37 research outputs found

    An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY challenge

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    Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

    An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

    Get PDF
    There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

    Behavioral Corporate Finance: An Updated Survey

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    Proceedings of the Virtual 3rd UK Implementation Science Research Conference : Virtual conference. 16 and 17 July 2020.

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    Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results

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    Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed six recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Though gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior

    Influenza Vaccine Effectiveness Against Antigenically Drifted Influenza Higher Than Expected in Hospitalized Adults: 2014-2015

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    BACKGROUND: The 2014-2015 influenza season was severe, with circulating influenza A (H3N2) viruses that were antigenically drifted from the vaccine virus. Reported vaccine effectiveness (VE) estimates from ambulatory care settings were markedly decreased. METHODS: Adults, hospitalized at 2 hospitals in southeast Michigan for acute respiratory illnesses, defined by admission diagnoses, of ≤10 days duration were prospectively enrolled. Throat and nasal swab specimens were collected, combined, and tested for influenza by real-time reverse transcription polymerase chain reaction. VE was estimated by comparing the vaccination status of those testing positive for influenza with those testing negative in logistic regression models adjusted for age, sex, hospital, calendar time, time from illness onset to specimen collection, frailty score, and Charlson comorbidity index (CCI). RESULTS: Among 624 patients included in the analysis, 421 (68%) were vaccinated, 337 (54%) were female, 220 (35%) were age ≥65 years, and 92% had CCI \u3e 0, indicating ≥1 comorbid conditions. Ninety-eight (16%) patients tested positive for influenza A (H3N2); among 60 (61%) A (H3N2) viruses tested by pyrosequencing, 53 (88%) belonged to the drifted 3C.2a genetic group. Adjusted VE was 43% (95% confidence interval [CI], 4-67) against influenza A (H3N2); 40% (95% CI, -13 to 68) for those \u3c65 \u3eyears, and 48% (95% CI, -33 to 80) for those ≥65 years. Sensitivity analyses largely supported these estimates. CONCLUSIONS: VE estimates appeared higher than reports from similar studies in ambulatory care settings, suggesting that the 2014-2015 vaccine may have been more effective in preventing severe illness requiring hospitalization
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