自发性小型颅内出血后情感障碍和认知障碍的预测因素。

IF 4.5 2区 医学 Q1 CLINICAL NEUROLOGY
Qiuyi Jiang, Chunyang Liu, Hongli Zhang, Rui Liu, Jian Zhang, Jinyi Guo, Enzhou Lu, Shouyue Wu, Jianda Sun, Yan Gao, Qiunan Yang, Guangyao Shi, Chao Yuan, Yanchao Liang, Huan Xiang, Lu Wang, Guang Yang
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引用次数: 0

摘要

背景和目的:情感障碍和认知功能障碍是脑内出血(ICH)的常见后遗症,但这些结果的预测模型仍然有限,尤其是对于自发性小血肿幕上ICH(方法:我们回顾性分析了哈尔滨医科大学附属第一医院2018年1月至2020年12月期间的1692例自发性幕上ICH患者:我们回顾性分析了哈尔滨医科大学附属第一医院 2018 年 1 月至 2020 年 12 月期间的 1692 例自发性脑室上 ICH 患者。其中,1563 名患者完成了中位 3.5 年的随访。认知功能采用改良认知状态电话访谈法进行评估,情感障碍采用汉密尔顿抑郁量表和汉密尔顿焦虑量表进行评估。采用限制性三次样条分析来研究预测因素与结果之间的关系:在这批患者中,58.5%的人有认知障碍,52.8%的人有抑郁症状,39.4%的人有焦虑症状。使用博鲁塔算法的逻辑回归模型显示出很强的预测能力,认知障碍的曲线下面积为 0.82,抑郁症状为 0.78,焦虑症状为 0.73。血肿体积与抑郁症状(几率比[OR] 1.56,95% 置信区间[CI] 1.38-1.76)明显相关,与认知障碍(OR 0.67,95% 置信区间 0.59-0.77)成反比。尿酸水平与认知障碍呈非线性关系(OR 0.70,95% CI 0.61-0.81)。住院天数明显增加了抑郁症状(OR 1.16,95% CI 1.03-1.30)和焦虑症状(OR 1.17,95% CI 1.04-1.31)的风险:经 Boruta 算法增强的逻辑回归模型是预测 ICH 后情感障碍和认知障碍的重要工具。它有助于早期识别和改进对小血肿患者神经精神疾病后果的风险评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictors of affective disturbances and cognitive impairment following small spontaneous supratentorial intracerebral hemorrhage.

Background and purpose: Affective disturbances and cognitive impairment are common sequelae of intracerebral hemorrhage (ICH), yet predictive models for these outcomes remain limited, especially for spontaneous supratentorial ICH with small hematomas (<30 mL). The aim of this study was to investigate predictors of affective disturbances and cognitive impairment following small spontaneous supratentorial intracerebral hemorrhage.

Methods: We retrospectively analyzed 1692 patients with spontaneous supratentorial ICH between January 2018 and December 2020 at the First Affiliated Hospital of Harbin Medical University. Of these, 1563 patients completed a median follow-up of 3.5 years. Cognitive function was evaluated using the modified Telephone Interview for Cognitive Status, and affective disturbances using the Hamilton Depression Scale and the Hamilton Anxiety Scale. Restricted cubic spline analyses were employed to examine the relationships between predictors and outcomes.

Results: In this cohort, 58.5% had cognitive impairment, 52.8% reported depressive symptoms, and 39.4% exhibited anxiety symptoms. Logistic regression models using Boruta's algorithm demonstrated strong predictive capacity, with areas under the curve of 0.82 for cognitive impairment, 0.78 for depressive symptoms, and 0.73 for anxiety symptoms. Hematoma volume was significantly linked to depressive symptoms (odds ratio [OR] 1.56, 95% confidence interval [CI] 1.38-1.76) and inversely to cognitive impairment (OR 0.67, 95% CI 0.59-0.77). Uric acid levels displayed a nonlinear relationship with cognitive impairment (OR 0.70, 95% CI 0.61-0.81). Hospitalization days significantly raised the risk of both depressive (OR 1.16, 95% CI 1.03-1.30) and anxiety symptoms (OR 1.17, 95% CI 1.04-1.31).

Conclusions: The logistic regression model, enhanced by Boruta's algorithm, provides a valuable tool for predicting affective disturbances and cognitive impairment after ICH. It facilitates early identification and improves risk assessment for these neuropsychiatric outcomes in patients with small hematomas.

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来源期刊
European Journal of Neurology
European Journal of Neurology 医学-临床神经学
CiteScore
9.70
自引率
2.00%
发文量
418
审稿时长
1 months
期刊介绍: The European Journal of Neurology is the official journal of the European Academy of Neurology and covers all areas of clinical and basic research in neurology, including pre-clinical research of immediate translational value for new potential treatments. Emphasis is placed on major diseases of large clinical and socio-economic importance (dementia, stroke, epilepsy, headache, multiple sclerosis, movement disorders, and infectious diseases).
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