables. Our new nomograms were superior to the WFNS scale, HH systems, and Fisher scale in predicting prognosis and are readily available.

Factors associated with clinical and radiological status on admission in patients with aneurysmal subarachnoid hemorrhage

Grading scales yield objective measure of the severity of aneurysmal subarachnoid hemorrhage and serve as to guide treatment decisions and for prognostication. The purpose of this cohort study was to determine what factors govern a patient's disease-specific admission scores in a representative Central European cohort. The Swiss Study of Subarachnoid Hemorrhage includes anonymized data from all tertiary referral centers serving subarachnoid hemorrhage patients in Switzerland. The 2009-2014 dataset was used to evaluate the impact of patient and aneurysm characteristics on the patients' status at admission using descriptive and multivariate regression analysis. The primary/co-primary endpoints were the GCS and the WFNS grade. The secondary endpoints were the Fisher grade, the presence of a thick cisternal or ventricular clot, the presence of a new focal neurological deficit or cranial nerve palsy, and the patient's intubation status. In our cohort of 1787 consecutive patients, increasing patient age by 10 years and low pre-ictal functional status (mRS 3-5) were inversely correlated with "high" GCS score (GCS ≥ 13) (OR 0.91, 95% CI 0.84-0.97 and OR 0.67, 95% CI 0.31-1.46), "low" WFNS grade (grade VI-V) (OR 1.21, 95% CI 1.04-1.20 and OR 1.47, 95% CI 0.66-3.27), and high Fisher grade (grade III-IV) (OR 1.08, 95% CI 1.00-1.17 and OR 1.54, 95% CI 0.55-4.32). Other independent predictors for the patients' clinical and radiological condition at admission were the ruptured aneurysms' location and its size. In sum, chronological age and pre-ictal functional status, as well as the ruptured aneurysm's location and size, determine the patients' clinical and radiological condition at admission to the tertiary referral hospital.

Prognostication of long-term outcomes after subarachnoid hemorrhage: The FRESH score

OBJECTIVE

To create a multidimensional tool to prognosticate long-term functional, cognitive, and quality of life outcomes after spontaneous subarachnoid hemorrhage (SAH) using data up to 48 hours after admission.

METHODS

Data were prospectively collected for 1,619 consecutive patients enrolled in the SAH outcome project July 1996 to March 2014. Linear models (LMs) were applied to identify factors associated with outcome in 1,526 patients with complete data. Twelve-month functional, cognitive, and quality of life outcomes were measured using the modified Rankin scale (mRS), Telephone Interview for Cognitive Status, and Sickness Impact Profile. Based on the LM residuals, we constructed the FRESH score (Functional Recovery Expected after Subarachnoid Hemorrhage). Score performance, discrimination, and internal validity were tested using the area under the receiver operating characteristic curve (AUC), Nagelkerke and Cox/Snell R(2) , and bootstrapping. For external validation, we used a control population of SAH patients from the CONSCIOUS-1 study (n = 413).

RESULTS

The FRESH score was composed of Hunt & Hess and APACHE-II physiologic scores on admission, age, and aneurysmal rebleed within 48 hours. Separate scores to prognosticate 1-year cognition (FRESH-cog) and quality of life (FRESH-quol) were developed controlling for education and premorbid disability. Poor functional outcome (mRS = 4-6) for score levels 1 through 9 respectively was present in 3, 6, 12, 38, 61, 83, 92, 98, and 100% at 1-year follow-up. Performance of FRESH (AUC = 0.90), FRESH-cog (AUC = 0.80), and FRESH-quol (AUC = 0.78) was high. External validation of our cohort using mRS as endpoint showed satisfactory results (AUC = 0.77). To allow for convenient score calculation, we built a smartphone app available for free download.

INTERPRETATION

FRESH is the first clinical tool to prognosticate long-term outcome after spontaneous SAH in a multidimensional manner. Ann Neurol 2016;80:46-58.

Ethnic disparities in end-of-life care after subarachnoid hemorrhage

BACKGROUND

It is common for patients who die from subarachnoid hemorrhage to have a focus on comfort measures at the end of life. The potential role of ethnicity in end-of-life decisions after brain injury has not been extensively studied.

METHODS

Patients with subarachnoid hemorrhage were prospectively followed in an observational database. Demographic information including ethnicity was collected from medical records and self-reported by patients or their family. Significant in-hospital events including do-not-resuscitate orders, comfort measures only orders (CMO; care withheld or withdrawn), and mortality were recorded prospectively.

RESULTS

1255 patients were included in our analysis: 650 (52 %) were White, 387 (31 %) Hispanic, and 218 (17 %) Black. Mortality was similar between the groups. CMO was more commonly observed in Whites (14 %) compared to either Blacks (10 %) or Hispanics (9 %) (p = 0.04). In a multivariate analysis controlling for age and Hunt-Hess grade, Hispanics were less likely to have CMO than Whites (OR, 0.6; 95 %CI, 0.4-0.9; p = 0.02). Of the 229 patients who died, 77 % of Whites had CMO compared to 54 % of Blacks and 49 % of Hispanics (p < 0.01). In a multivariate analysis, Blacks (OR, 0.3; 95 %CI, 0.2-0.7; p < 0.01) and Hispanics (OR, 0.3; 95 %CI, 0.2-0.6; p < 0.01) were less likely to die with CMO orders than Whites.

CONCLUSION

After subarachnoid hemorrhage, Blacks and Hispanics are less likely to die with CMO orders than Whites. Further research to confirm and investigate the causes of these ethnic differences should be performed.

Cocaine use as an independent predictor of seizures after aneurysmal subarachnoid hemorrhage

OBJECTIVE

Seizures are relatively common after aneurysmal subarachnoid hemorrhage (aSAH). Seizure prophylaxis is controversial and is often based on risk stratification; middle cerebral artery (MCA) aneurysms, associated intracerebral hemorrhage (ICH), poor neurological grade, increased clot thickness, and cerebral infarction are considered highest risk for seizures. The purpose of this study was to evaluate the impact of recent cocaine use on seizure incidence following aSAH.

METHODS

Prospectively collected data from aSAH patients admitted to 2 institutional neuroscience critical care units between 1991 and 2009 were reviewed. The authors analyzed factors that potentially affected the incidence of seizures, including patient demographic characteristics, poor clinical grade (Hunt and Hess Grade IV or V), medical comorbidities, associated ICH, intraventricular hemorrhage (IVH), hydrocephalus, aneurysm location, surgical clipping and cocaine use. They further studied the impact of these factors on "early" and "late" seizures (defined, respectively, as occurring before and after clipping/coiling).

RESULTS

Of 1134 aSAH patients studied, 182 (16%) had seizures; 81 patients (7.1%) had early and 127 (11.2%) late seizures, with 26 having both. The seizure rate was significantly higher in cocaine users (37 [26%] of 142 patients) than in non-cocaine users (151 [15.2%] of 992 patients, p = 0.001). Eighteen cocaine-positive patients (12.7%) had early seizures compared with 6.6% of cocaine-negative patients (p = 0.003); 27 cocaine users (19%) had late seizures compared with 10.5% non-cocaine users (p = 0.001). Factors that showed a significant association with increased risk for seizure (early or late) on univariate analysis included younger age (< 40 years) (p = 0.009), poor clinical grade (p = 0.029), associated ICH (p = 0.007), and MCA aneurysm location (p < 0.001); surgical clipping was associated with late seizures (p = 0.004). Following multivariate analysis, age < 40 years (OR 2.04, 95% CI 1.355-3.058, p = 0.001), poor clinical grade (OR 1.62, 95% CI 1.124-2.336, p = 0.01), ICH (OR 1.95, 95% CI 1.164-3.273, p = 0.011), MCA aneurysm location (OR 3.3, 95% CI 2.237-4.854, p < 0.001), and cocaine use (OR 2.06, 95% CI 1.330-3.175, p = 0.001) independently predicted seizures.

CONCLUSIONS

Cocaine use confers a higher seizure risk following aSAH and should be considered during risk stratification for seizure prophylaxis and close neuromonitoring.

Predictor's of Mortality in Patients with Aneurysmal Subarachnoid Haemorrhage and Reebleding

Methods. “Ameijeiras Brother's” and “Cmdt. Manuel Fajardo” Hospitals enrolled 64 patients (multicentre retrospective cohort) with aneurysmal subarachnoid haemorrhage and rebleeding. The patients were admitted to the Stroke Unit (SU) between January 1, 2006, and December 1, 2013. Demographic, clinical, and radiological variables were examined in logistic regression to evaluate independent factors for increasing the risk of death. Results. Patients with systolic blood pressure >160 mmHg (P = 0.02), serum glucose >7 mmol/L (P = 0.02), aneurysm location in artery communicant anterior (P = 0.03), and black/mixed race (P = 0.008) were significant related to death in univariate analysis. Risk factors (HTA, smoke, alcohol consumption, and DM), complication, multiplex rebleeding and stage of WFNS, and Fisher's scale were not related to mortality. Patients with three or more complications had a higher mortality rate (P = 0.002). The results of the multivariate logistic regression analysis indicated that race (black/mixed, P = 0.00, OR 4.62, and 95% IC 1.40–16.26), systolic blood pressure (>160 mmHg, P = 0.05, OR 2.54, and 95% IC 1.01–3.13), and serum glucose (>7.0 mmol/L, P = 0.05, OR 1.82, and 95% IC 1.27–2.67) were independent risk factors for death. Conclusions. The black/mixed race, SBP, and serum glucose were independent predictors of mortality. Three or more complications were associated with increasing the probability to death. Further investigation is necessary to validate these findings.

Impact of case volume on aneurysmal subarachnoid hemorrhage outcomes

PURPOSE

To compare aneurysmal subarachnoid hemorrhage (aSAH) outcomes between high- and low-volume referral centers with dedicated neurosciences critical care units (NCCUs) and shared neurosurgical, endovascular, and neurocritical care practitioners.

MATERIALS AND METHODS

Prospectively collected data of aSAH patients admitted to 2 institutional NCCUs were reviewed. NCCU A is a 22-bed unit staffed 24/7 with overnight in-house NCCU fellow and resident coverage. NCCU B is a 14-bed unit with home call by NCCU attending/fellow and in-house residents.

RESULTS

A total of 161 aSAH patients (27%) were admitted to NCCU B compared with 447 at NCCU A (73%). Among factors that independently impacted hospital mortality, there were no differences in baseline characteristics: mean age (A: 53.5 ± 14.1 years, B: 53.1 ± 13.6 years), poor grade Hunt and Hess (A: 28.2%, B: 26.7%), presence of multiple medical comorbidities (A: 28%, B: 31.1%), and associated cocaine use (A: 11.6%, B: 14.3%). There was no significant difference in hospital mortality (A: 17.9%, B: 18%), poor functional outcome (A: 30%, B: 25.4%), aneurysm rerupture (A: 2.8%, B: 2.4%), or delayed cerebral ischemia (A: 14.1%, B: 16.1%).

CONCLUSIONS

The noninferior outcomes at the lower SAH volume center suggests that provider expertise, not patient volume, is critical to providing high-quality specialized care.

Withdrawal of technological life support following subarachnoid hemorrhage

BACKGROUND

Prognostication of mortality or severe disability often prompts withdrawal of technological life support in patients following aneurysmal subarachnoid hemorrhage (aSAH). We assessed admission factors impacting decisions to withdraw treatment after aSAH.

METHODS

Prospectively collected data of aSAH patients admitted to our institution between 1991 and 2009 were reviewed. Patients given comfort care measures were identified, including early withdrawal of treatment (<72 h after admission). Independent predictors of treatment withdrawal were assessed with multivariable analysis.

RESULTS

The study included 1,134 patients, of whom 72 % were female, 58 % white, and 38 % black or African-American. Mean age was 52.5 ± 14.0 years. In-hospital mortality was 18.3 %. Of the 207 patients who died, treatment was withdrawn in 72 (35 %) and comfort measures instituted early in 31 (15 %). Among patients who died, WOLST was associated with older age (63.6 ± 14.2 years, WOLST vs. 55.6 ± 13.7 years, no WOLST, p < 0.001); GCS score <8 (62 % of WOLST vs. 44 % with no WOLST, p = 0.010); HH >3 (72 % of WOLST vs. 53 % with no WOLST, p = 0.008); and hydrocephalus (81 % of WOLST vs. 63 % with no WOLST, p = 0.009). Independent predictors of WOLST were poorer Hunt and Hess grade (AOR 1.520, 95 % CI 1.160-1.992, p = 0.002) and older age (AOR 1.045, 95 % CI 1.022-1.068, p < 0.001) with the latter also impacting early WOLST decisions.

CONCLUSIONS

Older age and poor clinical grade on presentation predicted WOLST, and age predicted decisions to withdraw treatment earlier following aSAH. While based on prognosis, and in some cases patient wishes, this may also constitute a self-fulfilling prophecy in others.

End-of-life decisions in patients with severe acute brain injury

Most in-hospital deaths of patients with stroke, traumatic brain injury, or postanoxic encephalopathy after cardiac arrest occur after a decision to withhold or withdraw life-sustaining treatments. Decisions on treatment restrictions in these patients are generally complex and are based only in part on evidence from published work. Prognostic models to be used in this decision-making process should have a strong discriminative power. However, for most causes of acute brain injury, prognostic models are not sufficiently accurate to serve as the sole basis of decisions to limit treatment. These decisions are also complicated because patients often do not have the capacity to communicate their preferences. Additionally, surrogate decision makers might not accurately represent the patient's preferences. Finally, in the acute stage, prediction of how a patient would adapt to a life with major disability is difficult.