Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (6): 28-33.doi: 10.6040/j.issn.1671-7554.0.2019.1442

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Gaussian process model for risk assessment of readmission for patients with chronic heart failure within one year

ZHANG Chuanbei1*, LI Fang2*, ZHAI Chunxiao3, YU Yongming4, SHU Minglei5, WANG Yidan3, XU Liangdong6, HAO Enkui3   

  1. 1. Clinical Medical College of Weifang Medical College, Weifang 261000, Shandong, China;
    2. Department of Health, Jinan Central Hospital, Jinan 250012, Shandong, China;
    3. Department of Cardiology, Shandong Provincial Qianfoshan Hospital, Jinan 250012, Shandong, China;
    4. School of Control Science and Materials, Shandong University, Jinan 250012, Shandong, China;
    5. National Supercomputer Center in Jinan, Jinan 250012, Shandong, China;
    6. Emergency Department, Dezhou Peoples Hospital, Dezhou 253000, Shandong, China
  • Published:2022-09-27

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Abstract: Objective To explore the predictive value of a 1-year readmission risk assessment for patients with chronic left ventricular systolic function(LVSD)by using a Gaussian process model(GPM)and echocardiographic parameters. Methods A total of 290 patients with chronic LVSD were collected, and re-hospitalization within one year was the end point of the study. All patients underwent routine echocardiography to collect data including mitral regurgitation, tricuspid regurgitation, pleural effusion, pericardial effusion, pulmonary artery systolic pressure, left ventricular diameter and left ventricular ejection fraction. The 290 patients were randomly divided into 70% training group(modeling group)and 30% testing group(prediction group). The information interaction analysis on the training dataset was carried out with machine learning algorithms. The importance of each parameter was evaluated, and echocardiographic parameters were merged to establish GPM. Subsequently, the readmission risk of the testing dataset was analyzed using GPM. In addition, the risk of all patients was predicted with the echocardiography parameter scoring system. Finally the two methods were compared with receiver operating characteristic(ROC)curve. Results GPM information interaction analysis showed the weights of echocardiographic parameters were: mitral regurgitation 23.64%, tricuspid regurgitation 22.09%, pleural effusion 16.18%, pericardial effusion 14.36%, pulmonary artery contraction pressure 9.04%, left ventricular diameter 8.86%, and left ventricular ejection fraction 5.83%. Based on GPM and echocardiography parameter scoring system, the area under the ROC curve(AUC)was 83.10%(95% CI: 0.797-0.864), 70.60%(95% CI: 0.647-0.765), respectively. Conclusion GPM based on echocardiographic parameters can well predict the readmission risk of LVSD patients within one year, and it is superior to echocardiography parameter scoring system.

Key words: Left ventricular systolic dysfunction, Gaussian Process Model, Echocardiography, One-year readmission rate

CLC Number: 

  • R541.6
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