37 research outputs found

    Evidence-Based Cognitive Rehabilitation: Systematic Review of the Literature From 2009 Through 2014

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    Objective To conduct an updated, systematic review of the clinical literature, classify studies based on the strength of research design, and derive consensual, evidence-based clinical recommendations for cognitive rehabilitation of people with TBI or stroke. Data Sources Online Pubmed and print journal searches identified citations for 250 articles published from 2009 through 2014. Study Selection 186 articles were selected for inclusion after initial screening. 50 articles were initially excluded (24 healthy, pediatric or other neurologic diagnoses, 10 non-cognitive interventions, 13 descriptive protocols or studies, 3 non-treatment studies). 15 articles were excluded after complete review (1 other neurologic diagnosis, 2 non-treatment studies, 1 qualitative study, 4 descriptive papers, 7 secondary analyses). 121 studies were fully reviewed. Data Extraction Articles were reviewed by CRTF members according to specific criteria for study design and quality, and classified as providing Class I, Class II, or Class III evidence. Articles were assigned to 1 of 6 possible categories (based on interventions for attention, vision and neglect, language and communication skills, memory, executive function, or comprehensive-integrated interventions). Data Synthesis Of 121 studies, 41 were rated as Class I, 3 as Class Ia, 14 as Class II, and 63 as Class III. Recommendations were derived by CRTF consensus from the relative strengths of the evidence, based on the decision rules applied in prior reviews. Conclusions CRTF has now evaluated 491 papers (109 Class I or Ia, 68 Class II, and 314 Class III) and makes 29 recommendations for evidence-based practice of cognitive rehabilitation (9 Practice Standards, 9 Practice Guidelines and 11 Practice Options). Evidence supports Practice Standards for attention deficits after TBI or stroke; visual scanning for neglect after right hemisphere stroke; compensatory strategies for mild memory deficits; language deficits after left hemisphere stroke; social communication deficits after TBI; metacognitive strategy training for deficits in executive functioning; and comprehensive-holistic neuropsychological rehabilitation to reduce cognitive and functional disability after TBI or stroke

    Marijuana use and DNA methylation-based biological age in young adults

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    BACKGROUND: Marijuana is the third most commonly used drug in the USA and efforts to legalize it for medical and recreational use are growing. Despite the increase in use, marijuana\u27s effect on aging remains understudied and understanding the effects of marijuana on molecular aging may provide novel insights into the role of marijuana in the aging process. We therefore sought to investigate the association between cumulative and recent use of marijuana with epigenetic age acceleration (EAA) as estimated from blood DNA methylation. RESULTS: A random subset of participants from The Coronary Artery Risk Development in Young Adults (CARDIA) Study with available whole blood at examination years (Y) 15 and Y20 underwent epigenomic profiling. Four EAA estimates (intrinsic epigenetic age acceleration, extrinsic epigenetic age acceleration, PhenoAge acceleration, and GrimAge acceleration) were calculated from DNA methylation levels measured at Y15 and Y20. Ever use and cumulative marijuana-years were calculated from the baseline visit to Y15 and Y20, and recent marijuana use (both any and number of days of use in the last 30 days) were calculated at Y15 and Y20. Ever use of marijuana and each additional marijuana-year were associated with a 6-month (P \u3c 0.001) and a 2.5-month (P \u3c 0.001) higher average in GrimAge acceleration (GAA) using generalized estimating equations, respectively. Recent use and each additional day of recent use were associated with a 20-month (P \u3c 0.001) and a 1-month (P \u3c 0.001) higher GAA, respectively. A statistical interaction between marijuana-years and alcohol consumption on GAA was observed (P = 0.011), with nondrinkers exhibiting a higher GAA (β = 0.21 [95% CI 0.05, 0.36], P = 0.008) compared to heavy drinkers (β = 0.05 [95% CI - 0.09, 0.18], P = 0.500) per each additional marijuana-year. No associations were observed for the remaining EAA estimates. CONCLUSIONS: These findings suggest cumulative and recent marijuana use are associated with age-related epigenetic changes that are related to lifespan. These observed associations may be modified by alcohol consumption. Given the increase in use and legalization, these findings provide novel insight on the effect of marijuana use on the aging process as captured through blood DNA methylation

    PARP inhibitors and the treatment of breast cancer: beyond BRCA1/2?

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    Poly(ADP-ribose) polymerase (PARP) inhibitors have been explored as therapeutic agents for the treatment of hereditary breast and ovarian cancers harboring mutations in BRCA1 or BRCA2. In a new study, Inbar-Rozensal and colleagues show that phenanthridine-derived PARP inhibitors promote cell cycle arrest and cell death in breast cancer cells lacking BRCA1 and BRCA2 mutations and prevent the growth of tumors from xenografts of these cells in immunocompromised mice. These results suggest a potential broader utility of PARP-1 inhibitors in the treatment of breast cancer, although further mechanistic studies are needed

    The current understanding of precision medicine and personalised medicine in selected research disciplines:study protocol of a systematic concept analysis

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    INTRODUCTION: The terms ‘precision medicine’ and ‘personalised medicine’ have become key terms in health-related research and in science-related public communication. However, the application of these two concepts and their interpretation in various disciplines are heterogeneous, which also affects research translation and public awareness. This leads to confusion regarding the use and distinction of the two concepts. Our aim is to provide a snapshot of the current understanding of these concepts. METHODS AND ANALYSIS: Our study will use Rodgers’ evolutionary concept analysis to systematically examine the current understanding of the concepts ‘precision medicine’ and ‘personalised medicine’ in clinical medicine, biomedicine (incorporating genomics and bioinformatics), health services research, physics, chemistry, engineering, machine learning and artificial intelligence, and to identify their respective attributes (clusters of characteristics) and surrogate and related terms. A systematic search of the literature will be conducted for 2016–2022 using databases relevant to each of these disciplines: ACM Digital Library, CINAHL, Cochrane Library, F1000Research, IEEE Xplore, PubMed/Medline, Science Direct, Scopus and Web of Science. These are among the most representative databases for the included disciplines. We will examine similarities and differences in definitions of ‘precision medicine’ and ‘personalised medicine’ in the respective disciplines and across (sub)disciplines, including attributes of each term. This will enable us to determine how these two concepts are distinguished. ETHICS AND DISSEMINATION: Following ethical and research standards, we will comprehensively report the methodology for a systematic analysis following Rodgers’ concept analysis method. Our systematic concept analysis will contribute to the clarification of the two concepts and distinction in their application in given settings and circumstances. Such a broad concept analysis will contribute to non-systematic syntheses of the concepts, or occasional systematic reviews on one of the concepts that have been published in specific disciplines, in order to facilitate interdisciplinary communication, translational medical research and implementation science

    Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions.

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    BACKGROUND: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745

    Effect of remote ischaemic conditioning on clinical outcomes in patients with acute myocardial infarction (CONDI-2/ERIC-PPCI): a single-blind randomised controlled trial.

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    BACKGROUND: Remote ischaemic conditioning with transient ischaemia and reperfusion applied to the arm has been shown to reduce myocardial infarct size in patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). We investigated whether remote ischaemic conditioning could reduce the incidence of cardiac death and hospitalisation for heart failure at 12 months. METHODS: We did an international investigator-initiated, prospective, single-blind, randomised controlled trial (CONDI-2/ERIC-PPCI) at 33 centres across the UK, Denmark, Spain, and Serbia. Patients (age >18 years) with suspected STEMI and who were eligible for PPCI were randomly allocated (1:1, stratified by centre with a permuted block method) to receive standard treatment (including a sham simulated remote ischaemic conditioning intervention at UK sites only) or remote ischaemic conditioning treatment (intermittent ischaemia and reperfusion applied to the arm through four cycles of 5-min inflation and 5-min deflation of an automated cuff device) before PPCI. Investigators responsible for data collection and outcome assessment were masked to treatment allocation. The primary combined endpoint was cardiac death or hospitalisation for heart failure at 12 months in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT02342522) and is completed. FINDINGS: Between Nov 6, 2013, and March 31, 2018, 5401 patients were randomly allocated to either the control group (n=2701) or the remote ischaemic conditioning group (n=2700). After exclusion of patients upon hospital arrival or loss to follow-up, 2569 patients in the control group and 2546 in the intervention group were included in the intention-to-treat analysis. At 12 months post-PPCI, the Kaplan-Meier-estimated frequencies of cardiac death or hospitalisation for heart failure (the primary endpoint) were 220 (8·6%) patients in the control group and 239 (9·4%) in the remote ischaemic conditioning group (hazard ratio 1·10 [95% CI 0·91-1·32], p=0·32 for intervention versus control). No important unexpected adverse events or side effects of remote ischaemic conditioning were observed. INTERPRETATION: Remote ischaemic conditioning does not improve clinical outcomes (cardiac death or hospitalisation for heart failure) at 12 months in patients with STEMI undergoing PPCI. FUNDING: British Heart Foundation, University College London Hospitals/University College London Biomedical Research Centre, Danish Innovation Foundation, Novo Nordisk Foundation, TrygFonden

    Elevated Risk of Chronic Respiratory Conditions within 60 Days of COVID-19 Hospitalization in Veterans

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    SARS-CoV-2 infection prominently affects the respiratory system, and patients hospitalized with COVID-19 are at an increased risk of developing respiratory conditions. We examined the risk of new respiratory conditions of COVID-19 among hospitalized patients in the national Veterans Health Administration between 15 February 2020 and 16 June 2021. The study cohort included all COVID-19-tested, hospitalized individuals who survived the index admission and did not have any previously diagnosed chronic respiratory conditions (asthma, bronchitis, chronic lung disease, chronic obstructive pulmonary disease (COPD), emphysema, or venous thromboembolism) before SARS-CoV-2 testing. Of 373,048 patients hospitalized after SARS-CoV-2 testing, 18,686 positive and 37,372 negative patients met the inclusion/exclusion criteria and were matched by age, sex, and race using propensity score matching. The results showed that the SARS-CoV-2 positive group had a greater risk of developing asthma (adjusted odds ratio (aOR) = 1.37), bronchitis (aOR = 2.81), chronic lung disease (aOR = 2.14), COPD (aOR = 1.56), emphysema (aOR = 1.52), and venous thromboembolism (aOR = 1.92) within 60 days after the index COVID date of testing. These findings could inform that the clinical care team considers a risk of new respiratory conditions and address these conditions in the post-hospitalization management of the patient, which could potentially lead to reduce the risk of complications and optimize recovery

    Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans

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    The role of smoking in the risk of SARS-CoV-2 infection is unclear. We used a retrospective cohort design to study data from veterans’ Electronic Medical Record to assess the impact of smoking on the risk of SARS-CoV-2 infection. Veterans tested for the SARS-CoV-2 virus from 02/01/2020 to 02/28/2021 were classified as: Never Smokers (NS), Former Smokers (FS), and Current Smokers (CS). We report the adjusted odds ratios (aOR) for potential confounders obtained from a cascade machine learning algorithm. We found a 19.6% positivity rate among 1,176,306 veterans tested for SARS-CoV-2 infection. The positivity proportion among NS (22.0%) was higher compared with FS (19.2%) and CS (11.5%). The adjusted odds of testing positive for CS (aOR:0.51; 95%CI: 0.50, 0.52) and FS (aOR:0.89; 95%CI:0.88, 0.90) were significantly lower compared with NS. Four pre-existing conditions, including dementia, lower respiratory infections, pneumonia, and septic shock, were associated with a higher risk of testing positive, whereas the use of the decongestant drug phenylephrine or having a history of cancer were associated with a lower risk. CS and FS compared with NS had lower risks of testing positive for SARS-CoV-2. These findings highlight our evolving understanding of the role of smoking status on the risk of SARS-CoV-2 infection
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