Distinct comorbidity phenotypes among post-9/11 Veterans with epilepsy are linked to diverging outcomes and mortality risks.

IF 6.6 1区 医学 Q1 CLINICAL NEUROLOGY Epilepsia Pub Date : 2024-11-02 DOI:10.1111/epi.18170
Mary Jo Pugh, Heidi Munger Clary, Madeleine Myers, Eamonn Kennedy, Megan Amuan, Alicia A Swan, Sidney Hinds, W Curt LaFrance, Hamada Altalib, Alan Towne, Amy Henion, Abigail White, Christine Baca, Chen-Pin Wang
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Abstract

Objective: To investigate phenotypes of comorbidity before and after an epilepsy diagnosis in a national cohort of post-9/11 Service Members and Veterans and explore phenotypic associations with mortality.

Methods: Among a longitudinal cohort of Service Members and Veterans receiving care in the Veterans Health Administration (VHA) from 2002 to 2018, annual diagnoses for 26 conditions associated with epilepsy were collected over 5 years, ranging from 2 years prior to 2 years after the year of first epilepsy diagnosis. Latent class analysis (LCA) was used to identify probabilistic comorbidity phenotypes with distinct health trajectories. Descriptive statistics were used to describe the characteristics of each phenotype. Fine and Gray cause-specific survival models were used to measure mortality outcomes for each phenotype up to 2021.

Results: Six distinct phenotypes were identified: (1) relatively healthy, (2) post-traumatic stress disorder, (3) anxiety and depression, (4) chronic disease, (5) bipolar/substance use disorder, and (6) polytrauma. Accidents were the most common cause of death overall, followed by suicide/mental health and cancer, respectively. Each phenotype exhibited unique associations with mortality and cause of death, highlighting the differential impact of comorbidity patterns on patient outcomes.

Significance: By delineating clinically meaningful epilepsy comorbidity phenotypes, this study offers a framework for clinicians to tailor interventions. Moreover, these data support systems of care that facilitate treatment of epilepsy and comorbidities within an interdisciplinary health team that allows continuity of care. Targeting treatment toward patients with epilepsy who present with specific heightened risks could help mitigate adverse outcomes and enhance overall patient care.

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9/11事件后退伍军人癫痫患者不同的合并症表型与不同的治疗结果和死亡风险有关。
目的调查9/11后军人和退伍军人全国队列中癫痫诊断前后的合并症表型,并探讨表型与死亡率的关联:在2002年至2018年期间接受退伍军人健康管理局(VHA)护理的军人和退伍军人纵向队列中,收集了与癫痫相关的26种疾病的年度诊断,诊断时间为首次癫痫诊断年之前2年至之后2年,历时5年。潜类分析(LCA)用于识别具有不同健康轨迹的概率合并症表型。描述性统计用于描述每种表型的特征。使用 Fine 和 Gray 病因特异性生存模型来测量每个表型直到 2021 年的死亡率结果:结果:确定了六种不同的表型:结果:确定了六种不同的表型:(1) 相对健康;(2) 创伤后应激障碍;(3) 焦虑和抑郁;(4) 慢性疾病;(5) 躁郁症/药物使用障碍;(6) 多重创伤。事故是最常见的死亡原因,其次分别是自杀/精神疾病和癌症。每种表型都与死亡率和死因有独特的关联,凸显了合并症模式对患者预后的不同影响:本研究通过划分具有临床意义的癫痫合并症表型,为临床医生提供了一个量身定制干预措施的框架。此外,这些数据还支持在跨学科医疗团队内促进癫痫和合并症治疗的护理系统,从而实现护理的连续性。对具有特定高风险的癫痫患者进行针对性治疗,有助于减轻不良后果并加强对患者的整体护理。
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来源期刊
Epilepsia
Epilepsia 医学-临床神经学
CiteScore
10.90
自引率
10.70%
发文量
319
审稿时长
2-4 weeks
期刊介绍: Epilepsia is the leading, authoritative source for innovative clinical and basic science research for all aspects of epilepsy and seizures. In addition, Epilepsia publishes critical reviews, opinion pieces, and guidelines that foster understanding and aim to improve the diagnosis and treatment of people with seizures and epilepsy.
期刊最新文献
Automatic responsiveness testing in epilepsy with wearable technology: The ARTiE Watch. WONOEP appraisal: Targeted therapy development for early onset epilepsies. Issue Information Association of cognitive and structural correlates of brain aging and incident epilepsy. The Framingham Heart Study. Epilepsia – November 2024 Announcements
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