Diagnostic and medical needs for therapeutic drug monitoring of antibiotics

Therapeutic drug monitoring (TDM) of antibiotics has been practiced for more than half a century, but it is still not widely applied for infected patients. It has a traditional focus on limiting toxicity of specific classes of antibiotics such as aminoglycosides and vancomycin. With more patients in critical care with higher levels of sickness severity and immunosuppression as well as an increasingly obese and ageing population, an increasing risk of suboptimal antibiotic exposure continues to escalate. As such, the value of TDM continues to expand, especially for beta-lactams which constitute the most frequently used antibiotic class. To date, the minimum inhibitory concentration (MIC) of infectious microbes rather than classification in terms of susceptible and resistant can be reported. In parallel, increasingly sophisticated TDM technology is becoming available ensuring that TDM is feasible and can deliver personalized antibiotic dosing schemes. There is an obvious need for extensive studies that will quantify the improvements in clinical outcome of individual TDM-guided dosing. We suggest that a broad diagnostic and medical investigation of the TDM arena, including marke

Innovative strategies to fight antimicrobial resistance: crowdsourcing to expand medical training

Background: Antimicrobial resistance is a serious public health concern across the world, but public awareness is low, few educational resources on diagnostics exist and professional interest in infectious diseases is waning. To spur interest in infectious disease, emphasize the role of diagnostics in management of resistant infections and develop educational resources to support antimicrobial stewardship. Methods: We employed crowdsourcing methods, using an open challenge contest to solicit clinical cases on antimicrobial resistance and clinical diagnostics. Results: We received 25 clinical cases from nine countries. After screening, 23 cases were eligible for judging. Three cases emerged as the top finalists and were further developed into an open access learning module on diagnostics and antimicrobial resistance. Conclusions: Crowdsourcing methods are beneficial for generating interest in infectious disease and developing educational resources to support antibiotic stewardship.</ns4:p

Circulating adrenomedullin estimates survival and reversibility of organ failure in sepsis: the prospective observational multinational Adrenomedullin and Outcome in Sepsis and Septic Shock-1 (AdrenOSS-1) study

Background: Adrenomedullin (ADM) regulates vascular tone and endothelial permeability during sepsis. Levels of circulating biologically active ADM (bio-ADM) show an inverse relationship with blood pressure and a direct relationship with vasopressor requirement. In the present prospective observational multinational Adrenomedullin and Outcome in Sepsis and Septic Shock 1 (, AdrenOSS-1) study, we assessed relationships between circulating bio-ADM during the initial intensive care unit (ICU) stay and short-term outcome in order to eventually design a biomarker-guided randomized controlled trial. Methods: AdrenOSS-1 was a prospective observational multinational study. The primary outcome was 28-day mortality. Secondary outcomes included organ failure as defined by Sequential Organ Failure Assessment (SOFA) score, organ support with focus on vasopressor/inotropic use, and need for renal replacement therapy. AdrenOSS-1 included 583 patients admitted to the ICU with sepsis or septic shock. Results: Circulating bio-ADM levels were measured upon admission and at day 2. Median bio-ADM concentration upon admission was 80.5 pg/ml [IQR 41.5-148.1 pg/ml]. Initial SOFA score was 7 [IQR 5-10], and 28-day mortality was 22%. We found marked associations between bio-ADM upon admission and 28-day mortality (unadjusted standardized HR 2.3 [CI 1.9-2.9]; adjusted HR 1.6 [CI 1.1-2.5]) and between bio-ADM levels and SOFA score (p &lt; 0.0001). Need of vasopressor/inotrope, renal replacement therapy, and positive fluid balance were more prevalent in patients with a bio-ADM &gt; 70 pg/ml upon admission than in those with bio-ADM ≤ 70 pg/ml. In patients with bio-ADM &gt; 70 pg/ml upon admission, decrease in bio-ADM below 70 pg/ml at day 2 was associated with recovery of organ function at day 7 and better 28-day outcome (9.5% mortality). By contrast, persistently elevated bio-ADM at day 2 was associated with prolonged organ dysfunction and high 28-day mortality (38.1% mortality, HR 4.9, 95% CI 2.5-9.8). Conclusions: AdrenOSS-1 shows that early levels and rapid changes in bio-ADM estimate short-term outcome in sepsis and septic shock. These data are the backbone of the design of the biomarker-guided AdrenOSS-2 trial. Trial registration: ClinicalTrials.gov, NCT02393781. Registered on March 19, 2015

Coupled Aerothermomechanical Simulation for a Turbine Disk Through a Full Transient Cycle

Use of computational fluid dynamics (CFD) to model the complex, 3D disk cavity flow and heat transfer in conjunction with an industrial finite element analysis (FEA) of turbine disk thermomechanical response during a full transient cycle is demonstrated. The FEA and CFD solutions were coupled using a previously proposed efficient coupling procedure. This iterates between FEA and CFD calculations at each time step of the transient solution to ensure consistency of temperature and heat flux on the appropriate component surfaces. The FEA model is a 2D representation of high pressure and intermediate pressure (IP) turbine disks with surrounding structures. The front IP disk cavity flow is calculated using 45 deg sector CFD models with up to 2.8 million mesh cells. Three CFD models were initially defined for idle, maximum take-off, and cruise conditions, and these are updated by the automatic coupling procedure through the 13,000 s full transient cycle from stand-still to idle, maximum take-off, and cruise conditions. The obtained disk temperatures and displacements are compared with an earlier standalone FEA model that used established methods for convective heat transfer modeling. It was demonstrated that the coupling could be completed using a computer cluster with 60 cores within about 2 weeks. This turn around time is considered fast enough to meet design phase requirements, and in validation, it also compares favorably to that required to hand-match a FEA model to engine test data, which is typically several months. [DOI: 10.1115/1.4003242