Clinical decision support capabilities of commercially-available clinical information systems.

BACKGROUND: The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems. Purpose The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems. METHODS: The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features. RESULTS: Six of the nine reviewed systems offered all the applicable event-driven, action-oriented, real-time clinical decision support triggers required for initiating clinical decision support interventions. Five of the nine systems could access all the patient-specific data items identified as necessary. Six of the nine systems supported all the intervention types identified as necessary to allow clinical information systems to tailor their interventions based on the severity of the clinical situation and the user's workflow. Only one system supported all the offered choices identified as key to allowing physicians to take action directly from within the alert. Discussion The principal finding relates to system-by-system variability. The best system in our analysis had only a single missing feature (from 42 total) while the worst had eighteen.This dramatic variability in CDS capability among commercially available systems was unexpected and is a cause for concern. CONCLUSIONS: These findings have implications for four distinct constituencies: purchasers of clinical information systems, developers of clinical decision support, vendors of clinical information systems and certification bodies.

Association of pellicle growth morphological characteristics and clinical presentation of Mycobacterium tuberculosis isolates

Trehalose dimycolate (TDM) is a mycobacterial glycolipid that is released from the surface of virulent M. tuberculosis. We evaluated the rate of growth, colony characteristics and production of TDM by Mycobacterium tuberculosis strains isolated from different clinical sites. Since detergent removes TDM from organisms, we analyzed growth rate and colony morphology of 79 primary clinical isolates grown as pellicles on the surface of detergent free Middlebrook 7H9 media. The genotype of each had been previously characterized. TDM production was measured by thin layer chromatography on 32 of these isolates. We found that strains isolated from pulmonary sites produced large amounts of TDM, grew rapidly as thin spreading pellicles, showed early cording (<1 week) and climbed the sides of the dish. In contrast, the extrapulmonary isolates (lymph node and bone marrow) produced less TDM (p<0.01), grew as discrete patches with little tendency to spread or climb the walls (p<0.02). The Beijing pulmonary (BP) isolates produced more TDM than non Beijing pulmonary isolates. The largest differences were observed in Beijing strains. The Beijing pulmonary isolates produced more TDM and grew faster than the Beijing extrapulmonary isolates (p<0.01). This was true even when the pulmonary and extrapulmonary isolates were derived from the same clade. These growth characteristics were consistently observed only on the first passage after primary isolation. This suggests that the differences in growth rate and TDM production observed reflect differences in gene expression patterns of pulmonary and extrapulmonary infections, that Mycobacterium tuberculosis in the lung grows more rapidly and produces more TDM than it does in extrapulmonary sites. This provides new opportunities to investigate gene expression of Mycobacterium tuberculosis in human.^

A comparison of adherence with minocycline treatment in Parkinson's disease and rheumatoid arthritis clinical trials

Background: Little is known about the effects on patient adherence when the same study drug is administered in the same dose in two populations with two different diseases in two different clinical trials. The Minocycline in Rheumatoid Arthritis (MIRA) trial and the NIH Exploratory Trials in Parkinson's disease (NET-PD) Futility Study I provide a unique opportunity to do the above and to compare methods measuring adherence. This study may increase understanding of the influence of disease and adverse events on patient adherence and will provide insights to investigators selecting adherence assessment methods in clinical trials of minocycline and other drugs in future.^ Methods: Minocycline adherence by pill count and the effect of adverse events was compared in the MIRA and NET-PD FS1 trials using multivariable linear regression. Within the MIRA trial, agreement between assay and pill count was compared. The association of adverse events with assay adherence was examined using multivariable logistic regression.^ Results: Adherence derived from pill count in the MIRA and NET-PD FS1 trials did not differ significantly. Adverse events potentially related to minocycline did not appear useful to predict minocycline adherence. In the MIRA trial, adherence measured by pill count appears higher than adherence measured by assay. Agreement between pill count and assay was poor (kappa statistic = 0.25).^ Limitations: Trial and disease are completely confounded and hence the independent effect of disease on adherence to minocycline treatment cannot be studied.^ Conclusion: Simple pill count may be preferred over assay in the minocycline clinical trials to measure adherence. Assays may be less sensitive in a clinical setting where appointments are not scheduled in relation to medication administration time, given assays depend on many pharmacokinetic and instrument-related factors. However, pill count can be manipulated by the patient. Another study suggested that self-report method is more sensitive than pill count method in differentiating adherence from non-adherence. An effect of medication-related adverse events on adherence could not be detected.^

Adaptive clinical trial design for targeted therapy development

The development of targeted therapy involve many challenges. Our study will address some of the key issues involved in biomarker identification and clinical trial design. In our study, we propose two biomarker selection methods, and then apply them in two different clinical trial designs for targeted therapy development. In particular, we propose a Bayesian two-step lasso procedure for biomarker selection in the proportional hazards model in Chapter 2. In the first step of this strategy, we use the Bayesian group lasso to identify the important marker groups, wherein each group contains the main effect of a single marker and its interactions with treatments. In the second step, we zoom in to select each individual marker and the interactions between markers and treatments in order to identify prognostic or predictive markers using the Bayesian adaptive lasso. In Chapter 3, we propose a Bayesian two-stage adaptive design for targeted therapy development while implementing the variable selection method given in Chapter 2. In Chapter 4, we proposed an alternate frequentist adaptive randomization strategy for situations where a large number of biomarkers need to be incorporated in the study design. We also propose a new adaptive randomization rule, which takes into account the variations associated with the point estimates of survival times. In all of our designs, we seek to identify the key markers that are either prognostic or predictive with respect to treatment. We are going to use extensive simulation to evaluate the operating characteristics of our methods.^

Syntaxin 3b is a t-SNARE specific for ribbon synapses of the retina.

Previous studies have demonstrated that ribbon synapses in the retina do not contain the t-SNARE (target-soluble N-ethylmaleimide-sensitive factor attachment protein receptor) syntaxin 1A that is found in conventional synapses of the nervous system. In contrast, ribbon synapses of the retina contain the related isoform syntaxin 3. In addition to its localization in ribbon synapses, syntaxin 3 is also found in nonneuronal cells, where it has been implicated in the trafficking of transport vesicles to the apical plasma membrane of polarized cells. The syntaxin 3 gene codes for four different splice forms, syntaxins 3A, 3B, 3C, and 3D. We demonstrate here by using analysis of EST databases, RT-PCR, in situ hybridization, and Northern blot analysis that cells in the mouse retina express only syntaxin 3B. In contrast, nonneuronal tissues, such as kidney, express only syntaxin 3A. The two major syntaxin isoforms (3A and 3B) have an identical N-terminal domain but differ in the C-terminal half of the SNARE domain and the C-terminal transmembrane domain. These two domains are thought to be directly involved in synaptic vesicle fusion. The interaction of syntaxin 1A and syntaxin 3B with other synaptic proteins was examined. We found that both proteins bind Munc18/N-sec1 with similar affinity. In contrast, syntaxin 3B had a much lower binding affinity for the t-SNARE SNAP25 compared with syntaxin 1A. By using an in vitro fusion assay, we could demonstrate that vesicles containing syntaxin 3B and SNAP25 could fuse with vesicles containing synaptobrevin2/VAMP2, demonstrating that syntaxin 3B can function as a t-SNARE.