Development and validation of a predictive model for hypothalamic obesity following craniopharyngioma resection.
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OBJECTIVE: To analyze the risk factors for hypothalamic obesity (HO) after craniopharyngioma surgery, construct a predictive model and verify its efficacy. METHODS: A retrospective analysis was conducted on 136 patients diagnosed with craniopharyngioma at The First Affiliated Hospital of Zhengzhou University between September 2018 and February 2024. Clinical and follow-up data were collected and split into training and validation cohorts (7: 3) randomly and divided into HO and non-HO groups post-surgery. Logistic regression was used to analyse risk factors for postoperative HO, and a prediction model was constructed and its efficacy was verified. RESULTS: In the training cohort, the preoperative body mass index (BMI), preoperative serum sodium, preoperative uric acid levels, postoperative calcium levels, the probability of intraoperative blood loss ≥ 100 ml and preoperative hypothalamic injury and T-type tumors were higher in HO group. Small tumors (< 5 cm³) were less frequent in HO group (all P < 0.05). Logistic regression analysis showed that preoperative high BMI and intraoperative blood loss ≥ 100 ml were independent risk factors for postoperative HO, while older age at onset and smaller tumor size were protective factors (all P < 0.05). The model developed from the training cohort showed that the area under the receiver operating characteristic curve (AUC) was 0.865(95%CI of 0.793 ~ 0.937), with a sensitivity of 79.5% and a specificity of 80.8%, the validation cohort had an AUC of 0.864(95%CI:0.744-0.983), with a sensitivity of 90.9% and a specificity of 72.2%. The calibration curve and Hosmer-Lemeshow test demonstrated that the predicted value of the model was in agreement with the observed values in both the training and verification cohorts (P > 0.05). CONCLUSION: Preoperative high BMI and intraoperative blood loss ≥ 100 ml are independent risk factors for HO after craniopharyngioma surgery. A predictive model based on preoperative BMI, age at onset, intraoperative blood loss, and tumor size shows potential for predicting the risk of postoperative HO, aiding in early identification for high-risk patients. CLINICAL TRIAL NUMBER: Not applicable.