The risk factors and predictive model for cardiac valve calcification in patients on maintenance peritoneal dialysis: a single-center retrospective study.

BACKGROUND: Cardiovascular calcification includes cardiac valve calcification (CVC) and vascular calcification. We aimed to analyze risk factors for CVC, and construct a predictive model in maintenance peritoneal dialysis (MPD) patients.

METHODS: We retrospectively analyzed MPD patients who began peritoneal dialysis between January 2014 and September 2021. Patients were randomly assigned to the derivation cohort and validation cohort in a 7:3 ratio. The patients in the derivation cohort were divided into the CVC group and non-CVC group. Logistic regression was used to analyze risk factors, then the rms package in R language was used to construct a nomogram model to predict CVC.

RESULTS: 1,035 MPD patients were included, with the age of 50.0 ± 14.2 years and 632 males (61.1%). Their median follow-up time was 25 (12, 46) months. The new-onset CVC occurred in 128 patients (12.4%). In the derivation cohort, multivariate logistic regression indicated old age, female, high systolic blood pressure (SBP), high calcium-phosphorus product (Ca × P), high Charlson comorbidity index (CCI) and long dialysis time were independent risk factors for CVC ( p  < 0.05). We constructed a nomogram model for predicting CVC in the derivation cohort, with a C index of 0.845 (95% CI 0.803-0.886). This model was validated with a C index of 0.845 (95%CI 0.781-0.909) in the validation cohort.

CONCLUSION: We constructed a nomogram model for CVC in MPD patients, using independent risk factors including age, sex, SBP, Ca × P, CCI and dialysis time. This model achieved high efficiency in CVC prediction.