Analysis of risk factors for pulmonary infection after heart valve replacement and construction of nomogram prediction model_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

CAI Wenqian ^1,2 ,  WU Dequan ^2,1 , LLÜ Wenjing ^1,2 , LIU Bo ^1,2 , SUN Yue ^1,2

1. Nursing School of Anhui Medical University, Hefei, 230032, P. R. China;
2. Department of Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, 230601, Hefei, P. R. China;

Corresponding author：

WU Dequan, Email: wdq2981288742@sina.com

Keywords：

Heart valve replacement surgery; pulmonary infection; risk factors; nomogram; prediction model

DOI：

10.7507/1007-4848.202411031

Video：

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Objective To develop and validate a nomogram prediction model for pulmonary infection in patients following cardiac valve replacement surgery, providing a reference for early screening of high-risk populations and implementing targeted preventive measures. Methods Clinical data of patients who underwent cardiac valve replacement surgery at the Second Affiliated Hospital of Anhui Medical University from January 2020 to October 2023 were collected. Patients were randomly assigned to a modeling group and a validation group in a 7 : 3 ratio. Based on the occurrence of pulmonary infection post-surgery, patients were divided into a pulmonary infection group and a non-pulmonary infection group. Risk factors for pulmonary infection after cardiac valve replacement were analyzed using least absolute shrinkage and selection operator (LASSO) regression and logistic regression to establish a risk prediction model, which was subsequently validated. Model evaluation was conducted using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Results A total of 689 patients were included, comprising 354 males and 335 females, with a mean age of (57.37±12.76) years. The incidence of pulmonary infection was 16.0% (110/689). Independent risk factors for pulmonary infection following cardiac valve replacement included emergency admission, smoking history, chronic obstructive pulmonary disease, duration of cardiopulmonary bypass, duration of tracheal intubation, and postoperative renal injury. The AUC for the modeling group was 0.911 [95%CI (0.877, 0.946) ], with a Hosmer-Lemeshow χ²-value of 6.577 (P=0.583) in the training group. The AUC value was 0.891 [95%CI (0.840, 0.941) ], with a Hosmer-Lemeshow χ²-value of 5.486（P=0.705）in the validation group. The model demonstrated good discrimination, calibration, and net benefit. Conclusion The established nomogram prediction model has significant predictive value and can be applied to risk assessment and individualized treatment for pulmonary infection in patients following cardiac valve replacement surgery.

1.	Roth GA, Mensah GA, Johnson CO, et al. Global burden of cardiovascular diseases and risk factors, 1990-2019: Update from the GBD 2019 study. J Am Coll Cardiol, 2020, 76(25): 2982-3021.
2.	Writing Committee Members, Otto CM, Nishimura RA, et al. 2020 ACC/AHA guideline for the management of patients with valvular heart disease: Executive summary: A report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol, 2021, 77(4): 450-500.
3.	杨书强, 康娜, 王俊生, 等. 心脏瓣膜置换术后肺部感染的影响因素及其与TNF-α基因多态性的关联. 中华医院感染学杂志, 2023, 33(11): 1650-1654.Yang SQ, Kang N, Wang JS, et al. Influencing factors for postoperative pulmonary infection in heart valve replacement patients and their association with TNF-α gene polymonrphisms. Chin J Nosocomiol, 2023, 33(11): 1650-1654.
4.	Passos LSA, Nunes MCP, Aikawa E. Rheumatic heart valve disease pathophysiology and underlying mechanisms. Fronti Cardiovasc Med, 2021, 7: 612716.
5.	Yao X, Li N, Lu R, et al. Development of a nomogram for predicting nosocomial infections among patients after cardiac valve replacement surgery. J Clin Nurs, 2023, 32(7-8): 1466-1475.
6.	Zhou Y, Yu F, Yu Y, et al. Clinical significance of MDRO screening and infection risk factor analysis in the ICU. Am J Transl Res, 2021, 13(4): 3717-3723.
7.	Wang D, Lu Y, Sun M, et al. Pneumonia after cardiovascular surgery: Incidence, risk factors and interventions. Front Cardiovasc Med, 2022, 9: 911878.
8.	Papazian L, Klompas M, Luyt C-E. Ventilator-associated pneumonia in adults: A narrative review. Intensive Care Med, 2020, 46(5): 888-906.
9.	张静, 李娟, 朱鑫灜, 等. 心脏外科术后肺部并发症发生风险的列线图预测模型构建. 安徽医学, 2022, 43(9): 1012-1017.Zhang J, Li J, Zhu XY, et al. Construction of a nomogram prediction model for risk of pulmonary complications after cardiac surgery. Anhui Med J, 2022, 43(9): 1012-1017.
10.	高翠平, 孙淑玲, 肖茹, 等. 中老年心脏瓣膜置换术肺部感染危险因素调查. 中国消毒学杂志, 2023, 40(4): 284-286,290.Gao CP, Sun SL, Xiao R, et al. Study on risk factors of pulmonary infection in middle aged and elderly patients undergoing cardiac valve replacement. Chin J Dis, 2023, 40(4): 284-286,290.
11.	方萍, 金平, 霍佳佳, 等. 急性脑卒中患者肺部感染风险预测模型的构建及验证. 护理学杂志, 2023, 38(16): 30-33.Fang P, Jin P, Huo JJ, et al. Construction and verification of a risk prediction model for pulmonary infection in patients with acute stroke. J Nurs Sci, 2023, 40(4): 284-286, 290.
12.	Wang DS, Huang XF, Wang HF, et al. Clinical risk score for postoperative pneumonia following heart valve surgery. Chin Med J, 2021, 134(20): 2447-2456.
13.	费蕾, 高明昕, 吴曙华, 等. 老年冠心病并发心力衰竭患者院内肺部感染影响因素及风险预测模型构建. 中华老年心脑血管病杂志, 2024, 26(11): 1277-1280.Fei L, Gao MX, Wu SH, et al. Influencing factors of pulmonary infection in elderly CHD patients with HF and construction on a risk prediction model for the infection. Chin J Geriatr Heart Brain Vessel Dis, 2024, 26(11): 1277-1280.
14.	Wang D, Huang X, Wang H, et al. Risk factors for postoperative pneumonia after cardiac surgery: a prediction model. J Thorac Dis, 2021, 13(4): 2351-2362.
15.	金茜, 刘永花, 杨艳, 等. 老年急性左心衰并发肺部感染病原菌与危险因素及其预测模型的预测价值. 中华医院感染学杂志, 2024(3): 346-350.Jin X, Liu YH, Yang Y, et al. Pathogenic bacteria and risk factors for pulmonary infections complicating acute left heart failure in the elderly and the predictive value of their predictive model. Chin J Nosocomiol, 2024(3): 346-350.
16.	Hua L, Kong L, Hu J, et al. Perioperative risk factors for post-operative pneumonia after type A acute aortic dissection surgery. Curr Med Sci, 2022, 43(1): 69-79.
17.	Cursino de Moura JF, Oliveira CB, Coelho Figueira Freire AP, et al. Preoperative respiratory muscle training reduces the risk of pulmonary complications and the length of hospital stay after cardiac surgery: A systematic review. J Physiother, 2024, 70(1): 16-24.
18.	刘兴红, 王慧华, 胡玉婷, 等. 冠状动脉旁路移植患者术后肺部并发症预防及管理的证据总结. 护理学杂志, 2023, 38(16): 46-52.Liu XH, Wang HH, Hu YT, et al. Summary of evidence on prevention and management of postoperative pulmonary complications in patients undergoing coronary artery bypass grafting. J Nurs Sci, 2023, 38(16): 46-52.
19.	林希, 黄娜. 慢性阻塞性肺疾病急性加重期继发肺部真菌感染的列线图预测模型. 中国呼吸与危重监护杂志, 2024, 23(2): 77-85.Lin X, Huang N. A nomogram for predicting secondary pulmonary fungal infection in patients with acute exacerbations of chronic obstructive pulmonary disease. Chin J Respir Crit Care Med, 2024, 23(2): 77-85.
20.	Mali S, Haghaninejad H. Pulmonary complications following cardiac surgery. Arch Med Sci Atheroscler Dis, 2019, 4: e280-e285.
21.	胡凯利, 杨斯钰, 吴前胜, 等. 心脏术后患者机械通气时间延长风险预测模型的构建及验证. 护理学报, 2022, 29(20): 60-64.Hu KL, Yang SY, Wu QS, et al. Construction of risk prediction model for prolonged mechanical ventilation in patients after cardiac surgery. J Nurs, 2022, 29(20): 60-64.
22.	Liu J, Li X, Xie W, et al. Risk factors and short-term outcomes of postoperative pulmonary complications in elderly patients after cardiopulmonary bypass. Clin Interv Aging, 2024, 19: 31-39.
23.	den Os MM, van den Brom CE, van Leeuwen ALI, et al. Microcirculatory perfusion disturbances following cardiopulmonary bypass: A systematic review. Crit Care, 2020, 24(1): 218.
24.	赵映, 刘苏, 刘淑芳, 等. 心脏大血管术后肺部感染病原学及危险因素. 中华医院感染学杂志, 2021, 31(7): 1039-1042.Zhao Y, Liu S, Liu SF, et al. Etiological characteristice and risk factors for postoperative pulmonary infcetion in cardio-macrovascular surgery patients. Chin J Nosocomiol, 2021, 31(7): 1039-1042.
25.	Gao Y, Wang C, Wang Y, et al. Establishment and Validation of a nomogram to predict hospital-acquired infection in elderly patients after cardiac surgery. Clin Interv Aging, 2022, 17: 141-150.
26.	Pozuelo-Carrascosa DP, Herráiz-Adillo Á, Alvarez-Bueno C, et al. Subglottic secretion drainage for preventing ventilator-associated pneumonia: An overview of systematic reviews and an updated meta-analysis. Eur Respir Rev, 2020, 29(155): 190107.
27.	刘霞, 郭丝雨, 张紫薇. 长期卧床老年病人并发肺炎的危险因素及Nomogram预测模型构建. 护理研究, 2023, 37(16): 2909-2914.Liu X, Guo SY, Zhang ZW. Risk factors and Nomogram prediction model construction for complications of pneumonia in long-term bedridden elderly patients. Chin Nurs Res, 2023, 37(16): 2909-2914.
28.	Mertes P-M, Kindo M, Amour J, et al. Guidelines on enhanced recovery after cardiac surgery under cardiopulmonary bypass or off-pump. Anaesth Crit Care Pain Med, 2022, 41(3): 101059.
29.	Küllmar M, Zarbock A, Engelman DT, et al. Prevention of acute kidney injury. Crit Care Clin, 2020, 36(4): 691-704.
30.	罗丹, 陈晶晶, 胡忠, 等. 慢性阻塞性肺疾病急性加重期合并肺部感染患者肾损伤的危险因素及预测模型建立. 中华医院感染学杂志, 2023, 33(12): 1800-1803.Luo D, Chen JJ, Hu Z, et al. Risk factors of renal injury and construction of prediction model in patients with acute exacerbation of choric obstructive pulmonary disease and pulmonary infection. Chin J Nosocomiol, 2023, 33(12): 1800-1803.

1. Roth GA, Mensah GA, Johnson CO, et al. Global burden of cardiovascular diseases and risk factors, 1990-2019: Update from the GBD 2019 study. J Am Coll Cardiol, 2020, 76(25): 2982-3021.
2. Writing Committee Members, Otto CM, Nishimura RA, et al. 2020 ACC/AHA guideline for the management of patients with valvular heart disease: Executive summary: A report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol, 2021, 77(4): 450-500.
3. 杨书强, 康娜, 王俊生, 等. 心脏瓣膜置换术后肺部感染的影响因素及其与TNF-α基因多态性的关联. 中华医院感染学杂志, 2023, 33(11): 1650-1654.Yang SQ, Kang N, Wang JS, et al. Influencing factors for postoperative pulmonary infection in heart valve replacement patients and their association with TNF-α gene polymonrphisms. Chin J Nosocomiol, 2023, 33(11): 1650-1654.
4. Passos LSA, Nunes MCP, Aikawa E. Rheumatic heart valve disease pathophysiology and underlying mechanisms. Fronti Cardiovasc Med, 2021, 7: 612716.
5. Yao X, Li N, Lu R, et al. Development of a nomogram for predicting nosocomial infections among patients after cardiac valve replacement surgery. J Clin Nurs, 2023, 32(7-8): 1466-1475.
6. Zhou Y, Yu F, Yu Y, et al. Clinical significance of MDRO screening and infection risk factor analysis in the ICU. Am J Transl Res, 2021, 13(4): 3717-3723.
7. Wang D, Lu Y, Sun M, et al. Pneumonia after cardiovascular surgery: Incidence, risk factors and interventions. Front Cardiovasc Med, 2022, 9: 911878.
8. Papazian L, Klompas M, Luyt C-E. Ventilator-associated pneumonia in adults: A narrative review. Intensive Care Med, 2020, 46(5): 888-906.
9. 张静, 李娟, 朱鑫灜, 等. 心脏外科术后肺部并发症发生风险的列线图预测模型构建. 安徽医学, 2022, 43(9): 1012-1017.Zhang J, Li J, Zhu XY, et al. Construction of a nomogram prediction model for risk of pulmonary complications after cardiac surgery. Anhui Med J, 2022, 43(9): 1012-1017.
10. 高翠平, 孙淑玲, 肖茹, 等. 中老年心脏瓣膜置换术肺部感染危险因素调查. 中国消毒学杂志, 2023, 40(4): 284-286,290.Gao CP, Sun SL, Xiao R, et al. Study on risk factors of pulmonary infection in middle aged and elderly patients undergoing cardiac valve replacement. Chin J Dis, 2023, 40(4): 284-286,290.
11. 方萍, 金平, 霍佳佳, 等. 急性脑卒中患者肺部感染风险预测模型的构建及验证. 护理学杂志, 2023, 38(16): 30-33.Fang P, Jin P, Huo JJ, et al. Construction and verification of a risk prediction model for pulmonary infection in patients with acute stroke. J Nurs Sci, 2023, 40(4): 284-286, 290.
12. Wang DS, Huang XF, Wang HF, et al. Clinical risk score for postoperative pneumonia following heart valve surgery. Chin Med J, 2021, 134(20): 2447-2456.
13. 费蕾, 高明昕, 吴曙华, 等. 老年冠心病并发心力衰竭患者院内肺部感染影响因素及风险预测模型构建. 中华老年心脑血管病杂志, 2024, 26(11): 1277-1280.Fei L, Gao MX, Wu SH, et al. Influencing factors of pulmonary infection in elderly CHD patients with HF and construction on a risk prediction model for the infection. Chin J Geriatr Heart Brain Vessel Dis, 2024, 26(11): 1277-1280.
14. Wang D, Huang X, Wang H, et al. Risk factors for postoperative pneumonia after cardiac surgery: a prediction model. J Thorac Dis, 2021, 13(4): 2351-2362.
15. 金茜, 刘永花, 杨艳, 等. 老年急性左心衰并发肺部感染病原菌与危险因素及其预测模型的预测价值. 中华医院感染学杂志, 2024(3): 346-350.Jin X, Liu YH, Yang Y, et al. Pathogenic bacteria and risk factors for pulmonary infections complicating acute left heart failure in the elderly and the predictive value of their predictive model. Chin J Nosocomiol, 2024(3): 346-350.
16. Hua L, Kong L, Hu J, et al. Perioperative risk factors for post-operative pneumonia after type A acute aortic dissection surgery. Curr Med Sci, 2022, 43(1): 69-79.
17. Cursino de Moura JF, Oliveira CB, Coelho Figueira Freire AP, et al. Preoperative respiratory muscle training reduces the risk of pulmonary complications and the length of hospital stay after cardiac surgery: A systematic review. J Physiother, 2024, 70(1): 16-24.
18. 刘兴红, 王慧华, 胡玉婷, 等. 冠状动脉旁路移植患者术后肺部并发症预防及管理的证据总结. 护理学杂志, 2023, 38(16): 46-52.Liu XH, Wang HH, Hu YT, et al. Summary of evidence on prevention and management of postoperative pulmonary complications in patients undergoing coronary artery bypass grafting. J Nurs Sci, 2023, 38(16): 46-52.
19. 林希, 黄娜. 慢性阻塞性肺疾病急性加重期继发肺部真菌感染的列线图预测模型. 中国呼吸与危重监护杂志, 2024, 23(2): 77-85.Lin X, Huang N. A nomogram for predicting secondary pulmonary fungal infection in patients with acute exacerbations of chronic obstructive pulmonary disease. Chin J Respir Crit Care Med, 2024, 23(2): 77-85.
20. Mali S, Haghaninejad H. Pulmonary complications following cardiac surgery. Arch Med Sci Atheroscler Dis, 2019, 4: e280-e285.
21. 胡凯利, 杨斯钰, 吴前胜, 等. 心脏术后患者机械通气时间延长风险预测模型的构建及验证. 护理学报, 2022, 29(20): 60-64.Hu KL, Yang SY, Wu QS, et al. Construction of risk prediction model for prolonged mechanical ventilation in patients after cardiac surgery. J Nurs, 2022, 29(20): 60-64.
22. Liu J, Li X, Xie W, et al. Risk factors and short-term outcomes of postoperative pulmonary complications in elderly patients after cardiopulmonary bypass. Clin Interv Aging, 2024, 19: 31-39.
23. den Os MM, van den Brom CE, van Leeuwen ALI, et al. Microcirculatory perfusion disturbances following cardiopulmonary bypass: A systematic review. Crit Care, 2020, 24(1): 218.
24. 赵映, 刘苏, 刘淑芳, 等. 心脏大血管术后肺部感染病原学及危险因素. 中华医院感染学杂志, 2021, 31(7): 1039-1042.Zhao Y, Liu S, Liu SF, et al. Etiological characteristice and risk factors for postoperative pulmonary infcetion in cardio-macrovascular surgery patients. Chin J Nosocomiol, 2021, 31(7): 1039-1042.
25. Gao Y, Wang C, Wang Y, et al. Establishment and Validation of a nomogram to predict hospital-acquired infection in elderly patients after cardiac surgery. Clin Interv Aging, 2022, 17: 141-150.
26. Pozuelo-Carrascosa DP, Herráiz-Adillo Á, Alvarez-Bueno C, et al. Subglottic secretion drainage for preventing ventilator-associated pneumonia: An overview of systematic reviews and an updated meta-analysis. Eur Respir Rev, 2020, 29(155): 190107.
27. 刘霞, 郭丝雨, 张紫薇. 长期卧床老年病人并发肺炎的危险因素及Nomogram预测模型构建. 护理研究, 2023, 37(16): 2909-2914.Liu X, Guo SY, Zhang ZW. Risk factors and Nomogram prediction model construction for complications of pneumonia in long-term bedridden elderly patients. Chin Nurs Res, 2023, 37(16): 2909-2914.
28. Mertes P-M, Kindo M, Amour J, et al. Guidelines on enhanced recovery after cardiac surgery under cardiopulmonary bypass or off-pump. Anaesth Crit Care Pain Med, 2022, 41(3): 101059.
29. Küllmar M, Zarbock A, Engelman DT, et al. Prevention of acute kidney injury. Crit Care Clin, 2020, 36(4): 691-704.
30. 罗丹, 陈晶晶, 胡忠, 等. 慢性阻塞性肺疾病急性加重期合并肺部感染患者肾损伤的危险因素及预测模型建立. 中华医院感染学杂志, 2023, 33(12): 1800-1803.Luo D, Chen JJ, Hu Z, et al. Risk factors of renal injury and construction of prediction model in patients with acute exacerbation of choric obstructive pulmonary disease and pulmonary infection. Chin J Nosocomiol, 2023, 33(12): 1800-1803.

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Latest ArticlesAnalysis of risk factors for pulmonary infection after heart valve replacement and construction of nomogram prediction model

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