Bone Metabolism Biomarkers after Parathyroidectomy: The Impact on Patient Survival

Abstract

Abstract Background The purpose of this study was to explore the risk factors from a series of bone metabolism indicators in perioperative period for long-term prognosis and develop a prediction model with internal validation among hemodialysis patients underwent parathyroidectomy. Methods This study was a single-center, retrospective cohort study in Huashan Hospital of Fudan University. Patients who underwent parathyroidectomy and followed for at least one year were enrolled and divided into development cohort and validation cohort. Multivariable Logistic regression was used to establish the prediction model for composite endpoint of cardiovascular disease and all-cause mortality and operating characteristic (ROC) curve to determine the cut-off value of each predictive variable. Results A total of 109 patients were enrolled. The averaged follow-up vintage was (51.67 ± 34.70) months. A total of 16 (14.7%) patients died and cardiovascular disease occurred in 15 (13.8%) patients. The final development and validation cohorts included 82 and 27 patients, respectively. Multivariable Logistic regression analysis showed age (OR = 1.086, P = 0.048, 95%CI = 1.001–1.179), △P which was defined as the difference between preoperative and the 7th-day postoperative serum phosphorus levels (OR = 2.665, P = 0.028, 95%CI = 1.111–6.397), 7th-day postoperative intact parathyroid hormone (iPTH) of grafted arm (OR = 1.024, P = 0.036, 95%CI = 1.002–1.047) and 7th-day postoperative bone-specific alkaline phosphatase (BAP) (OR = 0.95, P = 0.04, 95%CI = 0.905–0.998) were correlated with CVD and all-cause mortality. △P which contributed to 36% of the total weights had the greatest impact on the endpoint. Conclusion Age, △P, 7th-day postoperative iPTH of grafted arm, 7th-day postoperative BAP can predict long-term cardiovascular events and all-cause mortality in hemodialysis patients after parathyroidectomy.