Middle Meningeal Artery Embolization: A Paradigm Shift in Approach of Chronic Subdural Hematoma

Hanif, Hamza; Farook, Shanza; Suriya, Sajid; Gondal, Muhammad Umer Riaz; Bilal, Mohammad; Sheikh, Abu Baker

doi:10.55729/2000-9666.1086

Journal of Community Hospital Internal Medicine Perspectives

2022

DOI: 10.55729/2000-9666.1086

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Middle Meningeal Artery Embolization: A Paradigm Shift in Approach of Chronic Subdural Hematoma

Hamza Hanif¹,

Shanza Farook²,

Sajid Suriya³

et al.

Abstract: Chronic subdural hematoma (SDH) is commonly seen in the aged population. It is hypothesized to occur due to damage to the dural border cells, resulting in an inflammation–proliferation reaction. Inadequate repair leads to the formation of an external layer of cells and fragile capillaries, which are vulnerable to damage, contributing to worsening of the condition. Conventionally, asymptomatic chronic SDH was managed by observation, while symptomatic cases by surgical evacuation. However, the recurrence rate of… Show more

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An artificial intelligence (AI)-based approach to clinical trial recruitment: The impact of Viz RECRUIT on enrollment in the EMBOLISE trial

et al. 2023

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Background EMBOLISE (NCT 04402632) is an ongoing randomized controlled trial investigating the safety and efficacy of middle meningeal artery embolization for the treatment of subacute or chronic subdural hematoma (SDH). Viz RECRUIT SDH is an artificial intelligence (AI)-based software platform that can automatically detect SDH in noncontrast computed tomography (NCHCT) images and report the volume, maximum thickness, and midline shift. We hypothesized that the mobile recruitment platform would aid enrollment and coordinate communication and image sharing among the entire research team. Materials and methods Patient enrollment in EMBOLISE prior to and after implementation of Viz RECRUIT SDH at a large comprehensive stroke center was compared along with the performance of the software platform. The EMBOLISE trial was activated on May 5, 2021, and Viz RECRUIT SDH was activated on October 6, 2021. The pre-AI cohort consisted of all patients from EMBOLISE to AI activation (153 days), and the post-AI cohort consisted of all patients from AI activation until August 18, 2022 (316 days). All alerts for suspected SDH candidates were manually reviewed to determine the positive predictive value (PPV) of the algorithm. Results Prior to AI-software implementation, there were 5 patients enrolled (0.99 patients/month) and one screen failure. After the implementation of the software, enrollment increased by 36% to 1.35 patients/month (14 total enrolled), and there were no screen failures. Over the entire post-AI period, a total of 6244 NCHCTs were processed by the system with 207 total SDH detections (3% prevalence). 35% of all alerts for suspected SDH were viewed within 10 min, and 50% were viewed within an hour. The PPV of the algorithm was 81.4 (CI [75.3, 86.7]). Conclusion The implementation of an AI-based software for the automatic screening of SDH patients increased the enrollment rate in the EMBOLISE trial, and the software performed well in a real-world, clinical trial setting.

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An artificial intelligence (AI)-based approach to clinical trial recruitment: The impact of Viz RECRUIT on enrollment in the EMBOLISE trial

et al. 2023

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Predictors of Outcomes and a Weighted Mortality Score for Moderate to Severe Subdural Hematoma

Vazquez,

Jain,

Nolan

et al. 2024

Life

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As the incidence of subdural hematoma is increasing, it is important to understand symptomatology and clinical variables associated with treatment outcomes and mortality in this population; patients with subdural hematoma were selected from the National Inpatient Sample (NIS) Database between 2016 and 2020 using International Classification of Disease 10th Edition (ICD10) codes. Moderate-to-severe subdural hematoma patients were identified using the Glasgow Coma Scale (GCS). Multivariate regression was first used to identify predictors of in-hospital mortality and then beta coefficients were used to create a weighted mortality score. Of 29,915 patients admitted with moderate-to-severe subdural hematomas, 12,135 (40.6%) died within the same hospital admission. In a multivariate model of relevant demographic and clinical covariates, age greater than 70, diabetes mellitus, mechanical ventilation, hydrocephalus, and herniation were independent predictors of mortality (p < 0.001 for all). Age greater than 70, diabetes mellitus, mechanical ventilation, hydrocephalus, and herniation were assigned a “1” in a weighted mortality score. The ROC curve for our model showed an area under the curve of 0.64. Age greater than 70, diabetes mellitus, mechanical ventilation, hydrocephalus, and herniation were predictive of mortality. We created the first clinically relevant weighted mortality score that can be used to stratify risk, guide prognosis, and inform family discussions.

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Middle Meningeal Artery Embolization: A Paradigm Shift in Approach of Chronic Subdural Hematoma

Cited by 2 publications

References 47 publications

An artificial intelligence (AI)-based approach to clinical trial recruitment: The impact of Viz RECRUIT on enrollment in the EMBOLISE trial

An artificial intelligence (AI)-based approach to clinical trial recruitment: The impact of Viz RECRUIT on enrollment in the EMBOLISE trial

Predictors of Outcomes and a Weighted Mortality Score for Moderate to Severe Subdural Hematoma

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