Abstract：
OBJECTIVE: The increasing implementation of electronic health records allows the use of advanced text-mining methods for establishing new patient phenotypes and stratification, and for revealing outcome correlations. In this study, we aimed to explore the electronic narrative clinical reports of a cohort of patients with Dravet syndrome (DS) longitudinally followed at our center, to identify the capacity of this methodology to retrace natural history of DS during the early years.
METHODS: We used a document-based clinical data warehouse employing natural language processing to recognize the phenotype concepts in the narrative medical reports. We included patients with DS who have a medical report produced before the age of 2 years and a follow-up after the age of 3 years (\"DS cohort,\" 56 individuals). We selected two control populations, a \"general control cohort\" (275 individuals) and a \"neurological control cohort\" (281 individuals), with similar characteristics in terms of gender, number of reports, and age at last report. To find concepts specifically associated with DS, we performed a phenome-wide association study using Cox regression, comparing the reports of the three cohorts. We then performed a qualitative analysis of the surviving concepts based on their median age at first appearance.
RESULTS: A total of 76 concepts were prevalent in the reports of children with DS. Concepts appearing during the first 2 years were mostly related with the epilepsy features at the onset of DS (convulsive and prolonged seizures triggered by fever, often requiring in-hospital care). Subsequently, concepts related to new types of seizures and to drug resistance appeared. A series of non-seizure-related concepts emerged after the age of 2-3 years, referring to the nonseizure comorbidities classically associated with DS.
CONCLUSIONS: The extraction of clinical terms by narrative reports of children with DS allows outlining the known natural history of this rare disease in early childhood. This original model of \"longitudinal phenotyping\" could be applied to other rare and very rare conditions with poor natural history description.
METHODS: We used a document-based clinical data warehouse employing natural language processing to recognize the phenotype concepts in the narrative medical reports. We included patients with DS who have a medical report produced before the age of 2 years and a follow-up after the age of 3 years (\"DS cohort,\" 56 individuals). We selected two control populations, a \"general control cohort\" (275 individuals) and a \"neurological control cohort\" (281 individuals), with similar characteristics in terms of gender, number of reports, and age at last report. To find concepts specifically associated with DS, we performed a phenome-wide association study using Cox regression, comparing the reports of the three cohorts. We then performed a qualitative analysis of the surviving concepts based on their median age at first appearance.
RESULTS: A total of 76 concepts were prevalent in the reports of children with DS. Concepts appearing during the first 2 years were mostly related with the epilepsy features at the onset of DS (convulsive and prolonged seizures triggered by fever, often requiring in-hospital care). Subsequently, concepts related to new types of seizures and to drug resistance appeared. A series of non-seizure-related concepts emerged after the age of 2-3 years, referring to the nonseizure comorbidities classically associated with DS.
CONCLUSIONS: The extraction of clinical terms by narrative reports of children with DS allows outlining the known natural history of this rare disease in early childhood. This original model of \"longitudinal phenotyping\" could be applied to other rare and very rare conditions with poor natural history description.
摘要：
目的：电子健康记录的日益实施允许使用高级文本挖掘方法来建立新的患者表型和分层，以及揭示结果相关性。在这项研究中，我们旨在探索在我们中心纵向随访的Dravet综合征（DS）患者队列的电子叙事临床报告，以确定这种方法在早期追溯DS自然史的能力。
方法：我们使用基于文档的临床数据仓库，采用自然语言处理来识别叙事医学报告中的表型概念。我们纳入了DS患者，他们在2岁之前出具了医学报告，在3岁之后进行了随访（“DS队列”-56人）。我们选择了两个对照种群，“一般控制队列”（275人）和“神经控制队列”（281人），在性别方面具有相似的特征，报告的数量和上次报告的年龄。要查找与DS特别相关的概念，我们使用Cox回归进行了全表型关联研究，比较三个队列的报告。然后，我们根据首次出现的中位年龄对幸存的概念进行了定性分析。
结果：共有76个概念在DS儿童的报告中普遍存在。最初2年内出现的概念主要与DS发作时的癫痫特征有关（由发烧引发的抽搐和长时间癫痫发作，通常需要住院护理)。随后，出现了与新型癫痫发作和耐药性相关的概念。在2-3岁之后出现了一系列与癫痫发作无关的概念，指的是与DS相关的非癫痫合并症。
结论：通过DS患儿的叙述性报告提取临床术语，允许概述这种罕见疾病在儿童早期的已知自然史。这种“纵向表型”的原始模型可应用于自然史描述较差的其他罕见和非常罕见的条件。
方法：我们使用基于文档的临床数据仓库，采用自然语言处理来识别叙事医学报告中的表型概念。我们纳入了DS患者，他们在2岁之前出具了医学报告，在3岁之后进行了随访（“DS队列”-56人）。我们选择了两个对照种群，“一般控制队列”（275人）和“神经控制队列”（281人），在性别方面具有相似的特征，报告的数量和上次报告的年龄。要查找与DS特别相关的概念，我们使用Cox回归进行了全表型关联研究，比较三个队列的报告。然后，我们根据首次出现的中位年龄对幸存的概念进行了定性分析。
结果：共有76个概念在DS儿童的报告中普遍存在。最初2年内出现的概念主要与DS发作时的癫痫特征有关（由发烧引发的抽搐和长时间癫痫发作，通常需要住院护理)。随后，出现了与新型癫痫发作和耐药性相关的概念。在2-3岁之后出现了一系列与癫痫发作无关的概念，指的是与DS相关的非癫痫合并症。
结论：通过DS患儿的叙述性报告提取临床术语，允许概述这种罕见疾病在儿童早期的已知自然史。这种“纵向表型”的原始模型可应用于自然史描述较差的其他罕见和非常罕见的条件。
