The relationship between preoperative systemic inflammation markers and postoperative complications in patients undergoing abdominal surgery

Abstract Objective This study aimed to evaluate the relationship between preoperative systemic inflammation markers and postoperative complications. Methods This study was conducted as a retrospective, single-center observational study. A total of 674 patients undergoing elective abdominal surgery under general anesthesia were included in the study. Data were collected through patient information forms, preoperative and postoperative laboratory values, and calculation of systemic inflammation markers. Independent samples t-test, Mann-Whitney U test, Pearson chi-square test, Wilcoxon test, Spearman correlation analysis, and multivariable logistic regression were used for data analysis. Results Data from 674 patients with a mean age of 57.17 ± 16.21 years were analyzed. Clavien-Dindo sınıflandırmasına göre hastaların %39,6’sında en az bir komplikasyon görülmüştür. A significant positive correlation was found between perioperative findings and systemic inflammation markers. Among the parameters evaluated, NLR (AUC = 0.995) and SII (AUC = 0.957) demonstrated the highest discriminative power, both remaining robust independent predictors in multivariable analysis. Conclusion This study demonstrated that measuring systemic inflammation markers preoperatively could be the easiest and most cost-effective method to predict postoperative complications. Therefore, routine assessment of these parameters before surgery may aid in the early identification of patients at risk, allowing for appropriate treatment planning.

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Publication Details

Journal
Langenbeck s Archives of Surgery
Published
2026-09-01
DOI
https://doi.org/10.1007/s00423-026-04182-4
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
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article

The relationship between preoperative systemic inflammation markers and postoperative complications in patients undergoing abdominal surgery

Alpen Yahya Gümüşoğlu, Muhammet Sait Toprak
Langenbeck s Archives of Surgery
Inflammatory Biomarkers in Disease Prognosis
article

The relationship between preoperative systemic inflammation markers and postoperative complications in patients undergoing abdominal surgery

Alpen Yahya Gümüşoğlu, Muhammet Sait Toprak
article en

Abstract

Abstract Objective This study aimed to evaluate the relationship between preoperative systemic inflammation markers and postoperative complications. Methods This study was conducted as a retrospective, single-center observational study. A total of 674 patients undergoing elective abdominal surgery under general anesthesia were included in the study. Data were collected through patient information forms, preoperative and postoperative laboratory values, and calculation of systemic inflammation markers. Independent samples t-test, Mann-Whitney U test, Pearson chi-square test, Wilcoxon test, Spearman correlation analysis, and multivariable logistic regression were used for data analysis. Results Data from 674 patients with a mean age of 57.17 ± 16.21 years were analyzed. Clavien-Dindo sınıflandırmasına göre hastaların %39,6’sında en az bir komplikasyon görülmüştür. A significant positive correlation was found between perioperative findings and systemic inflammation markers. Among the parameters evaluated, NLR (AUC = 0.995) and SII (AUC = 0.957) demonstrated the highest discriminative power, both remaining robust independent predictors in multivariable analysis. Conclusion This study demonstrated that measuring systemic inflammation markers preoperatively could be the easiest and most cost-effective method to predict postoperative complications. Therefore, routine assessment of these parameters before surgery may aid in the early identification of patients at risk, allowing for appropriate treatment planning.

Langenbeck s Archives of Surgery
Istanbul Kent University (TR), Bakırköy Dr.Sadi Konuk Eğitim ve Araştırma Hastanesi (TR), Sağlık Bilimleri Üniversitesi (TR)
Reduced inequalities
Openalex Percentile: Top 14%
Inflammatory Biomarkers in Disease Prognosis
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