104 research outputs found

    The American Congress of Rehabilitation Medicine Diagnostic Criteria for Mild Traumatic Brain Injury

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    Objective: To develop new diagnostic criteria for mild traumatic brain injury (TBI) that are appropriate for use across the lifespan and in sports, civilian trauma, and military settings. Design: Rapid evidence reviews on 12 clinical questions and Delphi method for expert consensus. Participants: The Mild Traumatic Brain Injury Task Force of the American Congress of Rehabilitation Medicine Brain Injury Special Interest Group convened a Working Group of 17 members and an external interdisciplinary expert panel of 32 clinician-scientists. Public stakeholder feedback was analyzed from 68 individuals and 23 organizations. Results: The first 2 Delphi votes asked the expert panel to rate their agreement with both the diagnostic criteria for mild TBI and the supporting evidence statements. In the first round, 10 of 12 evidence statements reached consensus agreement. Revised evidence statements underwent a second round of expert panel voting, where consensus was achieved for all. For the diagnostic criteria, the final agreement rate, after the third vote, was 90.7%. Public stakeholder feedback was incorporated into the diagnostic criteria revision prior to the third expert panel vote. A terminology question was added to the third round of Delphi voting, where 30 of 32 (93.8%) expert panel members agreed that ‘the diagnostic label ‘concussion’ may be used interchangeably with ‘mild TBI’ when neuroimaging is normal or not clinically indicated.’ Conclusions: New diagnostic criteria for mild TBI were developed through an evidence review and expert consensus process. Having unified diagnostic criteria for mild TBI can improve the quality and consistency of mild TBI research and clinical care.</p

    The American Congress of Rehabilitation Medicine Diagnostic Criteria for Mild Traumatic Brain Injury

    Get PDF
    Objective: To develop new diagnostic criteria for mild traumatic brain injury (TBI) that are appropriate for use across the lifespan and in sports, civilian trauma, and military settings. Design: Rapid evidence reviews on 12 clinical questions and Delphi method for expert consensus. Participants: The Mild Traumatic Brain Injury Task Force of the American Congress of Rehabilitation Medicine Brain Injury Special Interest Group convened a Working Group of 17 members and an external interdisciplinary expert panel of 32 clinician-scientists. Public stakeholder feedback was analyzed from 68 individuals and 23 organizations. Results: The first 2 Delphi votes asked the expert panel to rate their agreement with both the diagnostic criteria for mild TBI and the supporting evidence statements. In the first round, 10 of 12 evidence statements reached consensus agreement. Revised evidence statements underwent a second round of expert panel voting, where consensus was achieved for all. For the diagnostic criteria, the final agreement rate, after the third vote, was 90.7%. Public stakeholder feedback was incorporated into the diagnostic criteria revision prior to the third expert panel vote. A terminology question was added to the third round of Delphi voting, where 30 of 32 (93.8%) expert panel members agreed that ‘the diagnostic label ‘concussion’ may be used interchangeably with ‘mild TBI’ when neuroimaging is normal or not clinically indicated.’ Conclusions: New diagnostic criteria for mild TBI were developed through an evidence review and expert consensus process. Having unified diagnostic criteria for mild TBI can improve the quality and consistency of mild TBI research and clinical care.</p

    The American Congress of Rehabilitation Medicine Diagnostic Criteria for Mild Traumatic Brain Injury

    Get PDF
    Objective: To develop new diagnostic criteria for mild traumatic brain injury (TBI) that are appropriate for use across the lifespan and in sports, civilian trauma, and military settings. Design: Rapid evidence reviews on 12 clinical questions and Delphi method for expert consensus. Participants: The Mild Traumatic Brain Injury Task Force of the American Congress of Rehabilitation Medicine Brain Injury Special Interest Group convened a Working Group of 17 members and an external interdisciplinary expert panel of 32 clinician-scientists. Public stakeholder feedback was analyzed from 68 individuals and 23 organizations. Results: The first 2 Delphi votes asked the expert panel to rate their agreement with both the diagnostic criteria for mild TBI and the supporting evidence statements. In the first round, 10 of 12 evidence statements reached consensus agreement. Revised evidence statements underwent a second round of expert panel voting, where consensus was achieved for all. For the diagnostic criteria, the final agreement rate, after the third vote, was 90.7%. Public stakeholder feedback was incorporated into the diagnostic criteria revision prior to the third expert panel vote. A terminology question was added to the third round of Delphi voting, where 30 of 32 (93.8%) expert panel members agreed that ‘the diagnostic label ‘concussion’ may be used interchangeably with ‘mild TBI’ when neuroimaging is normal or not clinically indicated.’ Conclusions: New diagnostic criteria for mild TBI were developed through an evidence review and expert consensus process. Having unified diagnostic criteria for mild TBI can improve the quality and consistency of mild TBI research and clinical care.</p

    Indoor and outdoor particles in an air-conditioned building during and after the 2013 haze in Singapore

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    Particles released from biomass burning can contribute to severe air pollution. We monitored indoor and outdoor particles in a mechanically ventilated and air-conditioned building during and after the 2013 haze event in Singapore. Continuous monitoring of time-and size-resolved particles in the diameter range 0.01-10 μm was conducted for two weeks in each sampling campaign. During the haze event, the averaged size-resolved outdoor particle volume concentrations (dV/d(logDp)) for diameters larger than 0.3 μm were considerably higher than those during the post-haze days (9-185 μm3 cm-3 versus 1-35 μm3 cm-3). However, the average number concentration of particles with diameters in the range 10-200 nm was substantially lower on the hazy days than on the post-haze days (11,400 to 14,300 particles cm-3 for hazy days, versus an average of 23,700 particles cm-3 on post-haze days). The building mechanical ventilation system, equipped with MERV 7 filters, attenuated the penetration and persistence of outdoor particles into the monitored building. Indoor particle concentrations, in the diameter ranges 0.3-1.0 μm and 1.0-2.5 μm, closely tracked the corresponding patterns of outdoor particle concentrations. For particles in the size range 0.01-1.0 μm, the size-resolved mean indoor/outdoor (I/O) ratios were in the range 0.12-0.65 with the highest mean I/O ratio at 0.3 μm (0.59 in AC on mode and 0.64 in AC off mode). The air conditioning and mechanical ventilation system with MERV 7 filters provided low single-pass removal efficiency (less than ~ 30%) for particles with diameters of 0.01-1.0 μm. During the haze, for particles larger than ~0.2 μm, lower I/O ratios and higher removal efficiencies occurred with the air conditioning operating as compared to with mechanical ventilation only. This observation suggests the possibility of particle loss to air conditioning system surfaces, possibly enhanced by thermophoretic or diffusiophoretic effects

    Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

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    Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders 1 . They are heritable 2,3 and etiologically related 4,5 behaviors that have been resistant to gene discovery efforts 6–11 . In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures

    Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses

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    Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.</p

    Municipal Corporations, Homeowners, and the Benefit View of the Property Tax

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    Genetic mechanisms of critical illness in COVID-19.

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    Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

    Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

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    We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57
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