Abstract
PURPOSE: We aimed to describe and predict the risk of severe hypernatremia after surgical resection of craniopharyngioma and to identify the association of water intake, urine output, and sodium level change in the patients. METHOD: The outcome was postoperative severe hypernatremia. We identified risk factors associated with hypernatremia using multivariable regression. We trained machine learning models to predict the outcome. We compared serum sodium change, intravenous input, oral input, total input, urine output, and net fluid balance according to different nurse shifts. RESULTS: Among 234 included patients, 125 developed severe hypernatremia after surgery. The peak incidence occurred during day 0 and day 6 after surgery. The risk was increased in patients with gross total resection (odds ratio (OR) 2.41, P < 0.001), high Puget classification (OR 4.44, P = 0.026), preoperative adrenal insufficiency (OR 2.01, P = 0.040), and preoperative hypernatremia (OR 5.55, P < 0.001). The random forest algorithm had the highest area under the receiver operating characteristic curve (0.770, 95% CI, 0.727-0.813) in predicting the outcome and was validated in the prospective validation cohort. Overnight shifts were associated with the highest serum sodium increase (P = 0.010), less intravenous input (P < 0.001), and less desmopressin use (P < 0.001). CONCLUSION: The overall incidence of severe hypernatremia after surgical resection of craniopharyngioma was significant, especially in patients with gross total resection, hypothalamus distortion, preoperative adrenal insufficiency, and preoperative severe hypernatremia. Less intravenous input and less desmopressin use were associated with serum sodium increases, especially during overnight shifts.