Wu Ye-Jun, Hou Ming, Liu Hui-Xin, Peng Jun, Ma Liang-Ming, Yang Lin-Hua, Feng Ru, Liu Hui, Liu Yi, Feng Jia, Zhang Hong-Yu, Zhou Ze-Ping, Wang Wen-Sheng, Shen Xu-Liang, Zhao Peng, Fu Hai-Xia, Zeng Qiao-Zhu, Wang Xing-Lin, Huang Qiu-Sha, He Yun, Jiang Qian, Jiang Hao, Lu Jin, Zhao Xiang-Yu, Zhao Xiao-Su, Chang Ying-Jun, Xu Lan-Ping, Li Yue-Ying, Wang Qian-Fei, Zhang Xiao-Hui
Peking University People's Hospital, Peking University Institute of Hematology, Beijing, China.
Collaborative Innovation Center of Hematology, Peking University, Beijing, China.
Blood Adv. 2020 Nov 24;4(22):5846-5857. doi: 10.1182/bloodadvances.2020003074.
Infection is one of the primary causes of death from immune thrombocytopenia (ITP), and the lungs are the most common site of infection. We identified the factors associated with hospitalization for community-acquired pneumonia (CAP) in nonsplenectomized adults with ITP and established the [corrected] (ACPA) prediction model to predict the incidence of hospitalization for CAP. This was a retrospective study of nonsplenectomized adult patients with ITP from 10 large medical centers in China. The derivation cohort included 145 ITP inpatients with CAP and 1360 inpatients without CAP from 5 medical centers, and the validation cohort included the remaining 63 ITP inpatients with CAP and 526 inpatients without CAP from the other 5 centers. The 4-item ACPA model, which included age, Charlson Comorbidity Index score, initial platelet count, and initial absolute lymphocyte count, was established by multivariable analysis of the derivation cohort. Internal and external validation were conducted to assess the performance of the model. The ACPA model had an area under the curve of 0.853 (95% confidence interval [CI], 0.818-0.889) in the derivation cohort and 0.862 (95% CI, 0.807-0.916) in the validation cohort, which indicated the good discrimination power of the model. Calibration plots showed high agreement between the estimated and observed probabilities. Decision curve analysis indicated that ITP patients could benefit from the clinical application of the ACPA model. To summarize, the ACPA model was developed and validated to predict the occurrence of hospitalization for CAP, which might help identify ITP patients with a high risk of hospitalization for CAP.
感染是免疫性血小板减少症(ITP)导致死亡的主要原因之一,而肺部是最常见的感染部位。我们确定了非脾切除的ITP成年患者社区获得性肺炎(CAP)住院相关因素,并建立了校正后的CAP预测模型(ACPA)以预测CAP住院发生率。这是一项对来自中国10家大型医疗中心的非脾切除ITP成年患者的回顾性研究。推导队列包括来自5个医疗中心的145例合并CAP的ITP住院患者和1360例未合并CAP的住院患者,验证队列包括来自其他5个中心的其余63例合并CAP的ITP住院患者和526例未合并CAP的住院患者。通过对推导队列进行多变量分析,建立了包含年龄、查尔森合并症指数评分、初始血小板计数和初始绝对淋巴细胞计数的4项ACPA模型。进行内部和外部验证以评估模型性能。ACPA模型在推导队列中的曲线下面积为0.853(95%置信区间[CI],0.818 - 0.889),在验证队列中为0.862(95%CI,0.807 - 0.916),这表明模型具有良好的区分能力。校准图显示估计概率与观察概率之间高度一致。决策曲线分析表明ITP患者可从ACPA模型的临床应用中获益。总之,开发并验证了ACPA模型以预测CAP住院的发生,这可能有助于识别有CAP住院高风险的ITP患者。