Background: Timely empiric antimicrobial therapy is one of the cornerstones of the management of suspected bloodstream infection (BSI). However, studies about the effects of empiric therapy on mortality have reported inconsistent results. The objective of this study was to estimate the effect of delay of appropriate empiric therapy on early mortality in patients with BSI. Methods: Data for the propensity score matching (PSM) study were obtained from a cohort of patients with BSI. Inadequate empiric treatment was defined as in vitro resistance to the antimicrobial regimen administered <6 h after blood cultures were taken. The primary outcome measure was 14-day mortality. Thirty-day mortality and median length of stay (LOS) were secondary outcomes. PSM was applied to control for confounding. Results: Of a total of 893 included patients with BSI, 35.7% received inadequate initial empiric treatment. In the PSM cohort (n = 334), 14-day mortality was 9.6% for inadequate antibiotic treatment, compared to. 10.2% in adequate empiric treatment (p = 0.85). No prolonged median LOS was observed in patients who initially received inadequate therapy (10.5 vs. 10.7 days, p = 0.89). Conclusions: In this study, we found no clear effect of inadequate empirical treatment on mortality in a low-risk BSI population. The importance of early empiric therapy compared to other determinants, may be limited. This may not apply for specific subpopulations, e.g., patients with sepsis.

From a stewardship perspective it is recommended that antibiotic guidelines are adjusted to the local setting, accounting for the local epidemiology of pathogens. In many settings the prevalence of Gram-negative pathogens with resistance to empiric sepsis therapy is increasing. How and when to escalate standard sepsis therapy to a reserve antimicrobial agent, is a recurrent dilemma. The study objective was to develop decision strategies for empiric sepsis therapy based on local microbiological and clinical data, and estimate the number needed to treat with a carbapenem to avoid mismatch of empiric therapy in one patient (NNTC). We performed a nested case control study in patients (> 18 years) with Gram-negative bacteremia in 2013–2016. Cases were defined as patients with Gram-negative bacteremia with in vitro resistance to the combination 2nd generation cephalosporin AND aminoglycoside (C-2GC + AG). Control patients had Gram-negative bacteremia with in vitro susceptibility to cefuroxime AND/OR gentamicin, 1:2 ratio. Univariate and multivariable analysis was performed for demographic and clinical predictors of resistance. The adequacy rates of empiric therapy and the NNTC were estimated for different strategies. The cohort consisted of 486 episodes of Gram-negative bacteremia in 450 patients. Median age was 66 years (IQR 56–74). In vitro resistance to C-2GC + AG was present in 44 patients (8.8%). Independent predictors for resistance to empiric sepsis therapy were hematologic malignancy (adjusted OR 4.09, 95%CI 1.43–11.62, p < 0.01), previously cultured drug resistant pathogen (adjusted OR 3.72. 95%CI 1.72–8.03, p < 0.01) and antibiotic therapy during the preceding 2 months (adjusted OR 12.5 4.08–38.48, p < 0.01). With risk-based strategies, an adequacy rate of empiric therapy of 95.2–99.3% could be achieved. Compared to treating all patients with a carbapenem, the NNTC could be reduced by 82.8% (95%CI 78.5–87.5%) using the targeted approaches. A risk-based approach in empiric sepsis therapy has the potential to better target the use of reserve antimicrobial agents aimed at multi-resistant Gram-negative pathogens. A structured evaluation of the expected antimicrobial consumption and antibiotic adequacy rates is essential to be able to weigh the costs and benefits of potential antibiotic strategies and select the most appropriate approach.

Bacteria carry a wide array of genes, some of which have multiple alleles. These different alleles are often responsible for distinct types of virulence and can determine the classification at the subspecies levels (e.g., housekeeping genes for Multi Locus Sequence Typing, MLST). Therefore, it is important to rapidly detect not only the gene of interest, but also the relevant allele. Current sequencing-based methods are limited to mapping reads to each of the known allele reference, which is a time-consuming procedure. To address this limitation, we developed BacTag - a pipeline that rapidly and accurately detects which genes are present in a sequencing dataset and reports the allele of each of the identified genes. We exploit the fact that different alleles of the same gene have a high similarity. Instead of mapping the reads to each of the allele reference sequences, we preprocess the database prior to the analysis, which makes the subsequent gene and allele identification efficient. During the preprocessing, we determine a representative reference sequence for each gene and store the differences between all alleles and this chosen reference. Throughout the analysis we estimate whether the gene is present in the sequencing data by mapping the reads to this reference sequence; if the gene is found, we compare the variants to those in the preprocessed database. This allows to detect which specific allele is present in the sequencing data. Our pipeline was successfully tested on artificial WGS E. coli, S. pseudintermedius, P. gingivalis, M. bovis, Borrelia spp. and Streptomyces spp. data and real WGS E. coli and K. pneumoniae data in order to report alleles of MLST house-keeping genes. We developed a new pipeline for fast and accurate gene and allele recognition based on database preprocessing and parallel computing and performed better or comparable to the current popular tools. We believe that our approach can be useful for a wide range of projects, including bacterial subspecies classification, clinical diagnostics of bacterial infections, and epidemiological studies.