Citations

ABSTRACT The FilmArray respiratory panel (FARP) reliably and rapidly identifies 17 viruses and 3 bacterial pathogens. A nasopharyngeal swab FARP (NP FARP) is performed for many patients with respiratory symptoms. For patients who are acutely ill or immunocompromised or fail to improve, a bronchoalveolar lavage sample FARP (BAL FARP) is performed in addition to the NP FARP. To date, no studies have compared the yield of a BAL FARP with that of an NP FARP. We retrospectively studied all patients who had a BAL FARP within 7 days after an NP FARP between June 2013 and May 2014. Demographic information, comorbidities, FARP results, and all microbiologic data from BAL fluid were collected. Eighty-six patients had a BAL FARP performed within 7 days (mean, 1.6; median, 1) after an NP FARP. Of these, 66 (77%) had concordant BAL and NP FARP results: 15 (23%) had the same pathogen identified from the NP and BAL FARPs, and 51 (77%) had concordant negative FARP results. In 18 of the 86 patients (21%), a pathogen was detected from the NP FARP; of these, 15 (83%) had a concordant match on a subsequent BAL FARP, and the remaining 3 had negative BAL FARPs. In 17 of the 86 patients (20%), pathogens were identified from the BAL FARPs that were not detected by the NP FARPs; of these, 16 (94%) had initial negative NP FARPs. The data suggest that once a pathogen is identified by an NP FARP, a subsequent BAL FARP is unlikely to add new microbiologic information. However, a BAL FARP may provide new, useful microbiologic information when performed within 7 days after a negative NP FARP.

Background Most patients with atrial fibrillation ( AF ) require rate control; however, the optimal target heart rate remains under debate. We aimed to assess rate control and subsequent outcomes among patients with permanent AF . Methods and Results We studied 2812 US outpatients with permanent AF in the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation. Resting heart rate was measured longitudinally and used as a time‐dependent covariate in multivariable Cox models of all‐cause and cause‐specific mortality during a median follow‐up of 24 months. At baseline, 7.4% (n=207) had resting heart rate <60 beats per minute (bpm), 62% (n=1755) 60 to 79 bpm, 29% (n=817) 80 to 109 bpm, and 1.2% (n=33) ≥110 bpm. Groups did not differ by age, previous cerebrovascular disease, heart failure status, CHA 2 DS 2 ‐ VAS c scores, renal function, or left ventricular function. There were significant differences in race ( P =0.001), sinus node dysfunction ( P =0.004), and treatment with calcium‐channel blockers ( P =0.006) and anticoagulation ( P =0.009). In analyses of continuous heart rates, lower heart rate ≤65 bpm was associated with higher all‐cause mortality (adjusted hazard ratio [ HR ], 1.15 per 5‐bpm decrease; 95% CI , 1.01 to 1.32; P =0.04). Similarly, increasing heart rate >65 bpm was associated with higher all‐cause mortality (adjusted HR , 1.10 per 5‐bpm increase; 95% CI , 1.05 to 1.15; P <0.0001). This relationship was consistent across endpoints and in a broader sensitivity analysis of permanent and nonpermanent AF patients. Conclusions Among patients with permanent AF , there is a J‐shaped relationship between heart rate and mortality. These data support current guideline recommendations, and clinical trials are warranted to determine optimal rate control. Clinical Trial Registration URL : http://clinicaltrials.gov/ . Unique identifier: NCT01165710.

Abstract Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. Cancer Epidemiol Biomarkers Prev; 24(11); 1680–91. ©2015 AACR.

Objective Existing criteria for the classification of gout have suboptimal sensitivity and/or specificity, and were developed at a time when advanced imaging was not available. The current effort was undertaken to develop new classification criteria for gout. Methods An international group of investigators, supported by the American College of Rheumatology and the European League Against Rheumatism, conducted a systematic review of the literature on advanced imaging of gout, a diagnostic study in which the presence of monosodium urate monohydrate (MSU) crystals in synovial fluid or tophus was the gold standard, a ranking exercise of paper patient cases, and a multicriterion decision analysis exercise. These data formed the basis for developing the classification criteria, which were tested in an independent data set. Results The entry criterion for the new classification criteria requires the occurrence of at least 1 episode of peripheral joint or bursal swelling, pain, or tenderness. The presence of MSU crystals in a symptomatic joint/bursa (i.e., synovial fluid) or in a tophus is a sufficient criterion for classification of the subject as having gout, and does not require further scoring. The domains of the new classification criteria include clinical (pattern of joint/bursa involvement, characteristics and time course of symptomatic episodes), laboratory (serum urate, MSU‐negative synovial fluid aspirate), and imaging (double‐contour sign on ultrasound or urate on dual‐energy computed tomography, radiographic gout‐related erosion). The sensitivity and specificity of the criteria are high (92% and 89%, respectively). Conclusion The new classification criteria, developed using a data‐driven and decision analytic approach, have excellent performance characteristics and incorporate current state‐of‐the‐art evidence regarding gout.

AbstractBackground Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

Abstract Background: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. Methods: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). Results: We observed no significant association between genetic variants and prostate cancer survival. Conclusions: Common genetic variants with large impact on prostate cancer survival were not observed in this study. Impact: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes. Cancer Epidemiol Biomarkers Prev; 24(11); 1796–800. ©2015 AACR.