Suppr超能文献

埃塞俄比亚中部公立医院接受后续治疗的癫痫患者中癫痫相关损伤的发生率及预测因素。

Incidence and predictors of seizure-related injuries among epileptic patients undergoing follow-up treatment at public hospitals in Central Ethiopia.

作者信息

Begizew Selamawit Wondale, Muluneh Bethelhem Birhanu, Ashine Taye Mezgebu, Heliso Asnakech Zekiwos, Babore Getachew Ossabo, Ereta Elias Ezo, Saliya Sentayehu Admasu, Hailu Awoke Girma, Abdisa Elias Nigusu

机构信息

Adult Health Nursing, College of Medicine and Health Science, Wachemo University, Hosanna, Ethiopia.

Pediatric and Child Health Science, College of Medicine and Health Science, Wachemo University, Hosanna, Ethiopia.

出版信息

Sci Rep. 2025 Jan 31;15(1):3899. doi: 10.1038/s41598-025-86268-5.

Abstract

Seizure-related injuries represent a significant concern for both individuals with epilepsy and their caregivers. Compared to the general population, those diagnosed with epilepsy face a heightened risk of sustaining injuries. Despite this, there is a notable scarcity of data regarding seizure-related injuries among epileptic patients. This study aimed to evaluate the incidence of seizure-related injuries and identify their predictors among epileptic patients undergoing follow-up treatment at selected public hospitals in Central Ethiopia, in 2023. A prospective follow-up study was carried out in selected public hospitals in central Ethiopia. The study included epileptic patients aged ≥ 18 years who had not experienced any previous injury during follow-up treatment from January 1st, 2023, to December 31st, 2023. Data collection involved conducting interviews with participants using a structured questionnaire and reviewing patients' charts. Univariate analysis, multivariate, and regression analysis were performed to identify potential associations between variables and seizure-related injuries. Variables were deemed significantly associated with seizure-related injuries if they attained a p value of 0.05 with a 95% confidence interval. Out of the 561 participants, 265 (47.2%) experienced seizure-related injuries (95% CI 43.12, 51.38). The incidence density rate of seizure-related injuries among epileptic patients was 11.97 per 100 person-months of observation (95% CI 10.61, 13.50). In multivariate analysis, epileptic patients who had generalized tonic-clonic seizures (adjusted hazard ratio 1.4, 95% CI 1.07-1.84), comorbidities (adjusted hazard ratio 1.3, 95% CI 1.11-1.71), were on polytherapy drug regimens (adjusted hazard ratio 1.80, 95% CI 0.30-2.49), and consumed alcoholic drinks (adjusted hazard ratio 1.5, 95% CI 1.21-1.89) were identified as independent predictors of seizure-related injuries. The incidence rate of seizure-related injuries among epileptic patients was found to be significant. Risk factors identified included experiencing generalized tonic-clonic seizures, having at least one additional health condition, being on multiple medications, and consuming alcohol. To improve survival from injuries, targeted precautions for generalized tonic-clonic seizures, strict adherence to prescribed medication regimens, and avoiding alcohol consumption are recommended.

摘要

癫痫发作相关损伤是癫痫患者及其照料者极为关注的问题。与普通人群相比,被诊断患有癫痫的人遭受损伤的风险更高。尽管如此,关于癫痫患者中癫痫发作相关损伤的数据却明显匮乏。本研究旨在评估2023年在埃塞俄比亚中部选定公立医院接受后续治疗的癫痫患者中癫痫发作相关损伤的发生率,并确定其预测因素。在埃塞俄比亚中部选定的公立医院开展了一项前瞻性随访研究。该研究纳入了年龄≥18岁、在2023年1月1日至2023年12月31日的后续治疗期间未曾经历过任何既往损伤的癫痫患者。数据收集包括使用结构化问卷对参与者进行访谈以及查阅患者病历。进行单因素分析、多因素分析和回归分析以确定变量与癫痫发作相关损伤之间的潜在关联。如果变量的p值为0.05且95%置信区间,则认为其与癫痫发作相关损伤显著相关。在561名参与者中,265名(47.2%)经历了癫痫发作相关损伤(95%置信区间43.12, 51.38)。癫痫患者中癫痫发作相关损伤的发病密度率为每100人月观察期11.97例(95%置信区间10.61, 13.50)。在多因素分析中,全身性强直阵挛发作的癫痫患者(调整后风险比1.4,95%置信区间1.07 - 1.84)、患有合并症的患者(调整后风险比1.3,95%置信区间1.11 - 1.71)、采用联合药物治疗方案的患者(调整后风险比1.80,95%置信区间0.30 - 2.49)以及饮酒的患者(调整后风险比1.5,95%置信区间1.21 - 1.89)被确定为癫痫发作相关损伤的独立预测因素。癫痫患者中癫痫发作相关损伤的发生率被发现是显著的。确定的风险因素包括经历全身性强直阵挛发作、至少有一种其他健康状况、服用多种药物以及饮酒。为了提高损伤后的生存率,建议针对全身性强直阵挛发作采取有针对性的预防措施、严格遵守规定的药物治疗方案以及避免饮酒。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ad96/11785985/19a4a461c872/41598_2025_86268_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验