Analyzing Medication Documentation in Electronic Health Records: Dental Students’ Self-Reported Behaviors and Charting Practices

The aim of this two-part study was to assess third- and fourth-year dental students’ perceptions, self-reported behaviors, and actual charting practices regarding medication documentation in axiUm, the electronic health record (EHR) system. In part one of the study, in fall 2015, all 125 third- and 85 fourth-year dental students at one U.S. dental school were invited to complete a ten-item anonymous survey on medication history-taking. In part two of the study, the EHRs of 519 recent dental school patients were randomly chosen via axiUm query based on age >21 years and the presence of at least one documented medication. Documentation completeness was assessed per EHR and each medication based on proper medication name, classification, dose/frequency, indication, potential oral effects, and correct medication spelling. Consistency was evaluated by identifying the presence/absence of a medical reason for each medication. The survey response rate was 90.6% (N=187). In total, 64.5% of responding students reported that taking a complete medication history is important and useful in enhancing pharmacology knowledge; 90.4% perceived it helped improve their understanding of patients’ medical conditions. The fourth-year students were more likely than the third-year students to value the latter (p=0.0236). Overall, 48.6% reported reviewing patient medications with clinic faculty 76-100% of the time. The respondents’ most frequently cited perceived barriers to medication documentation were patients’ not knowing their medications (68.5%) and, to a much lesser degree, axiUm limitations (14%). Proper medication name was most often recorded (93.6%), and potential oral effects were recorded the least (3.0%). Medication/medical condition consistency was 70.6%. In this study, most of the students perceived patient medication documentation as important; however, many did not appreciate the importance of all elements of a complete medication history, and complete medication documentation was low

Bayes Optimal Informer Sets for Early-Stage Drug Discovery

An important experimental design problem in early-stage drug discovery is how to prioritize available compounds for testing when very little is known about the target protein. Informer based ranking (IBR) methods address the prioritization problem when the compounds have provided bioactivity data on other potentially relevant targets. An IBR method selects an informer set of compounds, and then prioritizes the remaining compounds on the basis of new bioactivity experiments performed with the informer set on the target. We formalize the problem as a two-stage decision problem and introduce the Bayes Optimal Informer SEt (BOISE) method for its solution. BOISE leverages a flexible model of the initial bioactivity data, a relevant loss function, and effective computational schemes to resolve the two-step design problem. We evaluate BOISE and compare it to other IBR strategies in two retrospective studies, one on protein-kinase inhibition and the other on anti-cancer drug sensitivity. In both empirical settings BOISE exhibits better predictive performance than available methods. It also behaves well with missing data, where methods that use matrix completion show worse predictive performance. We provide an R implementation of BOISE at https://github.com/wiscstatman/esdd/BOISEComment: 18 pages, 6 figure

Outbreak of encephalitic listeriosis in red-legged partridges (Alectoris rufa)

An outbreak of neurological disease was investigated in red-legged partridges between 8 and 28 days of age. Clinical signs included torticollis, head tilt and incoordination and over an initial eight day period approximately 30–40 fatalities occurred per day. No significant gross post mortem findings were detected. Histopathological examination of the brain and bacterial cultures followed by partial sequencing confirmed a diagnosis of encephalitis due to Listeria monocytogenes. Further isolates were obtained from follow-up carcasses, environmental samples and pooled tissue samples of newly imported day-old chicks prior to placement on farm. These isolates had the same antibiotic resistance pattern as the isolate of the initial post mortem submission and belonged to the same fluorescent amplified fragment length polymorphism (fAFLP) subtype. This suggested that the isolates were very closely related or identical and that the pathogen had entered the farm with the imported day-old chicks, resulting in disease manifestation in partridges between 8 and 28 days of age. Reports of outbreaks of encephalitic listeriosis in avian species are rare and this is to the best of our knowledge the first reported outbreak in red-legged partridges

Breaking the Rules: Low Trait or State Self-Control Increases Social Norm Violations

Two pilot and six studies indicated that poor self-control causes people to violate social norms and rules that are effortful to follow. Lower trait self-control was associated with a greater willingness to take ethical risks and use curse words. Participants who completed an initial self-control task that reduced the capacity for self-control used more curse words and were more willing to take ethical risks than participants who completed a neutral task. Poor self-control was also associated with violating explicit rules given by the experimenter. Depleting self-control resources in a self-control exercise caused participants subsequently to talk when they had been instructed to remain silent. Low trait self-control and poor performance on a behavioral measure of self-control (the Stroop task) predicted poor compliance following experimental instructions over a 2-week span. Poor self-control thus undermines adherence to some social rules and regulations, therefore possibly contributing to a broad variety of social ills

Investigation of the catalytic and structural roles of conserved histidines of human coproporphyrinogen oxidase using site-directed mutagenesis

Background: The catalytic contribution of four conserved histidines of human coproporphyrinogen oxidase (CPO) has been investigated using site-directed mutagenesis to change histidine (H) into alanine (A). Material/Methods: The wild-type and mutant enzyme forms were analyzed for their ability to utilize coproporphyrinogen-III, mesoporphvrinogen-VI, and harderoporphyrinogen as substrates. Results: Wild-type CPO had specific activities of 4.9 +/- 0.9 nmole product/min/mg for coproporphyrinogen-III, 1.7 +/- 0.7 nmole ptoduct/min/mg for mesoporphyrinogen-VI, and 5.1 +/- 1.8 nmole product/min/mg for harderoporphyrinogen. The four mutant enzymes were catalytically competent With all three substrates, but to varying degrees. The most affected Mutant was the H158A enzyme which exhibited approximately 50-fold lower activity than wild-type recombinant CPO. Conclusions: Thus, His 158 of human CPO may have a role ill the active site, but none of the conserved histidine residues of human coproporphyrinogen oxidase is essential for catalytic activity although changes in histidines have been implicated in the disease state hereditary coproporphyria

Antiphospholipid autoantibodies as blood biomarkers for detection of early stage Alzheimer's disease

A robust blood biomarker is urgently needed to facilitate early prognosis for those at risk for Alzheimer's disease (AD). Redox reactive autoantibodies (R-RAAs) represent a novel family of antibodies detectable only after exposure of cerebrospinal fluid (CSF), serum, plasma or immunoglobulin fractions to oxidizing agents. We have previously reported that R-RAA antiphospholipid antibodies (aPLs) are significantly decreased in the CSF and serum of AD patients compared to healthy controls (HCs). These studies were extended to measure R-RAA aPL in serum samples obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI). Serum samples from the ADNI-1 diagnostic groups from participants with mild cognitive impairment (MCI), AD and HCs were blinded for diagnosis and analyzed for R-RAA aPL by ELISA. Demographics, cognitive data at baseline and yearly follow-up were subsequently provided by ADNI after posting assay data. As observed in CSF, R-RAA aPL in sera from the AD diagnostic group were significantly reduced compared to HC. However, the sera from the MCI population contained significantly elevated R-RAA aPL activity relative to AD patient and/or HC sera. The data presented in this study indicate that R-RAA aPL show promise as a blood biomarker for detection of early AD, and warrant replication in a larger sample. Longitudinal testing of an individual for increases in R-RAA aPL over a previously established baseline may serve as a useful early sero-epidemiologic blood biomarker for individuals at risk for developing dementia of the Alzheimer's type

A network-based approach for predicting missing pathway interactions

Embedded within large-scale protein interaction networks are signaling pathways that encode response cascades in the cell. Unfortunately, even for well-studied species like S. cerevisiae, only a fraction of all true protein interactions are known, which makes it difficult to reason about the exact flow of signals and the corresponding causal relations in the network. To help address this problem, we introduce a framework for predicting new interactions that aid connectivity between upstream proteins (sources) and downstream transcription factors (targets) of a particular pathway. Our algorithms attempt to globally minimize the distance between sources and targets by finding a small set of shortcut edges to add to the network. Unlike existing algorithms for predicting general protein interactions, by focusing on proteins involved in specific responses our approach homes-in on pathway-consistent interactions. We applied our method to extend pathways in osmotic stress response in yeast and identified several missing interactions, some of which are supported by published reports. We also performed experiments that support a novel interaction not previously reported. Our framework is general and may be applicable to edge prediction problems in other domains

Cancer and thrombosis: Managing the risks and approaches to thromboprophylaxis

Patients with cancer are at increased risk of venous thromboembolism (VTE) compared with patients without cancer. This results from both the prothrombotic effects of the cancer itself and iatrogenic factors, such as chemotherapy, radiotherapy, indwelling central venous devices and surgery, that further increase the risk of VTE. Although cancer-associated thrombosis remains an important cause of morbidity and mortality, it is often underdiagnosed and undertreated. However, evidence is accumulating to support the use of low-molecular-weight heparins (LMWHs) in the secondary prevention of VTE in patients with cancer. Not only have LMWHs been shown to be at least as effective as coumarin derivatives in this setting, but they have a lower incidence of complications, including bleeding, and are not associated with the practical problems of warfarin therapy. Furthermore, a growing number of studies indicate that LMWHs may improve survival among patients with cancer due to a possible antitumor effect. Current evidence suggests that LMWHs should increasingly be considered for the long-term management of VTE in patients with cancer

Not a Waste: Wastewater Surveillance to Enhance Public Health

Domestic wastewater, when collected and evaluated appropriately, can provide valuable health-related information for a community. As a relatively unbiased and non-invasive approach, wastewater surveillance may complement current practices towards mitigating risks and protecting population health. Spurred by the COVID-19 pandemic, wastewater programs are now widely implemented to monitor viral infection trends in sewersheds and inform public health decision-making. This review summarizes recent developments in wastewater-based epidemiology for detecting and monitoring communicable infectious diseases, dissemination of antimicrobial resistance, and illicit drug consumption. Wastewater surveillance, a quickly advancing Frontier in environmental science, is becoming a new tool to enhance public health, improve disease prevention, and respond to future epidemics and pandemics