Development and validation of a new model for predicting hypocalcaemia after total thyroidectomy: the NuGra model.

BACKGROUND: Hypocalcaemia is the most frequent complication after total thyroidectomy. Finding a method for its early detection has become a priority. A single-center prospective cohort study was conducted to identify risk factors for postoperative hypocalcaemia, develop an early detection model, and test its validity in a different group of patients. METHODS: The sample was composed of patients who underwent a total thyroidectomy between May 2012 and September 2015. Demographic, clinical, laboratory, and surgical data were collected. The incidence of hypocalcaemia and permanent hypoparathyroidism was calculated. Bivariate and multivariate analysis identified several independent predictors of hypocalcaemia, which were used to design a predictive model. The validity of the model was subsequently tested in a different cohort. Area under the ROC curve (AUROC) was calculated to determine its predictive power. RESULTS: The study and validation groups included 352 and 118 patients, respectively. Seventy-three patients developed laboratory-confirmed hypocalcaemia (20.7%), and symptomatic in 43 (12.2%). Multivariate analysis confirmed as independent predictors of hypocalcaemia the higher number of parathyroid glands identified [OR 1.41(0.98, 2.02); p = 0.063] and pre-to-postoperative gradient of parathormone decline [OR 1.06(1.04, 1.08); p < 0.001]. Based on these variables, the NuGra (Number of parathyroid glands identified-Gradient of decline) model was developed for predicting laboratory-confirmed hypocalcaemia. Its predictive power was high (AUROC 0.902, CI 0.857-0.947) for the study and the validation group (AUROC 0.956, CI 0.919-0.993). CONCLUSIONS: A higher number of parathyroid glands identified and a higher gradient of parathormone decline are risk factors for post-thyroidectomy hypocalcaemia. The NuGra model is useful for early prediction of individual risk for hypocalcaemia.

Usefulness of the Wisconsin and CaPTHUS indices for predicting multiglandular disease in patients with primary hyperparathyroidism in a southern European population.

BACKGROUND: Focused parathyroidectomy is a safe technique for the treatment of primary hyperparathyroidism. The CaPTHUS score and the Wisconsin index are preoperative diagnostic tools designed to distinguish between single- and multigland disease. The aim of the study is to evaluate the usefulness of these models for predicting multiglandular disease in a European population. METHODS: Retrospective review of a database of patients operated upon for primary hyperparathyroidism at a referral center. The sensitivity, specificity, positive and negative predictive values, and reliability of both scores for the prediction of multiglandular disease, were calculated. Receiver operating characteristic (ROC) curves were constructed to assess the sensitivity and specificity of CaPTHUS score and Wisconsin Index for predicting single-gland disease. A level of P<0.05 was accepted as significant. RESULTS: Two hundred and eighty-one patients who underwent successful surgery from January 2001 to December 2018 were included. Single-gland disease was detected in 92.5%, and 73.7% had a CaPTHUS score of ≥3. The sensitivity, specificity, positive and negative predictive values of this model for predicting single-gland disease with a score of ≥3 were 76.9%, 66.7%, 96.6%, and 18.9% respectively. The area under the curve value of the CaPTHUS score for predicting single-gland disease was 0.74. A Wisconsin Index >2,000 and an excised gland weight above one gram presented a positive predictive value for single-gland disease of 92.5%. CONCLUSIONS: Despite the good performance of both scales, the established cut-off points did not definitively rule out parathyroid multiglandular disease in our population. In cases with a minimal suspicion of this condition, additional intraoperative techniques must be used, or bilateral neck explorations should be performed.