title: Predicting bacteraemia in validated models--a systematic review.
abstract: Bacteraemia is associated with high mortality. Although many models for predicting bacteraemia have been developed, not all have been validated, and even when they were, the validation processes varied. We identified validated models that have been developed; asked whether they were successful in defining groups with a very low or high prevalence of bacteraemia; and whether they were used in clinical practice. Electronic databases were searched to identify studies that underwent validation on prediction of bacteraemia in adults. We included only studies that were able to define groups with low or high probabilities for bacteraemia (arbitrarily defined as below 3% or above 30%). Fifteen publications fulfilled inclusion criteria, including 59 276 patients. Eleven were prospective and four retrospective. Study populations and the parameters included in the different models were heterogeneous. Ten studies underwent internal validation; the model performed well in all of them. Twelve performed external validation. Of the latter, seven models were validated in a different hospital, using a new independent database. In five of these, the model performed well. After contacting authors, we found that none of the models was implemented in clinical practice. We conclude that heterogeneous studies have been conducted in different defined groups of patients with limited external validation. Significant savings to the system and the individual patient can be gained by refraining from performing blood cultures in groups of patients in which the probability of true bacteraemia is very low, while the probability of contamination is constant. Clinical trials of existing or new models should be done to examine whether models are helpful and safe in clinical use, preferably multicentre in order to secure utility and safety in diverse clinical settings.
authors: Unit of Infectious Diseases Rabin Medical Center, Beilinson Hospital, Petah-Tikva, Israel; Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel. Electronic address: noaeliakim@gmail.com.
authors: N
authors: N
authors: Eliakim-Raz
authors: Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA.
authors: D W
authors: DW
authors: Bates
authors: Department of Medicine E, Rabin Medical Center, Beilinson Hospital, Petah-Tikva, Israel; Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel.
authors: L
authors: L
authors: Leibovici
mesh_terms: D016470:Bacteremia / Q000175:diagnosis*; D001769:Blood / Q000382:microbiology; D003661:Decision Support Techniques; D006801:Humans; D008828:Microbiological Techniques / Q000379:methods
keywords: Bacterial bloodstream infections; blood cultures; prediction models; sepsis; validation