Diagnostic Value of the Systemic Immune-Inflammation Index in Newborns with Urinary Tract Infection

Aim of this study is to investigate the diagnostic role of the systemic immune-inflammation index (SII; neutrophil × platelet [PLT]/lymphocyte) in the prediction of renal involvement in newborns with urinary tract infection (UTI).

We conducted a retrospective cohort study among 117 newborns with a gestational age greater than 35 weeks and hospitalized in the NICU. Laboratory values obtained from blood samples taken before the initiation of antibiotics were evaluated for renal function tests, complete blood count, and acute phase reactants. The ratios of platelet-to-lymphocyte (PLR), neutrophil-to-lymphocyte (NLR), and SII were calculated. The patients were divided into two main groups according to the presence of urinary tract pathology in ultrasonography (US): group 1, UTI with renal involvement (n = 43) and group 2, UTI without renal involvement (n = 74). Predictive values of different tests were compared.

The mean white blood cell, PLT, mean PLT volume, and neutrophile counts were higher, while lymphocyte counts were significantly lower in group 1 than those of group 2. Interleukin 6 (IL-6; pg/mL; IL-6), C-reactive protein (CRP; mg/L), NLR, PLR, and SII values were also higher in group 1. Receiver operating characteristics curve showed that SII, CRP, IL-6, PLR, and NLR have a predictive ability to discriminate renal involvement from normal renal findings in newborns with UTI. The SII produced an area under curve of 0.75 (72% sensitivity and 60.8% specificity). To define renal involvement, the cut-off values of SII, CRP, IL-6, PLR, and NLR were 217, 3.06, 23, 65.5, and 0.60, respectively.

Our results showed that SII might be used as an additional parameter in the prediction of renal involvement in newborns with UTIs. Further studies are required.

· Most UTIs in newborns present with upper UTI rather than simple cystitis.. · Some inflammatory markers can be used for the diagnosis of UTIs.. · SII may be useful in the prediction of urinary tract infections..