Abstract
PurposeThe objective of this retrospective cohort study was to investigate the predictive value of stress-induced hyperglycemia parameters for delayed healing after tibial fracture post-surgery.MethodsA cohort of 108 participants who underwent surgical intervention for tibial fractures caused by trauma was included in this retrospective study. Data collected from electronic medical records encompassed demographic characteristics, bone healing assessments, stress-induced hyperglycemia parameters, inflammatory markers, and stress-related hormones. Comparative analyses, correlation analyses, univariate logistic regression analyses, and receiver operating characteristic (ROC) curve analyses were conducted to assess the predictive value of the studied parameters.ResultsThe delayed healing group exhibited higher levels of fasting blood glucose, postprandial glucose, and HbA1c, as well as elevated levels of inflammatory markers and stress-related hormones compared to the normal healing group. Correlation analysis and logistic regression demonstrated positive associations between stress-induced hyperglycemia parameters, inflammatory markers, stress-related hormones, and delayed union of tibial fractures (R2: 0.183 ~ 0.403;OR: 1.091 ~ 16.332). ROC curve analysis revealed high area under the curve (AUC = 0.911) values for stress-induced hyperglycemia parameters, indicating their potential as predictive markers for delayed healing. Multivariate regression analysis further substantiated the predictive capability of stress-induced hyperglycemia parameters.ConclusionThe study findings highlight the complex interplay between stress-induced hyperglycemia, inflammatory response, and bone healing outcomes in patients undergoing surgical intervention for tibial fractures. The identification of stress-induced hyperglycemia parameters as potential predictive markers for delayed healing after tibial fracture surgery offers insights for risk assessment and patient management, emphasizing the need for comprehensive understanding of these factors to optimize postoperative recovery in orthopedic patients.
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