Demographic characteristics and comorbidities of patients with narcolepsy: a propensity-matched cohort study.

Melissa C Lipford, Wui Ip, Samir Awasthi, J Layne Moore, Maja Tippmann-Peikert, Shahir Asfahan, Praveen Kumar-M, Gajinder Pal Singh, Jennifer Gudeman
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Abstract

Study objectives: Narcolepsy has a complex phenotype owing to differences in symptomatology, disease severity, and comorbidities. This is the first study to use aggregate electronic health record (EHR) data and natural language processing (NLP) algorithms to characterize the demographics and comorbidities of a large cohort of patients with narcolepsy.

Methods: First-time Mayo Clinic patients (2000-2020) who had ≥1 narcolepsy-specific ICD-9/10 code and ≥1 disease-supportive statement in the clinical notes (identified using an NLP algorithm) were identified. A control cohort was propensity matched for birth year, age at first institutional encounter, sex, race, ethnicity, number of diagnosis codes, and mortality. Common comorbidities were compared and ranked between cohorts.

Results: In the EHR database (N = 6 389 186 patients), 2057 patients with narcolepsy were identified (median age, 32 years; 59.6% female; 92.6% white; and 89.2% non-Hispanic) and propensity matched with a control cohort. Among the top 20 comorbidities occurring more frequently in the narcolepsy cohort compared with the control cohort (odds ratio [OR], 1.67-3.94; p < .001]) were sleep disorders (restless legs syndrome, obstructive sleep apnea, and insomnia), mood disorders (depression, dysthymia, and anxiety), and pain disorders (chronic pain syndrome, migraine, fibromyalgia, carpal tunnel syndrome, and myalgia). Other comorbidities significantly associated with narcolepsy (OR, 1.33-1.95) were irritable bowel syndrome (p < .001), asthma (p < .001), cervical spondylosis (p < .01), syncope (p < .01), and hypothyroidism (p < .05).

Conclusions: This propensity-matched cohort study demonstrates increased psychiatric, sleep, and pain disorders in patients living with narcolepsy and challenges beyond narcolepsy-specific symptoms in this population. Understanding common narcolepsy-associated comorbidities may assist in tailoring treatment modalities.

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嗜睡症患者的人口统计学特征和合并症:倾向匹配队列研究。
研究目的:由于症状、疾病严重程度和并发症的不同,嗜睡症的表型非常复杂。这是第一项使用电子健康记录(EHR)数据和自然语言处理(NLP)算法来描述一大批嗜睡症患者的人口统计学特征和合并症的研究:对首次就诊于梅奥诊所(2000-2020 年)的患者进行鉴定,这些患者的临床笔记中≥1 个嗜睡症特异性 ICD-9/10 编码且≥1 个疾病支持性声明(使用 NLP 算法鉴定)。对照组的出生年份、首次就诊年龄、性别、种族、民族、诊断代码数量和死亡率进行了倾向匹配。对不同队列的常见合并症进行了比较和排序:在电子病历数据库(N = 6 389 186 名患者)中,确定了 2057 名嗜睡症患者(中位年龄为 32 岁;59.6% 为女性;92.6% 为白人;89.2% 为非西班牙裔),并与对照组进行了倾向匹配。在前 20 种合并症中,嗜睡症队列与对照队列相比发生率更高(几率比 [OR],1.67-3.94;p p p p p p p p p p p p p 结论:这项倾向匹配队列研究表明,嗜睡症患者的精神、睡眠和疼痛疾病有所增加,该人群面临着嗜睡症特异性症状之外的挑战。了解常见的嗜睡症相关合并症可能有助于定制治疗模式。
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