LAUSR

Abstract Objective To predict the risk factors for cardiovascular events within 5 years in patients with peritoneal dialysis-associated peritonitis and establish a nomogram for clinical prediction. Methods A prediction model was established by conducting an observational study in 150 patients with peritoneal dialysis-associated peritonitis obtained from the Information Database of AnHui Medical University Affiliated Hospital. The nomogram was constructed using the multivariate COX regression model. The C-index and the calibration plot were used to assess the discrimination and calibration of the prediction model. Results The elderly [HR = 2.453 (1.071–5.619)], history of cardiovascular events [HR = 2.296 (1.220–4.321)], alkaline phosphatase [HR = 1.004 (1.002–1.005)] and culture-positive [HR= 2.173 (1.009–4.682)] were identified as risk predictors of cardiovascular events, while serum albumin [HR = 0.396(0.170–0.924)] was identified as protective predictors of cardiovascular events. Combined with clinical studies, we constructed a nomogram based on the minimum value of the Akaike Information Criterion or Bayesian Information Criterion. The C index of the nomogram is 0.732, revealing great discrimination and appropriate calibration. Through the total score of the nomogram and the result of ROC, we classify patients into high-risk groups (cardiovascular events group) and low-risk groups (no cardiovascular events group). Cardiovascular events were significantly different for patients in the high-risk group compared to the low-risk group (HR = 3.862(2.202–6.772; p < 0.001). Conclusions The current novel nomogram can accurately predict cardiovascular events in patients with peritonitis associated with peritoneal dialysis. However, external validation is required before the model can be used in clinic settings.