Development of a risk prediction model for preoperative hypokalemia in gastrointestinal tumor patients
10.3760/cma.j.cn211501-20240709-01792
- VernacularTitle:胃肠肿瘤患者术前低钾血症的风险预测模型构建
- Author:
Jing ZHOU
1
;
Xiao LIU
;
Chen CHEN
;
Xuefen CHEN
;
Luxia ZHAO
;
Yunhe GAO
;
Ying WANG
Author Information
1. 中国人民解放军总医院第一医学中心普通外科医学部，北京 100853
- Publication Type:Journal Article
- Keywords:
Gastrointestinal tumor;
Preoperative hypokalemia;
Prediction model;
Screening tool
- From:
Chinese Journal of Practical Nursing
2025;41(21):1622-1629
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze and identify the risk factors for preoperative hypokalemia in patients with gastrointestinal tumors and to construct a risk prediction model.Methods:A prospective research design was implemented. Patients with gastrointestinal tumors who underwent surgical treatment at the First Medical Center of the People ′s Liberation Army General Hospital between March 2023 and February 2024 were recruited as research participants through convenience sampling. These participants were randomly allocated into a modeling group or a validation group in a 7:3 ratio. Preoperative hypokalemia was defined as the outcome indicator. Multivariate Logistic regression analysis was employed to screen for risk factors, and a nomogram was subsequently constructed and validated. Results:Finally, a total of 600 patients were included in the study. In the modeling group ( n=420), 282 were male and 138 were female, 169 patients were under 60 years old, 233 patients were aged between 60 and 80 years, and 18 patients were over 80 years old. In the verification group ( n=180), there were 123 males and 57 females. Among these, 69 patients were under 60 years old, 102 patients were aged between 60 and 80 years, and 9 patients were over 80 years old. The multivariate Logistic regression analysis revealed that body mass index, occupation type, dietary habits, 6m walking speed test, grip strength relative to body mass index, and presence of digestive tract symptoms were independent risk factors for the development of preoperative hypokalemia ( χ2 values were 8.21~27.78, all P<0.05). The results of the model validation demonstrated that the areas under the receiver operating characteristic curves for the modeling and validation groups were 0.853 (95% CI 0.811-0.895) and 0.834 (95% CI 0.756-0.912), respectively, indicating a satisfactory level of predictive performance. Conclusions:The developed predictive model for preoperative hypokalemia in gastrointestinal tumors facilitates the accurate evaluation of the risk of preoperative hypokalemia and serves as a reference for effective clinical intervention.
