Risk Factor Analysis and Prediction of Severe Hypocalcemia after Total Parathyroidectomy without Auto-Transplantation in Patients with Secondary Hyperparathyroidism.

Abstract

Our study aimed to develop and validate a nomogram to predict severe hypocalcemia (SH) before total parathyroidectomy (TPTX) without auto-transplantation in patients with secondary hyperparathyroidism. A total of 299 consecutive patients who underwent TPTX without transplantation for secondary hyperparathyroidism were selected from the General Hospital of Northern Theater Command between January 2013 and December 2021. Of these, patients who underwent surgery between January 2013 and December 2020 formed the training cohort (n = 208) to develop a nomogram, and those who underwent surgery thereafter formed the validation cohort (n = 91) to validate the performance of this nomogram. Univariate and multivariate logistic regression analyses were used to identify the risk factors associated with SH, and then, a nomogram was constructed. The incidence of postoperative SH was 27.9% and 35.2% in the training and validation cohorts, respectively. The preoperative factors associated with SH were younger age, lower serum calcium (Ca) level, higher intact parathyroid hormone (iPTH) level, and higher serum alkaline phosphatase (ALP) level. Incorporating these 4 factors, the nomogram achieved good concordance indexes of 0.866 (95%CI, 0.816-0.916) and 0.867 (95% CI, 0.793-0.941) in predicting SH in the training and validation cohorts, respectively, and had well-fitted calibration curves. The positive predictive values of the nomogram were 64.7% (54.1%-78.4%) and 75.0% (58.6%-88.5%), and negative predictive values of the nomogram were 90.0% (82.9%-93.6%) and 86.4% (73.5%-94.0%) for the training and validation cohorts, respectively. We developed and validated a nomogram for the prediction of SH in patients who underwent TPTX without auto-transplantation for secondary hyperparathyroidism. Our nomogram may facilitate the identification of high-risk SH in patients after TPTX and optimization of preoperative decision-making.