Strunk Andrew, Midura Margaretta, Papagermanos Vassiliki, Alloo Allireza, Garg Amit
Department of Dermatology, Hofstra Northwell School of Medicine, New Hyde Park, NY, USA.
Dermatology. 2017;233(1):53-57. doi: 10.1159/000468148. Epub 2017 Apr 28.
Requisite to the application of clinical databases for observational research in hidradenitis suppurativa (HS) is the identification of an accurate case cohort.
To assess the validity of utilizing administrative codes to establish the HS cohort from a large clinical database.
In this retrospective study using chart review as the reference standard, we calculated several estimates of the diagnostic accuracy of at least 1 ICD-9 code for HS.
Estimates of the diagnostic accuracy of at least 1 ICD-9 code for HS include sensitivity 100% (95% CI 98-100), specificity 83% (95% CI 77-88), positive predictive value 79% (95% CI 72-85), negative predictive value 100% (95% CI 98-100), accuracy 90% (95% CI 86-93), and kappa statistic 79% (95% CI 73-86).
The case-finding algorithm employing at least 1 ICD-9 code for HS provides balance in achieving accuracy and adequate power, both necessary in the evaluation of a less common disease and its potential association with uncommon or even rare events.
在化脓性汗腺炎（HS）的观察性研究中应用临床数据库的前提是确定准确的病例队列。
评估利用行政编码从大型临床数据库中建立HS队列的有效性。
在这项以图表审查作为参考标准的回顾性研究中，我们计算了至少1个HS的ICD-9编码诊断准确性的几种估计值。
至少1个HS的ICD-9编码诊断准确性的估计值包括灵敏度100%（95%置信区间98-100）、特异度83%（95%置信区间77-88）、阳性预测值79%（95%置信区间72-85）、阴性预测值100%（95%置信区间98-100）、准确度90%（95%置信区间86-93）和kappa统计量79%（95%置信区间73-86）。
采用至少1个HS的ICD-9编码的病例发现算法在实现准确性和足够的检验效能方面取得了平衡，这两者在评估一种不太常见的疾病及其与不常见甚至罕见事件的潜在关联时都是必要的。
