Discovering prescription patterns in pediatric acute-onset neuropsychiatric syndrome patients,Journal of Biomedical informatics

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Discovering prescription patterns in pediatric acute-onset neuropsychiatric syndrome patients
Journal of Biomedical informatics ( IF 4.0 ) Pub Date : 2020-12-28 , DOI: 10.1016/j.jbi.2020.103664
Arturo Lopez Pineda ₁ , Armin Pourshafeie ₂ , Alexander Ioannidis ₃ , Collin McCloskey Leibold ₄ , Avis L Chan ₅ , Carlos D Bustamante ₆ , Jennifer Frankovich ₅ , Genevieve L Wojcik ₇

Affiliation

Objective

Pediatric acute-onset neuropsychiatric syndrome (PANS) is a complex neuropsychiatric syndrome characterized by an abrupt onset of obsessive-compulsive symptoms and/or severe eating restrictions, along with at least two concomitant debilitating cognitive, behavioral, or neurological symptoms. A wide range of pharmacological interventions along with behavioral and environmental modifications, and psychotherapies have been adopted to treat symptoms and underlying etiologies. Our goal was to develop a data-driven approach to identify treatment patterns in this cohort.

Materials and methods

In this cohort study, we extracted medical prescription histories from electronic health records. We developed a modified dynamic programming approach to perform global alignment of those medication histories. Our approach is unique since it considers time gaps in prescription patterns as part of the similarity strategy.

Results

This study included 43 consecutive new-onset pre-pubertal patients who had at least 3 clinic visits. Our algorithm identified six clusters with distinct medication usage history which may represent clinician’s practice of treating PANS of different severities and etiologies i.e., two most severe groups requiring high dose intravenous steroids; two arthritic or inflammatory groups requiring prolonged nonsteroidal anti-inflammatory drug (NSAID); and two mild relapsing/remitting group treated with a short course of NSAID. The psychometric scores as outcomes in each cluster generally improved within the first two years.

Discussion and conclusion

Our algorithm shows potential to improve our knowledge of treatment patterns in the PANS cohort, while helping clinicians understand how patients respond to a combination of drugs.

中文翻译：

发现小儿急性发作神经精神病综合症患者的处方模式

目的

小儿急性发作性神经精神病综合症（PANS）是一种复杂的神经精神病综合症，其特征在于突然出现强迫症和/或严重的饮食限制，以及至少两种同时使人衰弱的认知，行为或神经系统症状。广泛的药理干预措施以及行为和环境改变以及心理疗法已被采用来治疗症状和潜在病因。我们的目标是开发一种数据驱动的方法来识别该队列中的治疗方式。

材料和方法

在这项队列研究中，我们从电子健康记录中提取了医疗处方历史。我们开发了一种经过修改的动态编程方法来对这些用药历史进行全局调整。我们的方法是独特的，因为它将处方模式中的时间间隔视为相似策略的一部分。

结果

这项研究包括43位连续新发青春期前患者，他们至少接受了3次门诊就诊。我们的算法确定了六个具有不同药物使用历史的簇，这可能代表临床医生治疗不同严重程度和病因的PANS的实践，即，两个最严重的组需要大剂量静脉内类固醇治疗；两个关节炎或炎症组需要延长的非甾体抗炎药（NSAID）；以及两个接受短期NSAID治疗的轻度复发/缓解组。在每个组中，作为结果的心理测验得分通常在头两年内有所改善。