Increasing numbers and complexity of Staphylococcus aureus bloodstream infection-14 years of prospective evaluation at a German tertiary care centre with multi-centre validation of findings.

OBJECTIVES: Staphylococcus aureus bloodstream infection (SAB) is a common and severe infection. This study aims to describe temporal trends in numbers, epidemiological characteristics, clinical manifestations, and outcomes of SAB. METHODS: We performed a post-hoc analysis of three prospective SAB cohorts at the University Medical Centre Freiburg between 2006 and 2019. We validated our findings in a large German multi-centre cohort of five tertiary care centres (R-Net consortium, 2017-2019). Time-dependent trends were estimated using Poisson or beta regression models. RESULTS: We included 1797 patients in the mono-centric and 2336 patients in the multi-centric analysis. Overall, we observed an increasing number of SAB cases over 14 years (6.4%/year and 1000 patient days, 95% CI: 5.1% to 7.7%), paralleled by an increase in the proportion of community-acquired SAB (4.9%/year [95% CI: 2.1% to 7.8%]) and a decrease in the rate of methicillin-resistant-SAB (-8.5%/year [95% CI: -11.2% to -5.6%]). All of these findings were confirmed in the multi-centre validation cohort (6.2% cases per 1000 patient cases/year [95% CI: -0.6% to 12.6%], community-acquired-SAB 8.7% [95% CI: -1.2% to 19.6%], methicillin-resistant S. aureus-SAB -18.6% [95% CI: -30.6 to -5.8%]). Moreover, we found an increasing proportion of patients with multiple risk factors for complicated/difficult-to-treat SAB (8.5%/year, 95% CI: 3.6% to 13.5%, p < 0.001), alongside an overall higher level of comorbidities (Charlson comorbidity score 0.23 points/year, 95% CI: 0.09 to 0.37, p 0.005). At the same time, the rate of deep-seated foci such as osteomyelitis or deep-seated abscesses significantly increased (6.7%, 95% CI: 3.9% to 9.6%, p < 0.001). A reduction of in-hospital mortality by 0.6% per year (95% CI: 0.08% to 1%) was observed in the subgroup of patients with infectious diseases consultations. DISCUSSION: We found an increasing number of SAB combined with a significant increase in comorbidities and complicating factors in tertiary care centres. The resulting challenges in securing adequate SAB management in the face of high patient turnover will become an important task for physicians.

Implementation of Antibiotic Stewardship Improves the Quality of Blood Culture Diagnostics at an Intensive Care Unit of a University Hospital.

Background: Bloodstream infections increase morbidity and mortality in hospitalized patients and pose a significant burden for health care systems worldwide. Optimal blood culture diagnostics are essential for early detection and specific treatment. After assessing the quality parameters at a surgical intensive care unit for six months, we implemented a diagnostic stewardship bundle (DSB) to optimize blood culture diagnostics and then reevaluated its effects after six months. Material and Methods: All patients ≥18 years old and on the ward were included: pre-DSB 137 and post-DSB 158. The standard quality parameters were defined as the number of blood culture sets per diagnostic episode (≥2), the rate of contamination (2-3%), the rate of positivity (5-15%), the collection site (≥1 venipuncture per episode) and the filling volume of the bottles (8-10 mL, only post-DSB). The DSB included an informational video, a standard operating procedure, and ready-to-use paper crates with three culture sets. Results: From pre- to post-interventional, the number of ≥2 culture sets per episode increased from 63.9% (257/402) to 81.3% (230/283), and venipunctures increased from 42.5% (171/402) to 77.4% (219/283). The positivity rate decreased from 15.1% (108/714) to 12.8% (83/650), as did the contamination rate (3.8% to 3.6%). The majority of the aerobic bottles were filled within the target range (255/471, 54.1%), but in 96.6%, the anaerobic bottles were overfilled (451/467). Conclusions: The implementation of DSB improved the quality parameters at the unit, thus optimizing the blood culture diagnostics. Further measures seem necessary to decrease the contamination rate and optimize bottle filling significantly.

Urine Flow Cytometry Parameter Cannot Safely Predict Contamination of Urine-A Cohort Study of a Swiss Emergency Department Using Machine Learning Techniques.

BACKGROUND: Urine flow cytometry (UFC) analyses urine samples and determines parameter counts. We aimed to predict different types of urine culture growth, including mixed growth indicating urine culture contamination. METHODS: A retrospective cohort study (07/2017-09/2020) was performed on pairs of urine samples and urine cultures obtained from adult emergency department patients. The dataset was split into a training (75%) and validation set (25%). Statistical analysis was performed using a machine learning approach with extreme gradient boosting to predict urine culture growth types (i.e., negative, positive, and mixed) using UFC parameters obtained by UF-4000, sex, and age. RESULTS: In total, 3835 urine samples were included. Detection of squamous epithelial cells, bacteria, and leukocytes by UFC were associated with the different types of culture growth. We achieved a prediction accuracy of 80% in the three-class approach. Of the n = 126 mixed cultures in the validation set, 11.1% were correctly predicted; positive and negative cultures were correctly predicted in 74.0% and 96.3%. CONCLUSIONS: Significant bacterial growth can be safely ruled out using UFC parameters. However, positive urine culture growth (rule in) or even mixed culture growth (suggesting contamination) cannot be adequately predicted using UFC parameters alone. Squamous epithelial cells are associated with mixed culture growth.

Quantifying the effect of covariates on concentrations and effects of steady-state phenprocoumon using a population pharmacokinetic/pharmacodynamic model.

BACKGROUND AND OBJECTIVES: The oral anticoagulant phenprocoumon, similar to other vitamin K antagonists, is characterized by pronounced interindividual variability in the doses needed to achieve the desired therapeutic effect. Previous studies assessed the effect of genetic and demographic covariates on empirical dose requirements of phenprocoumon to enable individualized dose prediction. The aim of the present study was to quantify major sources of interindividual variability separately on the pharmacokinetics and pharmacodynamics of phenprocoumon using a population pharmacokinetic-pharmacodynamic model. METHODS: A single steady-state blood sample was collected from 278 patients and assayed by liquid chromatography-tandem mass spectrometry for phenprocoumon and its metabolites. Genotyping was performed for variants of the cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex, subunit 1 (VKORC1) genes. Effects were quantified by international normalized ratio (INR). Data were analyzed simultaneously using NONMEM VII. RESULTS: The model confirmed CYP2C9 and VKORC1 variants as the major predictors of variability in phenprocoumon concentrations and effects, together with body weight, age, comedication with CYP3A modifiers (i.e. inhibitors or inducers) and presence of atrial fibrillation. These covariates explained 50.0 % of the observed variability in the model parameters. Phenprocoumon clearance fractions mediated per CYP2C9 allele were 13.4, 9.5 and 5.7 mL/h for the 1, 2 and 3 variants, respectively. An additional clearance fraction of 5.3 mL/h was independent of CYP2C9 activity. Homozygous VKORC1 wild-type carriers were estimated to have a 2.13-fold higher phenprocoumon exposure requirement than homozygous 1173 C>T carriers to achieve the same effect on INR. CONCLUSIONS: The model provides a deeper insight in the separate pharmacokinetic and pharmacodynamic parts of phenprocoumon action. Thus, it provides important information for individualized dose prediction, with the option to include further covariates not studied here with known effects on individual pharmacokinetic or pharmacodynamic processes.