Retrospective link of altered mental status and cryptococcal meningitis.

International review of neurobiology Pub Date : 2025-01-01 Epub Date: 2025-04-16 DOI:10.1016/bs.irn.2025.04.003
Punithkumar Naraganahalli Krishnaraj, Chandavi Venkatesh, Dhanu Anneyplar Shivakumar, Nagalambika Prasad, Guru Kumar Dugganaboyana, Kumar Jajur Ramanna
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Abstract

Cryptococcal meningitis (CM) is a severe central nervous system infection primarily affecting immunocompromised patients, significantly contributing to global morbidity and mortality. This chapter explores the link between altered mental status (AMS) and CM, focusing on pathophysiological mechanisms and clinical correlations. Cryptococcus neoformans invades the central nervous system, evading immune defenses and causing increased intracranial pressure, inflammation, and neuronal damage. AMS, a frequent early symptom in CM, signals neurological involvement and disease severity, ranging from subtle cognitive issues to severe deficits. Retrospective studies highlight AMS as a prognostic marker, often associated with worse outcomes. Diagnostic challenges are discussed, emphasizing early recognition for timely intervention. Advances in artificial intelligence and machine learning are proposed to enhance diagnostic accuracy, prognosis, and management of CM. The chapter also covers antifungal therapies and supportive interventions to mitigate AMS-related complications. Future research directions include AI-driven diagnostics and novel treatments to improve outcomes in CM and its neurological manifestations.

精神状态改变与隐球菌性脑膜炎的回顾性联系。
隐球菌性脑膜炎(CM)是一种严重的中枢神经系统感染,主要影响免疫功能低下患者,对全球发病率和死亡率有重要影响。本章探讨了精神状态改变(AMS)和CM之间的联系,重点是病理生理机制和临床相关性。新型隐球菌侵入中枢神经系统,逃避免疫防御,引起颅内压升高、炎症和神经元损伤。AMS是CM常见的早期症状,表明神经系统受累和疾病严重程度,从细微的认知问题到严重的缺陷。回顾性研究强调AMS是一种预后标志物,通常与较差的预后相关。讨论了诊断挑战,强调早期识别及时干预。提出了人工智能和机器学习的进展,以提高CM的诊断准确性,预后和管理。本章还涵盖了抗真菌治疗和支持性干预措施,以减轻ams相关并发症。未来的研究方向包括人工智能驱动的诊断和新的治疗方法,以改善CM的预后及其神经学表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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