Institute of Family Medicine, University Medical Centre Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.
Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany.
J Med Internet Res. 2023 Dec 14;25:e46929. doi: 10.2196/46929.
Primary care is known to be one of the most complex health care settings because of the high number of theoretically possible diagnoses. Therefore, the process of clinical decision-making in primary care includes complex analytical and nonanalytical factors such as gut feelings and dealing with uncertainties. Artificial intelligence is also mandated to offer support in finding valid diagnoses. Nevertheless, to translate some aspects of what occurs during a consultation into a machine-based diagnostic algorithm, the probabilities for the underlying diagnoses (odds ratios) need to be determined.
Cough is one of the most common reasons for a consultation in general practice, the core discipline in primary care. The aim of this scoping review was to identify the available data on cough as a predictor of various diagnoses encountered in general practice. In the context of an ongoing project, we reflect on this database as a possible basis for a machine-based diagnostic algorithm. Furthermore, we discuss the applicability of such an algorithm against the background of the specifics of general practice.
The PubMed, Scopus, Web of Science, and Cochrane Library databases were searched with defined search terms, supplemented by the search for gray literature via the German Journal of Family Medicine until April 20, 2023. The inclusion criterion was the explicit analysis of cough as a predictor of any conceivable disease. Exclusion criteria were articles that did not provide original study results, articles in languages other than English or German, and articles that did not mention cough as a diagnostic predictor.
In total, 1458 records were identified for screening, of which 35 articles met our inclusion criteria. Most of the results (11/35, 31%) were found for chronic obstructive pulmonary disease. The others were distributed among the diagnoses of asthma or unspecified obstructive airway disease, various infectious diseases, bronchogenic carcinoma, dyspepsia or gastroesophageal reflux disease, and adverse effects of angiotensin-converting enzyme inhibitors. Positive odds ratios were found for cough as a predictor of chronic obstructive pulmonary disease, influenza, COVID-19 infections, and bronchial carcinoma, whereas the results for cough as a predictor of asthma and other nonspecified obstructive airway diseases were inconsistent.
Reliable data on cough as a predictor of various diagnoses encountered in general practice are scarce. The example of cough does not provide a sufficient database to contribute odds to a machine learning-based diagnostic algorithm in a meaningful way.
初级保健被认为是医疗保健中最复杂的环境之一，因为理论上可能的诊断数量众多。因此，初级保健中的临床决策过程包括复杂的分析和非分析因素，例如直觉和应对不确定性。人工智能也被要求提供支持以找到有效的诊断。然而，要将咨询过程中的某些方面转化为基于机器的诊断算法，需要确定潜在诊断的概率（优势比）。
咳嗽是全科医生咨询最常见的原因之一，是初级保健的核心学科。本综述的目的是确定咳嗽作为全科医生中遇到的各种诊断的预测因素的可用数据。在一个正在进行的项目中，我们反思了这个数据库，作为基于机器的诊断算法的可能基础。此外，我们还讨论了在全科医学的具体背景下应用这种算法的适用性。
使用定义的搜索词在 PubMed、Scopus、Web of Science 和 Cochrane Library 数据库中进行搜索，并通过德国家庭医学杂志补充灰色文献的搜索，直到 2023 年 4 月 20 日。纳入标准是明确分析咳嗽作为任何可想象疾病的预测因素。排除标准是未提供原始研究结果的文章、非英语或德语的文章以及未将咳嗽作为诊断预测因素提及的文章。
共筛选出 1458 条记录，其中 35 篇文章符合我们的纳入标准。大多数结果（11/35，31%）是针对慢性阻塞性肺疾病的。其余的分布在哮喘或未指定的气道阻塞性疾病、各种传染病、支气管癌、消化不良或胃食管反流病以及血管紧张素转换酶抑制剂的不良反应的诊断中。作为慢性阻塞性肺疾病、流感、COVID-19 感染和支气管癌的预测因素，咳嗽的阳性优势比得到了发现，而咳嗽作为哮喘和其他未指定的气道阻塞性疾病的预测因素的结果则不一致。
有关咳嗽作为全科医生中遇到的各种诊断的预测因素的可靠数据稀缺。咳嗽的例子没有提供足够的数据库，无法为基于机器学习的诊断算法提供有意义的概率。
