Abstract

Background

The factors associated with postoperative hypokalemia in patients with oral cancer remain unclear. We determined the preoperative factors associated with postoperative hypokalemia in patients with oral cancer following en bloc cancer resection and established a nomogram for postoperative hypokalemia prediction.

Methods

Data from 381 patients with oral cancer who underwent en bloc cancer resection were retrospectively analyzed. Univariate and multivariate analyses were performed to identify the risk factors for postoperative hypokalemia. We used receiver operating characteristic (ROC) curves to quantify the factors’ effectiveness. A nomogram was created to show each predictor’s relative weight and the likelihood of postoperative hypokalemia development. The multinomial regression model’s effectiveness was also evaluated.

Results

Preoperative factors, including sex, preoperative serum potassium level, and preoperative platelet-to-lymphocyte ratio (PLR), were significantly associated with postoperative hypokalemia. Based on the ROC curve, the preoperative serum potassium and PLR cut-off levels were 3.98 mmol/L and 117, respectively. Further multivariate analysis indicated that female sex, preoperative serum potassium level < 3.98 mmol/L, and preoperative PLR ≥ 117 were independently associated with postoperative hypokalemia. We constructed a predictive nomogram with all these factors for the risk of postoperative hypokalemia with good discrimination and internal validation.

Conclusions

The predictive nomogram for postoperative hypokalemia risk constructed with these factors had good discrimination and internal validation. The developed nomogram will add value to these independent risk factors that can be identified at admission in order to predict postoperative hypokalemia.

Details

Title
Prediction of postoperative hypokalemia in patients with oral cancer undergoing en bloc cancer resection: a retrospective cohort study
Author
Bao, Qilin; Song, Lei; Ma, Liyuan; Wang, Meng; Hou, Zhaohuan; Lin, Jie; Li, Chunjie
Pages
1-12
Section
Research
Publication year
2023
Publication date
2023
Publisher
BioMed Central
e-ISSN
14726831
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2865397930
Copyright
© 2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.