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在全国综合性医疗保健系统中,患有医学诊断为丛集性头痛的男性和女性的特征:一项退伍军人健康管理局队列研究。

Characteristics of men and women with medically diagnosed cluster headache in a national integrated healthcare system: A Veterans Health Administration cohort study.

机构信息

Veterans Affairs Headache Centers of Excellence Research, Education, Evaluation, Engagement Center Activities Center for Headache (RE3ACH), West Haven, Connecticut, USA.

Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, New York, USA.

出版信息

Headache. 2024 Nov-Dec;64(10):1273-1284. doi: 10.1111/head.14842. Epub 2024 Oct 14.

DOI:10.1111/head.14842
PMID:39400858
Abstract

OBJECTIVE

Describe the epidemiology of cluster headache (CH) using Veterans Health Administration (VHA) Electronic Health Record (EHR) data.

BACKGROUND

Epidemiologic studies of CH at the population level are difficult because it has a prevalence of ~0.1%. Hospital system-wide studies are an attractive alternative as they have large numbers of patients and broader populations than headache or neurology clinic-based studies. The VHA is an ideal hospital-based system in which to study CH because it is nationwide, predominantly male, has a strong focus on mood disorders and suicidality, and has accessible individual medical records. Here, we report the first headache study based on an ongoing longitudinal cohort of patients with CH using VHA EHR data.

METHODS

The VHA EHR data were accessed from Fiscal Year 2008 to 2019. Patients with CH consisted of all patients with at least one outpatient visit containing a CH diagnosis code from the International Classification of Diseases (ICD)-9 or -10. We extracted data on demographic features, incidence, and prevalence, as well as pain and psychiatric comorbidities.

RESULTS

Of the 1,524,960 distinct patients who presented for headache treatment in the VHA between Fiscal Year 2008-2019, 24,131 had at least one visit with a CH diagnosis. The 1-year period prevalence of a CH diagnosis in the VHA ranges from 0.08% to 0.10% for women and 0.10% to 0.18% for men. A larger proportion of women versus men received a diagnosis of unspecified CH (59.6% [1412/2368] vs. 53.6% [11,663/21,763], p < 0.001). Most patients with CH had both comorbid headache and non-headache pain diagnoses. Headache not-otherwise-specified was the most common comorbid headache disorder at 70.0% (16,885/24,131) and was more common in women (76.1%, 1801/2368) compared to men (69.3%, 15,084/21,763). Other common comorbidities included migraine, depression, tobacco use, and obstructive sleep apnea. Rates of suicidal ideation or attempt were almost 50% higher in women (5-year proportion 9.4%, 222/2368) with CH compared to men (6.6%, 1433/21,763).

CONCLUSIONS

To our knowledge this is the largest hospital system study of CH to date and reinforces several previous studies. Pain, mental health, and sleep disorders comorbidities are particularly prevalent in this group and were often more common in women compared to men with CH. Future work should examine gender and race stratified prevalence estimates within the VHA and other healthcare systems.

摘要

目的

利用退伍军人事务部电子健康记录(EHR)数据描述集群性头痛(CH)的流行病学特征。

背景

在人群层面上对 CH 进行流行病学研究是困难的,因为其患病率约为 0.1%。全系统的医院研究是一种有吸引力的替代方法,因为它们拥有大量的患者和比头痛或神经病学诊所研究更广泛的人群。退伍军人事务部是研究 CH 的理想的医院系统,因为它是全国性的,主要是男性,对情绪障碍和自杀倾向有强烈的关注,并且可以访问个人的医疗记录。在这里,我们报告了第一个使用退伍军人事务部 EHR 数据的正在进行的 CH 患者纵向队列的头痛研究。

方法

从 2008 财年到 2019 财年,我们从退伍军人事务部的 EHR 数据中获取了数据。CH 患者包括至少有一次门诊就诊记录的所有患者,这些就诊记录中包含国际疾病分类(ICD)第 9 或 10 版的 CH 诊断代码。我们提取了人口统计学特征、发病率和患病率,以及疼痛和精神共病的相关数据。

结果

在 2008 财年至 2019 财年期间,在退伍军人事务部就诊的 1524960 名不同头痛患者中,有 24131 名患者至少有一次 CH 诊断的就诊记录。退伍军人事务部中 CH 的 1 年期间患病率,女性为 0.08%至 0.10%,男性为 0.10%至 0.18%。与男性相比,更多的女性被诊断为未特指的 CH(59.6%[1412/2368]vs.53.6%[11,663/21,763],p<0.001)。大多数 CH 患者既有共患头痛,也有非头痛性疼痛的诊断。未特指的头痛是最常见的共患头痛障碍,占 70.0%(16,885/24131),在女性中更为常见(76.1%,1801/2368),而在男性中则较为常见(69.3%,15,084/21,763)。其他常见的共病包括偏头痛、抑郁症、烟草使用和阻塞性睡眠呼吸暂停。在患有 CH 的女性中,自杀意念或尝试的比例几乎高出 50%(5 年比例为 9.4%,222/2368),而男性则为 6.6%(1433/21,763)。

结论

据我们所知,这是迄今为止对 CH 进行的最大规模的医院系统研究,它强化了几项先前的研究。疼痛、心理健康和睡眠障碍共病在这一人群中尤为普遍,与男性相比,女性中这些共病更为常见。未来的工作应该在退伍军人事务部和其他医疗保健系统中检查性别和种族分层的患病率估计。

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