191 research outputs found

    Impact of opioid substitution therapy on antiretroviral therapy outcomes:a systematic review and meta-analysis

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    BACKGROUND: Human immunodeficiency virus (HIV)-infected people who inject drugs (PWID) frequently encounter barriers accessing and remaining on antiretroviral therapy (ART). Some studies have suggested that opioid substitution therapy (OST) could facilitate PWID's engagement with HIV services. We conducted a systematic review and meta-analysis to evaluate the impact of concurrent OST use on ART-related outcomes among HIV-infected PWID. METHODS: We searched Medline, PsycInfo, Embase, Global Health, Cochrane, Web of Science, and Social Policy and Practice databases for studies between 1996 to November 2014 documenting the impact of OST, compared to no OST, on ART outcomes. Outcomes considered were coverage and recruitment onto ART, adherence, viral suppression, attrition from ART, and mortality. Meta-analyses were conducted using random-effects modeling, and heterogeneity assessed using Cochran Q test and I2 statistic. RESULTS: We identified 4685 articles, and 32 studies conducted in North America, Europe, Indonesia, and China were included. OST was associated with a 69% increase in recruitment onto ART (hazard ratio [HR], 1.69; 95% confidence interval [CI], 1.32-2.15), a 54% increase in ART coverage (odds ratio [OR], 1.54; 95% CI, 1.17-2.03), a 2-fold increase in adherence (OR, 2.14; 95% CI, 1.41-3.26), and a 23% decrease in the odds of attrition (OR, 0.77; 95% CI, .63-.95). OST was associated with a 45% increase in odds of viral suppression (OR, 1.45; 95% CI, 1.21-1.73), but there was limited evidence from 6 studies for OST decreasing mortality for PWID on ART (HR, 0.91; 95% CI, .65-1.25). CONCLUSIONS: These findings support the use of OST, and its integration with HIV services, to improve the HIV treatment and care continuum among HIV-infected PWID

    Measuring the costs of outreach motivational interviewing for smoking cessation and relapse prevention among low-income pregnant women

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    <p>Abstract</p> <p>Background</p> <p>Economic theory provides the philosophical foundation for valuing costs in judging medical and public health interventions. When evaluating smoking cessation interventions, accurate data on costs are essential for understanding resource consumption. Smoking cessation interventions, for which prior data on resource costs are typically not available, present special challenges. We develop a micro-costing methodology for estimating the real resource costs of outreach motivational interviewing (MI) for smoking cessation and relapse prevention among low-income pregnant women and report results from a randomized controlled trial (RCT) employing the methodology. Methodological standards in cost analysis are necessary for comparison and uniformity in analysis across interventions. Estimating the costs of outreach programs is critical for understanding the economics of reaching underserved and hard-to-reach populations.</p> <p>Methods</p> <p>Randomized controlled trial (1997-2000) collecting primary cost data for intervention. A sample of 302 low-income pregnant women was recruited from multiple obstetrical sites in the Boston metropolitan area. MI delivered by outreach health nurses vs. usual care (UC), with economic costs as the main outcome measures.</p> <p>Results</p> <p>The total cost of the MI intervention for 156 participants was 48,672or48,672 or 312 per participant. The total cost of 311.8perparticipantfortheMIinterventioncomparedwithacostof311.8 per participant for the MI intervention compared with a cost of 4.82 per participant for usual care, a difference of 307([CI],307 ([CI], 289.2 to 322.8).ThetotalfixedcostsoftheMIwere322.8). The total fixed costs of the MI were 3,930 and the total variable costs of the MI were $44,710. The total expected program costs for delivering MI to 500 participants would be 147,430, assuming no economies of scale in program delivery. The main cost components of outreach MI were intervention delivery, travel time, scheduling, and training.</p> <p>Conclusion</p> <p>Grounded in economic theory, this methodology systematically identifies and measures resource utilization, using a process tracking system and calculates both component-specific and total costs of outreach MI. The methodology could help improve collection of accurate data on costs and estimates of the real resource costs of interventions alongside clinical trials and improve the validity and reliability of estimates of resource costs for interventions targeted at underserved and hard-to-reach populations.</p

    Development of a peer support intervention to encourage dietary behaviour change towards a Mediterranean diet in adults at high cardiovascular risk.

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    BACKGROUND: Mediterranean diet (MD) interventions are demonstrated to significantly reduce cardiovascular disease (CVD) risk but are typically resource intensive and delivered by health professionals. There is considerable interest to develop interventions that target sustained dietary behaviour change and that are feasible to scale-up for wider public health benefit. The aim of this paper is to describe the process used to develop a peer support intervention to encourage dietary behaviour change towards a MD in non-Mediterranean adults at high CVD risk. METHODS: The Medical Research Council (MRC) and Behaviour Change Wheel (BCW) frameworks and the COM-B (Capability, Opportunity, Motivation, Behaviour) theoretical model were used to guide the intervention development process. We used a combination of evidence synthesis and qualitative research with the target population, health professionals, and community health personnel to develop the intervention over three main stages: (1) we identified the evidence base and selected dietary behaviours that needed to change, (2) we developed a theoretical basis for how the intervention might encourage behaviour change towards a MD and selected intervention functions that could drive the desired MD behaviour change, and (3) we defined the intervention content and modelled outcomes. RESULTS: A theory-based, culturally tailored, peer support intervention was developed to specifically target behaviour change towards a MD in the target population. The intervention was a group-based program delivered by trained peer volunteers over 12-months, and incorporated strategies to enhance social support, self-efficacy, problem-solving, knowledge, and attitudes to address identified barriers to adopting a MD from the COM-B analysis. CONCLUSIONS: The MRC and BCW frameworks provided a systematic and complementary process for development of a theory-based peer support intervention to encourage dietary behaviour change towards a MD in non-Mediterranean adults at high CVD risk. The next step is to evaluate feasibility, acceptability, and diet behaviour change outcomes in response to the peer support intervention (change towards a MD and nutrient biomarkers) using a randomized controlled trial design

    Psychology and aggression

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68264/2/10.1177_002200275900300301.pd

    Incidence and phenotypes of childhood-onset genetic epilepsies:a prospective population-based national cohort

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    Epilepsy is common in early childhood. In this age group it is associated with high rates of therapy-resistance, and with cognitive, motor, and behavioural comorbidity. A large number of genes, with wide ranging functions, are implicated in its aetiology, especially in those with therapy-resistant seizures. Identifying the more common single-gene epilepsies will aid in targeting resources, the prioritization of diagnostic testing and development of precision therapy. Previous studies of genetic testing in epilepsy have not been prospective and population-based. Therefore, the population-incidence of common genetic epilepsies remains unknown. The objective of this study was to describe the incidence and phenotypic spectrum of the most common single-gene epilepsies in young children, and to calculate what proportion are amenable to precision therapy. This was a prospective national epidemiological cohort study. All children presenting with epilepsy before 36 months of age were eligible. Children presenting with recurrent prolonged (&gt;10 min) febrile seizures; febrile or afebrile status epilepticus (&gt;30 min); or with clusters of two or more febrile or afebrile seizures within a 24-h period were also eligible. Participants were recruited from all 20 regional paediatric departments and four tertiary children’s hospitals in Scotland over a 3-year period. DNA samples were tested on a custom-designed 104-gene epilepsy panel. Detailed clinical information was systematically gathered at initial presentation and during follow-up. Clinical and genetic data were reviewed by a multidisciplinary team of clinicians and genetic scientists. The pathogenic significance of the genetic variants was assessed in accordance with the guidelines of UK Association of Clinical Genetic Science (ACGS). Of the 343 patients who met inclusion criteria, 333 completed genetic testing, and 80/333 (24%) had a diagnostic genetic finding. The overall estimated annual incidence of single-gene epilepsies in this well-defined population was 1 per 2120 live births (47.2/100 000; 95% confidence interval 36.9–57.5). PRRT2 was the most common single-gene epilepsy with an incidence of 1 per 9970 live births (10.0/100 000; 95% confidence interval 5.26–14.8) followed by SCN1A: 1 per 12 200 (8.26/100 000; 95% confidence interval 3.93–12.6); KCNQ2: 1 per 17 000 (5.89/100 000; 95% confidence interval 2.24–9.56) and SLC2A1: 1 per 24 300 (4.13/100 000; 95% confidence interval 1.07–7.19). Presentation before the age of 6 months, and presentation with afebrile focal seizures were significantly associated with genetic diagnosis. Single-gene disorders accounted for a quarter of the seizure disorders in this cohort. Genetic testing is recommended to identify children who may benefit from precision treatment and should be mainstream practice in early childhood onset epilepsy

    Crop Updates 2006 - Lupins and Pulses

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    This session covers sixty six papers from different authors: 2005 LUPIN AND PULSE INDUSTRY HIGHLIGHTS 1. Lupin Peter White, Department of Agriculture 2. Pulses Mark Seymour, Department of Agriculture 3. Monthly rainfall at experimental sites in 2005 4. Acknowledgements Amelia McLarty EDITOR 5. Contributors 6. Background Peter White, Department of Agriculture 2005 REGIONAL ROUNDUP 7. Northern agricultural region Wayne Parker, Department of Agriculture 8. Central agricultural region Ian Pritchard and Bob French, Department of Agriculture 9. Great southern and lakes Rodger Beermier, Department of Agriculture 10. South east region Mark Seymour, Department of Agriculture LUPIN AND PULSE PRODUCTION AGRONOMY AND GENETIC IMPROVEMENT 11. Lupin Peter White, Department of Agriculture 12. Narrow-leafed lupin breeding Bevan Buirchell, Department of Agriculture 13. Progress in the development of pearl lupin (Lupinus mutabilis) for Australian agriculture, Mark Sweetingham1,2, Jon Clements1, Geoff Thomas2, Roger Jones1, Sofia Sipsas1, John Quealy2, Leigh Smith1 and Gordon Francis1 1CLIMA, The University of Western Australia 2Department of Agriculture 14. Molecular genetic markers and lupin breeding, Huaan Yang, Jeffrey Boersma, Bevan Buirchell, Department of Agriculture 15. Construction of a genetic linkage map using MFLP, and identification of molecular markers linked to domestication genes in narrow-leafed lupin (Lupinus augustiflolius L) Jeffrey Boersma1,2, Margaret Pallotta3, Bevan Buirchell1, Chengdao Li1, Krishnapillai Sivasithamparam2 and Huaan Yang1 1Department of Agriculture, 2The University of Western Australia, 3Australian Centre for Plant Functional Genomics, South Australia 16. The first gene-based map of narrow-leafed lupin – location of domestication genes and conserved synteny with Medicago truncatula, M. Nelson1, H. Phan2, S. Ellwood2, P. Moolhuijzen3, M. Bellgard3, J. Hane2, A. Williams2, J. Fos‑Nyarko4, B. Wolko5, M. Książkiewicz5, M. Cakir4, M. Jones4, M. Scobie4, C. O’Lone1, S.J. Barker1, R. Oliver2, and W. Cowling1 1School of Plant Biology, The University of Western Australia, 2Australian Centre for Necrotrophic Fungal Pathogens, Murdoch University, 3Centre for Bioinformatics and Biological Computing, Murdoch University, 4School of Biological Sciences and Biotechnology, SABC, Murdoch University,5Institute of Plant Genetics, Polish Academy of Sciences, Poznań, Poland 17. How does lupin optimum density change row spacing? Bob French and Laurie Maiolo, Department of Agriculture 18. Wide row spacing and seeding rate of lupins with conventional and precision seeding machines Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 19. Influence of row spacing and plant density on lupin competition with annual ryegrass, Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 20. Effect of timing and speed of inter-row cultivation on lupins, Martin Harries, Jo Walker and Steve Cosh, Department of Agriculture 21. The interaction of atrazine herbicide rate and row spacing on lupin seedling survival, Martin Harries and Jo Walker Department of Agriculture 22. The banding of herbicides on lupin row crops, Martin Harries, Jo Walker and Murray Blyth, Department of Agriculture 23. Large plot testing of herbicide tolerance of new lupin lines, Wayne Parker, Department of Agriculture 24. Effect of seed source and simazine rate of seedling emergence and growth, Peter White and Greg Shea, Department of Agriculture 25. The effect of lupin row spacing and seeding rate on a following wheat crop, Martin Harries, Jo Walker and Dirranie Kirby, Department of Agriculture 26. Response of crop lupin species to row spacing, Leigh Smith1, Kedar Adhikari1, Jon Clements2 and Patrizia Guantini3, 1Department of Agriculture, 2CLIMA, The University of Western Australia, 3University of Florence, Italy 27. Response of Lupinus mutabilis to lime application and over watering, Peter White, Leigh Smith and Mark Sweetingham, Department of Agriculture 28. Impact of anthracnose on yield of Andromeda lupins, Geoff Thomas, Kedar Adhikari and Katie Bell, Department of Agriculture 29. Survey of lupin root health (in major production areas), Geoff Thomas, Ken Adcock, Katie Bell, Ciara Beard and Anne Smith, Department of Agriculture 30. Development of a generic forecasting and decision support system for diseases in the Western Australian wheatbelt, Tim Maling1, Art Diggle1,2, Debbie Thackray1, Kadambot Siddique1 and Roger Jones1,2 1CLIMA, The University of Western Australia, 2Department of Agriculture 31.Tanjil mutants highly tolerant to metribuzin, Ping Si1, Mark Sweetingham1,2, Bevan Buirchell1,2 and Huaan Yang l,2 1CLIMA, The University of Western Australia, 2Department of Agriculture 32. Precipitation pH vs. yield and functional properties of lupin protein isolate, Vijay Jayasena1, Hui Jun Chih1 and Ken Dods2 1Curtin University of Technology, 2Chemistry Centre 33. Lupin protein isolation with the use of salts, Vijay Jayasena1, Florence Kartawinata1,Ranil Coorey1 and Ken Dods2 1Curtin University of Technology, 2Chemistry Centre 34. Field pea, Mark Seymour, Department of Agriculture 35. Breeding highlights Kerry Regan1,2, Tanveer Khan1,2, Stuart Morgan1 and Phillip Chambers1 1Department of Agriculture, 2CLIMA, The University of Western Australia 36. Variety evaluation, Kerry Regan1,2, Tanveer Khan1,2, Jenny Garlinge1 and Rod Hunter1 1Department of Agriculture, 2CLIMA, The University of Western Australia 37. Days to flowering of field pea varieties throughout WA Mark Seymour1, Ian Pritchard1, Rodger Beermier1, Pam Burgess1 and Dr Eric Armstrong2 Department of Agriculture, 2NSW Department of Primary Industries, Wagga Wagga 38. Semi-leafless field peas yield more, with less ryegrass seed set, in narrow rows, Glen Riethmuller, Department of Agriculture 39. Swathing, stripping and other innovative ways to harvest field peas, Mark Seymour, Ian Pritchard, Rodger Beermier and Pam Burgess, Department of Agriculture 40. Pulse demonstrations, Ian Pritchard, Wayne Parker, Greg Shea, Department of Agriculture 41. Field pea extension – focus on field peas 2005, Ian Pritchard, Department of Agriculture 42. Field pea blackspot disease in 2005: Prediction versus reality, Moin Salam, Jean Galloway, Pip Payne, Bill MacLeod and Art Diggle, Department of Agriculture 43. Pea seed-borne mosaic virus in pulses: Screening for seed quality defects and virus resistance, Rohan Prince, Brenda Coutts and Roger Jones, Department of Agriculture, and CLIMA, The University of Western Australia 44. Yield losses from sowing field peas infected with pea seed-borne mosaic virus, Rohan Prince, Brenda Coutts and Roger Jones, Department of Agriculture, and CLIMA, The University of Western Australia 45. Desi chickpea, Wayne Parker, Department of Agriculture 46. Breeding highlights, Tanveer Khan 1,2, Pooran Gaur3, Kadambot Siddique2, Heather Clarke2, Stuart Morgan1and Alan Harris1, 1Department of Agriculture2CLIMA, The University of Western Australia, 3International Crop Research Institute for Semi Arid Tropics (ICRISAT), India 47. National chickpea improvement program, Kerry Regan1, Ted Knights2 and Kristy Hobson3,1Department of Agriculture, 2Agriculture New South Wales 3Department of Primary Industries, Victoria 48. Chickpea breeding lines in CVT exhibit excellent ascochyta blight resistance, Tanveer Khan1,2, Alan Harris1, Stuart Morgan1 and Kerry Regan1,2, 1Department of Agriculture, 2CLIMA, The University of Western Australia 49. Variety evaluation, Kerry Regan1,2, Tanveer Khan1,2, Jenny Garlinge2 and Rod Hunter2, 1CLIMA, The University of Western Australia 2Department of Agriculture 50. Desi chickpeas for the wheatbelt, Wayne Parker and Ian Pritchard, Department of Agriculture 51. Large scale demonstration of new chickpea varieties, Wayne Parker, MurrayBlyth, Steve Cosh, Dirranie Kirby and Chris Matthews, Department of Agriculture 52. Ascochyta management with new chickpeas, Martin Harries, Bill MacLeod, Murray Blyth and Jo Walker, Department of Agriculture 53. Management of ascochyta blight in improved chickpea varieties, Bill MacLeod1, Colin Hanbury2, Pip Payne1, Martin Harries1, Murray Blyth1, Tanveer Khan1,2, Kadambot Siddique2, 1Department of Agriculture, 2CLIMA, The University of Western Australia 54. Botrytis grey mould of chickpea, Bill MacLeod, Department of Agriculture 55. Kabuli chickpea, Kerry Regan, Department of Agriculture, and CLIMA, The University of Western Australia 56. New ascochyta blight resistant, high quality kabuli chickpea varieties, Kerry Regan1,2, Kadambot Siddique2, Tim Pope2 and Mike Baker1, 1Department of Agriculture, 2CLIMA, The University of Western Australia 57. Crop production and disease management of Almaz and Nafice, Kerry Regan and Bill MacLeod, Department of Agriculture, and CLIMA, The University of Western Australia 58. Faba bean,Mark Seymour, Department of Agriculture 59. Germplasm evaluation – faba bean, Mark Seymour1, Tim Pope2, Peter White1, Martin Harries1, Murray Blyth1, Rodger Beermier1, Pam Burgess1 and Leanne Young1,1Department of Agriculture, 2CLIMA, The University of Western Australia 60. Factors affecting seed coat colour of faba bean during storage, Syed Muhammad Nasar-Abbas1, Julie Plummer1, Kadambot Siddique2, Peter White 3, D. Harris4 and Ken Dods4.1The University of Western Australia, 2CLIMA, The University of Western Australia, 3Department of Agriculture, 4Chemistry Centre 61. Lentil,Kerry Regan, Department of Agriculture, and CLIMA, The University of Western Australia 62. Variety and germplasm evaluation, Kerry Regan1,2, Tim Pope2, Leanne Young1, Phill Chambers1, Alan Harris1, Wayne Parker1 and Michael Materne3, 1Department of Agriculture 2CLIMA, The University of Western Australia, 3Department of Primary Industries, Victoria Pulse species 63. Land suitability for production of different crop species in Western Australia, Peter White, Dennis van Gool, and Mike Baker, Department of Agriculture 64. Genomic synteny in legumes: Application to crop breeding, Huyen Phan1, Simon Ellwood1, J. Hane1, Angela Williams1, R. Ford2, S. Thomas3 and Richard Oliver1,1Australian Centre of Necrotrophic Plant Pathogens, Murdoch University 2BioMarka, School of Agriculture and Food Systems, ILFR, University of Melbourne 3NSW Department of Primary Industries 65. ALOSCA – Development of a dry flow legume seed inoculant, Rory Coffey and Chris Poole, ALOSCA Technologies Pty Ltd 66. Genetic dissection of resistance to fungal necrotrophs in Medicago truncatula, Simon Ellwood1, Theo Pfaff1, Judith Lichtenzveig12, Lars Kamphuis1, Nola D\u27Souza1, Angela Williams1, Emma Groves1, Karam Singh2 and Richard Oliver1 1Australian Centre of Necrotrophic Plant Pathogens, Murdoch University, 2CSIRO Plant Industry APPENDIX I: LIST OF COMMON ACRONYM

    Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

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    We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352

    Development and validation of a targeted gene sequencing panel for application to disparate cancers

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    Next generation sequencing has revolutionised genomic studies of cancer, having facilitated the development of precision oncology treatments based on a tumour’s molecular profile. We aimed to develop a targeted gene sequencing panel for application to disparate cancer types with particular focus on tumours of the head and neck, plus test for utility in liquid biopsy. The final panel designed through Roche/Nimblegen combined 451 cancer-associated genes (2.01 Mb target region). 136 patient DNA samples were collected for performance and application testing. Panel sensitivity and precision were measured using well-characterised DNA controls (n = 47), and specificity by Sanger sequencing of the Aryl Hydrocarbon Receptor Interacting Protein (AIP) gene in 89 patients. Assessment of liquid biopsy application employed a pool of synthetic circulating tumour DNA (ctDNA). Library preparation and sequencing were conducted on Illumina-based platforms prior to analysis with our accredited (ISO15189) bioinformatics pipeline. We achieved a mean coverage of 395x, with sensitivity and specificity of >99% and precision of >97%. Liquid biopsy revealed detection to 1.25% variant allele frequency. Application to head and neck tumours/cancers resulted in detection of mutations aligned to published databases. In conclusion, we have developed an analytically-validated panel for application to cancers of disparate types with utility in liquid biopsy
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