Characterization of Chronic Pain and its Biopsychosocial Mechanisms in Lupus using Electronic Health Records

多达1亿美国人生活在持续的痛苦中，每年花费6350亿美元。在美国，有 有20多万人患有系统性红斑狼疮，这是一种多器官的慢性炎症性风湿病 不成比例地影响女性和少数族裔的参与。患有慢性疾病，如 系统性红斑狼疮带来了多重挑战。疼痛是系统性红斑狼疮患者常见的自我报告症状，通常是首发症状之一。 这种疾病的症状。尽管治疗取得了进展，但疼痛仍然是最突出的、未被解决的患者 投诉。系统性红斑狼疮的疼痛管理最近变得更具挑战性，因为 阿片类药物滥用造成的成瘾流行和死亡率。估计31-46%的系统性红斑狼疮患者使用 处方类阿片。在一项研究中，70%的阿片类药物使用者在≥中使用了1年，22%的人 同时服用≥-2类阿片类药物。系统性红斑狼疮患者的患病几率几乎是普通患者的两倍。 与阿片类药物相关的过量住院人数。然而，减少阿片类药物滥用的努力不能 在没有对潜在的临床研究进行详细了解和持续投资的情况下实现 产生和维持慢性疼痛的机制。系统性红斑狼疮慢性疼痛负担的特征是 对至少两项指控提出质疑。首先，我们缺乏关于SLE慢性疼痛的患病率和负担的数据， 部分原因是缺乏可靠的方法来识别具有临床显著疼痛的患者的电子 健康记录(EHR)。其次，迫切需要了解生物-心理-社会机制和 导致系统性红斑狼疮疼痛体验的相关因素。在这个指导职业发展奖(K01)中，Titilola博士 法拉辛努将利用计算方法提高对慢性阻塞性肺疾病临床管理的认识 使用EHR治疗系统性红斑狼疮的疼痛。在目标1中，法拉辛努博士将开发一种计算性慢性疼痛表型 使用诊断代码、疼痛评分、叙述性临床记录和从电子病历中提取的药物的算法 两个大型医疗保健系统(n~2400)。然后，她将使用该算法来估计慢性疼痛的流行率 在基于人口的登记中(n~76,000)。在目标2中，法拉辛努博士将全面表型 慢性疼痛的生物-心理-社会相关性使用现有的登记的约500名SLE患者参加 多学科疼痛中心。在整个奖项过程中，法拉辛努博士将以她的博士培训为基础 流行病学家和生物统计学家在生物医学信息学方面开发新技能以传导冲击性疼痛 医学研究。这些技能将包括使用电子病历和注册表数据、机器学习和自然 语言处理、疼痛科学、拨款申请和科学交流。通过课程学习，临床 在疼痛医学诊所、导师以及外部会议和研讨会上的观察，法拉辛努医生将 获得申请她的第一个R01所需的技能，并追求终身教职轨道首席调查员的职业生涯。

Up to 100 million Americans live with ongoing pain, costing $635 billion annually. In the United States, there are more than 200,000 people living with SLE, a chronic inflammatory rheumatic disease with multi-organ involvement that disproportionately affects females and racial minorities. Living with a chronic disease such as SLE confers multiple challenges. Pain is a frequent self-reported symptom in SLE and is often one of the first symptoms of the disease. Despite treatment advances, pain remains the most prominent, unaddressed patient complaint. The management of pain in SLE has recently become more challenging because of the alarming epidemic of addiction and mortality attributed to opioid misuse. An estimated 31-46% of patients with SLE use prescription opioids. In one study, 70% of individuals using opioids used them for ≥1 year, and 22% were taking ≥2 opioid medications at the same time. Patients with SLE are nearly twice as likely as the general population to have opioid-related overdose hospitalizations. However, efforts to mitigate opioid misuse cannot be achieved without a detailed understanding and sustained investment in clinical research on the underlying mechanisms that produce and maintain chronic pain. Characterizing the burden of chronic pain in SLE is challenging on at least two counts. First, we lack data on the prevalence and burden of chronic pain in SLE, partly due to the absence of reliable approaches to identify patients with clinically significant pain in electronic health records (EHR). Second, there is a critical need to understand the biopsychosocial mechanisms and correlates that drive the pain experience in SLE. In this mentored career development award (K01), Dr. Titilola Falasinnu will use computational methods to increase the understanding of the clinical management chronic pain in SLE using EHR. In Aim 1, Dr. Falasinnu will develop a computational chronic pain phenotyping algorithm using diagnostic codes, pain scores, narrative clinic notes and medications extracted from the EHRs of two large healthcare systems (n~2,400). She will then use the algorithm to estimate chronic pain prevalence in a population-based registry (n~76,000). In Aim 2, Dr. Falasinnu will comprehensively phenotype biopsychosocial correlates of chronic pain using an existing registry of ~500 patients with SLE attending a multi-disciplinary pain center. Throughout the award, Dr. Falasinnu will build on her doctoral training as an epidemiologist and biostatistician to develop new skills in biomedical informatics to conduct impactful pain medicine research. These skills will include working with EHR and registry data, machine learning and natural language processing, pain science, grant-writing, and scientific communication. Through coursework, clinical observation in pain medicine clinics, mentorship, and external conferences and workshops, Dr. Falasinnu will gain the skills needed to apply for her first R01 and pursue a career as a tenure-track principal investigator.