Nomogram to predict postoperative cognitive dysfunction in elderly patients undergoing gastrointestinal tumor resection

Huifan Huang; Jing Chou; Yongzhong Tang; Wen Ouyang; Xiaoxia Wu; Yuan Le

doi:10.3389/fnagi.2022.1037852

Nomogram to predict postoperative cognitive dysfunction in elderly patients undergoing gastrointestinal tumor resection

Front Aging Neurosci. 2022 Oct 25:14:1037852. doi: 10.3389/fnagi.2022.1037852. eCollection 2022.

Authors

Huifan Huang¹, Jing Chou², Yongzhong Tang¹, Wen Ouyang^{1

3}, Xiaoxia Wu⁴, Yuan Le^{1

3}

Affiliations

¹ Department of Anesthesiology, The Third Xiangya Hospital, Central South University, Changsha, China.
² Department of Gastrointestinal Surgery, The Third Xiangya Hospital, Central South University, Changsha, China.
³ Hunan Province Key Laboratory of Brain Homeostasis, The Third Xiangya Hospital, Central South University, Changsha, China.
⁴ Department of Nursing, The Third Xiangya Hospital, Central South University, Changsha, China.

Abstract

Objective: To establish a nomogram model for the prediction of postoperative cognitive dysfunction (POCD) in elderly patients undergoing gastrointestinal tumor resection.

Methods: A total of 369 elderly patients scheduled for elective gastrointestinal tumor resection under general anesthesia were included. The cognitive function of each participant was assessed by the Mini-Mental State Examination (MMSE) 1 day before surgery and 7 days after surgery for the diagnosis of POCD. According to the results, patients were divided into a POCD group and a non-POCD group. The differences in hospitalization data and examination results between the two groups were compared. A logistic regression model was used to explore the risk factors for POCD in elderly patients undergoing gastrointestinal tumor resection, and a nomogram was then constructed based on these factors. The diagnostic performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUROC) and a calibration plot. The clinical usefulness of the nomogram was estimated using decision curve analysis (DCA).

Results: Among the 369 patients undergoing gastrointestinal tumor resection, 79 patients had POCD, with a positive rate of 21.4%. The nomogram model comprised the following variables: age, body mass index (BMI), history of cerebrovascular disease, preoperative white blood cell (WBC) count, preoperative hemoglobin (Hb) level, intra-operative blood loss, and operation time. The model showed good discrimination, with an area under the curve (AUC) of 0.710 (95% CI = 0.645-0.775), and good calibration (Hosmer-Lemeshow test, χ² = 5.133, p = 0.274). Internal validation also maintained ideal discrimination and calibration. Decision curves indicated that when the threshold probability was above 0.1, the nomogram achieved more benefit than both the treat-all and treat-none policies.

Conclusion: This scoring system is the first nomogram model developed for the prediction of POCD in elderly patients undergoing gastrointestinal tumor resection. It has good efficacy in the prediction of POCD risk and could provide an important reference for the prevention, management, and treatment of POCD.

Keywords: gastrointestinal tumors; nomogram; postoperative cognitive dysfunction; prediction model; risk factors.