ArticleFrontiers in human neuroscience2024
Toward a systematic grading for the selection of patients to undergo awake surgery: identifying suitable predictor variables.
Article in Frontiers in human neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Efficacy and safety of awake craniotomy versus general anesthesia for glioma resection: A systematic review.Surgical neurology international · 2026Review
- Intraoperative integration of nTMS, CCEPs and DCS for language. A glance to the next future?Acta neurochirurgica · 2025Article
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7 authors.
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Abstract
Background: Awake craniotomy is the standard of care for treating language eloquent gliomas. However, depending on preoperative functionality, it is not feasible in each patient and selection criteria are highly heterogeneous. Thus, this study aimed to identify broadly applicable predictor variables allowing for a more systematic and objective patient selection. Methods: We performed post-hoc analyses of preoperative language status, patient and tumor characteristics including language eloquence of 96 glioma patients treated in a single neurosurgical center between 05/2018 and 01/2021. Multinomial logistic regression and stepwise variable selection were applied to identify significant predictors of awake surgery feasibility. Results: Stepwise backward selection confirmed that a higher number of paraphasias, lower age, and high language eloquence level were suitable indicators for an awake surgery in our cohort. Subsequent descriptive and ROC-analyses indicated a cut-off at ≤54 years and a language eloquence level of at least 6 for awake surgeries, which require further validation. A high language eloquence, lower age, preexisting semantic and phonological aphasic symptoms have shown to be suitable predictors. Conclusion: The combination of these factors may act as a basis for a systematic and standardized grading of patients' suitability for an awake craniotomy which is easily integrable into the preoperative workflow across neurosurgical centers.
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