Relationship Between White Blood Cell Count and Bacteremia Using Interval Likelihood Ratios in Hospitalized Patients.

BACKGROUND

Patients with bacteremia often have elevated white blood cell (WBC) and neutrophil counts, yet these alone are poor predictors of bacteremia. Data on the continuous relationship between WBC response and bacteremia are lacking.

OBJECTIVE

This study aims to characterize the relationship of WBC count, neutrophil percentage, and absolute neutrophil count (ANC) to bacteremia using interval likelihood ratios (ILRs) derived from a large sample of hospitalized patients.

DESIGN

Retrospective cohort study in a large healthcare system from 2017 to 2018.

PATIENTS

This study included non-surgical inpatients who had at least one complete blood count (CBC) with differential up to 24 hours after admission and a blood culture. Patients with immunosuppression and malignancy or who received antibiotics before negative blood cultures were excluded.

MAIN MEASURES

Predictors were WBC count, ANC, and neutrophil percentage. The outcome was bacteremia. We compared test discrimination using the area under the receiver operating characteristics curve (AUROC). We calculated ILRs for bacteremia across test value intervals. As a practical example, we assumed a 5% pre-test probability of bacteremia and calculated the post-test probability for each interval. We compared this approach to a threshold approach using a threshold of 70% neutrophils.

RESULTS

Of 25,776 patients with a CBC with differential and blood culture, 1160 had bacteremia. AUROC was highest for neutrophil percentage (0.74), followed by ANC (0.63) and WBC count (0.58). Probability of bacteremia increased exponentially from neutrophil percentage 80 to 100%. Odds of bacteremia varied 35-fold based on neutrophil percentage. A threshold approach with a cut-off of 70% significantly underestimated bacteremia risk at higher levels.

CONCLUSIONS

ILRs offered a more discriminating approach to estimating the probability of bacteremia than a single threshold. Physicians assessing risk of bacteremia should pay attention to the magnitude of abnormality because very high and very low values have much stronger predictive power than dichotomized results.