title: Can We Reduce Negative Blood Cultures With Clinical Scores and Blood Markers? Results From an Observational Cohort Study.
abstract: Only a small proportion of blood cultures routinely performed in emergency department (ED) patients is positive. Multiple clinical scores and biomarkers have previously been examined for their ability to predict bacteremia. Conclusive clinical validation of these scores and biomarkers is essential.This observational cohort study included patients with suspected infection who had blood culture sampling at ED admission. We assessed 5 clinical scores and admission concentrations of procalcitonin (PCT), C-reactive protein (CRP), lymphocyte and white blood cell counts, the neutrophil-lymphocyte count ratio (NLCR), and the red blood cell distribution width (RDW). Two independent physicians assessed true blood culture positivity. We used logistic regression models with area under the curve (AUC) analysis.Of 1083 patients, 104 (9.6%) had positive blood cultures. Of the clinical scores, the Shapiro score performed best (AUC 0.729). The best biomarkers were PCT (AUC 0.803) and NLCR (AUC 0.700). Combining the Shapiro score with PCT levels significantly increased the AUC to 0.827. Limiting blood cultures only to patients with either a Shapiro score of ≥4 or PCT > 0.1 μg/L would reduce negative sampling by 20.2% while still identifying 100% of positive cultures. Similarly, a Shapiro score ≥3 or PCT >0.25 μg/L would reduce cultures by 41.7% and still identify 96.1% of positive blood cultures.Combination of the Shapiro score with admission levels of PCT can help reduce unnecessary blood cultures with minimal false negative rates.The study was registered on January 9, 2013 at the 'ClinicalTrials.gov' registration web site (NCT01768494).
authors.affiliation: From the University Department of Internal Medicine, Medical Faculty of the University of Basel, Kantonsspital Aarau, Switzerland (SL, NK, DS, ACR, AK, SF, LF, BM, PS); Asclepius Medical Communications LLC, Ridgewood, NJ, USA (PK); University Clinic of Infectious Diseases, University Hospital Bern (SH); Institute of Psychology, University of Bern (LF); Department of Laboratory Medicine, Kantonsspital (AH); and Clinic of Infectious Diseases, Kantonsspital Aarau, Switzerland (CAF).
authors.forename: Svenja
authors.initials: S
authors.lastname: Laukemann
authors.forename: Nina
authors.initials: N
authors.lastname: Kasper
authors.forename: Prasad
authors.initials: P
authors.lastname: Kulkarni
authors.forename: Deborah
authors.initials: D
authors.lastname: Steiner
authors.forename: Anna Christina
authors.initials: AC
authors.lastname: Rast
authors.forename: Alexander
authors.initials: A
authors.lastname: Kutz
authors.forename: Susan
authors.initials: S
authors.lastname: Felder
authors.forename: Sebastian
authors.initials: S
authors.lastname: Haubitz
authors.forename: Lukas
authors.initials: L
authors.lastname: Faessler
authors.forename: Andreas
authors.initials: A
authors.lastname: Huber
authors.forename: Christoph A
authors.initials: CA
authors.lastname: Fux
authors.forename: Beat
authors.initials: B
authors.lastname: Mueller
authors.forename: Philipp
authors.initials: P
authors.lastname: Schuetz
mesh_terms: D000368:Aged; D016470:Bacteremia / Q000097:blood* / Q000175:diagnosis*; D001431:Bacteriological Techniques / Q000379:methods*; D015415:Biomarkers; D002097:C-Reactive Protein / Q000032:analysis; D002116:Calcitonin / Q000097:blood; D015740:Calcitonin Gene-Related Peptide; D004912:Erythrocytes; D005188:False Negative Reactions; D005260:Female; D006801:Humans; D007958:Leukocyte Count; D008214:Lymphocytes; D008297:Male; D008875:Middle Aged; D009504:Neutrophils; D011446:Prospective Studies; D011498:Protein Precursors / Q000097:blood
chemical_list: D015415:Biomarkers; C000606589:CALCA protein, human; D011498:Protein Precursors; D002116:Calcitonin; D002097:C-Reactive Protein; D015740:Calcitonin Gene-Related Peptide