Development and validation of a nomogram for assessment postoperative sodium disturbance in PAs patients: a retrospective cohort study

Author:

Li Wenpeng12,Tang Dongfang3,Wang Qiwei2,Li Shiwei1,Zhao Wenbo4,You Lili5

Affiliation:

1. Department of Neurosurgery, Sun Yat-sen Memorial Hospital, Guang Zhou, China

2. Orthopedics, Sun Yat-sen University, Guangzhou, China

3. Department of Neurosurgery, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China

4. Neurosurgery, Second Hospital of Shanxi Medical University, Shanxi, China

5. Department of Endocrinology, Sun Yat-sen Memorial Hospital, Guang Zhou, China

Abstract

Background 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. Objective To develop and validate a nomogram for assessment the incidence of postoperative sodium disturbance (SD) in patients with PAs. Methods 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. Results 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. Conclusion A practical and effective nomogram for predicting SD after PAs surgery is presented in this study.

Funder

Guangzhou Key Research and Development Program

Natural Science Foundation of Guangdong Province

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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