ArticleBMC oral health2024
Multi-factor early monitoring method based on D-dimer for iliac crest flap loss.
Article in BMC oral health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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5 authors.
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Abstract
backgroundIn recent years, the utilization of autogenous vascularized iliac crest flap for repairing jaw defects has seen a significant rise. However, the visual monitoring of iliac bone flaps present challenges, frequently leading to delayed detection of flap loss. Consequently, there's a urgent need to develop effective indicators for monitoring postoperative complications in iliac crest flaps.
methodsA retrospective analysis was conducted on 160 patients who underwent vascularized iliac crest flap transplantation for jawbone reconstruction from January 2020 to December 2022. We investigated the changes in D-dimer levels among patients with or without postoperative complications. Additionally, multivariable logistic regression analysis was performed to explore potential individual risk factors, including surgical duration, age, pathology type, absolute and relative D-dimer levels, and gender, culminating in the development of a nomogram.
resultsOn the first day following surgery, patients who experienced thrombosis exhibited a substantial increase in plasma D-dimer levels, reaching 3.75 mg/L, 13.84 times higher than the baseline. This difference was statistically significant (P < 0.05) compared to patients without postoperative complications. Furthermore, the nomogram we have developed and validated effectively predicts venous thrombosis, assigning individual risk scores to patients. This predictive tool was assessed in both training and validation cohorts, achieving areas under the curve (AUC) of 0.630 and 0.600, with the 95% confidence intervals of 0.452-0.807 and 0.243-0.957, respectively.
conclusionsOur study illustrates that postoperative plasma D-dimer levels can serve as a sensitive biomarker for monitoring thrombosis-induced flap loss. Moreover, we have developed a novel prediction model that integrates multiple factors, thereby enhancing the accuracy of early identification of patients at risk of thrombosis-associated flap loss. This advancement contributes to improving the overall management and outcomes of such procedures.
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