Volumetric quantification of aneurysmal subarachnoid hemorrhage independently predicts hydrocephalus and seizures

Daou, Badih; Khalsa, Siri Sahib S.; Anand, Sharath Kumar; Williamson, Craig A.; Cutler, N.; Aaron, Bryan; Srinivasan, Saumini; Rajajee, Venkatakrishna; Sheehan, Kyle M.; Pandey, Aditya S.

doi:10.3171/2020.8.jns201273

Cited by 7 publications

(2 citation statements)

References 53 publications

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“…The precise quantification of this volume can be achieved using a conventional computed tomography slice and multiplying it by the thickness of the haemorrhagic area involved. A correct appreciation of this volume can also be considered with the prediction of other long-term complications, including hydrocephalus and seizures [ 61 ].…”

Section: A Detailed Overview Of Complicationsmentioning

confidence: 99%

Non-Aneurysmal Perimesencephalic Subarachnoid Hemorrhage: A Literature Review

et al. 2023

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Spontaneous non-aneurysmal subarachnoid haemorrhage (NAPMSAH) (addressing point 1) is a relatively rare occurrence in clinical settings as it is rarely misdiagnosed and usually involves a significantly better prognosis than the classical aneurysmal pattern. We hereby focused on a comprehensive analysis of this distinct pathological entity with the purpose of analysing possible pathophysiological entities, outcomes and treatment options involving this diagnosis with a focus on demographical, epidemiological and clinical data. The clinical setting includes focal neurological signs related to the anatomical structures, while computer tomography followed by tomographic angiography are the most common diagnosis tools, with a typical hyperdense lesion involving the midbrain, fourth ventricle and subthalamic areas without an angiographic correspondent, such as an aneurysmal pathology. Further investigations can also be used to highlight this diagnosis, such as interventional angiography or magnetic resonance imaging. Given the rarity of this condition and its relatively better prognosis, treatment options usually remain conservative. In the present review, the main characteristics of NAPMSAH are discussed.

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Section: A Detailed Overview Of Complicationsmentioning

confidence: 99%

Non-Aneurysmal Perimesencephalic Subarachnoid Hemorrhage: A Literature Review

et al. 2023

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“…Aneurysm occlusion represents only the first step of the complex aSAH management. The amount of blood clots and their toxic degradation products are the principal trigger factors for early and delayed brain injury [13][14][15][16][17][18]. The prevention and management of early and delayed brain injuries may significantly improve the functional outcome.…”

Section: Introductionmentioning

confidence: 99%

The Role of Cisternostomy and Cisternal Drainage in the Treatment of Aneurysmal Subarachnoid Hemorrhage: A Comprehensive Review

Vandenbulcke,

Messerer,

Daniel

et al. 2023

Brain Sciences

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Aneurysmal subarachnoid hemorrhage (aSAH) provokes a cascade reaction that is responsible for early and delayed brain injuries mediated by intracranial hypertension, hydrocephalus, cerebral vasospasm (CV), and delayed cerebral ischemia (DCI), which result in increased morbidity and mortality. During open microsurgical repair, cisternal access is achieved essentially to gain proximal vascular control and aneurysm exposition. Cisternostomy also allows brain relaxation, removal of cisternal clots, and restoration of the CSF dynamics through the communication between the anterior and posterior circulation cisterns and the ventricular system, with the opening of the Membrane of Liliequist and lamina terminalis, respectively. Continuous postoperative CSF drainage through a cisternal drain (CD) is a valuable option for treating acute hydrocephalus and intracranial hypertension. Moreover, it efficiently removes the blood and toxic degradation products, with a potential benefit on CV, DCI, and shunt-dependent hydrocephalus. Finally, the CD is an effective pathway to administer vasoactive, fibrinolytic, and anti-oxidant agents and shows promising results in decreasing CV and DCI rates while minimizing systemic effects. We performed a comprehensive review to establish the adjuvant role of cisternostomy and CD performed in cases of direct surgical repair for ruptured intracranial aneurysms and their role in the prevention and treatment of aSAH complications.

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Early prediction of ventricular peritoneal shunt dependency in aneurysmal subarachnoid haemorrhage patients by recurrent neural network-based machine learning using routine intensive care unit data

Schweingruber,

Bremer,

Wiehe

et al. 2024

J Clin Monit Comput

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Aneurysmal subarachnoid haemorrhage (aSAH) can lead to complications such as acute hydrocephalic congestion. Treatment of this acute condition often includes establishing an external ventricular drainage (EVD). However, chronic hydrocephalus develops in some patients, who then require placement of a permanent ventriculoperitoneal (VP) shunt. The aim of this study was to employ recurrent neural network (RNN)-based machine learning techniques to identify patients who require VP shunt placement at an early stage. This retrospective single-centre study included all patients who were diagnosed with aSAH and treated in the intensive care unit (ICU) between November 2010 and May 2020 (n = 602). More than 120 parameters were analysed, including routine neurocritical care data, vital signs and blood gas analyses. Various machine learning techniques, including RNNs and gradient boosting machines, were evaluated for their ability to predict VP shunt dependency. VP-shunt dependency could be predicted using an RNN after just one day of ICU stay, with an AUC-ROC of 0.77 (CI: 0.75–0.79). The accuracy of the prediction improved after four days of observation (Day 4: AUC-ROC 0.81, CI: 0.79–0.84). At that point, the accuracy of the prediction was 76% (CI: 75.98–83.09%), with a sensitivity of 85% (CI: 83–88%) and a specificity of 74% (CI: 71–78%). RNN-based machine learning has the potential to predict VP shunt dependency on Day 4 after ictus in aSAH patients using routine data collected in the ICU. The use of machine learning may allow early identification of patients with specific therapeutic needs and accelerate the execution of required procedures.

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Volumetric quantification of aneurysmal subarachnoid hemorrhage independently predicts hydrocephalus and seizures

Cited by 7 publications

References 53 publications

Non-Aneurysmal Perimesencephalic Subarachnoid Hemorrhage: A Literature Review

Non-Aneurysmal Perimesencephalic Subarachnoid Hemorrhage: A Literature Review

The Role of Cisternostomy and Cisternal Drainage in the Treatment of Aneurysmal Subarachnoid Hemorrhage: A Comprehensive Review

Early prediction of ventricular peritoneal shunt dependency in aneurysmal subarachnoid haemorrhage patients by recurrent neural network-based machine learning using routine intensive care unit data

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