Email Alert | RSS

Journal of Tuberculosis and Lung Disease ›› 2024, Vol. 5 ›› Issue (1): 20-27.doi: 10.19983/j.issn.2096-8493.2024003

• Original Articles • Previous Articles     Next Articles

Analysis of risk factors and construction of risk prediction model for anemia in patients with chronic obstructive pulmonary disease

Fu Yiting1, Liu Lei2, Zhao Qian1, Meng Jixian1, Zhen Ziyi1, Wang Yang3, Li Rongmei1()   

  1. 1Department of Public Health, Shenyang Medical College, Shenyang 110034, China
    2Department of Nursing, Liaoning University of Traditional Chinese Medicine, Shenyang 116600, China
    3Department of Respiratory Medicine, the Second Affiliated Hospital of Shenyang Medical College, Shenyang 110035, China
  • Received:2023-11-19 Online:2024-02-20 Published:2024-02-02
  • Contact: Li Rongmei, Email:
  • Supported by:
    Social Science Planning Fund 2022 of Liaoning Province(L22BCL047);Shenyang Medical College Master’s Science and Technology Innovation Fund(Y20220513);2024 Research Project on Economic and Social Development of Liaoning Province(2024lslybkt-032)


Objective: To explore the risk factors of anemia in patients with chronic obstructive pulmonary disease (COPD), and construct a nomograph prediction model. Methods: COPD patients admitted to the Respiratory Department of the Second Affiliated Hospital of Shenyang Medical College from December 2019 to March 2023 were retrospectively selected as the study objects (492 patients). LASSO regression was used to screen risk factors, and logistic regression analysis was used to construct a prediction model of anemia in COPD patients, and a nomogram prediction model was constructed. The model was validated internally by Bootstrap resample method. The calibration curve and its C-index were used to evaluate the differentiation of the model. The area under receiver operating characteristic (ROC) curve and clinical decision curve (DCA) were used to evaluate the prediction ability and clinical applicability of the nomogram prediction model, respectively. Results: A total of 492 COPD patients were included, 19.51% (96/492) of them had anemia. Nine candidate predictors were identified by LASSO regression analysis: gender, creatinine, hypoproteinemia, diabetes, hypertension, COVID-19 infection, red blood cells (RBC), hemoglobin (Hb), body mass index (BMI). They were included in logistic regression analysis, and the results showed that gender being female (OR=3.353, 95%CI: 1.530-7.349), elevated creatinine levels (OR=1.024, 95%CI: 1.010-1.037), elevated Hb levels (OR=0.928, 95%CI: 0.905-0.951), hypoproteinemia (OR=6.239, 95%CI: 2.845-13.678), diabetes mellitus (OR=0.198, 95%CI: 0.056-0.703) were all independent influencing factors for anemia. Calibration curve of the nomogram prediction model showed good fitness, with a C-index of 0.933 (95%CI: 0.910-1.848), indicating that the model was well distinguished. The area under the curve was 0.933 (95%CI: 0.910-0.957), and DCA curve showed good clinical applicability of the model. Conclusion: The prediction model of COPD combined with anemia is simple and accurate, has certain value in early clinical screening of high-risk groups of anemia and the formulation of individualized precise prevention and treatment plans.

Key words: Pulmonary disease, chronic obstructive, Anemia, Factor analysis, statistical, Forecasting, Nomograms

CLC Number: