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To characterize emergency department sedation practices in mechanically ventilated patients, and test the hypothesis that deep sedation in the emergency department is associated with worse outcomes.Multicenter, prospective cohort study.The emergency department and ICUs of 15 medical centers.Mechanically ventilated adult emergency department patients.None.All data involving sedation (medications, monitoring) were recorded. Deep sedation was defined as Richmond Agitation-Sedation Scale of -3 to -5 or Sedation-Agitation Scale of 2 or 1. A total of 324 patients were studied. Emergency department deep sedation was observed in 171 patients (52.8%), and was associated with a higher frequency of deep sedation in the ICU on day 1 (53.8% vs 20.3%; p0.001) and day 2 (33.3% vs 16.9%; p = 0.001), when compared to light sedation. Mean (SD) ventilator-free days were 18.1 (10.8) in the emergency department deep sedation group compared to 20.0 (9.8) in the light sedation group (mean difference, 1.9; 95% CI, -0.40 to 4.13). Similar results according to emergency department sedation depth existed for ICU-free days (mean difference, 1.6; 95% CI, -0.54 to 3.83) and hospital-free days (mean difference, 2.3; 95% CI, 0.26-4.32). Mortality was 21.1% in the deep sedation group and 17.0% in the light sedation group (between-group difference, 4.1%; odds ratio, 1.30; 0.74-2.28). The occurrence rate of acute brain dysfunction (delirium and coma) was 68.4% in the deep sedation group and 55.6% in the light sedation group (between-group difference, 12.8%; odds ratio, 1.73; 1.10-2.73).Early deep sedation in the emergency department is common, carries over into the ICU, and may be associated with worse outcomes. Sedation practice in the emergency department and its association with clinical outcomes is in need of further investigation.

Gene expression is a critical process in biological system that is influenced and modulated by many factors including genetic variation. Expression Quantitative Trait Loci (eQTL) analysis provides a powerful way to understand how genetic variants affect gene expression. For genome wide eQTL analysis, the number of genetic variants and that of genes are large and thus the search space is tremendous. Therefore, eQTL analysis brings about computational and statistical challenges. In this paper, we provide a comprehensive review of recent advances in methods for eQTL analysis in population-based studies. We first present traditional pairwise association methods, which are widely used in human genetics. To account for expression heterogeneity, we investigate the methods for correcting confounding factors. Next, we discuss newly developed statistical learning methods including Lasso-based models. In the conclusion, we provide an overview of future method development in analyzing eQTL associations. Although we focus on human genetics in this review, the methods are applicable to many other organisms.

Objectives While the Affordable Care Act seeks to reduce emergency department (ED) visits for outpatient-treatable conditions, it remains unclear whether Medicaid patients or the uninsured have adequate access to follow-up care. The goal of this study was to determine the availability of follow-up orthopedic care by insurance status. Methods Using simulated patient methodology, all 102 eligible general orthopedic practices in Dallas-Fort Worth, Texas, were contacted twice by a caller requesting follow-up for an ankle fracture diagnosed in a local ED using a standardized script that differed by insurance status. Practices were randomly assigned to paired private and uninsured or Medicaid and uninsured scenarios. Results We completed 204 calls: 59 private, 43 Medicaid, and 102 uninsured. Appointment success rate was 83.1% for privately insured (95% confidence interval [CI] = 73.2% to 92.9%), 81.4% for uninsured (95% CI = 73.7% to 89.1%), and 14.0% for Medicaid callers (95% CI = 3.2% to 24.7%). Controlling for paired calls to the same practice, an uninsured caller had 5.7 times higher odds (95% CI = 2.74 to 11.71) of receiving an appointment than a Medicaid caller (p

Over time, HCV therapy with pegylated interferon and ribavirin has evolved from a fixed duration strategy to one of response guided therapy and this has enabled us to optimize treatment duration. With the evolution of protease inhibitor based therapy, the paradigm of response guided therapy has further helped in decreasing treatment duration in greater number of patients and which then translates into shorter duration of adverse events. However, several population groups have done better with extended duration therapy as opposed to response guided therapy despite early viral clearance. These include the Black population, and those with cirrhosis, decreased interferon sensitivity, and unfavorable IL28B genotypes. The proper identification of those who might benefit from extended duration HCV therapy will undoubtedly lead to optimal care and outcomes.

Renal dysfunction prior to liver transplantation has a marked impact on post-transplant kidney outcomes. Aim The aim of this study was to assess post-transplant renal function in patients with chronic kidney disease (CKD) receiving orthotopic liver transplantation (OLT) alone. Methods Retrospective review of 40 OLT recipients with pre-transplant CKD (serum creatinine ≥2 mg/dL for at least three months) at the University of Pennsylvania from February 2002 to July 2010. Primary outcome was estimated glomerular filtration rate (eGFR) up to three years post-transplant. Secondary outcomes included incidence of stage 4 CKD (eGFR

The COllaborative Proximity ImmunoAssay (COPIA) is a multiplexed protein microarray platform that utilizes the formation of a unique immuno-complex requiring co-localization of two detector-antibodies. The detector-antibodies are conjugated with corresponding channeling-enzymes, glucose oxidase (GO) and horseradish peroxidase (HRP). Once target proteins are bound by the capture antibodies, the channeling events between GO and HRP in proximity enables the profiling of the target proteins with extreme sensitivity. COPIA delivers extremely high analytical specificity as it requires multiple entities within target specific proximity for the signal generation/amplification. COPIA can also be configured for each specific target protein to allow differential detection of truncated targets (i.e., p95HER2) from their normal counter parts (i.e., full length-HER2). We applied COPIA to investigate the levels of expression and activation of HER1, HER2, p95HER2, HER3, IGF1-R, c-MET, PI3K, Shc, VEGFR, panCK, and other targets in signal transduction pathways. Here, we report the functional pathway signatures for multiple proteins in 250 frozen tissues obtained from BCA patients with various primary histology and from 50 fine needle aspirate (FNA) samples collected from metastatic sites (mFNA) in advanced BCA patients with various ER/PR/HER2 status. There was a high concordance between primary HER2-IHC status and COPIA-HER2 expression analysis. Significant levels of p95HER2 were observed in over 40% of HER2-positive (HER2: 3+ and 2+ with FISH+) patients, and low but detectable levels in some sample tissues with IHC-HER2 negative (2+ with FISH - / 1+ /0) were also observed. Over 50% of p95HER2-expressors had activated p95HER2, and over 25% of HER2-positive samples also had HER1, HER3, IGF1-R and other RTKs and transduction protein expression and/or activation. As the disease profile often shifts in recurrent breast cancer, our unique assay format can be utilized to provide valuable clinical information on limited samples obtained from evolving disease to help oncologists adjust their disease treatment options for each patient according to their ‘personal’ cancer profile-shift. Having the ability to profile tumors at different metastatic sites with an expanded pathway panel could provide information on their differential metastatic potentials; hence minimally invasive single-passage-mFNA samples may be utilized to tailor therapy options accordingly. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3179.