Franz Ratzinger

Utility of sepsis biomarkers and the infection probability score to discriminate sepsis and systemic inflammatory response syndrome in standard care patients.

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.

Azithromycin suppresses CD4 + T-cell activation by direct modulation of mTOR activity

Advanced macrolides, such as azithromycin (AZM) or clarithromycin (CLM), are antibiotics with immunomodulatory properties. Here we have sought to evaluate their in vitro influence on the activation of CD4+ T-cells. Isolated CD4+ T-cells were stimulated with agonistic anti-CD3/anti-CD28 monoclonal antibodies in the presence of 0.6 mg/L, 2.5 mg/L, 10 mg/L or 40 mg/L AZM or CLM. Cell proliferation, cytokine level in supernatants and cell viability was assessed. Intracellular signaling pathways were evaluated using reporter cell lines, FACS analysis, immunoblotting and in vitro kinase assays. AZM inhibited cell proliferation rate and cytokine secretion of CD4+ T-cells in a dose-dependent manner. Similarly, high concentrations of CLM (40 mg/L) also suppressed these T-cell functions. Analysis of molecular signaling pathways revealed that exposure to AZM reduced the phosphorylation of the S6 ribosomal protein, a downstream target of mTOR. This effect was also observed at 40 mg/L CLM. In vitro kinase studies using recombinant mTOR showed that AZM inhibited mTOR activity. In contrast to rapamycin, this inhibition was independent of FKBP12. We show for the first time that AZM and to a lesser extent CLM act as immunosuppressive agents on CD4+ T-cells by inhibiting mTOR activity. Our results might have implications for the clinical use of macrolides.

Lupus-anticoagulant testing at NOAC trough levels

Non-vitamin K antagonist oral anticoagulants (NOAC), including rivaroxaban, apixaban or dabigatran, regularly show relevant effects on coagulation tests, making the interpretation of results difficult. The aim of this study was to evaluate possible interferences of NOACs in trough level concentrations in lupus anticoagulant (LA) testing. Citrate plasma specimens of 30 healthy volunteers were spiked with rivaroxaban, apixaban or dabigatran in four plasma concentration levels at or below trough NOAC levels. The NOAC concentration was measured using dedicated surrogate concentration tests and a stepwise diagnostic procedure for LA-testing was applied using screening, mixing and confirmatory testing. Results were compared to NOAC-free specimens. Starting with a plasma concentration of 12.5 ng/ml, dabigatran-spiked specimens showed significant prolongations in the lupus anticoagulant-sensitive activated partial thromboplastin time (aPTT-LA) as well as in the Dilute Russell viper venom time (dRVVT), leading to 43.3 % false positives in confirmatory testing in the dRVVT. In contrast, rivaroxaban, beginning with 7.5 ng/ml, exclusively affected dRVVT-based tests. In confirmatory tests, 30.0 % of rivaroxaban-spiked specimens showed false positive results. Starting with 18.75 ng/ml apixaban, a significant prolongation of the dRVVT and up to 20.7 % false positives in confirmatory tests were found. In contrast to other NOACs tested, apixaban did not present with a dose-dependent increase of the dRVVT ratio. In conclusion, the rate of false positive results in LA-testing is unacceptably high at expected trough levels of NOACs. Even at plasma concentrations below the LLOQ of commercially available surrogate tests, LA testing is best avoided in patients with NOAC therapy.

The tryptophan metabolite picolinic acid suppresses proliferation and metabolic activity of CD4+ T cells and inhibits c-Myc activation

Tryptophan metabolites, including kynurenine, 3‐hydroxyanthranilic acid, and picolinic acid, are key mediators of immunosuppression by cells expressing the tryptophan‐catabolizing enzyme indoleamine2,3‐dioxygenase. In this study, we assessed the influence of picolinic acid on cell viability and effector functions of CD4+ T cells following in vitro activation with agonistic anti‐CD3/anti‐CD28 antibodies. In contrast to kynurenine and 3‐hydroxyanthranilic acid, exposure of T cells with picolinic acid did not affect cell viability, whereas proliferation and metabolic activity were suppressed in a dose‐dependent manner. On the other hand, cytokine secretion and up‐regulation of cell surface activation markers were not or only weakly inhibited by picolinic acid. Picolinic acid exposure induced a state of deep anergy that could not be overcome by the addition of exogenous IL‐2 and inhibited Th cell polarization. On the molecular level, important upstream signaling molecules, such as the MAPKs ERK and p38 and the mammalian target of rapamycin target protein S6 ribosomal protein, were not affected by picolinic acid. Likewise, NFAT, NF‐κB, and AP‐1 promoter activity in Jurkat T cells was not influenced by exposure to picolinic acid. Whereas transcriptional levels of v‐myc avian myelocytomatosis viral oncogene homolog were not affected by picolinic acid, phosphorylation at Ser62 was strongly reduced in picolinic acid‐exposed T cells following activation. In conclusion, picolinic acid mediates a unique immunosuppressive program in T cells, mainly inhibiting cell cycle and metabolic activity, while leaving other effector functions intact. These functional features are accompanied by reduced phosphorylation of v‐myc avian myelocytomatosis viral oncogene homolog. It remains to be determined whether this effect is mediated by direct inhibition of ERK activity or whether indirect mechanisms apply.

Effect of preanalytical time-delay on platelet function as measured by multiplate, PFA-100 and VerifyNow.

Abstract Background and aims: Platelet function testing may help to identify poor responders to antiplatelet drugs. The aim of this study was to compare three commonly used platelet function tests with special focus on the pre-analytical influence of time-delay on the tested parameters. Methods: We assessed ADP-induced platelet function by the Multiplate, Platelet Function Analyzer-100 (PFA-100) and VerifyNow in nine healthy volunteers and 36 patients receiving clopidogrel or prasugrel 1 and 3 hours after sampling. Results: The PFA-100 demonstrated non-closure time in 23 patients. A more graded response could be detected with the two other devices. Aggregation in whole blood (Multiplate) decreased after 3 hours compared to 1 hour in all subjects (p < 0.05). Furthermore, aggregation levels obtained by the VerifyNow showed a decrease in patients taking P2Y12 inhibitors after 3 hours (p < 0.05), except in three patients, in whom an increase was observed. Conclusion: Responses to ADP are time-dependent after blood sampling for the Multiplate in all subjects and for the VerifyNow in patients on antiplatelet drugs. For both devices, platelet aggregation was reduced 3 hours after sampling which may affect data interpretation and clinical consequences.

Sepsis biomarkers in neutropaenic systemic inflammatory response syndrome patients on standard care wards

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.

Evaluation of the Septifast MGrade Test on Standard Care Wards--A Cohort Study.

Background The immediate need for appropriate antimicrobial therapy in septic patients requires the detection of the causative pathogen in a timely and reliable manner. In this study, the real-time PCR Septifast MGrade test was evaluated in adult patients meeting the systemic inflammatory response syndrome (SIRS) criteria that were treated at standard care wards. Methods Patients with clinical suspected infection, drawn blood cultures (BC), the Septifast MGrade test (SF) and sepsis biomarkers were prospectively screened for fulfillment of SIRS criteria and evaluated using the criteria of the European Centre of Disease Control (ECDC) for infection point prevalence studies. Results In total, 220 patients with SIRS were prospectively enrolled, including 56 patients with detection of bacteria in the blood (incidence: 25.5%). BC analysis resulted in 75.0% sensitivity (95% confidence interval, CI: 61.6%– 85.6%) with 97.6% specificity (CI: 93.9%– 99.3%) for detecting bacteria in the blood. In comparison to BC, SF presented with 80.4% sensitivity (CI: 67.6%– 89.8%) and with 97.6% specificity (CI: 93.9%– 99.3%). BC and SF analysis yielded comparable ROC-AUCs (0.86, 0.89), which did not differ significantly (p = 0.558). A trend of a shorter time-to-positivity of BC analysis was not seen in bacteremic patients with a positive SF test than those with a negative test result. Sepsis biomarkers, including PCT, IL-6 or CRP, did not help to explain discordant test results for BC and SF. Conclusion Since negative results do not exclude bacteremia, the Septifast MGrade test is not suited to replacing BC, but it is a valuable tool with which to complement BC for faster detection of pathogens.

A Risk Prediction Model for Screening Bacteremic Patients: A Cross Sectional Study

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 models generalizability is needed for further appreciation of the usefulness of this tool.

Rapid Diagnostic Algorithms as a Screening Tool for Tuberculosis: An Assessor Blinded Cross-Sectional Study

Background A major obstacle to effectively treat and control tuberculosis is the absence of an accurate, rapid, and low-cost diagnostic tool. A new approach for the screening of patients for tuberculosis is the use of rapid diagnostic classification algorithms. Methods We tested a previously published diagnostic algorithm based on four biomarkers as a screening tool for tuberculosis in a Central European patient population using an assessor-blinded cross-sectional study design. In addition, we developed an improved diagnostic classification algorithm based on a study population at a tertiary hospital in Vienna, Austria, by supervised computational statistics. Results The diagnostic accuracy of the previously published diagnostic algorithm for our patient population consisting of 206 patients was 54% (CI: 47%–61%). An improved model was constructed using inflammation parameters and clinical information. A diagnostic accuracy of 86% (CI: 80%–90%) was demonstrated by 10-fold cross validation. An alternative model relying solely on clinical parameters exhibited a diagnostic accuracy of 85% (CI: 79%–89%). Conclusion Here we show that a rapid diagnostic algorithm based on clinical parameters is only slightly improved by inclusion of inflammation markers in our cohort. Our results also emphasize the need for validation of new diagnostic algorithms in different settings and patient populations.

25(OH)D and 1,25(OH)D vitamin D fails to predict sepsis and mortality in a prospective cohort study

The clinical role of vitamin D in sepsis and mortality prediction is controversially discussed. Therefore, we conducted a prospective cohort study on standard care wards, including 461 patients with suspected sepsis fulfilling two or more SIRS criteria. On the first and third day after onset of SIRS symptoms levels of 25(OH)D, 1,25(OH)D and sepsis biomarkers were analysed for their predictive capacity for identifying infection, bacteraemia and an elevated mortality risk. Additionally, several SNPs associated with vitamin D metabolism were evaluated. Bacteraemic patients (28.5%) presented with significantly lower 1,25(OH)D levels than SIRS patients without bacteraemia on the first and third day, while 25(OH)D did not show a predictive capacity. No significant differences of either 1,25(OH)D or 25(OH)D levels were found between SIRS patients with and without infections or between survivors and non-survivors. Sepsis biomarkers, including procalcitonin and CRP, showed a significantly higher discriminatory capacity for these classification tasks. The vitamin D metabolism-related SNPs analysed did not indicate any association with our outcome measures. In conclusion, 1,25(OH)D but not 25(OH)D showed a minor discriminatory value for the prediction of bacteraemia that was inferior to CRP and PCT but both failed to predict sepsis and mortality in a prospective cohort of SIRS patients.