Biomarkers for Detecting Surgical Emergency in Acute Abdomen—A Prospective Observational Study
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: In the emergency setting, acute abdominal pain is a diagnostic challenge. We evaluated the diagnostic value of selected inflammatory and stress biomarkers to identify surgical emergency. METHODS: Patients presenting to the emergency department (ED) with acute abdominal pain were included in this prospective observational study. Copeptin, cortisol, procalcitonin, and interleukin 6 (IL-6) were measured upon presentation and at 4 h, in addition to C-reactive protein (CRP), and leukocyte and neutrophil cell counts. At 2 weeks, follow-up was performed by telephone interview. RESULTS: Of the 304 patients included, 46 (15%) patients had a surgical emergency and 87 (29%) a medical emergency. On admission, CRP, procalcitonin, and leukocyte and neutrophil cell counts were higher in patients with a surgical emergency (P = 0.024, P = 0.009, P = 0.0032, and P < 0.0001, respectively) and medical emergency (all P < 0.001) as compared to patients without emergency. Area under the receiver operating characteristic curve (AUC) was to predict surgical emergency and were good for leukocyte (AUC 0.75, 95% CI, 0.66-0.84) and neutrophil cell count (AUC 0.75, 95%, CI 0.66-0.84), mediocre for CRP (AUC 0.64, 95% CI, 0.55-0.73) and procalcitonin (AUC 0.62, 95%CI 0.45-0.75), and not useful for IL-6, copeptin, or cortisol. A recursive partitioning prediction model yielded CRP as the most relevant biomarker to predict surgical emergency. CONCLUSIONS: The stress biomarkers copeptin and cortisol were not useful for identifying surgical emergency. Among the tested biomarkers, initial leukocyte and neutrophil cell counts, CRP and procalcitonin, and IL-6 at Hour 4, performed similarly to identify surgical emergency in acute abdomen. CLINICALTRIALS.GOV REGISTRATION NUMBER: NCT02399150.
DOI: 10.1093/jalm/jfaf137
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,212
OpenAlex ID: W4415958751
