Improving medication safety in the Intensive Care by identifying relevant drug-drug interactions - Results of a multicenter Delphi study

Purpose: Drug-drug interactions (DDIs) may cause adverse outcomes in patients admitted to the Intensive Care Unit (ICU). Computerized decision support systems (CDSSs) may help prevent DDIs by timely showing relevant warning alerts, but knowledge on which DDIs are clinically relevant in the ICU setting is limited. Therefore, the purpose of this study was to identify DDIs relevant for the ICU. Materials and methods: We conducted a modified Delphi procedure with a Dutch multidisciplinary expert panel consisting of intensivists and hospital pharmacists to assess the clinical relevance of DDIs for the ICU. The procedure consisted of two rounds, each included a questionnaire followed by a live consensus meeting. Results: In total the clinical relevance of 148 DDIs was assessed, of which agreement regarding the relevance was reached for 139 DDIs (94%). Of these 139 DDIs, 53 (38%) were considered not clinically relevant for the ICU setting. Conclusions: A list of clinically relevant DDIs for the ICU setting was established on a national level. The clinical value of CDSSs for medication safety could be improved by focusing on the identified clinically relevant DDIs, thereby avoiding alert fatigue

Biomarker-guided individualization of antibiotic therapy

Treatment failure of antibiotic therapy due to insufficient efficacy or occurrence of toxicity is a major clinical challenge, and is expected to become even more urgent with the global rise of antibiotic resistance. Strategies to optimize treatment in individual patients are therefore of crucial importance. Currently, therapeutic drug monitoring plays an important role in optimizing antibiotic exposure to reduce treatment failure and toxicity. Biomarker-based strategies may be a powerful tool to further quantify and monitor antibiotic treatment response, and reduce variation in treatment response between patients. Host response biomarkers, such as CRP, procalcitonin, IL-6, and presepsin, could potentially carry significant information to be utilized for treatment individualization. To achieve this, the complex interactions among immune system, pathogen, drug, and biomarker need to be better understood and characterized. The purpose of this tutorial is to discuss the use and evidence of currently available biomarker-based approaches to inform antibiotic treatment. To this end, we also included a discussion on how treatment response biomarker data from preclinical, healthy volunteer, and patient-based studies can be further characterized using pharmacometric and system pharmacology based modeling approaches. As an illustrative example of how such modeling strategies can be used, we describe a case study in which we quantitatively characterize procalcitonin dynamics in relation to antibiotic treatments in patients with sepsis.Pharmacolog

Population Pharmacokinetic Model and Pharmacokinetic Target Attainment of Micafungin in Intensive Care Unit Patients

_Objective:_ To study the pharmacokinetics of micafungin in intensive care patients and assess pharmacokinetic (PK) target attainment for various dosing strateg

Do intensive care data on respiratory infections reflect influenza epidemics?

Objectives Severe influenza can lead to Intensive Care Unit (ICU) admission. We explored whether ICU data reflect influenza like illness (ILI) activity in the general population, and whether ICU respiratory infections can predict influenza epidemics. Methods We calculated the time lag and correlation between ILI incidence (from ILI sentinel surveillance, based on general practitioners (GP) consultations) and percentages of ICU admissions with a respiratory infection (from the Dutch National Intensive Care Registry) over the years 2003–2011. In addition, ICU data of the first three years was used to build three regression models to predict the start and end of influenza epidemics in the years thereafter, one to three weeks ahead. The predicted start and end of influenza epidemics were compared with observed start and end of such epidemics according to the incidence of ILI. Results Peaks in respiratory ICU admissions lasted longer than peaks in ILI incidence rates. Increases in ICU admissions occurred on average two days earlier compared to ILI. Predicting influenza epidemics one, two, or three weeks ahead yielded positive predictive values ranging from 0.52 to 0.78, and sensitivities from 0.34 to 0.51. Conclusions ICU data was associated with ILI activity, with increases in ICU data often occurring earlier and for a longer time period. However, in the Netherlands, predicting influenza epidemics in the general population using ICU data was imprecise, with low positive predictive values and sensitivities

The effect of ICU-tailored drug-drug interaction alerts on medication prescribing and monitoring: Protocol for a cluster randomized stepped-wedge trial

Background: Drug-drug interactions (DDIs) can cause patient harm. Between 46 and 90% of patients admitted to the Intensive Care Unit (ICU) are exposed to potential DDIs (pDDIs). This rate is twice as high as patients on general wards. Clinical decision support systems (CDSSs) have shown their potential to prevent pDDIs. However, the literature shows that there is considerable room for improvement of CDSSs, in particular by increasing the clinical relevance of the pDDI alerts they generate and thereby reducing alert fatigue. However, consensus on which pDDIs are clinically relevant in the ICU setting is lacking. The primary aim of this study is to evaluate the effect of alerts based on only clinically relevant interactions for the ICU setting on the prevention of pDDIs among Dutch ICUs. Methods: To define the clinically relevant pDDIs, we will follow a rigorous two-step Delphi procedure in which a national expert panel will assess which pDDIs are perceived clinically relevant for the Dutch ICU setting. The intervention is the CDSS that generates alerts based on the clinically relevant pDDIs. The intervention will be evaluated in a stepped-wedge trial. A total of 12 Dutch adult ICUs using the same patient data management system, in which the CDSS will operate, were invited to participate in the trial. Of the 12 ICUs, 9 agreed to participate and will be enrolled in the trial. Our primary outcome measure is the incidence of clinically relevant pDDIs per 1000 medication administrations. Discussion: This study will identify pDDIs relevant for the ICU setting. It will also enhance our understanding of the effectiveness of alerts confined to clinically relevant pDDIs. Both of these contributions can facilitate the successful implementation of CDSSs in the ICU and in other domains as well. Trial registration: Nederlands Trial register Identifier: NL6762. Registered November 26, 2018

Hard probes of short-range nucleon-nucleon correlations

One of the primary goals of nuclear physics is providing a complete description of the structure of atomic nuclei. While mean-field calculations provide detailed information on the nuclear shell structure for a wide range of nuclei, they do not capture the complete structure of nuclei, in particular the impact of small, dense structures in nuclei. The strong, short-range component of the nucleon-nucleon potential yields hard interactions between nucleons which are close together, generating a high-momentum tail to the nucleon momentum distribution, with momenta well in excess of the Fermi momentum. This high-momentum component of the nuclear wave-function is one of the most poorly understood parts of nuclear structure. Utilizing high-energy probes, we can isolate scattering from high-momentum nucleons, and use these measurements to examine the structure and impact of short-range nucleon-nucleon correlations. Over the last decade we have moved from looking for evidence of such short-range structures to mapping out their strength in nuclei and examining their isospin structure. This has been made possible by high-luminosity and high-energy accelerators, coupled with an improved understanding of the reaction mechanism issues involved in studying these structures. We review the general issues related to short-range correlations, survey recent experiments aimed at probing these short-range structures, and lay out future possibilities to further these studies.Comment: Review article to appear in Prog.Part.Nucl.Phys. 77 pages, 33 figure

Methods for Optical Calibration of the BigBite Hadron Spectrometer

The techniques for optical calibration of Jefferson Lab's large-acceptance magnetic hadron spectrometer, BigBite, have been examined. The most consistent and stable results were obtained by using a method based on singular value decomposition. In spite of the complexity of the optics, the particles' positions and momenta at the target have been precisely reconstructed from the coordinates measured in the detectors by means of a single back-tracing matrix. The technique is applicable to any similar magnetic spectrometer and any particle type. For 0.55 GeV/c protons, we have established the vertex resolution of 1.2 cm, angular resolutions of 7 mrad and 16 mrad (in-plane and out-of-plane, respectively), and a relative momentum resolution of 1.6%.Comment: 26 pages, 13 figure

Cosmological parameters from SDSS and WMAP

We measure cosmological parameters using the three-dimensional power spectrum P(k) from over 200,000 galaxies in the Sloan Digital Sky Survey (SDSS) in combination with WMAP and other data. Our results are consistent with a ``vanilla'' flat adiabatic Lambda-CDM model without tilt (n=1), running tilt, tensor modes or massive neutrinos. Adding SDSS information more than halves the WMAP-only error bars on some parameters, tightening 1 sigma constraints on the Hubble parameter from h~0.74+0.18-0.07 to h~0.70+0.04-0.03, on the matter density from Omega_m~0.25+/-0.10 to Omega_m~0.30+/-0.04 (1 sigma) and on neutrino masses from <11 eV to <0.6 eV (95%). SDSS helps even more when dropping prior assumptions about curvature, neutrinos, tensor modes and the equation of state. Our results are in substantial agreement with the joint analysis of WMAP and the 2dF Galaxy Redshift Survey, which is an impressive consistency check with independent redshift survey data and analysis techniques. In this paper, we place particular emphasis on clarifying the physical origin of the constraints, i.e., what we do and do not know when using different data sets and prior assumptions. For instance, dropping the assumption that space is perfectly flat, the WMAP-only constraint on the measured age of the Universe tightens from t0~16.3+2.3-1.8 Gyr to t0~14.1+1.0-0.9 Gyr by adding SDSS and SN Ia data. Including tensors, running tilt, neutrino mass and equation of state in the list of free parameters, many constraints are still quite weak, but future cosmological measurements from SDSS and other sources should allow these to be substantially tightened.Comment: Minor revisions to match accepted PRD version. SDSS data and ppt figures available at http://www.hep.upenn.edu/~max/sdsspars.htm

Determination of |Vcb| using the semileptonic decay \bar{B}^0 --> D^{*+}e^-\bar{\nu}

We present a measurement of the Cabibbo-Kobayashi-Maskawa (CKM) matrix element |Vcb| using a 10.2 fb^{-1} data sample recorded at the \Upsilon(4S) resonance with the Belle detector at the KEKB asymmetric e^+e^- storage ring. By extrapolating the differential decay width of the \bar{B}^0 --> D^{*+}e^-\bar{\nu} decay to the kinematic limit at which the D^{*+} is at rest with respect to the \bar{B}^0, we extract the product of |Vcb| with the normalization of the decay form factor F(1), |Vcb |F(1)= (3.54+/-0.19+/-0.18)x10^{-2}, where the first error is statistical and the second is systematic. A value of |Vcb| = (3.88+/-0.21+/-0.20+/-0.19)x10^{-2} is obtained using a theoretical calculation of F(1), where the third error is due to the theoretical uncertainty in the value of F(1). The branching fraction B(\bar{B}^0 --> D^{*+}e^-\bar{\nu}) is measured to be (4.59+/-0.23+/-0.40)x10^{-2}.Comment: 20 pages, 6 figures, elsart.cls, submitted to PL