Literature DB >> 33232474

A risk score for predicting hospitalization for community-acquired pneumonia in ITP using nationally representative data.

Ye-Jun Wu1,2,3,4, Ming Hou5, Hui-Xin Liu6, Jun Peng5, Liang-Ming Ma7, Lin-Hua Yang8, Ru Feng9, Hui Liu9, Yi Liu10, Jia Feng11, Hong-Yu Zhang11, Ze-Ping Zhou12, Wen-Sheng Wang13, Xu-Liang Shen14, Peng Zhao1,2,3,4, Hai-Xia Fu1,2,3,4, Qiao-Zhu Zeng1,2,3,4, Xing-Lin Wang1,2,3,4, Qiu-Sha Huang1,2,3,4, Yun He1,2,3,4, Qian Jiang1,2,3,4, Hao Jiang1,2,3,4, Jin Lu1,2,3,4, Xiang-Yu Zhao1,2,3,4, Xiao-Su Zhao1,2,3,4, Ying-Jun Chang1,2,3,4, Lan-Ping Xu1,2,3,4, Yue-Ying Li15,16,17, Qian-Fei Wang15,16,17, Xiao-Hui Zhang1,2,3,4.   

Abstract

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 anti-citrullinated peptide antibody (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.
© 2020 by The American Society of Hematology.

Entities:  

Year:  2020        PMID: 33232474      PMCID: PMC7686895          DOI: 10.1182/bloodadvances.2020003074

Source DB:  PubMed          Journal:  Blood Adv        ISSN: 2473-9529


  70 in total

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