A predictive model based on serum bicarbonate for cardiovascular events after initiation of peritoneal dialysis

基于血清碳酸氢盐的腹膜透析后心血管事件预测模型

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Abstract

BACKGROUND: The risk of cardiovascular events (CVEs) in peritoneal dialysis (PD) patients is high, but varies widely among individuals. Metabolic acidosis is prevalent in PD patients and may be involved in the development of CVEs. The aim of the study was to evaluate serum bicarbonate as a risk factor and derive a model of new CVE. METHODS: A predictive model was established by performing an observational study in 187 PD patients obtained from the First Affiliated Hospital of Anhui Medical University. The variables were extracted using least absolute shrinkage and selection operator (LASSO) regression, and the modeling was developed using multivariable Cox regression. RESULTS: Left ventricular hypertrophy (HR = 1.965, 95%CI 1.086-3.557) and history of CVEs (HR = 2.435, 95%CI 1.342-4.49) were risk parameters for a new CVE. Serum albumin (HR = 0.924, 95%CI 0.864-0.989) and bicarbonate levels (HR = 0.817, 95%CI 0.689-0.969) were protective parameters, in which the risk of CVEs was reduced by 7.6% and 18.3% for each 1-unit increase in serum albumin (g/L) and bicarbonate (mmol/L) levels, respectively. A nomogram based on the above predictive indicators was proposed with a C-statistic of 0.806, indicating good discrimination. Moreover, it successfully stratified patients into low-, intermediate-, and high-risk groups. CONCLUSIONS: We performed a risk prediction model for the development of CVEs in patients with PD, which may help physicians to evaluate the risk of new CVEs and provide a scientific basis for further interventions. Further studies are needed to externally validate current risk models before clinical application.

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