Urinary biomarkers for diagnosing acute kidney injury in sepsis in the emergency department

尿液生物标志物在急诊科脓毒症急性肾损伤诊断中的应用

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作者:Sumin Baek, Inwon Park, Seonghye Kim, Young Woo Um, Hee Eun Kim, Kyunghoon Lee, Jae Hyuk Lee, You Hwan Jo

Background

Development of acute kidney injury (AKI) in patients with sepsis is associated with increased mortality, highlighting the importance of early detection and management. However, baseline creatinine or urine output measurements are required for AKI diagnosis, which can be challenging in emergency departments (EDs). We aimed to evaluate the association between urinary biomarkers and the AKI diagnosis or 30-day survival status in patients with sepsis in the ED.

Conclusion

None of the urinary biomarkers in the initial urine sample demonstrated an independent association with AKI diagnosis or 30-day survival status in patients with sepsis presenting to the ED. Further studies with larger population are necessary to confirm its clinical utility and explore its role.

Methods

This prospective observational study enrolled patients from a single ED. We enrolled adult patients presenting to the ED with symptoms suggestive of infection and an initial quick sequential organ failure assessment score ≥2. Initial urine samples were collected, and urinary biomarkers (dickkopf-3, soluble triggering receptor expressed on myeloid cells-1, kidney injury molecule-1, neutrophil gelatinase-associated lipocalin (NGAL), and tissue inhibitor of metalloproteinases-2 (TIMP-2), and insulin-like growth factor binding protein-7 (IGFBP-7), and TIMP-2 × IGFBP-7) were analyzed using an enzyme-linked immunosorbent assay kit. Multivariable logistic regression models were used to evaluate biomarker performance.

Results

Of 84 patients, 63 (75.0 %) were diagnosed with AKI and 16 (19.0 %) died within 30 days. None of the urinary biomarkers demonstrated significant differences between the survivors and non-survivors. NGAL (p = 0.014) and TIMP-2 × IGFBP-7 (p = 0.027) levels were different between the AKI and non-AKI groups. The multivariable logistic regression model suggested a higher area under the receiver operating characteristic curve for models, including TIMP-2 × IGFBP-7 (from 0.853 to 0.889, p = 0.018).

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