Gout Emergency Department Chief Complaint Corpora

The Gout Emergency Department Chief Complaint Corpora (GED3C) consists of 2 corpora of free text triage nurse chief complaints (up to 282 characters in length) collected from 2019 to 2020 at an academic medical center in the Deep South. The smaller corpus "GOUT-CC-2019-CORPUS" consists of 300 chief complaints from 2019 selected by the presence of the keyword "gout". The larger corpus "GOUT-CC-2020-CORPUS" contains 8037 chief complaints collected from a single month in 2020. No other selection criteria (gout or otherwise) was used to generate GOUT-CC-2020-CORPUS, making this corpus representative for medical conditions of interest in the underlying urban Black majority Emergency Department patient population.

We anticipate this corpus being useful in the development of Emergency Department alerting algorithms for gout. Both GOUT-CC-2019-CORPUS and GOUT-CC-2020-CORPUS were annotated with respect to predicted gout flare status as determined retrospectively by manual review of the chief complaint. A subset of patients with these chief complaints underwent chart review by rheumatologists to verify gout flare status guided by the Gaffo criteria. These corpora may be useful to researchers at other institutions who want to develop or validate existing alerting algorithms at a 2nd institution. These corpora are also available for use in masked language model development. Its terse, abbreviation-rich content sets it apart from more lengthy clinical text and to our knowledge this is the only chief complaint corpus publicly available.

Gout Emergency Department Chief Complaint Corpora（GED3C）由2019年至2020年间在南方某学术医疗中心收集的免费文本分级护士主诉（长度最多为282个字符）的两大语料库组成。较小的语料库“GOUT-CC-2019-CORPUS”包含2019年选取的300份含有关键词“痛风”的主诉。较大的语料库“GOUT-CC-2020-CORPUS”包含2020年一个月内收集的8037份主诉。在生成GOUT-CC-2020-CORPUS的过程中，未采用其他选择标准（包括痛风与否），使得该语料库能够代表基础城市黑人多数急诊科患者群体的医学关注疾病。我们预计该语料库将在痛风急诊科警报算法的开发中发挥重要作用。GOUT-CC-2019-CORPUS和GOUT-CC-2020-CORPUS均按照预测痛风发作状态进行了标注，该状态是通过回顾性人工审查主诉来确定的。具有这些主诉的患者子集接受了风湿病学家的病历审查，以Gaffo标准为指导验证痛风发作状态。这些语料库可能对其他机构的研究人员有用，他们希望在第二机构开发或验证现有的警报算法。这些语料库也适用于掩码语言模型的发展。其简洁、丰富的缩略语内容使其区别于更长的临床文本，据我们所知，这是唯一公开可用的主诉语料库。