Predictive value of urinalysis parameters for risk stratification of Staphylococcus aureus bacteremia in patients with Staphylococcus aureus bacteriuria

Aims Excluding bacteremia is clinically important in patients with Staphylococcus aureus bacteriuria (SABU), yet reliable predictors of concomitant S. aureus bacteremia (SAB) remain insufficiently defined. This study aimed to evaluate whether routine urinalysis parameters can predict concomitant SAB in patients with SABU.Methods This retrospective cohort study included 82 patients with SABU. Demographic characteristics, urinalysis findings, inflammatory markers, and blood culture results were analyzed. Receiver operating characteristic (ROC) curve analysis and multivariate logistic regression were performed to identify predictors of SAB.Results Concomitant SAB was detected in 29 patients (35.4%). Urinary bacterial count (31 vs 1/high-power field (HPF)) and erythrocyte count (39 vs 8/HPF) were significantly higher in bacteremic patients, together with elevated C-reactive protein (CRP) levels (all p < 0.05). ROC analysis identified an optimal cutoff value of 11/HPF for urinary bacterial count, with 82.8% sensitivity, 81.1% specificity, and a negative predictive value of 89.6% (AUC: 0.867). In multivariate analysis, urinary bacterial count, age, and CRP level remained independently associated with concomitant SAB.Conclusions In conclusion, increased urinary bacterial count was associated with concomitant SAB and demonstrated a high negative predictive value for excluding bacteremia. Routine urinalysis parameters may contribute to early risk stratification in patients with SABU.

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Journal
Future Microbiology
Published
2026-09-04
DOI
https://doi.org/10.1080/17460913.2026.2728898
Primary Topic
Urinary Tract Infections Management
Type
article
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article

Predictive value of urinalysis parameters for risk stratification of Staphylococcus aureus bacteremia in patients with Staphylococcus aureus bacteriuria

Fatih Çubuk, Murtaza Öz, Özlem Aldemir
Future Microbiology
Urinary Tract Infections Management
article

Predictive value of urinalysis parameters for risk stratification of Staphylococcus aureus bacteremia in patients with Staphylococcus aureus bacteriuria

Fatih Çubuk, Murtaza Öz, Özlem Aldemir
article en

Abstract

Aims Excluding bacteremia is clinically important in patients with Staphylococcus aureus bacteriuria (SABU), yet reliable predictors of concomitant S. aureus bacteremia (SAB) remain insufficiently defined. This study aimed to evaluate whether routine urinalysis parameters can predict concomitant SAB in patients with SABU.Methods This retrospective cohort study included 82 patients with SABU. Demographic characteristics, urinalysis findings, inflammatory markers, and blood culture results were analyzed. Receiver operating characteristic (ROC) curve analysis and multivariate logistic regression were performed to identify predictors of SAB.Results Concomitant SAB was detected in 29 patients (35.4%). Urinary bacterial count (31 vs 1/high-power field (HPF)) and erythrocyte count (39 vs 8/HPF) were significantly higher in bacteremic patients, together with elevated C-reactive protein (CRP) levels (all p < 0.05). ROC analysis identified an optimal cutoff value of 11/HPF for urinary bacterial count, with 82.8% sensitivity, 81.1% specificity, and a negative predictive value of 89.6% (AUC: 0.867). In multivariate analysis, urinary bacterial count, age, and CRP level remained independently associated with concomitant SAB.Conclusions In conclusion, increased urinary bacterial count was associated with concomitant SAB and demonstrated a high negative predictive value for excluding bacteremia. Routine urinalysis parameters may contribute to early risk stratification in patients with SABU.

Future Microbiology
Sivas Cumhuriyet Üniversitesi (TR), Sivas State Hospital (TR)
Openalex Percentile: Top 10%
Urinary Tract Infections Management
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Predictive value of urinalysis parameters for risk stratification of Staphylococcus aureus bacteremia in patients with Staphylococcus aureus bacteriuria — Fatih Çubuk, Murtaza Öz, et al. · Future Microbiology (2026) | TGRS Research Map | TGRS