Establishment and validation of a risk prediction model for delayed neurocognitive recovery after laparoscopic colorectal cancer surgery
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1.Department of Anesthesiology, Xiangya Hospital, Central South University, Changsha 410008, China;2.National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Changsha 410008, China

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R735.3

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    Abstract:

    Background and Aims The incidence rate of delayed neurocognitive recovery (DNR) following laparoscopic surgery for colorectal cancer is high and significantly affects patient recovery. Therefore, this study was performed to analyze the risk factors for postoperative DNR following laparoscopic surgery for colorectal cancer and to construct a risk prediction model, in order to provide evidence-based guidance for the prevention and treatment of postoperative DNR.Methods The clinical data of 227 patients with colorectal cancer who underwent laparoscopic surgery with intraoperative monitoring of regional cerebral tissue oxygen saturation (rScO2) in Xiangya Hospital, Central South University, from March 2018 to July 2020 were retrospectively analyzed. Common and potential factors for postoperative DNR were selected as analysis variables. Univariate and multivariate analyses were performed to determine the predictive factors of the model and construct a risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves, the fit between the model and data was assessed using calibration curves, and nomograms were plotted. Additionally, 30 patients meeting the inclusion and exclusion criteria from January 2021 to July 2021 were selected for external validation of the prediction model.Results The incidence rate of postoperative DNR in the modeling group was 15.4% (35/227). Multivariate analysis showed that age, years of education, comorbid diabetes, and lowest intraoperative rScO2 were independent influencing factors for postoperative DNR (all P<0.05). Based on this, a risk prediction model for postoperative DNR following laparoscopic surgery for colorectal cancer was constructed, with an area under the ROC curve of 0.757 (95% CI=0.676-0.839, P<0.001). The calibration curve demonstrated good model fit according to the Hosmer-Lemeshow test (P=0.516), and the external validation C-index was 0.617.Conclusion The risk prediction model for postoperative DNR associated with rScO2 monitoring can be used for individualized assessment of patients undergoing laparoscopic colorectal cancer surgery, and provide a clinical basis for the prevention of postoperative DNR.

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LUO Ning, YE Chunyan, LIU Xingyang, WANG Lu, WANG E, LI Longyan. Establishment and validation of a risk prediction model for delayed neurocognitive recovery after laparoscopic colorectal cancer surgery[J]. Chin J Gen Surg,2024,33(4):603-611.
DOI:10.7659/j. issn.1005-6947.2024.04.010

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History
  • Received:June 21,2023
  • Revised:December 08,2023
  • Adopted:
  • Online: April 29,2024
  • Published: