Assessing the impact of a national clinical guideline for the management of chronic pain on opioid prescribing rates:a controlled interrupted time series analysis

Background: Opioids can be effective analgesics, but long-term use may be associated with harms. In 2013, the first national, comprehensive, evidence-based pain management guideline was published, from the Scottish Intercollegiate Guideline Network (SIGN 136: Management of Chronic Pain) with key recommendations on analgesic prescribing. This study aimed to examine the potential impact on national opioid prescribing rates in Scotland. Methods: Trends in national and regional community opioid prescribing data for Scotland were analysed from quarter one (Q1) 2005 to Q2 2020. Interrupted time series regression examined the association of SIGN 136 publication with prescribing rates for opioid-containing drugs. Gabapentinoid prescribing was used as a comparison drug. Results: After a positive prescribing trend pre-publication, the timing of SIGN 136 publication was associated with a negative change in the trend of opioid prescribing rates (−2.82 items per 1000 population per quarter [PTPPQ]; P < 0.01). By Q2 2020, the relative reduction in the opioid prescribing rate was −20.67% (95% CI: −23.61, −17.76). This persisted after correcting for gabapentinoid prescribing and was mainly driven by the reduction in weak opioids, whereas strong opioid prescribing rates continued to rise. Gabapentinoid prescribing showed a significant rise in level (8.00 items per 1000 population; P = 0.01) and trend (0.27 items PTPPQ; P = 0.01) following SIGN 136 publication. Conclusions: The publication of SIGN 136 was associated with a reduction in opioid prescribing rates. This suggests that changes in clinical policy through evidence-based national clinical guidelines may affect community opioid prescribing, though this may be partially replaced by gabapentinoids, and other factors may also contribute

RuleMonkey: software for stochastic simulation of rule-based models

<p>Abstract</p> <p>Background</p> <p>The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen language (BNGL). A set of rules implicitly defines a (bio)chemical reaction network. The reaction network implied by a set of rules is often very large, and as a result, generation of the network implied by rules tends to be computationally expensive. Moreover, the cost of many commonly used methods for simulating network dynamics is a function of network size. Together these factors have limited application of the rule-based modeling approach. Recently, several methods for simulating rule-based models have been developed that avoid the expensive step of network generation. The cost of these "network-free" simulation methods is independent of the number of reactions implied by rules. Software implementing such methods is now needed for the simulation and analysis of rule-based models of biochemical systems.</p> <p>Results</p> <p>Here, we present a software tool called RuleMonkey, which implements a network-free method for simulation of rule-based models that is similar to Gillespie's method. The method is suitable for rule-based models that can be encoded in BNGL, including models with rules that have global application conditions, such as rules for intramolecular association reactions. In addition, the method is rejection free, unlike other network-free methods that introduce null events, i.e., steps in the simulation procedure that do not change the state of the reaction system being simulated. We verify that RuleMonkey produces correct simulation results, and we compare its performance against DYNSTOC, another BNGL-compliant tool for network-free simulation of rule-based models. We also compare RuleMonkey against problem-specific codes implementing network-free simulation methods.</p> <p>Conclusions</p> <p>RuleMonkey enables the simulation of rule-based models for which the underlying reaction networks are large. It is typically faster than DYNSTOC for benchmark problems that we have examined. RuleMonkey is freely available as a stand-alone application <url>http://public.tgen.org/rulemonkey</url>. It is also available as a simulation engine within GetBonNie, a web-based environment for building, analyzing and sharing rule-based models.</p

A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM

We present Korbit, a large-scale, open-domain, mixed-interface, dialogue-based intelligent tutoring system (ITS). Korbit uses machine learning, natural language processing and reinforcement learning to provide interactive, personalized learning online. Korbit has been designed to easily scale to thousands of subjects, by automating, standardizing and simplifying the content creation process. Unlike other ITS, a teacher can develop new learning modules for Korbit in a matter of hours. To facilitate learning across a widerange of STEM subjects, Korbit uses a mixed-interface, which includes videos, interactive dialogue-based exercises, question-answering, conceptual diagrams, mathematical exercises and gamification elements. Korbit has been built to scale to millions of students, by utilizing a state-of-the-art cloud-based micro-service architecture. Korbit launched its first course in 2019 on machine learning, and since then over 7,000 students have enrolled. Although Korbit was designed to be open-domain and highly scalable, A/B testing experiments with real-world students demonstrate that both student learning outcomes and student motivation are substantially improved compared to typical online courses

Minimally invasive mitral valve replacement: Port-access technique, feasibility, and myocardial functional preservation

AbstractObjective: This experiment examined the feasibility of minimally invasive port-access mitral valve replacement via a 2.5 cm incision. Methods: The study evaluated valvular performance and myocardial functional recovery in six mongrel dogs after port-access mitral valve replacement with a St. Jude Medical prosthesis (St. Jude Medical, Inc., St. Paul, Minn.). Femoro-femoral cardiopulmonary bypass and a balloon catheter system for myocardial protection with cardioplegic arrest (Heartport, Inc., Redwood City, Calif.) were used. The mitral valve was replaced through a 2.5 cm port in the left side of the chest, and the animals were weaned from bypass. Cardiac function was measured before and at 30 and 60 minutes after bypass. Left ventricular pressure and electrical conductance volume were used to calculate changes in load-independent indexes of ventricular function. Results: Each procedure was successfully completed. Recovery of left ventricular function was excellent at 30 and 60 minutes after bypass compared with the prebypass values for elastance (30 minutes = 4.04 ± 0.97 and 60 minutes = 4.27 ± 0.57 vs prebypass = 4.45 ± 0.96; p = 0.51) and for preload recruitable stroke work (30 minutes = 76.23 ± 4.80 and 60 minutes = 71.21 ± 2.99 vs prebypass = 71.23 ± 3.75; p = 0.45). Preload recruitable work area remained at 96% and 85% of baseline at 30 and 60 minutes (p = not significant). In addition, transesophageal echocardiography demonstrated normal prosthetic valve function, as well as normal regional and global ventricular wall motion. Autopsy revealed secure annular-sewing apposition and normal leaflet motion. Conclusions: These results suggest that minimally invasive mitral valve replacement using percutaneous cardiopulmonary bypass with cardioplegic arrest is technically reproducible, achieves normal valve placement, and results in complete cardiac functional recovery. Minimally invasive mitral valve replacement is now feasible, and clinical trials are indicated. (J Thorac Cardiovasc Surg 1997; 113:1022-31

Improving Information on Maternal Medication Use by Linking Prescription Data to Congenital Anomaly Registers: A EUROmediCAT Study

Research on associations between medication use during pregnancy and congenital anomalies is significative for assessing the safe use of a medicine in pregnancy. Congenital anomaly (CA) registries do not have optimal information on medicine exposure, in contrast to prescription databases. Linkage of prescription databases to the CA registries is a potentially effective method of obtaining accurate information on medicine use in pregnancies and the risk of congenital anomalies. We linked data from primary care and prescription databases to five European Surveillance of Congenital Anomalies (EUROCAT) CA registries. The linkage was evaluated by looking at linkage rate, characteristics of linked and non-linked cases, first trimester exposure rates for six groups of medicines according to the prescription data and information on medication use registered in the CA databases, and agreement of exposure. Of the 52,619 cases registered in the CA databases, 26,552 could be linked. The linkage rate varied between registries over time and by type of birth. The first trimester exposure rates and the agreements between the databases varied for the different medicine groups. Information on anti-epileptic drugs and insulins and analogue medicine use recorded by CA registries was of good quality. For selective serotonin reuptake inhibitors, anti-asthmatics, antibacterials for systemic use, and gonadotropins and other ovulation stimulants, the recorded information was less complete. Linkage of primary care or prescription databases to CA registries improved the quality of information on maternal use of medicines in pregnancy, especially for medicine groups that are less fully registered in CA registries

Student Attitudes toward Learning Analytics in Higher Education: "The Fitbit Version of the Learning World"

Increasingly, higher education institutions are exploring the potential of learning analytics to predict student retention, understand learning behaviors, and improve student learning through providing personalized feedback and support. The technical development of learning analytics has outpaced consideration of ethical issues surrounding their use. Of particular concern is the absence of the student voice in decision-making about learning analytics. We explored higher education students' knowledge, attitudes, and concerns about big data and learning analytics through four focus groups (N = 41). Thematic analysis of the focus group transcripts identified six key themes. The first theme, “Uninformed and Uncertain,” represents students' lack of knowledge about learning analytics prior to the focus groups. Following the provision of information, viewing of videos and discussion of learning analytics scenarios three further themes; “Help or Hindrance to Learning,” “More than a Number,” and “Impeding Independence”; represented students' perceptions of the likely impact of learning analytics on their learning. “Driving Inequality” and “Where Will it Stop?” represent ethical concerns raised by the students about the potential for inequity, bias and invasion of privacy and the need for informed consent. A key tension to emerge was how “personal” vs. “collective” purposes or principles can intersect with “uniform” vs. “autonomous” activity. The findings highlight the need the need to engage students in the decision making process about learning analytics

Migalastat improves diarrhea in patients with Fabry disease: clinical-biomarker correlations from the phase 3 FACETS trial

Background: Fabry disease is frequently characterized by gastrointestinal symptoms, including diarrhea. Migalastat is an orally-administered small molecule approved to treat the symptoms of Fabry disease in patients with amenable mutations. Methods: We evaluated minimal clinically important differences (MCID) in diarrhea based on the corresponding domain of the patient-reported Gastrointestinal Symptom Rating Scale (GSRS) in patients with Fabry disease and amenable mutations (N = 50) treated with migalastat 150 mg every other day or placebo during the phase 3 FACETS trial (NCT00925301). Results: After 6 months, significantly more patients receiving migalastat versus placebo experienced improvement in diarrhea based on a MCID of 0.33 (43% vs 11%; p = .02), including the subset with baseline diarrhea (71% vs 20%; p = .02). A decline in kidney peritubular capillary globotriaosylceramide inclusions correlated with diarrhea improvement; patients with a reduction > 0.1 were 5.6 times more likely to have an improvement in diarrhea than those without (p = .031). Conclusions: Migalastat was associated with a clinically meaningful improvement in diarrhea in patients with Fabry disease and amenable mutations. Reductions in kidney globotriaosylceramide may be a useful surrogate endpoint to predict clinical benefit with migalastat in patients with Fabry disease. Trial registration NCT00925301; June 19, 2009

NEXAFS Sensitivity to Bond Lengths in Complex Molecular Materials: A Study of Crystalline Saccharides

Detailed analysis of the C K near-edge X-ray absorption fine structure (NEXAFS) spectra of a series of saccharides (fructose, xylose, glucose, galactose, maltose monohydrate, α-lactose monohydrate, anhydrous β-lactose, cellulose) indicates that the precise determination of IPs and σ* shape resonance energies is sensitive enough to distinguish different crystalline saccharides through the variations in their average C–OH bond lengths. Experimental data as well as FEFF8 calculations confirm that bond length variations in the organic solid state of 10–2 Å can be experimentally detected, opening up the possibility to use NEXAFS for obtaining incisive structural information for molecular materials, including noncrystalline systems without long-range order such as dissolved species in solutions, colloids, melts, and similar amorphous phases. The observed bond length sensitivity is as good as that originally reported for gas-phase and adsorbed molecular species. NEXAFS-derived molecular structure data for the condensed phase may therefore be used to guide molecular modeling as well as to validate computationally derived structure models for such systems. Some results indicate further analytical value in that the σ* shape resonance analysis may distinguish hemiketals from hemiacetals (i.e., derived from ketoses and aldoses) as well as α from β forms of otherwise identical saccharides