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Purpose: This study aimed to compare treatment outcomes for bloodstream infections (BSI) caused by a piperacillin/tazobactam (PIP/TAZ)-susceptible E. coli among three patient groups: BSI caused by ampicillin/sulbactam (AMP/SLB)-resistant isolates treated with PIP/TAZ, BSI caused by AMP/SLB-sensitive isolates treated with PIP/TAZ, and BSI caused by AMP/SLB-resistant isolates treated with another monotherapy., Methods: This retrospective study was conducted in two academic centres in Europe. Adult patients with E. coli BSI were screened from 2014 to 2020. Inclusion criteria were non-ESBL BSI and initial monotherapy for ≥ 72 h. To reduce the expected bias between the patient groups, propensity score matching was performed. The primary outcome was early treatment response after 72 h and required absence of SOFA score increase in ICU/IMC patients, as well as resolution of fever, leukocytosis, and bacteraemia., Results: Of the 1707 patients screened, 315 (18.5%) were included in the final analysis. Urinary tract infection was the most common source of BSI (54.9%). Monotherapies other than PIP/TAZ were cephalosporins (48.6%), carbapenems (34.3%), and quinolones (17.1%). Enhanced early treatment response rate was detected (p = 0.04) in patients with BSI caused by AMP/SLB-resistant isolates treated with another monotherapy (74.3%) compared to those treated with PIP/TAZ (57.1%), and was mainly driven by the use of cephalosporins and quinolones (p ≤ 0.03). Clinical success, 28-day mortality, and rate of relapsing BSI did not significantly differ between the groups., Conclusions: Our study suggests that initial use of PIP/TAZ may be associated with reduced early treatment response in E. coli BSI caused by AMP/SLB-resistant isolates compared to alternative monotherapies., (© 2023. The Author(s).)

Background: , a leading cause of bacteremia and infective endocarditis, exploits the human coagulation system by using a wide range of specific virulence factors. However, the impact of these host-pathogen interactions on the outcome of patients with Staphylococcus aureus (S. aureus) bacteremia (SAB) remains unclear. Staphylococcus aureus bacteremia (SAB) remains unclear. Methods: bacteremia were included and analyzed regarding bacterial factors ( S. aureus bacteremia were included and analyzed regarding bacterial factors ( coa gene size, vWbp, clfA, clfB, fnbA, fnbB, fib) and clinical parameters. A stepwise multivariate Cox regression model and a Partitioning Around Medoids (PAM) cluster algorithm were used for statistical analysis. Results: Patients' risk factors for 28-day mortality were creatinine (OR 1.49, p < 0.001), age (OR 1.9, p < 0.002), fibrinogen (OR 0.44, p < 0.004), albumin (OR 0.63, p < 0.02), hemoglobin (OR 0.59, p < 0.03), and CRP (OR 1.72, p < 0.04). Five distinct bacterial clusters with different mortality rates were unveiled, whereof two showed a 2-fold increased mortality and an accumulation of specific coagulase gene sizes, 547-base pairs and 660-base pairs. Conclusions: Based on the data obtained in the present study an association of coagulase gene size and fib regarding 28-day mortality was observed in patients with S. aureus bloodstream infections. Further animal and prospective clinical studies are needed to confirm our preliminary findings., (Copyright © 2020 Karer, Kussmann, Ratzinger, Obermueller, Reischer, Winkler, Kriz, Burgmann, Jilma and Lagler.)

Background: Although blood cultures (BCs) are the "gold standard" for detecting bacteremia, the utility of BCs in patients with community-acquired pneumonia (CAP) is controversial. This study describes the proportion of patients with CAP and afebrile bacteremia and identifies the clinical characteristics predicting the necessity for BCs in patients who are afebrile., Methods: Bacteremia rates were determined in 4,349 patients with CAP enrolled in the multinational cohort study The Competence Network of Community-Acquired Pneumonia (CAPNETZ) and stratified by presence of fever at first patient contact. Independent predictors of bacteremia in patients who were afebrile were determined using logistic regression analysis., Results: Bacteremic pneumonia was present in 190 of 2,116 patients who were febrile (8.9%), 101 of 2,149 patients who were afebrile (4.7%), and one of 23 patients with hypothermia (4.3%). Bacteremia rates increased with the CURB-65 score from 3.5% in patients with CURB-65 score of 0 to 17.1% in patients with CURB-65 score of 4. Patients with afebrile bacteremia exhibited the highest 28-day mortality rate (9.9%). Positive pneumococcal urinary antigen test (adjusted OR [AOR], 4.6; 95% CI, 2.6-8.2), C-reactive protein level > 200 mg/L (AOR, 3.1; 95% CI, 1.9-5.2), and BUN level ≥ 30 mg/dL (AOR, 3.1; 95% CI, 1.9-5.3) were independent positive predictors, and antibiotic pretreatment (AOR, 0.3; 95% CI, 0.1-0.6) was an independent negative predictor of bacteremia in patients who were afebrile., Conclusions: A relevant proportion of patients with bacteremic CAP was afebrile. These patients had an increased mortality rate compared with patients with febrile bacteremia or nonbacteremic pneumonia. Therefore, the relevance of fever as an indicator for BC necessity merits reconsideration., (Copyright © 2019 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

During human diamine oxidase (DAO) ELISA development we noticed that in serum DAO concentrations appear to be higher when compared to plasma. Neutrophils contain DAO in the specific granules and we hypothesized that DAO is released from neutrophils during serum coagulation. If activation of neutrophils can release DAO, its concentrations might be elevated in vivo after lipopolysaccharide (LPS) administration and in bacteremic patients. Using blood from healthy volunteers DAO concentrations were measured ex vivo in serum, citrate, EDTA and heparin plasma over several hours and after activation of neutrophils. Lipopolysaccharide and granulocyte-colony stimulating factor (G-CSF) were administered to 15 and 8 healthy volunteers, respectively and DAO concentrations were measured at different timepoints. DAO antigen levels were also determined in three different subcohorts of patients with culture-proven bacteremia and high C-reactive protein (CRP) levels. DAO concentrations were elevated in a time-dependent manner in serum but not in EDTA or citrate plasma ( P  < 0.01). Neutrophil activation using phorbol myristate acetate (PMA) and zymosan dose-dependently caused DAO concentrations to be elevated more than 10-fold at both 22°C and 37°C (both P -values <0.001). Administration of LPS to healthy volunteers released DAO from neutrophils ( P  < 0.001). Of the 55 different bacteremic patients selected from three independent cohorts only 3 (5.4%) showed highly elevated DAO concentrations. Serum DAO concentrations do not accurately reflect circulating enzyme levels but coagulation-induced neutrophil activation and consequently DAO release. Only a few bacteremic patients show high DAO concentrations able to degrade histamine rapidly.

Bacteraemia is a life-threating condition requiring immediate diagnostic and therapeutic actions. Blood culture (BC) analyses often result in a low true positive result rate, indicating its improper usage. A predictive model might assist clinicians in deciding for whom to conduct or to avoid BC analysis in patients having a relevant bacteraemia risk. Predictive models were established by using linear and non-linear machine learning methods. To obtain proper data, a unique data set was collected prior to model estimation in a prospective cohort study, screening 3,370 standard care patients with suspected bacteraemia. Data from 466 patients fulfilling two or more systemic inflammatory response syndrome criteria (bacteraemia rate: 28.8%) were finally used. A 29 parameter panel of clinical data, cytokine expression levels and standard laboratory markers was used for model training. Model tuning was performed in a ten-fold cross validation and tuned models were validated in a test set (80:20 random split). The random forest strategy presented the best result in the test set validation (ROC-AUC: 0.729, 95%CI: 0.679-0.779). However, procalcitonin (PCT), as the best individual variable, yielded a similar ROC-AUC (0.729, 95%CI: 0.679-0.779). Thus, machine learning methods failed to improve the moderate diagnostic accuracy of PCT.

Adequate early empiric antibiotic therapy is pivotal for the outcome of patients with bloodstream infections. In clinical practice the use of surrogate laboratory parameters is frequently proposed to predict underlying bacterial pathogens; however there is no clear evidence for this assumption. In this study, we investigated the discriminatory capacity of predictive models consisting of routinely available laboratory parameters to predict the presence of Gram-positive or Gram-negative bacteremia. Major machine learning algorithms were screened for their capacity to maximize the area under the receiver operating characteristic curve (ROC-AUC) for discriminating between Gram-positive and Gram-negative cases. Data from 23,765 patients with clinically suspected bacteremia were screened and 1,180 bacteremic patients were included in the study. A relative predominance of Gram-negative bacteremia (54.0%), which was more pronounced in females (59.1%), was observed. The final model achieved 0.675 ROC-AUC resulting in 44.57% sensitivity and 79.75% specificity. Various parameters presented a significant difference between both genders. In gender-specific models, the discriminatory potency was slightly improved. The results of this study do not support the use of surrogate laboratory parameters for predicting classes of causative pathogens. In this patient cohort, gender-specific differences in various laboratory parameters were observed, indicating differences in the host response between genders.

Background: Neutropaenic patients are at a high risk of contracting severe infections. In particular, in these patients, parameters with a high negative predictive value are desirable for excluding infection or bacteraemia. This study evaluated sepsis biomarkers in neutropaenic patients suffering from systemic inflammatory response syndrome (SIRS). Further, the predictive capacities of evaluated biomarkers in neutropaenic SIRS patients were compared to non-neutropaenic SIRS patients., Material and Methods: In this prospective observational cohort study, patients with clinically suspected sepsis were screened. The predictive capacities of procalcitonin (PCT), C-reactive protein and lipopolysaccharide-binding protein (LBP) in neutropaenic SIRS patients were evaluated in terms of their potential to identify infection or bacteraemia and were compared to results for non-neutropaenic SIRS patients. To select an appropriate control cohort, propensity score matching was applied, balancing confounding factors between neutropaenic and non-neutropaenic SIRS patients., Results: Of 3370 prospectively screened patients with suspected infection, 51 patients suffered from neutropaenic SIRS. For the identification of infection, none of the assessed biomarkers presented a clinically relevant discriminatory potency. Lipopolysaccharide-binding protein and PCT demonstrated discriminatory capacity to discriminate between nonbacteraemic and bacteraemic SIRS in patients with neutropaenia [receiver-operating characteristics-area under the curves (ROC-AUCs): 0.860, 0.818]. In neutropaenic SIRS patients, LBP had a significantly better ROC-AUC than in a comparable non-neutropaenic patient cohort for identifying bacteraemia (P = 0.01)., Conclusion: In neutropaenic SIRS patients, none of the evaluated biomarkers was able to adequately identify infection. LBP and PCT presented a good performance in identifying bacteraemia. Therefore, these markers could be used for screening purposes to increase the pretest probability of blood culture analysis., (© 2015 Stichting European Society for Clinical Investigation Journal Foundation.)

Background: Bacteraemia is a frequent and severe condition with a high mortality rate. Despite profound knowledge about the pre-test probability of bacteraemia, blood culture analysis often results in low rates of pathogen detection and therefore increasing diagnostic costs. To improve the cost-effectiveness of blood culture sampling, we computed a risk prediction model based on highly standardizable variables, with the ultimate goal to identify via an automated decision support tool patients with very low risk for bacteraemia., Methods: In this retrospective hospital-wide cohort study evaluating 15,985 patients with suspected bacteraemia, 51 variables were assessed for their diagnostic potency. A derivation cohort (n = 14.699) was used for feature and model selection as well as for cut-off specification. Models were established using the A2DE classifier, a supervised Bayesian classifier. Two internally validated models were further evaluated by a validation cohort (n = 1,286)., Results: The proportion of neutrophile leukocytes in differential blood count was the best individual variable to predict bacteraemia (ROC-AUC: 0.694). Applying the A2DE classifier, two models, model 1 (20 variables) and model 2 (10 variables) were established with an area under the receiver operating characteristic curve (ROC-AUC) of 0.767 and 0.759, respectively. In the validation cohort, ROC-AUCs of 0.800 and 0.786 were achieved. Using predefined cut-off points, 16% and 12% of patients were allocated to the low risk group with a negative predictive value of more than 98.8%., Conclusion: Applying the proposed models, more than ten percent of patients with suspected blood stream infection were identified having minimal risk for bacteraemia. Based on these data the application of this model as an automated decision support tool for physicians is conceivable leading to a potential increase in the cost-effectiveness of blood culture sampling. External prospective validation of the model's generalizability is needed for further appreciation of the usefulness of this tool.

Physicians are regularly faced with severely ill patients at risk of developing infections. In literature, standard care wards are often neglected, although their patients frequently suffer from a systemic inflammatory response syndrome (SIRS) of unknown origin. Fast identification of patients with infections is vital, as they immediately require appropriate therapy. Further, tools with a high negative predictive value (NPV) to exclude infection or bacteremia are important to increase the cost effectiveness of microbiological examinations and to avoid inappropriate antibiotic treatment. In this prospective cohort study, 2,384 patients with suspected infections were screened for suffering from two or more SIRS criteria on standard care wards. The infection probability score (IPS) and sepsis biomarkers with discriminatory power were assessed regarding their capacity to identify infection or bacteremia. In this cohort finally consisting of 298 SIRS-patients, the infection prevalence was 72%. Bacteremia was found in 25% of cases. For the prediction of infection, the IPS yielded 0.51 ROC-AUC (30.1% sensitivity, 64.6% specificity). Among sepsis biomarkers, lipopolysaccharide binding protein (LBP) was the best parameter with 0.63 ROC-AUC (57.5% sensitivity, 67.1% specificity). For the prediction of bacteremia, the IPS performed slightly better with a ROC-AUC of 0.58 (21.3% sensitivity, 65% specificity). Procalcitonin was the best discriminator with 0.78 ROC-AUC, 86.3% sensitivity, 59.6% specificity and 92.9% NPV. Furthermore, bilirubin and LBP (ROC-AUC: 0.65, 0.62) might also be considered as useful parameters. In summary, the IPS and widely used infection parameters, including CRP or WBC, yielded a poor diagnostic performance for the detection of infection or bacteremia. Additional sepsis biomarkers do not aid in discriminating inflammation from infection. For the prediction of bacteremia procalcitonin, and bilirubin were the most promising parameters, which might be used as a rule for when to take blood cultures or using nucleic acid amplification tests for microbiological diagnostics.

Invasive infections with methicillin-resistant Staphylococcus aureus (MRSA) have been associated with increased morbidity and mortality. The aim of the present study was to identify independent predictors of early mortality and treatment failure in patients with MRSA bacteraemia. A total of 132 adult patients who developed MRSA bacteraemia during hospitalization in the University Hospital of Vienna between 2000 and 2011 were screened and 124 were included in a retrospective cohort study. Patient demographics, source of bacteraemia, antimicrobial treatment and microbiological characteristics were evaluated. The 28-day crude mortality was 30.6%. Predictors of early mortality identified in multivariate Cox regression analysis included higher patient age (adjusted hazard ratio (aHR) 1.03, 95% CI 1.01-1.06, p 0.006), pneumonia (aHR 3.86, 95% CI 1.83-8.12, p <0.001) and failure to use MRSA active treatment (aHR 8.77, 95% CI 3.50-21.93, p <0.001). Ninety-one (73.4%) patients received glycopeptides as specific MRSA treatment. Of 63 patients treated with vancomycin, only 14 (22.6%) patients had aimed trough levels of 15-20 mg/L. Vancomycin MIC ≥2 mg/L was detected in 28.2% and was associated with glycopeptide pretreatment (p 0.001). All MRSA isolates were susceptible to linezolid and tigecycline. Persistent bacteraemia ≥7 days was documented in 25 (20.2%) patients. Independent determinants for microbiological eradication failure in patients with MRSA bacteraemia included endocarditis (p <0.001) and vancomycin trough levels (p 0.014), but not vancomycin MIC. Failure of clinical and microbiological eradication of MRSA among patients with MRSA bacteraemia was associated with clinical entity rather than with bacterial traits. Pharmacokinetic parameters seem to be decisive on microbiological and clinical success., (© 2013 The Authors Clinical Microbiology and Infection © 2013 European Society of Clinical Microbiology and Infectious Diseases.)

Increased serum sCD14 concentrations are associated with poor outcome in Gram-negative sepsis and trauma patients. In the present study serum sCD14 concentrations were measured in patients with Gram-positive sepsis and compared with Gram-negative septic and nonseptic intensive care unit patients. Furthermore, serum sCD14 concentration was correlated with patient's outcome. Serum samples of 28 Gram-positive (8 nonsurvivors/20 survivors) and 10 Gram-negative bacteriemic patients (3 nonsurvivors/7 survivors) were obtained at the day they met the sepsis criteria defined by Bone et al. (Day 0) and at Days 4 and 7 and compared with 10 nonseptic ICU patients and 10 healthy volunteers. Serum concentrations of sCD14 were measured by ELISA. Significantly higher sCD14 serum concentrations were found on Days 4 and 7 in Gram-positive nonsurvivors than in Gram-positive survivors (Day 4: 5.85 +/- 0.48 vs 4.07 +/- 0.43 microgram/ml, P < 0.05; Day 7: 6.12 +/- 0.46 vs 3.53 +/- 0.33 microgram/ml, P < 0.01). In addition, sCD14 concentrations of Gram-positive nonsurvivors were significantly higher than those of nonseptic ICU patients and healthy volunteers at any time of observation. However, no significant difference was calculated between Gram-positive and Gram-negative patients. Summarizing our results, the serum level of sCD14 could be proven to be a good prognostic marker in the course of Gram-positive sepsis. Increased levels are associated with a high mortality.

This review is a brief attempt at providing an overview of a subject of enormous complexity-endotoxins and the mediators associated with its biological effects. More specifically it deals with biochemistry and biology of endotoxin, detection of endotoxin with the Limulus amebocyte lysate test, the molecular mechanisms and biological effects, and in the last part with future aspects of therapeutical strategies. It seems certain that the subject will become even more complex and possibly controversial as scientific knowledge further involves. However, because of the high mortality rate of patients suffering from gram-negative sepsis all efforts have to be made to find effective therapeutical strategies.