SURG-87. Impact of emergency department admissions on time to surgery in patients with glioblastoma
Year: 2025
Type: conference-abstract
Abstract: Glioblastoma (GBM) has a historically poor prognosis, and early intervention can decrease tumor burden and prolong overall survival. Patients are often diagnosed due to symptomology and sent to the emergency department (ED) for work-up and resection. We sought to determine the rates of patients with GBM admitted through the ED at the time of initial diagnosis and its impact on the speed from initial diagnostic imaging to surgery. Records of all patients at our institution with pathology confirmed diagnosis of Glioblastoma or high-grade astrocytoma from 2014-2022 were queried for analysis. Patients were excluded if surgery was performed for recurrence or age was less than 18 years old. The total analytical sample included 415 patients with 357 (86%) admitted through the ED. 54 (15.1%) of these patients were diagnosed with imaging outpatient before arrival and 127 (30.6%) were transferred from another hospital. Of the patients who arrived through the ED, 269 (75.4%) had resection of the tumor during their initial operation versus 88 (24.7%) who only had a biopsy of the tumor. There was no significance in operation type and admission route (p=0.198). The mean time from first image to operating room (OR) was 8 days (SE=0.5) in total and 6.2 days (SE=0.4) for ED admissions. The mean time to OR was significantly longer (p<0.001) in patients with scheduled surgeries outpatient versus ED admissions. The majority (86%) of our sample from 2014-2022 were admitted through the ED with patients being unable to choose their provider. However, the time to OR was faster than with outpatient admissions. A portion of the ED patients were immediately sent from their outpatient providers to the ED rather than direct referral to a multidisciplinary neurosurgical team.
Source: Neuro-Oncology
Authors: Isabelle Pelcher, Inigo Sistiaga, Danielle Golub, Shrey Patel, Brianna Donnelly, Sabrina Begley, Yonah Ziemba, Michael Schulder
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4416140282
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