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| Construction of a nomogram model for predicting the risk of chronic kidney disease in patients with hypertension |
| Hits 596 Download times 356 Received:October 23, 2021 |
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| DOI
10.11656/j.issn.1672-1519.2022.03.07 |
| Key Words
hypertension;chronic kidney disease;risk factor;nomogram model |
| Author Name | Affiliation | E-mail | | YANG Ji | Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China | | | ZHANG Yao | Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China | | | GAO Shengwei | Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China | | | ZHANG Xiuling | Xiditou Community Health Service Center of Beichen District in Tianjin, Tianjin 300408, China | | | ZHANG Qiuyue | Second Department of Cardiology, Second Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300250, China | | | ZHAO Yingqiang | Second Department of Cardiology, Second Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300250, China | zhaoyingqiang1000@126.com |
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| Abstract
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| [Objective] To analyze the risk factors related to the occurrence of chronic kidney disease in patients with hypertension,and construct a nomogram model for predicting chronic kidney disease in patients with hypertension. [Methods] Relying on Tianjin's primary medical and health information management system,using a cluster sampling method,selecting the daily resident health checkup data from January 1,2018 to December 31,2019 in Beichen District,Tianjin,which is in line with the diagnosis and data preservation of hypertension. The complete 4 784 patients with hypertension were the subjects of the study,including 2 193 males(44.67%),with an average age of (66.38±10.10) years;2 591 females (55.33%),with an average age of (67.52±8.80) years. Single factor and multivariate logistic analysis methods were used to screen the risk factors of hypertension patients with chronic kidney disease and establish a nomogram model. [Results] Univariate analysis showed that age,gender,white blood cell count,percentage of neutrophils,percentage of lymphocytes,fasting blood glucose,glycosylated hemoglobin,blood creatinine,blood urea nitrogen,triglycerides,smoking status,diet preference,exercise,high are significant differences in 23 factors such as the course of blood pressure,impaired glucose regulation,type 2 diabetes,coronary heart disease,old myocardial infarction,new-onset atrial fibrillation,fatty liver,hyperuricemia,family history of hypertension,and traditional Chinese medicine constitution(P<0.05),it is a suspicious risk factor for chronic kidney disease in patients with hypertension;multivariate logistic analysis showed that age,fasting blood glucose,blood urea nitrogen,coronary heart disease,new-onset atrial fibrillation,hyperuricemia,family history of hypertension,the course of hypertension and the constitution of traditional Chinese medicine are independent risk factors for patients with hypertension and chronic kidney disease. The nomogram model was constructed using the above 9 risk prediction indicators. The consistency index(C-index) was 0.742 and the diagnostic sensitivity,specificity,and accuracy were 63.18%,72.54% and 84.26%,respectively. The calibration curve shows the model prediction. The effect is basically the same as the actual disease probability. The clinical decision curve analysis also shows that the nomogram model has better clinical performance,especially when the threshold probability is 0.14~0.63,the nomogram model can bring net clinical benefits to patients. [Conclusion] This study constructed a nomogram model based on the risk factors associated with the occurrence of chronic kidney disease in patients with hypertension. The nomogram model was confirmed by relevant indicators to have good predictive ability and clinical efficacy,and it can accurately and effectively predict hypertension. Patients with chronic kidney disease are at risk,so as to assist clinicians to screen high-risk patients and formulate targeted intervention measures to reduce the incidence of chronic kidney disease in patients with hypertension. |
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