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Education For Health (Abingdon, England) 2016Medication errors are the second most frequently reported hospital incident in Australia and are a global concern. A "Medication Calculation and Administration" workshop...
Medication calculation and administration workshop and hurdle assessment increases student awareness towards the importance of safe practices to decrease medication errors in the future.
BACKGROUND
Medication errors are the second most frequently reported hospital incident in Australia and are a global concern. A "Medication Calculation and Administration" workshop followed by a "hurdle" assessment (compulsory task mandating a minimum level of performance as a condition of passing the course) was introduced into Year 2 of the James Cook University medical curriculum to decrease dosage calculation and administration errors among graduates. This study evaluates the effectiveness of this educational activity as a long-term strategy to teach medical students' essential skills in calculating and administering medications.
METHODS
This longitudinal study used a pre- and post-test design to determine whether medical students retained their calculation and administration skills over a period of 4 years. The ability to apply basic mathematical skills to medication dose calculation, principles of safe administration (Part 1), and ability to access reference materials to check indications, contraindications, and writing the medication order with correct abbreviations (Part 2) were compared between Year 2 and 6 assessments.
RESULTS
Scores for Parts 1, 2 and total scores were nearly identical from Year 2 to Year 6 (P = 0.663, 0.408, and 0.472, respectively), indicating minimal loss of knowledge by students in this period. Most Year 6 students (86%) were able to recall at least 5 of the "6 Rights of Medication Administration" while 84% reported accessing reference material and 91% reported checking their medical calculations.
DISCUSSION
The "Medication Calculation and Administration" workshop with a combined formative and summative assessment - a "hurdle" - promotes long-term retention of essential clinical skills for medical students. These skills and an awareness of the problem are strategies to assist medical graduates in preventing future medication-related adverse events.
Topics: Australia; Contraindications; Curriculum; Drug Dosage Calculations; Education, Medical, Undergraduate; Educational Measurement; Humans; Longitudinal Studies; Mathematics; Medication Errors; Pharmaceutical Preparations; Students, Medical
PubMed: 28406100
DOI: 10.4103/efh.EfH_312_14 -
Physical Review. E Mar 2016Nuclear magnetic resonance (NMR) diffusion experiments are widely employed as they yield information about structures hindering the diffusion process, e.g., about cell...
Nuclear magnetic resonance (NMR) diffusion experiments are widely employed as they yield information about structures hindering the diffusion process, e.g., about cell membranes. While it has been shown in recent articles that these experiments can be used to determine the shape of closed pores averaged over a volume of interest, it is still an open question how much information can be gained in open well-connected systems. In this theoretical work, it is shown that the full structure information of connected periodic systems is accessible. To this end, the so-called "SEquential Rephasing by Pulsed field-gradient Encoding N Time intervals" (SERPENT) sequence is used, which employs several diffusion encoding gradient pulses with different amplitudes. Two two-dimensional solid matrices that are surrounded by an NMR-visible medium are considered: a hexagonal lattice of cylinders and a rectangular lattice of isosceles triangles.
PubMed: 27078384
DOI: 10.1103/PhysRevE.93.032401 -
Scientific Reports Aug 2017Identifying drug-target interaction (DTI) candidates is crucial for drug repositioning. However, usually only positive DTIs are deposited in known databases, which...
Identifying drug-target interaction (DTI) candidates is crucial for drug repositioning. However, usually only positive DTIs are deposited in known databases, which challenges computational methods to predict novel DTIs due to the lack of negative samples. To overcome this dilemma, researchers usually randomly select negative samples from unlabeled drug-target pairs, which introduces a lot of false-positives. In this study, a negative sample extraction method named NDTISE is first developed to screen strong negative DTI examples based on positive-unlabeled learning. A novel DTI screening framework, PUDTI, is then designed to infer new drug repositioning candidates by integrating NDTISE, probabilities that remaining ambiguous samples belong to the positive and negative classes, and an SVM-based optimization model. We investigated the effectiveness of NDTISE on a DTI data provided by NCPIS. NDTISE is much better than random selection and slightly outperforms NCPIS. We then compared PUDTI with 6 state-of-the-art methods on 4 classes of DTI datasets from human enzymes, ion channels, GPCRs and nuclear receptors. PUDTI achieved the highest AUC among the 7 methods on all 4 datasets. Finally, we validated a few top predicted DTIs through mining independent drug databases and literatures. In conclusion, PUDTI provides an effective pre-filtering method for new drug design.
Topics: Algorithms; Databases, Pharmaceutical; Drug Delivery Systems; Drug Discovery; Drug Evaluation, Preclinical; Drug Interactions; Drug Repositioning; Humans; Pharmaceutical Preparations
PubMed: 28808275
DOI: 10.1038/s41598-017-08079-7 -
Physical Review. E Feb 2023Mechanical force has been widely used to study RNA folding and unfolding. Understanding how the force affects the opening and closing of a single base pair, which is a...
Mechanical force has been widely used to study RNA folding and unfolding. Understanding how the force affects the opening and closing of a single base pair, which is a basic step for RNA folding and unfolding and a fundamental behavior in some important biological activities, is crucial to understanding the mechanism of RNA folding and unfolding under mechanical force. In this work, we investigated the opening and closing process of an RNA base pair under mechanical force with constant-force stretching molecular dynamics simulations. It was found that high mechanical force results in overstretching, and the open state is a high-energy state. The enthalpy and entropy change of the base-pair opening-closing transition were obtained and the results at low forces were in good agreement with the nearest-neighbor model. The temperature and force dependence of the opening and closing rates were also obtained. The position of the transition state for the base-pair opening-closing transition under mechanical force was determined. The free energy barrier of opening a base pair without force is the enthalpy increase, and the work done by the force from the closed state to the transition state decreases the barrier and increases the opening rate. The free energy barrier of closing the base pair without force results from the entropy loss, and the work done by the force from the open state to the transition state increases the barrier and decreases the closing rate. The transition rates are strongly dependent on the temperature and force, while the transition path times are weakly dependent on force and temperature.
Topics: RNA; Molecular Dynamics Simulation; Base Pairing; Thermodynamics; Mechanical Phenomena; Kinetics
PubMed: 36932572
DOI: 10.1103/PhysRevE.107.024404 -
Physical Review. E Nov 2019Medical conditions due to acute cell injury, such as stroke and heart attack, are of tremendous impact and have attracted huge amounts of research effort. The biomedical...
Medical conditions due to acute cell injury, such as stroke and heart attack, are of tremendous impact and have attracted huge amounts of research effort. The biomedical research that seeks cures for these conditions has been dominated by a qualitative, inductive mind-set. Although the inductive approach has not been effective in developing medical treatments, it has amassed enough information to allow construction of quantitative, deductive models of acute cell injury. In this work we develop a modeling approach by extending an autonomous nonlinear dynamic theory of acute cell injury that offered new ways to conceptualize cell injury but possessed limitations that decrease its effectiveness. Here we study the global dynamics of the cell injury theory using a nonautonomous formulation. Different from the standard scenario in nonlinear dynamics that is determined by the steady state and fixed points of the model equations, in this nonautonomous model with a trivial fixed point, the system property is dominated by the transient states and the corresponding dynamic processes. The model gives rise to four qualitative types of dynamical patterns that can be mapped to the behavior of cells after clinical acute injuries. The nonautonomous theory predicts the existence of a latent stress response capacity (LSRC) possessed by injured cells. The LSRC provides a theoretical explanation of how therapies, such as hypothermia, can prevent cell death after lethal injuries. The nonautonomous theory of acute cell injury provides an improved quantitative framework for understanding cell death and recovery and lays a foundation for developing effective therapeutics for acute injury.
Topics: Adaptation, Physiological; Cell Death; Cells; Models, Biological; Nonlinear Dynamics; Stress, Physiological
PubMed: 31870014
DOI: 10.1103/PhysRevE.100.052407 -
Biomedical Chromatography : BMC Jan 2021Bioanalysis, a key supporting function for generating data for pre-clinical and clinical studies in drug development, is under the regulation of local agencies as well... (Review)
Review
Perspectives on updates, clarifications and controversies in chromatographic assay guidance for bioanalytical method validation from major regulatory agencies and organizations.
Bioanalysis, a key supporting function for generating data for pre-clinical and clinical studies in drug development, is under the regulation of local agencies as well as global organizations to ensure the data integrity and quality in submission. As major regulatory agencies and organizations, the US Food and Drug Administration, the European Medicines Agency and the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use have been updating their industry guidance for bioanalytical method validation, to keep up with the development new modalities, technologies and regulations. This article summarizes the recent updates and any clarifications and controversies triggered by those updates. Perspectives and recommendations are given based on our own experience as well as commonly accepted practice in the bioanalytical community.
Topics: Chemistry, Pharmaceutical; Chromatography; Clinical Trials as Topic; Humans; Pharmaceutical Preparations; Reproducibility of Results; Sensitivity and Specificity; United States; United States Food and Drug Administration
PubMed: 33201529
DOI: 10.1002/bmc.5030 -
Physical Review. E Jan 2018A bridge in a graph is an edge whose removal disconnects the graph and increases the number of connected components. We calculate the fraction of bridges in a wide range...
A bridge in a graph is an edge whose removal disconnects the graph and increases the number of connected components. We calculate the fraction of bridges in a wide range of real-world networks and their randomized counterparts. We find that real networks typically have more bridges than their completely randomized counterparts, but they have a fraction of bridges that is very similar to their degree-preserving randomizations. We define an edge centrality measure, called bridgeness, to quantify the importance of a bridge in damaging a network. We find that certain real networks have a very large average and variance of bridgeness compared to their degree-preserving randomizations and other real networks. Finally, we offer an analytical framework to calculate the bridge fraction and the average and variance of bridgeness for uncorrelated random networks with arbitrary degree distributions.
PubMed: 29448361
DOI: 10.1103/PhysRevE.97.012307 -
AMIA ... Annual Symposium Proceedings.... 2020Many adverse drug reactions (ADRs) are caused by drug-drug interactions (DDIs), meaning they arise from concurrent use of multiple medications. Detecting DDIs using...
Many adverse drug reactions (ADRs) are caused by drug-drug interactions (DDIs), meaning they arise from concurrent use of multiple medications. Detecting DDIs using observational data has at least three major challenges: (1) The number of potential DDIs is astronomical; (2) Associations between drugs and ADRs may not be causal due to observed or unobserved confounding; and (3) Frequently co-prescribed drug pairs that each independently cause an ADR do not necessarily causally interact, where causal interaction means that at least some patients would only experience the ADR if they take both drugs. We address (1) through data mining algorithms pre-filtering potential interactions, and (2) and (3) by fitting causal interaction models adjusting for observed confounders and conducting sensitivity analyses for unobserved confounding. We rank candidate DDIs robust to unobserved confounding more likely to be real. Our rigorous approach produces far fewer false positives than past applications that ignored (2) and (3).
Topics: Data Mining; Drug Interactions; Drug-Related Side Effects and Adverse Reactions; Humans; Pharmaceutical Preparations
PubMed: 33936409
DOI: No ID Found -
Journal of Hazardous Materials Sep 2018Removal of pharmaceutically active compounds (PhACs) in constructed wetlands (CWs) is a complex interplay of different processes. We studied fate and distribution of...
Removal of pharmaceutically active compounds (PhACs) in constructed wetlands (CWs) is a complex interplay of different processes. We studied fate and distribution of seven PhACs (caffeine, CAF; naproxen, NAP; metoprolol, MET; propranolol, PRO; ibuprofen, IBP; carbamazepine, CBZ; diclofenac, DFC) in mesocosm CWs and effects of irradiation via pre-photocatalysis, substrate composition (mainly sediment) through addition of litter (dead plant biomass), and plants. CWs showed high removal of CAF, NAP, MET, PRO, and IBP (79-99%). All seven PhACs were detected in substrate and plant tissues as well as IBP intermediates. Estimated PhAC mass balance showed that sorption dominated PRO removal in CWs while other PhACs were mainly removed by biodegradation and/or phytodegradation. Pre-photocatalysis significantly increased removal of PhACs except for CAF and IBP, and decreased accumulation of PhACs in substrate and plant tissues of the following wetland compartment. Litter addition in CW significantly enhanced removal of PRO and CBZ via biodegradation and/or phytodegradation. Plants played an essential and positive role in removing PhACs, resulting from direct phytoremediation and indirectly enhancing sorption and biodegradation. Our study provides knowledge to understand removal mechanisms of PhACs in CWs and to potentially enhance PhAC removal by developing pre-photocatalysis, adding dead plant biomass, and optimizing vegetation.
Topics: Adsorption; Biodegradation, Environmental; Light; Pharmaceutical Preparations; Plants; Waste Disposal, Fluid; Water Pollutants, Chemical; Wetlands
PubMed: 29886365
DOI: 10.1016/j.jhazmat.2018.05.035 -
Physical Review. E Aug 2019Hemodynamic modeling is used to explore the origin, predict, and analyze the power spectrum of the resting-state blood-oxygen-level-dependent (BOLD) signal measured by...
Hemodynamic modeling is used to explore the origin, predict, and analyze the power spectrum of the resting-state blood-oxygen-level-dependent (BOLD) signal measured by functional magnetic resonance imaging (fMRI), which has been reported to have a power-law form, i.e., P(f)∝f^{-s}, where P(f) is the power, f is the frequency, and s>0 is the power-law exponent. However, current fMRI experimental paradigms have limited acquisition durations, affecting the spectral resolution of fMRI data at the low-frequency regime. Here, the claimed power-law spectrum is investigated by using a recent hemodynamic model to analytically derive the BOLD power spectrum, with parameters that are related to neurophysiology. The theoretical results show that, for all realistic parameter combinations, the BOLD power spectrum is flat at f≲0.01Hz, has a weak resonance originating from intrinsic oscillations of vasodilatory response, and becomes a power law for high frequencies, all of which is in agreement with an empirical data set that describes the spectrum of one subject and brain region. However, the results are contrary to studies reporting a pure power-law spectrum at f≲0.2Hz. The discrepancy is attributed largely to data averaging employed by current approaches that averages together important properties of the BOLD power spectrum, such as its resonance, that biases the spectrum to only show a power law. Data averaging also reduces the high-frequency power-law exponent relative to individual cases. Overall, this work demonstrates how the model can reproduce BOLD dynamics and further analyze its low-frequency behavior. Moreover, it also uses the model to explain the impact of procedures, such as data averaging, on the reported features of the BOLD power spectrum.
Topics: Brain; Hemodynamics; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Models, Biological; Oxygen; Rest
PubMed: 31574765
DOI: 10.1103/PhysRevE.100.022418