Objective To compare the clinical characteristics of chronic cough, and to establish the Modified Cough Assessment Test and the simple decision tree to improve the efficacy of etiologic diagnosis. Methods Patients with chronic cough consulted in Tongji Hospital between October 2021 and August 2023 were enrolled in our study. The patients with identified single cause were divided into 3 groups accordingly: corticosteroid-responsive cough (CRC), upper airway cough syndrome (UACS) and gastroesophageal reflux-related cough (GERC). And the characteristics of chronic cough in different causes were assessed and compared by cough questionnaires. Independent predictors of various causes were identified by multivariate logistic regression analysis and used to establish the Modified Cough Assessment Test (MCET) and to construct the simple decision tree. Results A total of 358 patients were enrolled, including 201 with CRC (56.1%), 125 with UACS (34.9%) and 32 with GERC (8.94%). "Cough with wheezing or chest tightness" (OR=3.222, 95%CI 2.144 - 4.843, P<0.001), "Cough with daytime heaviness and nighttime lightness" (OR=1.755, 95%CI 1.264 - 2.435, P<0.001), and "Cough with acid reflux, heartburn or indigestion" (OR=15.580, 95%CI 5.894 - 41.184, P<0.001) were independent factors for each group, respectively. The area under ROC curve for classification of CRC, UACS and GERC were 0.871, 0.840 and 0.988 for MCET, which were better than those of Leicester Cough Questionnaire (LCQ) (0.792, 0.766 and 0.913) and Cough Evaluation Test (CET) (0.649, 0.691 and 0.580). The accuracy of the simple decision tree for the differential diagnosis of chronic cough was 77.4%. Conclusion The simple decision tree based on the Modified Cough Evaluation Test is a simple and effective method of etiologic diagnosis of chronic cough, which can be used as a tool to improve the efficacy of clinical diagnosis in outpatient settings.
ObjectiveTo explore the independent factors related to clinical severe events in community acquired pneumonia patients and to find out a simple, effective and more accurate prediction method.MethodsConsecutive patients admitted to our hospital from August 2018 to July 2019 were enrolled in this retrospective study. The endpoint was the occurrence of severe events defined as a condition as follows intensive care unit admission, the need for mechanical ventilation or vasoactive drugs, or 30-day mortality during hospitalization. The patients were divided into severe event group and non-severe event group, and general clinical data were compared between two groups. Multivariate logistic regression analysis was performed to identify the independent predictors of adverse outcomes. Receiver operating characteristic (ROC) curve was constructed to calculate and compare the area under curve (AUC) of different prediction methods.ResultsA total of 410 patients were enrolled, 96 (23.4%) of whom experienced clinical severe events. Age (OR: 1.035, 95%CI: 1.012 - 1.059, P=0.003), high-density lipoprotein (OR: 0.266, 95%CI: 0.088 - 0.802, P=0.019) and lactate dehydrogenase (OR: 1.006, 95%CI: 1.004 - 1.059, P<0.001) levels on admission were independent factors associated with clinical severe events in CAP patients. The AUCs in the prediction of clinical severe events were 0.744 (95%CI: 0.699 - 0.785, P=0.028) and 0.814 (95%CI: 0.772 - 0.850, P=0.025) for CURB65 and PSI respectively. CURB65-LH, combining CURB65, HDL and LDH simultaneously, had the largest AUC of 0.843 (95%CI: 0.804 - 0.876, P=0.022) among these prediction methods and its sensitivity (69.8%) and specificity (81.5%) were higher than that of CURB65 (61.5% and 76.1%) respectively.ConclusionCURB65-LH is a simple, effective and more accurate prediction method of clinical severe events in CAP patients, which not only has higher sensitivity and specificity, but also significantly improves the predictive value when compared with CURB65.