Plasma fibrinogen: A novel biomarker for preoperative prediction and quantification of peritoneal adhesions in emergency abdominal surgery

血浆纤维蛋白原:一种用于术前预测和量化急诊腹部手术中腹膜粘连的新型生物标志物

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Abstract

OBJECTIVE: Abdominal adhesions are the foremost complication following abdominal surgery, yet there is a noticeable lack of effective laboratory assessments that can be integrated with adhesion scoring systems to predict and quantify these adhesions. This study aims to explore the relationship between plasma fibrinogen (Fg) and abdominal adhesions, and to assess the feasibility of incorporating plasma Fg into a simplified Peritoneal Adhesion Index (PAI) score to predict and quantify these adhesions. METHODS: This retrospective study analyzed clinical data from 231 patients diagnosed with acute appendicitis who underwent surgery at The Third People's Hospital of Xinjiang Uygur Autonomous Region from July 2022 to August 2024. A comprehensive dataset including basic demographic information and laboratory results was compiled. Preoperative variables such as course of disease, plasma Fg, d-dimer, white blood cell count, neutrophil count, monocyte count, eosinophil count, basophil count, and lymphocyte countwere considered as independent variables. In the logistic regression analysis, the status of abdominal adhesion served as the dependent variable; in contrast, the simplified PAI score was the dependent variable in the multiple linear regression analysis. A cohort of 63 patients requiring emergency surgical intervention were prospectively enrolled for predictive modeling analysis between July 2022 and August 2024. RESULTS: Logistic regression analysis identified plasma Fg as an independent predictor of abdominal adhesion status, while other parameters showed no significant correlations. The area under the receiver operating characteristic curve (AUC) for diagnosing abdominal adhesion status using Fg was 0.856. The optimal cut-off value was identified as 3.205 g/L, with sensitivity and specificity values of 72.3% and 88.4%, respectively. The multiple linear regression analysis revealed significant associations of both course of disease (β=0.269, p = 0.001) and Fg (β=0.627, p < 0.001) with the simplified PAI score. The predictive equation formulated was: Y (simplified PAI score) = 1.928 + 0.269 * course (days) + 0.672 * Fg (g/L), resulting in an R-squared value of 0.487. The predictive model demonstrated an overall accuracy of 73.06% in identifying abdominal adhesion formation when using the predetermined cutoff value. Regarding the equation-based prediction of preoperative abdominal adhesions, the model showed limited predictive capability in adhesion-free patients, with an accuracy of merely 8.57%. However, in patients with abdominal adhesions, the predictive performance was as follows: precise prediction was achieved in 11 cases (39.28%), predictions with 1-point deviation were observed in 12 cases (42.86%), while deviations of 2 and 3 points were noted in 3 and 2 cases, respectively. By defining a Fg level below 3.205 g/L as indicative of no adhesions and applying the predictive equation only to patients with Fg levels of 3.205 g/L or higher, the overall predictive accuracy of the simplified PAI score significantly improved to 82.53% . CONCLUSION: Plasma Fg significantly correlates with abdominal adhesion and serves as a reliable predictor of abdominal adhesion status in patients undergoing acute abdominal surgery prior to intervention. The simplified PAI score correlates with both Fg and course of disease. However, used in isolation, the predictive equation shows suboptimal performance, particularly exhibiting reduced accuracy in patients without adhesions. To enhance predictive accuracy, it is advisable to integrate the criterion of Fg levels below 3.205 g/L as indicative of the absence of adhesions into the predictive equation for assessing abdominal adhesions.

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