Antimicrobial susceptibility testing (AST) should be fast and accurate, leading to proper interventions and therapeutic success. Clinical microbiology laboratories rely on phenotypic methods, but the continuous improvement and decrease in the cost of whole-genome sequencing (WGS) technologies make them an attractive alternative. Studies evaluating the performance of WGS-based prediction of antimicrobial resistance (AMR) for selected bacterial species have shown promising results. There are, however, significant gaps in the literature evaluating the applicability of WGS as a diagnostics method in real-life clinical settings against the range of bacterial pathogens experienced there. Thus, we compared standard phenotypic AST results with WGS-based predictions of AMR profiles in bacterial isolates without preselection of defined species, to evaluate the applicability of WGS as a diagnostics method in clinical settings. We collected all bacterial isolates processed by all Danish Clinical Microbiology Laboratories in 1 day. We randomly selected 500 isolates without any preselection of species. We performed AST through standard broth microdilution (BMD) for 488 isolates (n = 6,487 phenotypic AST results) and compared results with in silico antibiograms obtained through WGS (Illumina NextSeq) followed by bioinformatics analyses using ResFinder 4.0 (n = 5,229 comparisons). A higher proportion of AMR was observed for Gram-negative bacteria (10.9%) than for Gram-positive bacteria (6.1%). Comparison of BMD with WGS data yielded a concordance of 91.7%, with discordant results mainly due to phenotypically susceptible isolates harboring genetic AMR determinants. These cases correspond to 6.2% of all isolate-antimicrobial combinations analyzed and to 6.8% of all phenotypically susceptible combinations. We detected fewer cases of phenotypically resistant isolates without any known genetic resistance mechanism, particularly 2.1% of all combinations analyzed, which corresponded to 26.4% of all detected phenotypic resistances. Most discordances were observed for specific combinations of species-antimicrobial: macrolides and tetracycline in streptococci, ciprofloxacin and β-lactams in combination with β-lactamase inhibitors in Enterobacterales, and most antimicrobials in Pseudomonas aeruginosa. WGS has the potential to be used for surveillance and routine clinical microbiology. However, in clinical microbiology settings and especially for certain species and antimicrobial agent combinations, further developments in AMR gene databases are needed to ensure higher concordance between in silico predictions and expected phenotypic AMR profiles.

Background: Monitoring of microbiological cause of infective endocarditis (IE) remains key in the understanding of IE; however, data from large, unselected cohorts are sparse. We aimed to examine temporal changes, patient characteristics, and in‐hospital and long‐term mortality, according to microbiological cause in patients with IE from 2010 to 2017. Methods and Results: Linking Danish nationwide registries, we identified all patients with first‐time IE. In‐hospital and long‐term mortality rates were assessed according to microbiological cause and compared using multivariable adjusted logistic regression analysis and Cox proportional hazard analysis, respectively. A total of 4123 patients were included. Staphylococcus aureus was the most frequent cause (28.1%), followed by Streptococcus species (26.0%), Enterococcus species (15.5%), coagulase‐negative staphylococci (6.2%), and “other microbiological causes” (5.3%). Blood culture–negative IE was registered in 18.9%. The proportion of blood culture–negative IE declined during the study period, whereas no significant changes were seen for any microbiological cause. Patients with Enterococcus species were older and more often had a prosthetic heart valve compared with other causes. For Streptococcus species IE, in‐hospital and long‐term mortality (median follow‐up, 2.3 years) were 11.1% and 58.5%, respectively. Compared with Streptococcus species IE, the following causes were associated with a higher in‐hospital mortality: S aureus IE (odds ratio [OR], 3.48 [95% CI, 2.74–4.42]), Enterococcus species IE (OR, 1.48 [95% CI, 1.11–1.97]), coagulase‐negative staphylococci IE (OR, 1.79 [95% CI, 1.21–2.65]), “other microbiological cause” (OR, 1.47 [95% CI, 0.95–2.27]), and blood culture–negative IE (OR, 1.99 [95% CI, 1.52–2.61]); and the following causes were associated with higher mortality following discharge (median follow‐up, 2.9 years): S aureus IE (hazard ratio [HR], 1.39 [95% CI, 1.19–1.62]), Enterococcus species IE (HR, 1.31 [95% CI, 1.11–1.54]), coagulase‐negative staphylococci IE (HR, 1.07 [95% CI, 0.85–1.36]), “other microbiological cause” (HR, 1.45 [95% CI, 1.13–1.85]), and blood culture–negative IE (HR, 1.05 [95% CI, 0.89–1.25]). Conclusions: This nationwide study showed that S aureus was the most frequent microbiological cause of IE, followed by Streptococcus species and Enterococcus species. Patients with S aureus IE had the highest in‐hospital mortality .

Background: Pneumonia due to herpes simplex virus (HSV) is uncommon but can be seen in immunocompromised patients and has been associated with poor prognosis in this population. Aim: The aim was to study the results, outcome and mortality of HSV pneumonia in immunocompromised patients and patients receiving mechanical ventilation. Furthermore, it has been unclear whether to initiate prophylactic treatment with acyclovir or not. Methods: We have conducted a literature search using the keywords herpes simplex pneumonia, critically ill patients and intensive care unit for identification of relevant publications. Findings: HSV pneumonia can cause severe infection or even death in immunocompromised patients and critically ill patients. A clear diagnosis of HSV pneumonia can be difficult to establish. Respiratory condition may improve after initiation of acyclovir but data is scarce. Conclusion: HSV pneumonia should be considered in the immunocompromised patient and/or the intensive care patient who continues to deteriorate despite appropriate treatment. The value of prophylactic treatment with acyclovir is unproven but should be considered.

Objectives: Implementing whole-genome sequencing (WGS) technologies in clinical microbiology laboratories can increase the amount and quality of information available for healthcare practitioners. In this study, we analysed the applicability of this method and determined the distribution of bacterial species processed in clinical settings in Denmark. Methods: We performed a point-prevalence study of all bacterial isolates (n = 2,009) processed and reported in the Clinical Microbiology Laboratories in Denmark in one day in January 2018. We compared species identification as performed by classical methods (MALDI-TOF) and by bioinformatics analysis (KmerFinder and rMLST) of WGS (Illumina NextSeq) data. We compared the national point-prevalence of bacterial isolates observed in clinical settings with the research attention given to those same genera in scientific literature. Results: The most prevalent bacterium was Escherichia coli isolated from urine (n = 646), followed by Staphylococcus spp. from skin or soft tissues (n = 197). The distribution of bacterial species throughout the country was not homogeneous. We observed concordance of species identification for all methods in 95.7% (n = 1,919) of isolates, furthermore obtaining concordance for 99.7% (n = 1,999) at genus level. The number of scientific publications in the country did not correlate with the number of bacterial isolates of each genera analysed in this study. Conclusions: WGS technologies have the potential to be applied in clinical settings for routine diagnostics purposes. This study also showed that bioinformatics databases should be continuously improved and results from local point-prevalence surveys should not be applied at national levels without previously determining possible regional variations.

Background: Since 2008, Danish national surveillance of Clostridioides difficile has focused on binary toxin-positive strains in order to monitor epidemic types such as PCR ribotype (RT) 027 and 078. Additional surveillance is needed to provide a more unbiased representation of all strains from the clinical reservoir. Aim: Setting up a new sentinel surveillance scheme for an improved understanding of type distribution relative to time, geography and epidemiology, here presenting data from 2016 to 2019. Methods: For 2─4 weeks in spring and autumn each year between 2016 and 2019, all 10 Danish Departments of Clinical Microbiology collected faecal samples containing toxigenic C. difficile. Isolates were typed at the national reference laboratory at Statens Serum Institut. The typing method in 2016–17 used tandem-repeat-sequence typing, while the typing method in 2018–19 was whole genome sequencing. Results: During the study period, the sentinel surveillance scheme included ca 14–15% of all Danish cases of C. difficile infections. Binary toxin-negative strains accounted for 75% and 16 of the 20 most prevalent types. The most common sequence types (ST) were ST2/13 (RT014/020) (19.5%), ST1 (RT027) (10.8%), ST11 (RT078) (6.7%), ST8 (RT002) (6.6%) and ST6 (RT005/117) (5.1%). The data also highlighted geographical differences, mostly related to ST1 and temporal decline of ST1 (p = 0.0008) and the increase of ST103 (p = 0.002), ST17 (p = 0.004) and ST37 (p = 0.003), the latter three binary toxin-negative. Conclusion: Sentinel surveillance allowed nationwide monitoring of geographical differences and temporal changes in C. difficile infections in Denmark, including emerging types, regardless of binary toxin status.

Objectives and study design: In this population-based study of 602 patients, we amended C-reactive protein (CRP) and plasma albumin (PA) levels around the diagnosis of diffuse large B-cell lymphoma (DLBCL) to the International Prognostic Index (IPI) and assessed 0–90, 91–365, and +365-day survival. Results: The CRP did not contribute to the IPI's prognostic or discriminatory ability, regardless of time period, particularly not in models with PA. In contrast, the PA was an important contributor, especially in the 0–90 day period, but also up to one year after the diagnosis. For day 0–90, the model with the IPI only had an Area Under the Receiver Operating Characteristics (AUROC) of 0.742, whereas the IPI with PA as a continuous variable rendered an AUROC of 0.841. Especially the lower PA quartile (18–32 g/L) contributed to the worse prognosis. Conclusions: The amendment of PA to the IPI may significantly improve the short-term prognostic and discriminative ability.