Chronic obstructive lung disease "expert system": validation of a predictive tool for assisting diagnosis.
Chronic obstructive lung disease "expert system": validation of a predictive tool for assisting diagnosis.
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DOI：
10.2147/copd.s165533
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发表时间：
2018
影响因子：
2.8
通讯作者：
Solidoro P
中科院分区：
文献类型：
--
作者：
Braido F;Santus P;Corsico AG;Di Marco F;Melioli G;Scichilone N;Solidoro P
本研究的目的是开发和验证一个专家系统（ES），旨在支持慢性阻塞性肺疾病（COLD）的诊断。开发了一份调查问卷和一个WebFlex代码，并通过计算机进行了验证。对60例病例进行了专家小组试点验证，对241例病例进行了临床验证。开发的问卷和代码在计算机上验证，产生了一个合适的工具，以支持医疗诊断。ES的临床验证是在包括六个不同的呼吸系统疾病参考中心的学术环境中进行的。ES的结果表示为与患感冒的风险相关的评分，并与最终的临床诊断进行匹配和比较。一组60例患者由试点专家小组验证进行评价，目的是计算临床验证研究的样本量。这些初步ES评分与专家诊断之间的一致性分析表明，当专家和系统均确认COLD诊断时，准确率为94.7%，当排除COLD时，准确率为86.3%。基于这些结果，在240例患者中确定了验证集的样本量。对241例患者进行的临床验证，ES准确率为97.5%，53.6%的病例确诊为COLD，32%的病例排除了COLD诊断。在11.2%的病例中，专家诊断为COLD，尽管成像结果显示潜在的伴随疾病。这里介绍的ES（COLDES）是一种安全可靠的支持工具，用于初级保健环境中的COLD诊断。
The purposes of this study were development and validation of an expert system (ES) aimed at supporting the diagnosis of chronic obstructive lung disease (COLD). A questionnaire and a WebFlex code were developed and validated in silico. An expert panel pilot validation on 60 cases and a clinical validation on 241 cases were performed. The developed questionnaire and code validated in silico resulted in a suitable tool to support the medical diagnosis. The clinical validation of the ES was performed in an academic setting that included six different reference centers for respiratory diseases. The results of the ES expressed as a score associated with the risk of suffering from COLD were matched and compared with the final clinical diagnoses. A set of 60 patients were evaluated by a pilot expert panel validation with the aim of calculating the sample size for the clinical validation study. The concordance analysis between these preliminary ES scores and diagnoses performed by the experts indicated that the accuracy was 94.7% when both experts and the system confirmed the COLD diagnosis and 86.3% when COLD was excluded. Based on these results, the sample size of the validation set was established in 240 patients. The clinical validation, performed on 241 patients, resulted in ES accuracy of 97.5%, with confirmed COLD diagnosis in 53.6% of the cases and excluded COLD diagnosis in 32% of the cases. In 11.2% of cases, a diagnosis of COLD was made by the experts, although the imaging results showed a potential concomitant disorder. The ES presented here (COLDES) is a safe and robust supporting tool for COLD diagnosis in primary care settings.