Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Guang Zhou, China.
Orthopedics, Sun Yat-sen University, Guangzhou, China.
PeerJ. 2023 Aug 30;11:e15946. doi: 10.7717/peerj.15946. eCollection 2023.
Pituitary adenomas (PAs) are neuroendocrine tumors located in the sellar region. Surgery, being the primary treatment option for most PAs, is known to cause disruptions in sodium metabolism.
To develop and validate a nomogram for assessment the incidence of postoperative sodium disturbance (SD) in patients with PAs.
In this retrospective study, 208 patients with PAs who underwent resection surgery between 2013 and 2020 were included. Various demographic characteristics, clinical features and laboratory data were analyzed as potential predictors of postoperative sodium disturbance (SD). LASSO regression were used to identify independent preoperative variables associated with SD. Logistic regression was employed to calculate odds ratios (ORs) and 95% confidence intervals (CIs). A nomogram was constructed to visualize these results and evaluated using metrics such as the area under the curve (AUC) for discrimination, the Hosmer-Lemeshow test for calibration and decision curve for usefulness assessment.
The incidence of SD was 44.23% (92 cases out of 208). Six preoperative factors, including sex, types of PAs, phosphocreatine kinase (CK), serum iron (Fe), free fatty acids (NEFA) and mean corpuscular volume (MCV), were identified for constructing a predictive nomogram. The nomogram showed high accuracy, with AUC values of 0.851 (95% CI [0.799-0.923]) and 0.771 (95% CI [0.681-0.861]) in the training and validation datasets, respectively. Calibration assessment and decision curve analysis confirmed its good agreement and clinical utility.
A practical and effective nomogram for predicting SD after PAs surgery is presented in this study.
垂体腺瘤(PAs)是位于蝶鞍区的神经内分泌肿瘤。手术是大多数 PAs 的主要治疗选择,已知会导致钠代谢紊乱。
开发和验证一种用于评估 PAs 患者术后钠紊乱(SD)发生率的列线图。
在这项回顾性研究中,纳入了 208 例 2013 年至 2020 年间接受切除术的 PAs 患者。分析了各种人口统计学特征、临床特征和实验室数据,以确定与术后钠紊乱(SD)相关的潜在预测因素。使用 LASSO 回归识别与 SD 相关的独立术前变量。使用逻辑回归计算优势比(OR)和 95%置信区间(CI)。构建了一个列线图来可视化这些结果,并使用曲线下面积(AUC)等指标评估其区分度、Hosmer-Lemeshow 检验评估其校准度和决策曲线评估其有效性。
SD 的发生率为 44.23%(208 例中有 92 例)。确定了 6 个术前因素,包括性别、PAs 类型、磷酸肌酸激酶(CK)、血清铁(Fe)、游离脂肪酸(NEFA)和平均红细胞体积(MCV),用于构建预测列线图。该列线图具有较高的准确性,在训练和验证数据集中的 AUC 值分别为 0.851(95%CI[0.799-0.923])和 0.771(95%CI[0.681-0.861])。校准评估和决策曲线分析证实了其良好的一致性和临床实用性。
本研究提出了一种用于预测 PAs 手术后 SD 的实用且有效的列线图。