74 research outputs found

    Enablers and Barriers to Implementing ICU Follow-Up Clinics and Peer Support Groups Following Critical Illness: The Thrive Collaboratives

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    OBJECTIVES: Data are lacking regarding implementation of novel strategies such as follow-up clinics and peer support groups, to reduce the burden of postintensive care syndrome. We sought to discover enablers that helped hospital-based clinicians establish post-ICU clinics and peer support programs, and identify barriers that challenged them. DESIGN: Qualitative inquiry. The Consolidated Framework for Implementation Research was used to organize and analyze data. SETTING: Two learning collaboratives (ICU follow-up clinics and peer support groups), representing 21 sites, across three continents. SUBJECTS: Clinicians from 21 sites. MEASUREMENT AND MAIN RESULTS: Ten enablers and nine barriers to implementation of "ICU follow-up clinics" were described. A key enabler to generate support for clinics was providing insight into the human experience of survivorship, to obtain interest from hospital administrators. Significant barriers included patient and family lack of access to clinics and clinic funding. Nine enablers and five barriers to the implementation of "peer support groups" were identified. Key enablers included developing infrastructure to support successful operationalization of this complex intervention, flexibility about when peer support should be offered, belonging to the international learning collaborative. Significant barriers related to limited attendance by patients and families due to challenges in creating awareness, and uncertainty about who might be appropriate to attend and target in advertising. CONCLUSIONS: Several enablers and barriers to implementing ICU follow-up clinics and peer support groups should be taken into account and leveraged to improve ICU recovery. Among the most important enablers are motivated clinician leaders who persist to find a path forward despite obstacles

    Key mechanisms by which post-ICU activities can improve in-ICU care: results of the international THRIVE collaboratives

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    Objective: To identify the key mechanisms that clinicians perceive improve care in the intensive care unit (ICU), as a result of their involvement in post-ICU programs. Methods: Qualitative inquiry via focus groups and interviews with members of the Society of Critical Care Medicine’s THRIVE collaborative sites (follow-up clinics and peer support). Framework analysis was used to synthesize and interpret the data. Results: Five key mechanisms were identified as drivers of improvement back into the ICU: (1) identifying otherwise unseen targets for ICU quality improvement or education programs—new ideas for quality improvement were generated and greater attention paid to detail in clinical care. (2) Creating a new role for survivors in the ICU—former patients and family members adopted an advocacy or peer volunteer role. (3) Inviting critical care providers to the post-ICU program to educate, sensitize, and motivate them—clinician peers and trainees were invited to attend as a helpful learning strategy to gain insights into post-ICU care requirements. (4) Changing clinician’s own understanding of patient experience—there appeared to be a direct individual benefit from working in post-ICU programs. (5) Improving morale and meaningfulness of ICU work—this was achieved by closing the feedback loop to ICU clinicians regarding patient and family outcomes. Conclusions: The follow-up of patients and families in post-ICU care settings is perceived to improve care within the ICU via five key mechanisms. Further research is required in this novel area

    AAPT Diagnostic Criteria for Chronic Cancer Pain Conditions

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    Chronic cancer pain is a serious complication of malignancy or its treatment. Currently, no comprehensive, universally accepted cancer pain classification system exists. Clarity in classification of common cancer pain syndromes would improve clinical assessment and management. Moreover, an evidence-based taxonomy would enhance cancer pain research efforts by providing consistent diagnostic criteria, ensuring comparability across clinical trials. As part of a collaborative effort between the Analgesic, Anesthetic, and Addiction Clinical Trial Translations Innovations Opportunities and Networks (ACTTION) and the American Pain Society (APS), the ACTTION-APS Pain Taxonomy (AAPT) initiative worked to develop the characteristics of an optimal diagnostic system.59, 65 Following the establishment of these characteristics, a working group consisting of clinicians and clinical and basic scientists with expertise in cancer and cancer-related pain was convened to generate core diagnostic criteria for an illustrative sample of 3 chronic pain syndromes associated with cancer (i.e., bone pain and pancreatic cancer pain as models of pain related to a tumor) or its treatment (i.e., chemotherapy-induced peripheral neuropathy). A systematic review and synthesis was conducted to provide evidence for the dimensions that comprise this cancer pain taxonomy. Future efforts will subject these diagnostic categories and criteria to systematic empirical evaluation of their feasibility, reliability and validity and extension to other cancer-related pain syndromes

    The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

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    Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention

    Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

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    Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene-trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits

    The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

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    Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention

    Refining Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Genetic Loci by Integrating Summary Data From Genome-wide Association, Gene Expression, and DNA Methylation Studies

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    Background: Recent genome-wide association studies (GWASs) identified the first genetic loci associated with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The next step is to use these results to increase our understanding of the biological mechanisms involved. Most of the identified variants likely influence gene regulation. The aim of the current study is to shed light on the mechanisms underlying the genetic signals and prioritize genes by integrating GWAS results with gene expression and DNA methylation (DNAm) levels. Methods: We applied summary-data–based Mendelian randomization to integrate ADHD and ASD GWAS data with fetal brain expression and methylation quantitative trait loci, given the early onset of these disorders. We also analyzed expression and methylation quantitative trait loci datasets of adult brain and blood, as these provide increased statistical power. We subsequently used summary-data–based Mendelian randomization to investigate if the same variant influences both DNAm and gene expression levels. Results: We identified multiple gene expression and DNAm levels in fetal brain at chromosomes 1 and 17 that were associated with ADHD and ASD, respectively, through pleiotropy at shared genetic variants. The analyses in brain and blood showed additional associated gene expression and DNAm levels at the same and additional loci, likely because of increased statistical power. Several of the associated genes have not been identified in ADHD and ASD GWASs before. Conclusions: Our findings identified the genetic variants associated with ADHD and ASD that likely act through gene regulation. This facilitates prioritization of candidate genes for functional follow-up studies

    Genome-wide associations for birth weight and correlations with adult disease

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    Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P\textit{P}  < 5 × 108^{-8}). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (R\textit{R}g_{g} = -0.22, P\textit{P}  = 5.5 × 1013^{-13}), T2D (R\textit{R}g_{g} = -0.27, P\textit{P}  = 1.1 × 106^{-6}) and coronary artery disease (R\textit{R}g_{g} = -0.30, P\textit{P}  = 6.5 × 109^{-9}). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P\textit{P} = 1.9 × 104^{-4}). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.For a full list of the funders pelase visit the publisher's website and look at the supplemetary material provided. Some of the funders are: British Heart Foundation, Cancer Research UK, Medical Research Council, National Institutes of Health, Royal Society and Wellcome Trust
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