den Brinker Albertus C, Thackray-Nocera Susannah, Crooks Michael G, Morice Alyn H
Independent Researcher, NL-5708 DJ Helmond, The Netherlands.
Centre for Clinical Science, Hull York Medical School, University of Hull, Cottingham HU16 5JQ, UK.
J Clin Med. 2025 Jun 25;14(13):4506. doi: 10.3390/jcm14134506.
Cough monitoring for exacerbation detection is optimally effective if used for the appropriate cohort of chronic obstructive pulmonary disease (COPD) patients, i.e., increased cough during exacerbation and prodrome is a prerequisite enabling (early) detection. A post hoc analysis of data from a validation study on an alert system for exacerbation detection based on nighttime cough was used to study if patient data were predictive for the increased cough during exacerbation and for cough count distribution. The quantitative effect on the performance of the alert system when using patient stratification was studied as well. Patient data were not predictive for robust cough statistics: neither the nighttime cough count median nor the interquartile range were found to have statistically relevant correlation with the available patient data. Patients with and without increased cough during exacerbation did show differences in their characteristics. Using patient age and symptom questionnaire data, a classifier based on a logistic regression model was parametrised having an accuracy of 85% in predicting presence or absence of increased cough during exacerbation. Using the classifier for patient stratification, the performance of the exacerbation alert system increased with sensitivity going from 59 to 76%. The post hoc analysis suggests that patient data can be used to stratify COPD patients for cough monitoring.
如果将咳嗽监测用于慢性阻塞性肺疾病（COPD）患者的适当队列，以检测病情加重，那么它将具有最佳效果，即病情加重和前驱期咳嗽增加是（早期）检测的先决条件。基于夜间咳嗽的病情加重警报系统验证研究的数据进行了事后分析，以研究患者数据是否可预测病情加重期间咳嗽增加以及咳嗽计数分布情况。还研究了使用患者分层时对警报系统性能的定量影响。患者数据无法预测可靠的咳嗽统计数据：夜间咳嗽计数中位数和四分位数间距均与可用患者数据无统计学上的相关关联。病情加重期间咳嗽增加和未增加的患者在特征上确实存在差异。利用患者年龄和症状问卷数据，基于逻辑回归模型的分类器得以参数化，在预测病情加重期间咳嗽增加与否方面的准确率为85%。使用该分类器进行患者分层，病情加重警报系统的性能有所提高，敏感性从59%提高到76%。事后分析表明，患者数据可用于对COPD患者进行分层以进行咳嗽监测。
