Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Diabetes. Jul 15, 2026; 17(7): 119009
Published online Jul 15, 2026. doi: 10.4239/wjd.119009
Published online Jul 15, 2026. doi: 10.4239/wjd.119009
Diabetes as a determinant of neurosurgical vulnerability: Rethinking perioperative risk in meningioma resection
Riya Karmakar, Department of Integrated Bachelor of Technology, School of Engineering and Technology, Sanjivani University, Kopargaon 423603, Mahārāshtra, India
Ananya Kaushik, Department of Artificial Intelligence and Machine Learning, School of Engineering and Technology, Sanjivani University, Kopargaon 423603, Mahārāshtra, India
Pratham Gade, Department of Information Technology, Sanjivani College of Engineering, Kopargaon 423603, Mahārāshtra, India
Mahendra Gawali, Arvind Mukundan, Department of Computer Science Engineering, School of Engineering and Technology, Sanjivani University, Kopargaon 423603, Mahārāshtra, India
Arvind Mukundan, Department of Biomedical Imaging, Chennai Institute of Technology, Chen
Co-first authors: Riya Karmakar and Ananya Kaushik.
Author contributions: Karmakar R and Kaushik A designed the research study, contributed equally to this article and are the co-first authors of this manuscript; Karmakar R, Kaushik A, Gade P, Gawali M, and Mukundan A performed the research; Karmakar R and Mukundan A wrote the manuscript; and all authors contributed to revisions.
AI contribution statement: We would like to clarify that no AI tool was used to generate the scientific content, study design, data, analysis, results, interpretation, conclusions, or images in the manuscript. The only AI-assisted tool used was QuillBot, and its use was limited to paraphrasing and language refinement to improve readability and reduce grammatical or stylistic issues. The manuscript was not written or generated by ChatGPT, DeepL, or any other generative AI tool.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Arvind Mukundan, Associate Professor, Senior Postdoctoral Fellow, Senior Researcher, Department of Computer Science, School of Engineering and Technology, Sanjivani University, Singnapur, Kopargaon, Kopargaon 423603, Mahārāshtra, India.
Received: January 19, 2026
Revised: February 20, 2026
Accepted: May 13, 2026
Published online: July 15, 2026
Processing time: 173 Days and 13 Hours
Revised: February 20, 2026
Accepted: May 13, 2026
Published online: July 15, 2026
Processing time: 173 Days and 13 Hours
Core Tip
Core Tip: Type 2 diabetes has a major effect on patients having tumor excision during and after the surgery. Higher chances of surgical site infection, cerebral edema, neurological issues, prolonged hospital stays, and risk of tumor recurrence can result in high blood sugar, long-term inflammatory phase, slower wound healing, and disturbance of the blood brain barrier. This review highlights the need for customized preoperative glucose control, thorough postoperative monitoring, and prolonged metabolic improvement in diabetic patients. Diabetes should be viewed as an active biological disorder with neurosurgical risk factors rather than a passive disorder.