Procalcitonin guided antibiotic therapy and hospitalization in patients with lower respiratory tract infections: a prospective, multicenter, randomized controlled trial

<p>Abstract</p> <p>Background:</p> <p>Lower respiratory tract infections like acute bronchitis, exacerbated chronic obstructive pulmonary disease and community-acquired pneumonia are often unnecessarily treated with antibiotics, mainly because of physicians' difficulties to distinguish viral from bacterial cause and to estimate disease-severity. The goal of this trial is to compare medical outcomes, use of antibiotics and hospital resources in a strategy based on enforced evidence-based guidelines versus procalcitonin guided antibiotic therapy in patients with lower respiratory tract infections.</p> <p>Methods and design:</p> <p>We describe a prospective randomized controlled non-inferiority trial with an open intervention. We aim to randomize over a fixed recruitment period of 18 months a minimal number of 1002 patients from 6 hospitals in Switzerland. Patients must be >18 years of age with a lower respiratory tract infections <28 days of duration. Patients with no informed consent, not fluent in German, a previous hospital stay within 14 days, severe immunosuppression or chronic infection, intravenous drug use or a terminal condition are excluded. Randomization to either guidelines-enforced management or procalcitonin-guided antibiotic therapy is stratified by centre and type of lower respiratory tract infections. During hospitalization, all patients are reassessed at days 3, 5, 7 and at the day of discharge. After 30 and 180 days, structured phone interviews by blinded medical students are conducted. Depending on the randomization allocation, initiation and discontinuation of antibiotics is encouraged or discouraged based on evidence-based guidelines or procalcitonin cut off ranges, respectively. The primary endpoint is the risk of combined disease-specific failure after 30 days. Secondary outcomes are antibiotic exposure, side effects from antibiotics, rate and duration of hospitalization, time to clinical stability, disease activity scores and cost effectiveness. The study hypothesis is that procalcitonin-guidance is non-inferior (i.e., at worst a 7.5% higher combined failure rate) to the management with enforced guidelines, but is associated with a reduced total antibiotic use and length of hospital stay.</p> <p>Discussion:</p> <p>Use of and prolonged exposure to antibiotics in lower respiratory tract infections is high. The proposed trial investigates whether procalcitonin-guidance may safely reduce antibiotic consumption along with reductions in hospitalization costs and antibiotic resistance. It will additionally generate insights for improved prognostic assessment of patients with lower respiratory tract infections.</p> <p>Trial registration:</p> <p>ISRCTN95122877</p

Copeptin is associated with mortality and outcome in patients with acute intracerebral hemorrhage

Spontaneous intracerebral hemorrhage (ICH) accounts for a high mortality and morbidity. Early prediction of outcome is crucial for optimized care and treatment decision. Copeptin, the C-terminal part of provasopressin, has emerged as a new prognostic marker in a variety of diseases, but its prognostic value in ICH is unknown

Comparison of the temporal release pattern of copeptin with conventional biomarkers in acute myocardial infarction

Background Early detection of acute myocardial infarction (AMI) using cardiac biomarkers of myocardial necrosis remains limited since these biomarkers do not rise within the first hours from onset of AMI. We aimed to compare the temporal release pattern of the C-terminal portion of provasopressin (copeptin) with conventional cardiac biomarkers, including creatine kinase isoenzyme (CK-MB), cardiac troponin T (cTnT), and high-sensitivity cTnT (hs-cTnT), in patients with ST-elevation AMI. Methods We included 145 patients undergoing successful primary percutaneous coronary intervention (PCI) for a first ST-elevation AMI presenting within 12 h of symptom onset. Blood samples were taken on admission and at four time points within the first 24 h after PCI. Results In contrast to all other markers, copeptin levels were already elevated on admission and were higher with a shorter time from symptom onset to reperfusion and lower systolic blood pressure. Copeptin levels peaked immediately after symptom onset at a maximum of 249 pmol/L and normalized within 10 h. In contrast, CK-MB, cTnT, and hs-cTnT peaked after 14 h from symptom onset at a maximum of 275 U/L, 5.75 lg/L, and 4.16 lg/L, respectively, and decreased more gradually. Conclusions Copeptin has a distinct release pattern in patients with ST-elevation AMI, peaking within the first hour after symptom onset before conventional cardiac biomarkers and falling to normal ranges within the first day. Further studies are required to determine the exact role of copeptin in AMI suspects presenting within the first hours after symptom onset

Detection of rare variant effects in association studies: extreme values, iterative regression, and a hybrid approach

We develop statistical methods for detecting rare variants that are associated with quantitative traits. We propose two strategies and their combination for this purpose: the iterative regression strategy and the extreme values strategy. In the iterative regression strategy, we use iterative regression on residuals and a multimarker association test to identify a group of significant variants. In the extreme values strategy, we use individuals with extreme trait values to select candidate genes and then test only these candidate genes. These two strategies are integrated into a hybrid approach through a weighting technology. We apply the proposed methods to analyze the Genetic Analysis Workshop 17 data set. The results show that the hybrid approach is the most powerful approach. Using the hybrid approach, the average power to detect causal genes for Q1 is about 40% and the powers to detect FLT1 and KDR are 100% and 68% for Q1, respectively. The powers to detect VNN3 and BCHE are 34% and 30% for Q2, respectively

The role of copeptin as a diagnostic and prognostic biomarker for risk stratification in the emergency department

The hypothalamic-pituitary-adrenal axis is activated in response to stress. One of the activated hypothalamic hormones is arginine vasopressin, a hormone involved in hemodynamics and osmoregulation. Copeptin, the C-terminal part of the arginine vasopressin precursor peptide, is a sensitive and stable surrogate marker for arginine vasopressin release. Measurement of copeptin levels has been shown to be useful in a variety of clinical scenarios, particularly as a prognostic marker in patients with acute diseases such as lower respiratory tract infection, heart disease and stroke. The measurement of copeptin levels may provide crucial information for risk stratification in a variety of clinical situations. As such, the emergency department appears to be the ideal setting for its potential use. This review summarizes the recent progress towards determining the prognostic and diagnostic value of copeptin in the emergency department

Sex differences in the association between plasma copeptin and incident type 2 diabetes: the Prevention of Renal and Vascular Endstage Disease (PREVEND) study

AIMS/HYPOTHESIS: Vasopressin plays a role in osmoregulation, glucose homeostasis and inflammation. Therefore, plasma copeptin, the stable C-terminal portion of the precursor of vasopressin, has strong potential as a biomarker for the cardiometabolic syndrome and diabetes. Previous results were contradictory, which may be explained by differences between men and women in responsiveness of the vasopressin system. The aim of this study was to evaluate the usefulness of copeptin for prediction of future type 2 diabetes in men and women separately. METHODS: From the Prevention of Renal and Vascular Endstage Disease (PREVEND) study, 4,063 women and 3,909 men without diabetes at baseline were included. A total of 208 women and 288 men developed diabetes during a median follow-up of 7.7 years. RESULTS: In multivariable-adjusted models, we observed a stronger association of copeptin with risk of future diabetes in women (OR 1.49 [95% CI 1.24, 1.79]) than in men (OR 1.01 [95% CI 0.85, 1.19]) (p (interaction) < 0.01). The addition of copeptin to the Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR) clinical model improved the discriminative value (C-statistic,+0.007, p = 0.02) and reclassification (integrated discrimination improvement [IDI] = 0.004, p < 0.01) in women. However, we observed no improvement in men. The additive value of copeptin in women was maintained when other independent predictors, such as glucose, high sensitivity C-reactive protein (hs-CRP) and 24 h urinary albumin excretion (UAE), were included in the model. CONCLUSIONS/INTERPRETATION: The association of plasma copeptin with the risk of developing diabetes was stronger in women than in men. Plasma copeptin alone, and along with existing biomarkers (glucose, hs-CRP and UAE), significantly improved the risk prediction for diabetes in women

Improved Detection of Rare Genetic Variants for Diseases

Technology advances have promoted gene-based sequencing studies with the aim of identifying rare mutations responsible for complex diseases. A complication in these types of association studies is that the vast majority of non-synonymous mutations are believed to be neutral to phenotypes. It is thus critical to distinguish potential causative variants from neutral variation before performing association tests. In this study, we used existing predicting algorithms to predict functional amino acid substitutions, and incorporated that information into association tests. Using simulations, we comprehensively studied the effects of several influential factors, including the sensitivity and specificity of functional variant predictions, number of variants, and proportion of causative variants, on the performance of association tests. Our results showed that incorporating information regarding functional variants obtained from existing prediction algorithms improves statistical power under certain conditions, particularly when the proportion of causative variants is moderate. The application of the proposed tests to a real sequencing study confirms our conclusions. Our work may help investigators who are planning to pursue gene-based sequencing studies