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Abstract
Background
Alterations in blood cell count are well recognized features of bacteremia. The study objective was to determine the hematologic changes predictive of bacteremia.
Methods
We retrospectively studied febrile adult patients with neutrophilia and included patients were either bacteriologically proven cases or those who had clinically suspected bacterial infections. Hematologic findings derived from basic hematologic tests were compared between patients with and those without bacteremia.
Results
Of the 624 patients, 143 (22.9%) had significant bacteremia. The following items were significantly different between patients with and those without bacteremia by univariate analysis: absolute neutrophil count, neutrophil differential, absolute lymphocyte count, lymphocyte differential, platelet count and band-associated parameters such as absolute band neutrophil count (ABC). Multivariate analysis revealed platelet count, lymphocyte differential and ABC as independent predictors (P<0.0001, each). Platelet count, the most potent predictor of bacteremia, showed area under the curve (AUC) of 0.685. Analysis according to the primary diagnosis indicated that the most potent predictors of bacteremia in patients with respiratory tract, urinary tract and hepatobiliary system infections were platelet count (P=0.002, AUC=0.697), ABC (P=0.002, AUC=0.681) and neutrophil differential (P=0.0001, AUC=0.822), respectively.
Conclusions
Simple variables obtained from basic hematologic tests were associated with bacteremia even in febrile patients with neutrophilia. In particular, very high neutrophil differential was highly predictive of bacteremia in patients with hepatobiliary system infections and its clinical usefulness needs to be elucidated in a prospective study.
Figures and Tables
Fig. 1
ROC curve of neutrophil differential for the discrimination of bacteremic and non-bacteremic status in patients with hepatobiliary system infections. Areas under the ROC curve were 0.822 (95% confidence interval, 0.731 to 0.892). The sensitivity and specificity was 90.0% (95% confidence interval, 73.5 to 97.9) and 67.2% (95% confidence interval, 54.6 to 78.2), respectively, at the optimum cut-off level of 88.6%.
Table 2
Primary diagnoses of the patients
*Respiratory tract infection included pneumonia (N=266), pleural empyema (N=16), lung abscess (N=2), and acute tonsillitis (N=2); †Urinary tract infection included acute pyelonephritis (N=55), acute cystitis (N=7), acute prostatitis (N=2), and urinary tract infection, site unspecified (N=98); ‡Hepatobiliary system infection included acute cholecystitis (N=57), acute cholangitis (N=29), liver abscess (N=10), and pancreatic abscess (N=1); §Soft tissue or skin infection included cellulitis (N=16), skin abscess (N=8), pyomyositis (N=3), osteomyelitis (N=2), wound infection (N=1), and septic arthritis (N=1); ∥Gastrointestinal tract infection included enterocolitis (N=21), acute appendicitis (N=6), and rectal abscess (N=1); ¶Others included peritonitis (N=7), sepsis of unknown origin (N=4), pelvic inflammatory disease (N=3), typhoid fever (N=2), catheter-related infection (N=1), vibriosepsis (N=1), acute sinusitis (N=1), and meningitis (N=1).
Table 3
Comparison of continuous hematologic data between bacteremic and non-bacteremic patients
*All continuous variables are expressed as median (range); †P values were derived from univariate analysis using Mann-Whitney test; ‡Multivariate analysis revealed platelet count, lymphocyte differential, and ABC as the independent predictors (P<0.0001, P=0.004, and P=0.024, respectively).
Abbreviations: AUC, area under the curve; CI, confidence interval; CRP, C-reactive protein; WBC, white blood cell; ANC, absolute neutrophil count; ALC, absolute lymphocyte count; AEC, absolute eosinophil count; ABC, absolute band neutrophil count; BNR, band/segmented neutrophil ratio; ITR, immature granulocyte/total neutrophil ratio.
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