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The early identification of sepsis in surgical intensive care patients is challenging due to the physiological postoperative alterations of vital signs and inflammatory biomarkers. Soluble Delta-like protein 1 (sDLL1) may be a potential discriminatory biomarker for this purpose. For this reason, this study aimed to evaluate sDLL1 for the identification of sepsis in a cohort of surgical intensive care patients. This study comprises a secondary analysis of a prospective observational study including 80 consecutive patients. The study groups included 20 septic shock patients, 20 patients each undergoing major abdominal surgery (MAS) and cardiac artery bypass surgery (CABG), and 20 matched control subjects (CTRL). The surveillance period was 72 h. The plasma concentration of sDLL1 was measured with ELISA. The plasma levels of sDLL1 were significantly elevated in septic patients compared to both surgical cohorts (septic vs. all postoperative time points, data are shown as median and interquartile range [IQR]; septic shock: 17,363 [12,053-27,299] ng/mL, CABG 10,904 [8692-16,250] ng/mL; MAS 6485 [4615-9068] ng/mL; CTRL 5751 [3743-7109] ng/mL; septic shock vs. CABG: p < 0.001; septic shock vs. MAS: p < 0.001). ROC analysis showed a sufficient prediction of sepsis with limited specificity (AUCROC 0.82 [0.75-0.82], sensitivity 84%, specificity 68%). The plasma levels of sDLL correlated closely with renal parameters (creatinine: correlation coefficient = 0.60, r = 0.37, p < 0.0001; urea: correlation coefficient = 0.52, r = 0.26, p < 0.0001), resulting in a good predictive performance of sDLL1 for the identification of acute kidney injury (AKI; AUCROC 0.9 [0.82-0.9], sensitivity 83%, specificity 91%). By quantifying the plasma concentration of sDLL1, sepsis can be discriminated from the physiological postsurgical inflammatory response in abdominal and cardiac surgical patients. However, sDLL1 has only limited specificity for the detection of sepsis in cardiac surgical patients, which may be explained by impaired renal function. Based on these findings, this study identifies the predictive value of sDLL1 for the detection of AKI, making it a potential biomarker for surgical intensive care patients.Trial registration DRKS00013584, Internet Portal of the German Clinical Trials Register (DRKS), registration date 11.07.2018, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00013584 .