Radiodensity of intraventricular hemorrhage associated with aneurysmal subarachnoid hemorrhage may be a negative predictor of outcome

Different cerebrospinal fluid drainage methods and chronic hydrocephalus in patients with aneurysmal subarachnoid hemorrhage

Background

Chronic hydrocephalus represents a common complication following aneurysmal subarachnoid hemorrhage (aSAH); however, the underlying mechanisms driving its pathogenesis remain incompletely understood. Furthermore, current evidence regarding optimal preventive strategies to mitigate hydrocephalus development remains controversial within the neurosurgical community.

Objective

To investigate the efficacy of distinct cerebrospinal fluid (CSF) drainage modalities in mitigating the risk of developing chronic hydrocephalus among patients with aneurysmal subarachnoid hemorrhage (aSAH) through a comparative effectiveness study design.

Method

The patients with aSAH treated in our hospital from January 2021 to January 2024 were analyzed retrospectively. Firstly, the related factors of chronic hydrocephalus in patients with subarachnoid hemorrhage were compared between patients with cerebrospinal fluid drainage and patients without cerebrospinal fluid drainage. Then, the related factors of hydrocephalus in patients with aneurysm subarachnoid hemorrhage with different cerebrospinal fluid drainage were compared. Univariate and multivariate logical regression analysis was used to determine the risk factors associated with chronic hydrocephalus.

Result

Of the 246 hospitalized patients with aSAH, whether or not to receive cerebrospinal fluid drainage was associated with the formation of chronic hydrocephalus. A total of 67 patients (27.2%) developed hydrocephalus, of which 47 patients (34.8%) received cerebrospinal fluid drainage, while 20 (18%) patients developed chronic hydrocephalus. Of all IVH patients who received cerebrospinal fluid drainage, 34 (25.2%) received intermittent lumbar puncture drainage, 75 (55.5%) received continuous drainage in the lumbar cistern, and 26 (19.3%) received extraventricular drainage. Univariate analysis showed that different drainage methods had significant differences in postoperative chronic hydrocephalus in patients with aneurysmal subarachnoid hemorrhage (Purge 0.009). Multivariate Logistic regression analysis showed that different ways of cerebrospinal fluid drainage were independent risk factors for chronic hydrocephalus in patients with aneurysmal subarachnoid hemorrhage.

Conclusion

Patients with aneurysmal subarachnoid hemorrhage must perform cerebrospinal fluid drainage. Among the three different drainage methods: lumbar puncture intermittent drainage, lumbar cistern continuous drainage, and extraventricular drainage, continuous lumbar cistern drainage is more effective in reducing the formation of chronic hydrocephalus.

Cerebrospinal fluid drainage and chronic hydrocephalus in aneurysmal subarachnoid hemorrhage patients with intraventricular hemorrhage

Background

Patients with intraventricular hemorrhage (IVH) are at a higher risk of developing hydrocephalus and often require external ventricular drainage or long-term ventriculoperitoneal shunt surgery.

Objective

To investigate whether cerebrospinal fluid drainage in patients with IVH due to aneurysmal subarachnoid hemorrhage (aSAH) reduces the incidence of chronic hydrocephalus.

Method

A retrospective analysis was conducted on patients with aSAH treated at our hospital between January 2020 and December 2022. The first analysis compared patients with and without IVH, while the second analysis compared IVH patients with and without chronic hydrocephalus. The third analysis compared IVH patients who underwent in different drainage methods which is lumbar drainage (LD) or external ventricular drainage (EVD). The primary outcome measure was the incidence of chronic hydrocephalus.

Result

Of the 296 patients hospitalized with aSAH, 108 (36.5%) had IVH, which was associated with a significantly higher incidence of chronic hydrocephalus compared to patients without IVH (49.1% vs. 16.5%, p < 0.001). Multivariate logistic regression analysis showed that IVH was independently associated with the formation of chronic hydrocephalus (OR: 3.530, 95% CI: 1.958-6.362, p < 0.001). Among the 108 IVH patients, 53 (49.1%) developed chronic hydrocephalus. Multivariate logistic regression analysis revealed that the Hunt Hess grade at admission (OR: 3.362, 95% CI: 1.146-9.863, p = 0.027) and postoperative cerebrospinal fluid drainage (OR: 0.110, 95% CI: 0.036-0.336, p < 0.001) were independent risk factors for the development of chronic hydrocephalus in IVH patients. Among all IVH patients who underwent cerebrospinal fluid drainage, 45 (75%) received continuous lumbar puncture drainage, and 15 (25%) received external ventricular drainage. Univariate analysis did not show a statistically significant difference between the two groups in terms of postoperative chronic hydrocephalus (p = 0.283). However, multivariate logistic regression analysis suggested that the drainage methods of LD and EVD might be associated with the development of chronic hydrocephalus.

Conclusion

The presence of IVH increases the risk of chronic hydrocephalus in patients with aSAH, and postoperative cerebrospinal fluid drainage appears to reduce this risk. The specific effects of lumbar puncture drainage and ventricular drainage on the incidence of chronic hydrocephalus require further investigation.

Insular cortex Hounsfield units predict postoperative neurocardiogenic injury in patients with aneurysmal subarachnoid hemorrhage

OBJECTIVE

Our study aims to investigate the association between the Hounsfield unit (Hu) value of the insular cortex (IC) during emergency admission and the subsequent occurrence of post-operative neurocardiogenic injury (NCI) among patients afflicted with aneurysmal subarachnoid hemorrhage (aSAH).

METHODS

Patients baseline characteristics were juxtaposed between those with and without NCI. The significant variables were incorporated into a multivariable stepwise logistic regression model. Receiver operating characteristic (ROC) curves were drafted for each significant variable, yielding cutoff values and the area under the curve (AUC). Subgroup and sensitivity analyses were performed to assess the predictive performance across various cohorts and ascertain result stability. Propensity score matching (PSM) was ultimately employed to redress any baseline characteristic disparities.

RESULTS

Patients displaying a right IC Hu value surpassing 28.65 exhibited an escalated risk of postoperative NCI upon confounder adjustment (p < 0.001). The ROC curve eloquently manifested the predictive capacity of right IC Hu in relation to NCI (AUC = 0.650, 95%CI, 0.591-0.709, p < 0.001). Further subgroup analysis revealed significant interactions between right IC Hu and factors such as age, history of heart disease, and Graeb 5-12 score. Sensitivity analysis further upheld the results' significant (p = 0.002). The discrepancy in NCI incidence between the two groups, both prior (p < 0.002) and post (p = 0.039) PSM, exhibited statistical significance. After PSM implementation, the likelihood of NCI displayed an ascending trend with increasing right IC Hu values, from the Hu1 cohort onward, receding post the Hu4 cohort.

CONCLUSION

This study definitively establishes an elevated right IC Hu value in the early stages of emergency admission as an autonomous predictor for ensuing NCI subsequent to aSAH.

Intraventricular hemorrhage clot clearance rate as an outcome predictor in patients with aneurysmal subarachnoid hemorrhage: A retrospective study

Background

The development of intraventricular hemorrhage (IVH) in aneurysmal subarachnoid hemorrhage (aSAH) is linked with higher mortality and poor neurological recovery. Previous studies have investigated the effect of the amount and distribution of the initial IVH on the prognosis of aSAH. However, no studies have assessed the relationship between the changes in IVH over time and the prognosis of aSAH. The aim of this study was to analyze the effect of the clearance rate of IVH, which can be represented by the IVH clot clearance rate (CCR), on the outcomes of aSAH.

Methods

The IVH CCR was calculated based on the difference between the initial and follow-up modified Graeb scores (mGS), which were assessed by initial and 7-day follow-up brain computed tomography, respectively. Poor functional outcome was defined as a modified Rankin Scale score of 3-6. Univariate and multivariable analyses were performed to assess the relationships between IVH CCR and other risk factors and the prognosis of patients. Receiver operating characteristic curve analysis was performed to identify cut-off values of IVH CCR for predicting poor functional outcome.

Results

In total, 196 consecutive patients were diagnosed with aSAH between January 2014 and March 2018. According to the inclusion and exclusion criteria, 67 patients were finally included in the study. The univariate analysis revealed that a lower IVH CCR (p<0.001), higher initial mGS (p<0.001), older age (p<0.001), higher initial Hunt and Hess grade (p<0.001), presence of delayed infarction (p=0.03), and presence of shunt-dependent hydrocephalus (p=0.004) were significantly related to poor functional outcome. The multivariable analysis revealed that IVH CCR (odds ratio [OR] 0.941; p=0.029), initial mGS (OR 1.632; p=0.043), age (OR 1.561; p=0.007), initial Hunt and Hess grade (OR 227.296; p=0.030), and delayed infarction (OR 5310.632; p=0.023) were independent predictors of poor functional outcome. Optimal cut-off values of IVH CCR and mGS for poor outcome were 36.27%, and 13.5, respectively (all p< 0.001).

Conclusions

The IVH CCR might have an important predictive value on poor functional outcome in patients with aSAH and IVH, along with initial mGS, age, initial Hunt and Hess grade, and delayed infarction.

Head CT: Toward Making Full Use of the Information the X-Rays Give

Although clinical head CT images are typically interpreted qualitatively, automated methods applied to routine clinical head CTs enable quantitative assessment of brain volume, brain parenchymal fraction, brain radiodensity, and brain radiomass. These metrics gain clinical meaning when viewed relative to a reference database and expressed as quantile regression values. Quantitative imaging data can aid in objective reporting and in the identification of outliers, with possible diagnostic implications. The comparison to a reference database necessitates standardization of head CT imaging parameters and protocols. Future research is needed to learn the effects of virtual monochromatic imaging on the quantitative characteristics of head CT images.

Predicting intraventricular hemorrhage growth with a machine learning-based, radiomics-clinical model

We constructed a radiomics-clinical model to predict intraventricular hemorrhage (IVH) growth after spontaneous intracerebral hematoma. The model was developed using a training cohort (N=626) and validated with an independent testing cohort (N=270). Radiomics features and clinical predictors were selected using the least absolute shrinkage and selection operator (LASSO) method and multivariate analysis. The radiomics score (Rad-score) was calculated through linear combination of selected features multiplied by their respective LASSO coefficients. The support vector machine (SVM) method was used to construct the model. IVH growth was experienced by 13.4% and 13.7% of patients in the training and testing cohorts, respectively. The Rad-score was associated with severe IVH and poor outcome. Independent predictors of IVH growth included hypercholesterolemia (odds ratio [OR], 0.12 [95%CI, 0.02-0.90]; p=0.039), baseline Graeb score (OR, 1.26 [95%CI, 1.16-1.36]; p<0.001), time to initial CT (OR, 0.70 [95%CI, 0.58-0.86]; p<0.001), international normalized ratio (OR, 4.27 [95%CI, 1.40, 13.0]; p=0.011), and Rad-score (OR, 2.3 [95%CI, 1.6-3.3]; p<0.001). In the training cohort, the model achieved an AUC of 0.78, sensitivity of 0.83, and specificity of 0.66. In the testing cohort, AUC, sensitivity, and specificity were 0.71, 0.81, and 0.64, respectively. This radiomics-clinical model thus has the potential to predict IVH growth.

Scoring Model to Predict Functional Outcome in Poor-Grade Aneurysmal Subarachnoid Hemorrhage

Background: Patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH), defined as World Federation of Neurosurgical Societies (WFNS) grades IV–V have high rates of disability and mortality. The objective of this study was to accurately prognosticate the outcomes of patients with poor-grade aSAH by developing a new scoring model.

Methods: A total of 147 poor-grade aSAH patients in our center were enrolled. Risk variables identified by multivariate logistic regression analysis were used to devise a scoring model (total score, 0–9 points). The scores were estimated on the basis of β coefficients. A cohort of 68 patients from another institute was used to validate the model.

Results: Multivariate logistic regression analysis revealed that modified Fisher grade >2 [odds ratio [OR], 2.972; P = 0.034], age ≥65 years (OR, 3.534; P = 0.006), conservative treatment (OR, 5.078; P = 0.019), WFNS grade V (OR, 2.638; P = 0.029), delayed cerebral ischemia (OR, 3.170; P = 0.016), shunt-dependent hydrocephalus (OR, 3.202; P = 0.032), and cerebral herniation (OR, 7.337; P < 0.001) were significant predictors for poor prognosis [modified Rankin Scale [mRS] ≥3]. A scoring system was constructed by the integration of these factors and divided the poor-grade aSAH patients into three categories: low risk (0–1 points), intermediate risk (2–3 points), and high risk (4–9 points), with predicted risks of poor prognosis of 11, 52, and 87%, respectively (P < 0.001). The area under the curve in the derivation cohort was 0.844 (95% CI, 0.778–0.909). The AUC in the validation cohort was 0.831 (95% CI, 0.732–0.929).

Conclusions: The new scoring model can improve prognostication and help decision-making for subsequent complementary treatment in patients with aSAH.

Predicting the Poor Recovery Risk of Aneurysmal Subarachnoid Hemorrhage: Clinical Evaluation and Management Based on a New Predictive Nomogram

PURPOSE

To develop and validate a model for identifying the risk factors of poor recovery in patients with aneurysmal subarachnoid hemorrhage (aSAH).

METHODS

A prediction model was developed using training data obtained from 1577 aSAH patients from multiple centers. The patients were followed for 6 months on average and assessed using the modified Rankin Scale; patient information was collected with a prospective case report form. The least absolute shrinkage and selection operator regression were applied to optimize factor selection for the poor recovery risk model. Multivariable logistic regression, incorporating the factors selected in the previous step, was used for model predictions. Predictive ability and clinical effectiveness of the model were evaluated using C-index, receiver operating characteristic curve, and decision curve analysis. Internal validation was performed using the C-index, taking advantage of bootstrapping validation.

RESULTS

The predictors included household income per capita, hypertension, smoking, migraine within a week before onset, Glasgow Coma Scale at admission, average blood pressure at admission, modified Fisher score at admission, treatment method, and complications. Our newly developed model made satisfactory predictions; it had a C-index of 0.796 and an area under the receiver operating characteristic curve of 0.784. The decision curve analysis showed that the poor recovery nomogram was of clinical benefit when an intervention was decided at a poor recovery threshold between 2% and 50%. Internal validation revealed a C-index of 0.760.

CONCLUSION

Our findings indicate that the novel poor recovery nomogram may be conveniently used for risk prediction in aSAH patients. For patients with intracranial aneurysms, migraine needs to be vigilant. Quitting smoking and blood pressure management are also beneficial.