441 research outputs found
Cost-effectiveness of financial incentives to promote adherence to depot antipsychotic medication: economic evaluation of a cluster-randomised controlled trial
Background: Offering a modest financial incentive to people with psychosis can promote adherence to depot antipsychotic medication, but the cost-effectiveness of this approach has not been examined. Methods: Economic evaluation within a pragmatic cluster-randomised controlled trial. 141 patients under the care of 73 teams (clusters) were randomised to intervention or control; 138 patients with diagnoses of schizophrenia, schizo-affective disorder or bipolar disorder participated. Intervention participants received £15 per depot injection over 12 months, additional to usual acute, mental and community primary health services. The control group received usual health services. Main outcome measures: incremental cost per 20% increase in adherence to depot antipsychotic medication; incremental cost of ‘good’ adherence (defined as taking at least 95% of the prescribed number of depot medications over the intervention period). Findings: Economic and outcome data for baseline and 12-month follow-up were available for 117 participants. The adjusted difference in adherence between groups was 12.2% (73.4% control vs. 85.6% intervention); the adjusted costs difference was £598 (95% CI -£4 533, £5 730). The extra cost per patient to increase adherence to depot medications by 20% was £982 (95% CI -£8 020, £14 000). The extra cost per patient of achieving 'good' adherence was £2 950 (CI -£19 400, £27 800). Probability of cost-effectiveness exceeded 97.5%at willingness-to-pay values of £14 000 for a 20% increase in adherence and £27 800 for good adherence. Interpretation: Offering a modest financial incentive to people with psychosis is cost-effective in promoting adherence to depot antipsychotic medication. Direct healthcare costs (including costs of the financial incentive) are unlikely to be increased by this intervention. Trial Registration: ISRCTN.com 7776928
A manufacturable smart dressing with oxygen delivery and sensing capability for chronic wound management
Chronic non-healing wounds, impact over 6.5 million Americans, costs in excess of $25 billion to treat on an annual basis and its incidence is predicted to rise due to the prevalence of obesity and type-2 diabetes. One of the primary complications often associated with chronic wounds is the improper functionality of the peripheral vasculature to deliver O2-rich blood to the tissue which leads to wound hypoxia. Although hyperbaric oxygen therapy are widely used and accepted as an effective approach to bolster tissue O2 levels in hypoxic chronic wounds, most of such treatments require bulky equipment and often expose large areas of the body to unnecessarily elevated oxygen concentrations that can damage healthy tissue. In this paper, we present a smart low-cost wound dressing with integrated oxygen sensor and delivery for locally generating and delivering oxygen to selected hypoxic regions on the wound. The dressing is fabricated on a biocompatible water resistant/hydrophobic paper-based substrate with printed optical oxygen sensors and patterned catalytic oxygen generating regions that are connected to a flexible microfluidic systems. Oxygen generation occurs by flowing H2O2 through the channels and chemical decomposition at the catalyst printed regions on the paper substrate. The hydrophobic paper provides structural stability and flexibility while simultaneously offering printability, selective gaseous filtering, and physical/chemical protection. The fabrication process take advantage of scalable manufacturing technologies including laser processing, inkjet printing, and lamination
Low back pain and widespread pain predict sickness absence among industrial workers
BACKGROUND: The prevalence of musculoskeletal disorders (MSD) in the aluminium industry is high, and there is a considerable work-related fraction. More knowledge about the predictors of sickness absence from MSD in this industry will be valuable in determining strategies for prevention. The aim of this study was to analyse the relative impact of body parts, psychosocial and individual factors as predictors for short- and long-term sickness absence from MSD among industrial workers. METHODS: A follow-up study was conducted among all the workers at eight aluminium plants in Norway. A questionnaire was completed by 5654 workers at baseline in 1998. A total of 3320 of these participated in the follow-up study in 2000. Cox regression analysis was applied to investigate the relative impact of MSD in various parts of the body and of psychosocial and individual factors reported in 1998 on short-term and long-term sickness absence from MSD reported in 2000. RESULTS: MSD accounted for 45% of all working days lost the year prior to follow-up in 2000. Blue-collar workers had significantly higher risk than white-collar workers for both short- and long-term sickness absence from MSD (long-term sickness absence: RR = 3.04, 95% CI 2.08–4.45). Widespread and low back pain in 1998 significantly predicted both short- and long-term sickness absence in 2000. In addition, shoulder pain predicted long-term sickness absence. Low social support predicted short-term sickness absence (RR = 1.28, 95% CI 1.11–1.49). CONCLUSIONS: Reducing sickness absence from MSD among industrial workers requires focusing on the working conditions of blue-collar workers and risk factors for low back pain and widespread pain. Increasing social support in the work environment may have effects in reducing short-term sickness absence from MSD
Candidate gene analysis of spontaneous preterm delivery: New insights from re-analysis of a case-control study using case-parent triads and control-mother dyads
<p>Abstract</p> <p>Background</p> <p>Spontaneous preterm delivery (PTD) has a multifactorial etiology with evidence of a genetic contribution to its pathogenesis. A number of candidate gene case-control studies have been performed on spontaneous PTD, but the results have been inconsistent, and do not fully assess the role of how two genotypes can impact outcome. To elucidate this latter point we re-analyzed data from a previously published case-control candidate gene study, using a case-parent triad design and a hybrid design combining case-parent triads and control-mother dyads. These methods offer a robust approach to genetic association studies for PTD compared to traditional case-control designs.</p> <p>Methods</p> <p>The study participants were obtained from the Norwegian Mother and Child Cohort Study (MoBa). A total of 196 case triads and 211 control dyads were selected for the analysis. A case-parent triad design as well as a hybrid design was used to analyze 1,326 SNPs from 159 candidate genes. We compared our results to those from a previous case-control study on the same samples. Haplotypes were analyzed using a sliding window of three SNPs and a pathway analysis was performed to gain biological insight into the pathophysiology of preterm delivery.</p> <p>Results</p> <p>The most consistent significant fetal gene across all analyses was COL5A2. The functionally similar COL5A1 was significant when combining fetal and maternal genotypes. PON1 was significant with analytical approaches for single locus association of fetal genes alone, but was possibly confounded by maternal effects. Focal adhesion (hsa04510), Cell Communication (hsa01430) and ECM receptor interaction (hsa04512) were the most constant significant pathways.</p> <p>Conclusion</p> <p>This study suggests a fetal association of COL5A2 and a combined fetal-maternal association of COL5A1 with spontaneous PTD. In addition, the pathway analysis implied interactions of genes affecting cell communication and extracellular matrix.</p
Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.
To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity
Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways
OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels.
RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.
RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c.
CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c
Effects of 34 Risk Loci for Type 2 Diabetes or Hyperglycemia on Lipoprotein Subclasses and Their Composition in 6,580 Nondiabetic Finnish Men
Perceptions and experiences of patients living with implantable cardioverter defibrillators: a systematic review and meta-synthesis
Cognitive behavioral therapy for insomnia in euthymic bipolar disorder: study protocol for a randomized controlled trial
Association of Ketone Body Levels With Hyperglycemia and Type 2 Diabetes in 9,398 Finnish Men
We investigated the association of the levels of ketone bodies (KBs) with hyperglycemia and with 62 genetic risk variants regulating glucose levels or type 2 diabetes in the population-based Metabolic Syndrome in Men (METSIM) study, including 9,398 Finnish men without diabetes or newly diagnosed type 2 diabetes. Increasing fasting and 2-h plasma glucose levels were associated with elevated levels of acetoacetate (AcAc) and β-hydroxybutyrate (BHB). AcAc and BHB predicted an increase in the glucose area under the curve in an oral glucose tolerance test, and AcAc predicted the conversion to type 2 diabetes in a 5-year follow-up of the METSIM cohort. Impaired insulin secretion, but not insulin resistance, explained these findings. Of the 62 single nucleotide polymorphisms associated with the risk of type 2 diabetes or hyperglycemia, the glucose-increasing C allele of GCKR significantly associated with elevated levels of fasting BHB levels. Adipose tissue mRNA expression levels of genes involved in ketolysis were significantly associated with insulin sensitivity (Matsuda index). In conclusion, high levels of KBs predicted subsequent worsening of hyperglycemia, and a common variant of GCKR was significantly associated with BHB levels
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