Objective To construct a predictive model for assessing the risk of left ventricular hypertrophy(LVH)in pa-tients with chronic kidney disease(CKD)and evaluate its clinical application value.Methods The clinical data of 302 patients with stage Ⅲ-Ⅴ CKD,who were treated at Rugao Hospital Affiliated to Nantong University from January 2018 to August 2022 were collected.Patients were randomly divided into a modeling group(n=200)and a validation group(n=102)based on their ID number.Logistic regression was used to determine risk factors for LVH,and a nomogram model was constructed.The predictive ability of the model was evaluated by receiver operating characteristic curve and correc-tion curve.Results The incidence of LVH in CKD patients was 37.4％(113/302).Older age(OR=1.054,95％CI:1.020-1.089,P=0.002),cardiovascular history(OR=5.826,95％CI:2.263-15.003,P＜0.001),CKD Ⅴ stage(OR=5.831,95％CI:2.142-15.873,P=0.009),elevated systolic blood pressure(OR=1.019,95％CI:1.002-1.036,P=0.025)and hyperphosphatemia(OR=1.109,95％CI:1.029-1.195,P=0.007)were independent risk factors for LVH.The prediction model of LVH was constructed based on the above factors,and had AUC of 0.850(95％CI:0.796-0.904)in the modeling group and 0.792(95％CI:0.707-0.877)in validation group.The calibra-tion curve showed that the nomogram model exhibits good predictive ability for LVH.Conclusion The nomogram model,which is based on age,history of cardiovascular disease,CKD stage,systolic blood pressure,and blood phosphorus,pro-vides clinicians a simple and effective tool to identify CKD patients with high risk of LVH.
Chronic kidney diseaseLeft ventricular hypertrophyRisk factorsNomogramPredictive model
维普
万方数据
