自闭症谱系障碍中的共病聚类：电子健康记录时间序列分析。
Comorbidity clusters in autism spectrum disorders: an electronic health record time-series analysis.
机构信息
Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02115.
出版信息
Pediatrics. 2014 Jan;133(1):e54-63. doi: 10.1542/peds.2013-0819. Epub 2013 Dec 9.
OBJECTIVE
The distinct trajectories of patients with autism spectrum disorders (ASDs) have not been extensively studied, particularly regarding clinical manifestations beyond the neurobehavioral criteria from the Diagnostic and Statistical Manual of Mental Disorders. The objective of this study was to investigate the patterns of co-occurrence of medical comorbidities in ASDs.
METHODS
International Classification of Diseases, Ninth Revision codes from patients aged at least 15 years and a diagnosis of ASD were obtained from electronic medical records. These codes were aggregated by using phenotype-wide association studies categories and processed into 1350-dimensional vectors describing the counts of the most common categories in 6-month blocks between the ages of 0 to 15. Hierarchical clustering was used to identify subgroups with distinct courses.
RESULTS
Four subgroups were identified. The first was characterized by seizures (n = 120, subgroup prevalence 77.5%). The second (n = 197) was characterized by multisystem disorders including gastrointestinal disorders (prevalence 24.3%) and auditory disorders and infections (prevalence 87.8%), and the third was characterized by psychiatric disorders (n = 212, prevalence 33.0%). The last group (n = 4316) could not be further resolved. The prevalence of psychiatric disorders was uncorrelated with seizure activity (P = .17), but a significant correlation existed between gastrointestinal disorders and seizures (P < .001). The correlation results were replicated by using a second sample of 496 individuals from a different geographic region.
CONCLUSIONS
Three distinct patterns of medical trajectories were identified by unsupervised clustering of electronic health record diagnoses. These may point to distinct etiologies with different genetic and environmental contributions. Additional clinical and molecular characterizations will be required to further delineate these subgroups.
目的
自闭症谱系障碍（ASD）患者的不同轨迹尚未得到广泛研究，特别是在《精神障碍诊断与统计手册》的神经行为标准之外的临床表现方面。本研究旨在探讨 ASD 中合并症的共病模式。
方法
从电子病历中获取至少 15 岁且诊断为 ASD 的患者的国际疾病分类，第九版编码。这些编码通过表型广泛关联研究类别进行汇总，并处理为 1350 维向量，描述了 0 至 15 岁之间每 6 个月的最常见类别计数。使用层次聚类识别具有不同病程的亚组。
结果
鉴定出 4 个亚组。第一个以癫痫发作（n = 120，亚组患病率 77.5%）为特征。第二个（n = 197）以包括胃肠道疾病（患病率 24.3%）、听觉障碍和感染（患病率 87.8%）在内的多系统疾病为特征，第三个以精神疾病（n = 212，患病率 33.0%）为特征。最后一组（n = 4316）无法进一步分类。精神疾病的患病率与癫痫活动无关（P =.17），但胃肠道疾病与癫痫发作之间存在显著相关性（P <.001）。使用来自不同地理区域的第二个 496 人样本的复制结果验证了相关性。
结论
通过对电子健康记录诊断进行无监督聚类，确定了三种不同的医疗轨迹模式。这些可能指向具有不同遗传和环境贡献的不同病因。需要进行额外的临床和分子特征描述以进一步划分这些亚组。
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