Nomogram to aid selection of patients for short-stay thyroidectomy based on risk of postoperative hypocalcemia.

OBJECTIVE To develop statistical prediction tools to select patients for short-stay thyroidectomy based on dynamic quantification of individual risk for postoperative hypocalcemia. DESIGN Clinical and biochemical factors that could influence postoperative calcium levels were analyzed. A multivariable logistic regression model was used to study the predictive ability of each variable for hypocalcemia. A step-down model reduction selection method was used to rank the predictors according to their predictive accuracy. SETTING Memorial Sloan Kettering Cancer Center. PATIENTS A test population of 393 patients who met our inclusion criteria and who underwent total thyroidectomy at Memorial Sloan Kettering Cancer Center in the year 2008 made up the modeling data set, 116 of whom developed biochemical hypocalcemia postoperatively (29.5%). The nomograms were validated on an independent data set consisting of 296 selected patients who underwent total thyroidectomy during the year 2005, using the same selection criteria for inclusion as those for the modeling data set. MAIN OUTCOME MEASURES The 8 predictors with the highest predictive accuracy were selected to generate a nomogram, which was validated both internally and externally using an independent data set. A second nomogram was developed for assessing the probability of a patient stay of 24 hours or shorter, based on preoperative and intraoperative factors. RESULTS The 8 variables of highest predictive value were age, sex, medications, history of cancer, preoperative serum calcium level, creatinine concentration, central neck dissection, and alkaline phosphatase levels. A nomogram was created based on the final parsimonious model. The nomogram had excellent accuracy (concordance index of 74.6%) and scored high on internal validation tests. The concordance index of the second nomogram for predicting the likelihood of discharge from the hospital within 24 hours was 70%. CONCLUSION We have produced a set of nomograms that can dynamically quantify the risk of postthyroidectomy hypocalcemia and prolonged hospital stay based on preoperative clinical and biochemical variables and intraoperative surgical variables.