BACKGROUND:Human neutrophil lipocalin (HNL) is used as a novel biomarker for infections. However, only a few studies have focused on the usefulness of HNL. The purpose of this study was to evaluate the diagnostic efficiency of HNL for identifying bacterial infections and to compare HNL with procalcitonin (PCT) and C-reactive protein (CRP).
METHODS:Hospital patients with acute infections of bacterial origin (n = 439), viral origin (n = 71), and healthy volunteers (n = 67) were included in the study. The infection status of each patient was verified using microbiological, serological, and PCR testing. Additionally, CRP, HNL, and PCT levels were measured by established methods.
RESULTS:In distinguishing bacterial and viral infections, area under the curve (AUC) analysis showed that, with a value of 0.81 (95% CI, 0.76-0.86), HNL was superior to CRP at 0.73 (0.68-0.79) and PCT at 0.64 (0.58-0.70). Interestingly, the combination of HNL, PCT, and CRP improved the diagnostic potential significantly with an AUC of 0.86 (0.82-0.90, P < 0.05). Furthermore, when comparing different infection site subgroups with healthy patients, HNL levels were higher in all bacterial groups, albeit to widely varying degrees (P < 0.0001), and HNL reached a higher level in bloodstream and abdominal infections. CRP levels showed the same trend as HNL levels. PCT levels were significantly increased in bloodstream infections, abdominal infections, and in bacterial pneumonia (P < 0.0001), while no significant differences were found in soft tissue (P = 0.4378) or urinary tract infections (P = 0.423). There was no difference in HNL and CRP levels between patients with Gram-negative bacterial (GNB) or Gram-positive bacterial infections. However, compared with controls, PCT was only increased in GNB-infected patients.
CONCLUSION:HNL detection can help diagnose patients with infectious diseases, and the diagnostic efficacy of HNL is not affected by the infected site or by pathogenic bacterial species. The combination of HNL, PCT, and CRP has a superior performance at identifying bacterial infections compared with traditional biomarkers.