Association between adherence to calcium-channel blocker and statin medications and likelihood of cardiovascular events among US managed care enrollees

<p>Abstract</p> <p>Background</p> <p>Prior studies have found that patients taking single-pill amlodipine/atorvastatin (SPAA) have greater likelihood of adherence at 6 months than those taking 2-pill calcium-channel blocker and statin combinations (CCB/statin). This study examines whether this adherence benefit results in fewer cardiovascular (CV) events.</p> <p>Methods</p> <p>A retrospective cohort study was conducted using administrative claims data from the IMS LifeLink: US Health Plan Claims database, identifying adults already taking CCB or statin (but not both) who had an index event of either initiating treatment with SPAA or adding CCB to statin (or vice versa) between April 1, 2004 to August 31, 2005. Inclusion criteria included age 18+ years, continuously enrolled for minimum of 6 months prior and 18 months following treatment initiation, >1 diagnosis of hypertension, and no prescription claims for SPAA or added CCB or statin for 6 months prior. Exclusion criteria included >1 claim with missing or invalid days supplied, age 65+ years and not enrolled in Medicare Advantage, or history of prior CV events, cancer diagnosis, or chronic renal failure. The primary outcome measure was the rate of CV events (myocardial infarction, heart failure, angina, other ischemic heart disease, stroke, peripheral vascular disease, or revascularization procedure) from 6 to 18 months following index date, analyzed at three levels: 1) all adherent vs. non-adherent patients, 2) SPAA vs. dual-pill patients (regardless of adherence level), and 3) adherent SPAA, adherent dual-pill, and non-adherent SPAA patients vs. non-adherent dual-pill patients.</p> <p>Results</p> <p>Of 1,537 SPAA patients, 56.5% were adherent at 6 months, compared with 21.4% of the 17,910 CCB/statin patients (p < 0.001). Logistic regression found SPAA patients more likely to be adherent (OR = 4.7, p < 0.001) than CCB/statin patients. In Cox proportional hazards models, being adherent to either regimen was associated with significantly lower risk of CV event (HR = 0.77, p = 0.003). A similar effect was seen for SPAA vs. CCB/statin patients (HR = 0.68, p = 0.02). In a combined model, the risk of CV events was significantly lower for adherent CCB/statin patients (HR = 0.79, p = 0.01) and adherent SPAA patients (HR = 0.61, p = 0.03) compared to non-adherent CCB/statin patients.</p> <p>Conclusions</p> <p>Patients receiving SPAA rather than a 2-pill CCB/statin regimen are more likely to be adherent. In turn, adherence to CCB and statin medications is associated with lower risk of CV events in primary prevention patients.</p

Adherence to cardioprotective medications and mortality among patients with diabetes and ischemic heart disease

BACKGROUND: Patients with diabetes and ischemic heart disease (IHD) are at high risk for adverse cardiac outcomes. Clinical practice guidelines recommend multiple cardioprotective medications to reduce recurrent events. We evaluated the association between cardioprotective medication adherence and mortality among patients with diabetes and IHD. METHODS: In a retrospective cohort study of 3,998 patients with diabetes and IHD, we evaluated use of ACE inhibitors or angiotensin receptor blockers, β-blockers, and statin medications. Receipt of cardioprotective medications was based on filled prescriptions. Medication adherence was calculated as the proportion of days covered (PDC) for filled prescriptions. The primary outcome of interest was all-cause mortality. RESULTS: The majority of patients (92.8%) received at least 1 cardioprotective medication. Patients receiving any medications had lower unadjusted mortality rates compared to patients not receiving any medications (7.9% vs. 11.5%; p = 0.03). In multivariable analysis, receipt of any cardioprotective medication remained associated with lower all-cause mortality (OR 0.65; 95% CI 0.43–0.99). Among patients receiving cardioprotective medications, the majority (80.3%) were adherent (PDC ≥ 0.80). Adherent patients had lower unadjusted mortality rates (6.7% vs. 12.1%; p < 0.01). In multivariable analysis, medication adherence remained associated with lower all-cause mortality (OR 0.52; 95% CI 0.39–0.69) compared to non-adherence. In contrast, there was no mortality difference between patients receiving cardioprotective medications who were non-adherent compared to patients not receiving any medications (OR 1.01; 95% CI 0.64–1.61). CONCLUSION: In conclusion, medication adherence is associated with improved outcomes among patients with diabetes and IHD. Quality improvement interventions are needed to increase medication adherence in order for patients to maximize the benefit of cardioprotective medications

Molecular Evolution of Aminoacyl tRNA Synthetase Proteins in the Early History of Life

Aminoacyl-tRNA synthetases (aaRS) consist of several families of functionally conserved proteins essential for translation and protein synthesis. Like nearly all components of the translation machinery, most aaRS families are universally distributed across cellular life, being inherited from the time of the Last Universal Common Ancestor (LUCA). However, unlike the rest of the translation machinery, aaRS have undergone numerous ancient horizontal gene transfers, with several independent events detected between domains, and some possibly involving lineages diverging before the time of LUCA. These transfers reveal the complexity of molecular evolution at this early time, and the chimeric nature of genomes within cells that gave rise to the major domains. Additionally, given the role of these protein families in defining the amino acids used for protein synthesis, sequence reconstruction of their pre-LUCA ancestors can reveal the evolutionary processes at work in the origin of the genetic code. In particular, sequence reconstructions of the paralog ancestors of isoleucyl- and valyl- RS provide strong empirical evidence that at least for this divergence, the genetic code did not co-evolve with the aaRSs; rather, both amino acids were already part of the genetic code before their cognate aaRSs diverged from their common ancestor. The implications of this observation for the early evolution of RNA-directed protein biosynthesis are discussed.National Science Foundation (U.S.) (Grant DEB 0830024)National Science Foundation (U.S.) (Grant DEB 0936234)United States. National Aeronautics and Space Administration (NASA Postdoctoral Fellowship

DMSO and Betaine Greatly Improve Amplification of GC-Rich Constructs in De Novo Synthesis

In Synthetic Biology, de novo synthesis of GC-rich constructs poses a major challenge because of secondary structure formation and mispriming. While there are many web-based tools for codon optimizing difficult regions, no method currently exists that allows for potentially phenotypically important sequence conservation. Therefore, to overcome these limitations in researching GC-rich genes and their non-coding elements, we explored the use of DMSO and betaine in two conventional methods of assembly and amplification. For this study, we compared the polymerase (PCA) and ligase-based (LCR) methods for construction of two GC-rich gene fragments implicated in tumorigenesis, IGF2R and BRAF. Though we found no benefit in employing either DMSO or betaine during the assembly steps, both additives greatly improved target product specificity and yield during PCR amplification. Of the methods tested, LCR assembly proved far superior to PCA, generating a much more stable template to amplify from. We further report that DMSO and betaine are highly compatible with all other reaction components of gene synthesis and do not require any additional protocol modifications. Furthermore, we believe either additive will allow for the production of a wide variety of GC-rich gene constructs without the need for expensive and time-consuming sample extraction and purification prior to downstream application

Flexible mapping of homology onto structure with Homolmapper

<p>Abstract</p> <p>Background</p> <p>Over the past decade, a number of tools have emerged for the examination of homology relationships among protein sequences in a structural context. Most recent software implementations for such analysis are tied to specific molecular viewing programs, which can be problematic for collaborations involving multiple viewing environments. Incorporation into larger packages also adds complications for users interested in adding their own scoring schemes or in analyzing proteins incorporating unusual amino acid residues such as selenocysteine.</p> <p>Results</p> <p>We describe homolmapper, a command-line application for mapping information from a multiple protein sequence alignment onto a protein structure for analysis in the viewing software of the user's choice. Homolmapper is small (under 250 K for the application itself) and is written in Python to ensure portability. It is released for non-commercial use under a modified University of California BSD license. Homolmapper permits facile import of additional scoring schemes and can incorporate arbitrary additional amino acids to allow handling of residues such as selenocysteine or pyrrolysine. Homolmapper also provides tools for defining and analyzing subfamilies relative to a larger alignment, for mutual information analysis, and for rapidly visualizing the locations of mutations and multi-residue motifs.</p> <p>Conclusion</p> <p>Homolmapper is a useful tool for analysis of homology relationships among proteins in a structural context. There is also extensive, example-driven documentation available. More information about homolmapper is available at <url>http://www.mcb.ucdavis.edu/faculty-labs/lagarias/homolmapper_home/homolmapper%20web%20page.htm</url>.</p

Quality Measures for the Diagnosis and Non-Operative Management of Carpal Tunnel Syndrome in Occupational Settings

Introduction: Providing higher quality medical care to workers with occupationally associated carpal tunnel syndrome (CTS) may reduce disability, facilitate return to work, and lower the associated costs. Although many workers’ compensation systems have adopted treatment guidelines to reduce the overuse of unnecessary care, limited attention has been paid to ensuring that the care workers do receive is high quality. Further, guidelines are not designed to enable objective assessments of quality of care. This study sought to develop quality measures for the diagnostic evaluation and non-operative management of CTS, including managing occupational activities and functional limitations. Methods: Using a variation of the well-established RAND/UCLA Appropriateness Method, we developed draft quality measures using guidelines and literature reviews. Next, in a two-round modified-Delphi process, a multidisciplinary panel of 11 U.S. experts in CTS rated the measures on validity and feasibility. Results: Of 40 draft measures, experts rated 31 (78%) valid and feasible. Nine measures pertained to diagnostic evaluation, such as assessing symptoms, signs, and risk factors. Eleven pertain to non-operative treatments, such as the use of splints, steroid injections, and medications. Eleven others address assessing the association between symptoms and work, managing occupational activities, and accommodating functional limitations. Conclusions: These measures will complement existing treatment guidelines by enabling providers, payers, policymakers, and researchers to assess quality of care for CTS in an objective, structured manner. Given the characteristics of previous measures developed with these methods, greater adherence to these measures will probably lead to improved patient outcomes at a population level

Capturing judgement strategies in risk assessments with improved quality of clinical information: How nurses' strategies differ from the ecological model

Background: Nurses' risk assessments of patients at risk of deterioration are sometimes suboptimal. Advances in clinical simulation mean higher quality information can be used as an alternative to traditional paper-based approaches as a means of improving judgement. This paper tests the hypothesis that nurses' judgement strategies and policies change as the quality of information used by nurses in simulation changes. Methods: Sixty-three student nurses and 34 experienced viewed 25 paper-case based and 25 clinically simulated scenarios, derived from real cases, and judged whether the (simulated) patient was at 'risk' of acute deterioration. Criteria of judgement "correctness" came from the same real cases. Information relative weights were calculated to examine judgement policies of individual nurses. Group comparisons of nurses and students under both paper and clinical simulation conditions were undertaken using non parametric statistical tests. Judgment policies were also compared to the ecological statistical model. Cumulative relative weights were calculated to assess how much information nurses used when making judgements. Receiver operating characteristic (ROC) curves were generated to examine predictive accuracy amongst the nurses. Results: There were significant variations between nurses' judgement policies and those optimal policies determined by the ecological model. Nurses significantly underused the cues of consciousness level, respiration rate, and systolic blood pressure than the ecological model requires. However, in clinical simulations, they tended to make appropriate use of heart rate, with non-significant difference in the relative weights of heart rate between clinical simulations and the ecological model. Experienced nurses paid substantially more attention to respiration rate in the simulated setting compared to paper cases, while students maintained a similar attentive level to this cue. This led to a non-significant difference in relative weights of respiration rate between experienced nurses and students. Conclusions: Improving the quality of information by clinical simulations significantly impacted on nurses' judgement policies of risk assessments. Nurses' judgement strategies also varied with the increased years of experience. Such variations in processing clinical information may contribute to nurses' suboptimal judgements in clinical practice. Constructing predictive models of common judgement situations, and increasing nurses' awareness of information weightings in such models may help improve judgements made by nurses