Non-adherence to antipsychotic medication, relapse and rehospitalisation in recent-onset schizophrenia

<p>Abstract</p> <p>Background</p> <p>The aims of this study were to describe outcome with respect to persistent psychotic symptoms, relapse of positive symptoms, hospital admissions, and application of treatment by coercion among patients with recent onset schizophrenia being adherent and non-adherent to anti-psychotic medication.</p> <p>Materials and methods</p> <p>The study included 50 patients with recent onset schizophrenia, schizoaffective or schizophreniform disorders. The patients were clinically stable at study entry and had less than 2 years duration of psychotic symptoms. Good adherence to antipsychotic medication was defined as less than one month without medication. Outcomes for poor and good adherence were compared over a 24-month follow-up period.</p> <p>Results</p> <p>The Odds Ratio (OR) of having a psychotic relapse was 10.27 and the OR of being admitted to hospital was 4.00 among non-adherent patients. Use of depot-antipsychotics were associated with relapses (OR = 6.44).</p> <p>Conclusion</p> <p>Non-adherence was associated with relapse, hospital admission and having persistent psychotic symptoms. Interventions to increase adherence are needed.</p> <p>Trial registration</p> <p>Current Controlled Trials NCT00184509. Key words: Adherence, schizophrenia, antipsychotic medication, admittances, relapse.</p

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

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

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

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Corrigendum to "Translating big data to better treatment in bipolar disorder - a manifesto for coordinated action [European Neuropsychopharmacology (2020) 36, 121-136]"

The authors regret that there was an error in the author list, this should appear as above. The authors apologise for any inconvenience caused

THE ANALYSIS OF PUNCTUATION USE IN UNPUNCTUATED PASSAGES: A DISCOURSE-GRAPHOLOGY PERSPECTIVE

Diski Eginda Rismianti. 14111310149. The Analysis of Punctuation Use in Unpunctuated Passages: A Discourse-Graphology Perspective. Punctuation is the basic element in writing which is important to clarify meaning. Without punctuation or ignoring the rule of punctuation in a passage, the writing will be ambiguous. The writing course in IAIN Syekh Nurjati Cirebon is studied by English Student in 5 levels. Based the phenomenon, this research aims to find out the students’ error in the use of punctuation and how does the use relate to the meaning of restrictive and nonrestrictive elements. The analyses process in this research is constructed based on the theory from Marcella Frank. This research used qualitative method in analyzing data where the data contains the two original passages which is taken from the book of academic writing and the three participants’ work which are got by examining the passages as a main data source to be analyzed in this research. Those passages are changed be unpunctuated passages then examined to the 3 EFL learner which comes from the high score, medium score, and low score of writing. The result of this analysis shows that there are fifteen punctuation marks which are used in the two passages; they are capitalization, periods, commas, semicolons, colons, quotation marks, parentheses, apostrophes, hyphen, en dashes, ellipses, percent, underscore, at sign, and citation. FP has highest number of error in Capitalization with 100%. SP has big problem in commas exactly in the nineteenth rule with 90% and TP are wrong in parentheses. For restrictive and nonrestrictive elements, restrictive elements has higher number than nonrestrictive elements, except is in appositive. The numbers of the elements are same with the three participants. The differences come from the number of appositive which passages has higher number of nonrestrictive appositive than restrictive appositives. The results show that punctuation in unpunctuated passages used the rule from APA (American Psychological Association). The effects of the use of punctuation are in the number of sentences and clauses, types of phrases, and restrictive and nonrestrictive elements. For the students’ error, there are some sentences in FP and TP which only contain phrase. Key words: Punctuation Marks, Restrictive and Nonrestrictive Clause, Restrictive and Nonrestrictive Phrase, Restrictive and Nonrestrictive Appositives