Evidence mapPaperPMID 41310845Full record

ArticleEuropean journal of medical research2025

Prognostic significance of postoperative glycemic variability after gastric surgery: a retrospective cohort study and development of a mortality prediction model.

Yuanshuo Ge, Guangdong Wang, Yun Huang, Beilin Luo, Yaxin Zhang

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Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Yuanshuo Ge *Jinzhou Medical University, Jinzhou, 121001, Liaoning, China.
Guangdong Wang *Department of Respiratory and Critical Care Medicine, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shanxi, China.
Yun HuangDepartment of International Medical Center, First People's Hospital of Foshan, Foshan, 528000, Guangdong, China.
Beilin LuoThe Graduate School of Fujian Medical University, Fuzhou, 350000, China.
Yaxin ZhangDepartment of Neurology, Xiamen Humanity Hospital, Fujian Medical University, 3777 Xian Yue Road, Huli District, Xiamen, 361009, Fujian, China. yaxin1996@qq.com.

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6 · The paper itself

Abstract

backgroundGastric surgery is a critical intervention for conditions, such as gastric cancer, obesity, and peptic ulcer disease. Despite advances in surgical techniques and perioperative care, postoperative complications, including elevated mortality, remain a major concern. Glycemic variability (GV), calculated as the coefficient of variation of blood glucose levels during the ICU stay, has emerged as a potential predictor of adverse outcomes in critically ill patients. This study aimed to investigate the association between GV and postoperative mortality in patients undergoing gastric surgery.

methodsData were obtained from the MIMIC-IV database, which contains anonymized health records of ICU patients admitted to Beth Israel Deaconess Medical Center. The cohort included adult patients admitted to the ICU following gastric surgery. GV was assessed using the coefficient of variation of all recorded blood glucose measurements during the ICU stay. The primary outcome was 30-day all-cause in-hospital mortality; the secondary outcome was 90-day mortality. Associations between GV and outcomes were analyzed using Cox proportional hazards models and Kaplan-Meier survival analysis. In addition, machine learning models were developed to evaluate the predictive value of GV.

resultsA total of 1099 patients were included. Higher GV was significantly associated with increased 30-day and 90-day mortality (HR 1.15, 95% CI 1.09-1.21; and HR 1.14, 95% CI 1.09-1.20, respectively). Threshold analysis identified inflection points at GV = 20.24 for 30-day mortality and GV = 33.96 for 90-day mortality. The stacking ensemble model incorporating GV achieved strong predictive performance, with an area under the receiver operating characteristic curve (AUC) of 0.83.

conclusionsGV is a significant and independent predictor of postoperative mortality in gastric surgery patients. The observed threshold effects suggest that maintaining GV below critical levels may improve early outcomes. These findings highlight the prognostic value of GV and support its potential as a target for postoperative management. Further prospective, multicenter studies are warranted to validate these results and guide clinical practice.

Indexed as

Blood GlucosePostoperative ComplicationsAgedFemaleHospital MortalityHumansIntensive Care UnitsMachine LearningMaleMiddle AgedPostoperative PeriodPrognosisRetrospective StudiesBlood GlucoseCritical careGastric surgeryGlycemic variabilityMortalityThreshold effect

Identifiers

PMID41310845
PMCPMC12751670

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