Setting

This population-based cohort study was conducted in 2007–2008 in three areas: the Copenhagen City area (population ~625.000, served by five public hospitals), the Copenhagen County area (population ~600.000, served by three public hospitals) and the North Denmark Region (population ~575,000, served by eight public hospitals) [31]. In total, the population base comprised approximately 1/3 of the Danish population.

Unlimited access to health services free of charge is provided to all Danish residents through a tax-funded health care program. Only few patients, e.g. in need of solid organ transplantation, were referred to hospitals outside the area in which they resided. All Danish residents have a unique civil registration number, which is used for all health-care contacts, permitting unambiguous linkage between registries [32].

Data source

Data were obtained from the Danish Collaborative Bacteremia Network (DACOBAN), which includes the Departments of Clinical Microbiology (DCMs) in the North Denmark Region (DCM Aalborg) and the greater Copenhagen area (DCM Hvidovre and DCM Herlev) and cover the years 2000–2011 [31]. These DCMs use the same laboratory information system (ADBakt, Autonik, Sweden) and the same electronic platform is used at all three sites for real-time recording of key information on bacteraemia patients. This has allowed a uniform prospective registration of bacteraemias by physicians and a common database has been developed through linkage of data sets. The database includes the species, type, and susceptibility pattern of the bacterial and fungal isolates, origin of infection, suspected focus of infection (only for 2007–2008), and antibiotic treatment (at the time of the first notification (=EAT) and the second notification, only for 2007–2008), besides the patients’ age, gender, and day of admission. The data were linked to the Danish National Patient Registry [33] and the Danish Civil Registration System [32]. These registries hold information on the dates of admission and discharge and up to 20 physician-given discharge diagnoses, classified according to the Danish version of the International Classification of Diseases (ICD-10), and daily updated records on the vital status of all Danish residents, including date of emigration or death.

Assessment of bacteraemia

Figure 1 describes the derivation of the study cohort. The study comprised all patients with clinically and microbiologically verified bacteraemia. To be eligible, patients had to have an incident episode of bacteraemia, i.e. no prior bacteraemic episode during the preceding 365 days. Follow-up of recurrence and vital status was conducted through 2009. Patients dying on days 0 and 1 were excluded for several reasons: bacteraemia has a time-dependent progression that reflects the dynamic interplay of the infectious agent, the host’s immune responses, and therapeutic interventions, including EAT. The critical time for antibiotics to mitigate the lethal effects of infection is generally not known, whereas other interventions including goal directed therapy have been shown to be effective within hours [34–36].

Fig. 1 Derivation of the study population Full size image

An episode of bacteraemia was defined as all clinically important blood culture isolates within the initial two days of the drawing of the sentinel blood culture (days 0 and 1) and any re-isolation of the same species within 30 days. Polymicrobial bacteraemia was defined as an episode with more than one clinically important blood culture isolate detected within the initial two days. Recurrent episodes of bacteraemia were determined by either blood culture isolate(s) of a different species obtained more than two days after the incident episode or by blood culture of the same species more than 30 days after the incident episode [26, 37, 38]. In most cases, the arbitrary 30-day limit allows for time to resolution of the infection or immediate failure of therapy [39–41].

The infection was defined as community-acquired or nosocomial according to the CDC criteria of 1988 [42]. In addition, healthcare-associated bacteraemia was defined as an episode of bacteraemia in patients with hospital contact within 30 days prior to admission (regular visits, e.g. for haemodialysis or chemotherapy, or a hospital stay) in accordance with the definitions of Friedman et al. [43] except that we had no data on home nursing or residency in nursing homes.

Data were assessed for common skin contaminants (Bacillus spp., Corynebacterium spp. Propionibacterium spp., Micrococcus spp., and coagulase-negative staphylococci). Isolation of these organisms from at least two different sets of blood draws within a 5-day period was required to fulfil the criteria for bacteraemia [44].

Assessment of EAT

We defined EAT as the antibiotic treatment given at the 1st notification of a positive blood culture. It was recorded as appropriate if given intravenously (except fluoroquinolones, metronidazole, and fluconazole) and if all the blood isolates were susceptible to one or more of the antibiotics given. Inappropriate EAT covered recorded EAT that did not fulfil these criteria whereas unknown EAT comprised unrecorded EAT.

Assessment of comorbidity

Charlson comorbidity index scores were calculated using discharge data from the Danish National Patient Registry as previously described [26, 45]. Three levels of the index were defined: 0 (low), corresponding to no recorded underlying diseases implemented in the index, 1–2 (medium), and >2 (high).

Microbial identification and susceptibility testing

Blood cultures were processed using either the BacT/Alert™ system (bioMérieux, Marcy l´Etoile, France) (DCM Aalborg and DCM Hvidovre) or the BACTEC 9240™ system (Becton Dickinson, Sparks, MD, USA) (DCM Herlev). The standard method for susceptibility testing of non-fastidious bacteria was disk diffusion (NeoSensitabs, Rosco, Taastrup, Denmark (DCM Aalborg) or Oxoid, Basingstoke, UK) on Mueller-Hinton agar (DCM Aalborg) or Iso-Sensitest (ISA) medium (DCM Herlev and DCM Hvidovre). Minimum inhibitory concentration (MIC) break-points were as recommended by The Swedish Reference Group for Antibiotics with the exception that the wild-type population of Escherichia coli was categorized as susceptible to ampicillin at DCMs Herlev and Aalborg in accordance with national practice [46]. Susceptibility testing was standardized according to The Swedish Reference Group for Antibiotics (now NordicAST). All three laboratories use Neqas external quality control specimens.

Statistical analyses

We considered three different study outcomes: recurrence, 2–30 day mortality, and 31–365 day mortality. The start of follow-up was defined as the date of the sentinel blood culture.

The data were first analysed using contingency tables. Covariates were categorized as follows: age (0–15, 16–64, 65–79, 80+ years), gender, Charlson comorbidity index scores (0, 1–2, >2), origin of infection (community-acquired, nosocomial, healthcare-associated, unknown), speciality (medicine, surgery, intensive-care unit, paediatrics, unknown), group of microorganisms (monomicrobial Gram-positive, monomicrobial Gram-negative, monomicrobial anaerobic, fungal, polymicrobial), and focus of infection (urogenital, respiratory, abdominal, miscellaneous, unknown).

Cumulative incidence curves of recurrence by EAT status were computed, treating death as a competing risk. The cause-specific hazard for recurrence (2–365 days) was modelled by a Cox proportional hazards approach, treating death or end of follow-up period as censored. Hazard ratios (HR) for inappropriate EAT and unknown EAT were computed with 95% confidence intervals (CIs) using appropriate EAT as reference group. The following covariates were controlled for in the adjusted analyses: age, gender, Charlson comorbidity index score, origin of infection, speciality, and group of microorganism. The focus of infection was excluded due to correlation to microorganism and because of missing values.

To illustrate mortality over time, we computed crude survival curves (2-365 days mortality) stratified by EAT. For 2-30 and 31-365 day mortality we used logistic regression analysis to compute odds ratios (ORs) with 95% CIs, using appropriate EAT as reference group, while controlling for the same covariates as listed in the Cox regression analysis.

We further reiterated the regression analyses for patients with monotherapy and combination therapy.

Statistical analyses were performed using Stata® SE (StataCorp, College Station, TX, USA).