Department of Tuberculosis, Kunming Third People's Hospital/Yunnan Clinical Medical Center for Infectious Diseases, Kunming, 650041, China.
Department of Radiology, The People's Hospital of Lincang, Lincang, Yunnan, 677000, China.
BMC Infect Dis. 2024 Jun 8;24(1):571. doi: 10.1186/s12879-024-09461-3.
In this study, we examined the value of chest CT signs combined with peripheral blood eosinophil percentage in differentiating between pulmonary paragonimiasis and tuberculous pleurisy in children.
Patients with pulmonary paragonimiasis and tuberculous pleurisy were retrospectively enrolled from January 2019 to April 2023 at the Kunming Third People's Hospital and Lincang People's Hospital. There were 69 patients with pulmonary paragonimiasis (paragonimiasis group) and 89 patients with tuberculous pleurisy (tuberculosis group). Clinical symptoms, chest CT imaging findings, and laboratory test results were analyzed. Using binary logistic regression, an imaging model of CT signs and a combined model of CT signs and eosinophils were developed to calculate and compare the differential diagnostic performance of the two models.
CT signs were used to establish the imaging model, and the receiver operating characteristic (ROC) curve was plotted. The area under the curve (AUC) was 0.856 (95% CI: 0.799-0.913), the sensitivity was 66.7%, and the specificity was 88.9%. The combined model was established using the CT signs and eosinophil percentage, and the ROC was plotted. The AUC curve was 0.950 (95% CI: 0.919-0.980), the sensitivity was 89.9%, and the specificity was 90.1%. The differential diagnostic efficiency of the combined model was higher than that of the imaging model, and the difference in AUC was statistically significant.
The combined model has a higher differential diagnosis efficiency than the imaging model in the differentiation of pulmonary paragonimiasis and tuberculous pleurisy in children. The presence of a tunnel sign on chest CT, the absence of pulmonary nodules, and an elevated percentage of peripheral blood eosinophils are indicative of pulmonary paragonimiasis in children.
本研究旨在探讨胸部 CT 征象联合外周血嗜酸性粒细胞百分比在儿童肺吸虫病与结核性胸膜炎鉴别诊断中的价值。
回顾性纳入 2019 年 1 月至 2023 年 4 月于昆明市第三人民医院和临沧市人民医院就诊的肺吸虫病和结核性胸膜炎患儿，共纳入肺吸虫病患儿 69 例（肺吸虫组）和结核性胸膜炎患儿 89 例（结核组）。分析其临床症状、胸部 CT 影像学表现和实验室检查结果。采用二分类 Logistic 回归分析建立 CT 征象模型和 CT 征象与嗜酸性粒细胞联合模型，计算并比较两种模型的鉴别诊断效能。
基于 CT 征象建立的影像学模型绘制受试者工作特征（ROC）曲线，曲线下面积（AUC）为 0.856（95%CI：0.799～0.913），敏感度为 66.7%，特异度为 88.9%。建立 CT 征象与嗜酸性粒细胞联合模型，ROC 曲线下面积为 0.950（95%CI：0.919～0.980），敏感度为 89.9%，特异度为 90.1%。联合模型的鉴别诊断效率高于影像学模型，差异有统计学意义。
在儿童肺吸虫病与结核性胸膜炎的鉴别诊断中，联合模型的诊断效能高于影像学模型。胸部 CT 出现隧道征、无肺部结节、外周血嗜酸性粒细胞百分比升高提示儿童患有肺吸虫病。
