Influence Of Nanopolymers With Different End‐Functionalities On Platelets And Coagulation. An Ex‐Vivo Study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106058/1/jth03252.pd

Search for microwave emission from ultrahigh energy cosmic rays

We present a search for microwave emission from air showers induced by ultrahigh energy cosmic rays with the microwave detection of air showers experiment. No events were found, ruling out a wide range of power flux and coherence of the putative emission, including those suggested by recent laboratory measurements.Comment: 5 pages, 3 figure

What factors indicate prognosis for adults with depression in primary care? A protocol for meta-analyses of individual patient data using the Dep-GP database [version 2; peer review: 2 approved]

BACKGROUND: Pre-treatment severity is a key indicator of prognosis for those with depression. Knowledge is limited on how best to encompass severity of disorders. A number of non-severity related factors such as social support and life events are also indicators of prognosis. It is not clear whether this holds true after adjusting for pre-treatment severity as a) a depressive symptom scale score, and b) a broader construct encompassing symptom severity and related indicators: “disorder severity”. In order to investigate this, data from the individual participants of clinical trials which have measured a breadth of “disorder severity” related factors are needed. AIMS: 1) To assess the association between outcomes for adults seeking treatment for depression and the severity of depression pre-treatment, considered both as i) depressive symptom severity only and ii) “disorder severity” which includes depressive symptom severity and comorbid anxiety, chronicity, history of depression, history of previous treatment, functional impairment and health-related quality of life. 2) To determine whether i) social support, ii) life events, iii) alcohol misuse, and iv) demographic factors (sex, age, ethnicity, marital status, employment status, level of educational attainment, and financial wellbeing) are prognostic indicators of outcomes, independent of baseline “disorder severity” and the type of treatment received. METHODS: Databases were searched for randomised clinical trials (RCTs) that recruited adults seeking treatment for depression from their general practitioners and used the same diagnostic and screening instrument to measure severity at baseline – the Revised Clinical Interview Schedule; outcome measures could differ between studies. Chief investigators of all studies meeting inclusion criteria were contacted and individual patient data (IPD) were requested. CONCLUSIONS: In total 15 RCTs met inclusion criteria. The Dep-GP database will include the 6271 participants from the 13 studies that provided IPD. This protocol outlines how these data will be analysed. REGISTRATION: PROSPERO CRD42019129512 (01/04/2019

A Patient Stratification Approach to Identifying the Likelihood of Continued Chronic Depression and Relapse Following Treatment for Depression

BACKGROUND: Subgrouping methods have the potential to support treatment decision making for patients with depression. Such approaches have not been used to study the continued course of depression or likelihood of relapse following treatment. METHOD: Data from individual participants of seven randomised controlled trials were analysed. Latent profile analysis was used to identify subgroups based on baseline characteristics. Associations between profiles and odds of both continued chronic depression and relapse up to one year post-treatment were explored. Differences in outcomes were investigated within profiles for those treated with antidepressants, psychological therapy, and usual care. RESULTS: Seven profiles were identified; profiles with higher symptom severity and long durations of both anxiety and depression at baseline were at higher risk of relapse and of chronic depression. Members of profile five (likely long durations of depression and anxiety, moderately-severe symptoms, and past antidepressant use) appeared to have better outcomes with psychological therapies: antidepressants vs. psychological therapies (OR (95% CI) for relapse = 2.92 (1.24–6.87), chronic course = 2.27 (1.27–4.06)) and usual care vs. psychological therapies (relapse = 2.51 (1.16–5.40), chronic course = 1.98 (1.16–3.37)). CONCLUSIONS: Profiles at greater risk of poor outcomes could benefit from more intensive treatment and frequent monitoring. Patients in profile five may benefit more from psychological therapies than other treatments

Does publication bias inflate the apparent efficacy of psychological treatment for major depressive disorder? A systematic review and meta-analysis of US national institutes of health-funded trials

Background The efficacy of antidepressant medication has been shown empirically to be overestimated due to publication bias, but this has only been inferred statistically with regard to psychological treatment for depression. We assessed directly the extent of study publication bias in trials examining the efficacy of psychological treatment for depression. Methods and Findings We identified US National Institutes of Health grants awarded to fund randomized clinical trials comparing psychological treatment to control conditions or other treatments in patients diagnosed with major depressive disorder for the period 1972–2008, and we determined whether those grants led to publications. For studies that were not published, data were requested from investigators and included in the meta-analyses. Thirteen (23.6%) of the 55 funded grants that began trials did not result in publications, and two others never started. Among comparisons to control conditions, adding unpublished studies (Hedges’ g = 0.20; CI95% -0.11~0.51; k = 6) to published studies (g = 0.52; 0.37~0.68; k = 20) reduced the psychotherapy effect size point estimate (g = 0.39; 0.08~0.70) by 25%. Moreover, these findings may overestimate the "true" effect of psychological treatment for depression as outcome reporting bias could not be examined quantitatively. Conclusion The efficacy of psychological interventions for depression has been overestimated in the published literature, just as it has been for pharmacotherapy. Both are efficacious but not to the extent that the published literature would suggest. Funding agencies and journals should archive both original protocols and raw data from treatment trials to allow the detection and correction of outcome reporting bias. Clinicians, guidelines developers, and decision makers should be aware that the published literature overestimates the effects of the predominant treatments for depression

Effectiveness of counseling for anxiety and depression in mothers of children ages 0-30 months by community workers in Karachi, Pakistan: a quasi experimental study

<p>Abstract</p> <p>Background</p> <p>The prevalence of anxiety/depression is quite high during the perinatal period but unfortunately its detection and treatment have been less than satisfactory. Moreover, many women are reluctant to take pharmacotherapy for fear of excretion of drugs into their breast milk. This study assesses the effectiveness of counseling from minimally trained community health workers in reducing anxiety/depression, the rate of recurrence and the interval preceding recurrence in women during first two and a half years after childbirth.</p> <p>Methods</p> <p>In a quasi-experimental study, community women from two under-privileged communities were trained in data gathering, teaching healthy child-rearing practices, basic counseling skills, and screening for anxiety/depression by using an indigenously developed questionnaire, the Aga Khan University Anxiety and Depression Scale (AKUADS). The diagnosis was further confirmed by a clinical psychologist using DSM IV criteria. After obtaining consent, 420 women were screened and 102 were identified as having anxiety/depression. Screening was carried out after 1, 2, 6, 12, 18, 24 and 30 months of a live birth. Only 62 out of 102 agreed to be counseled and received eight weekly sessions. AKUADS was re-administered at 4 weeks and 8 weeks after the beginning of counseling; this was followed by the clinical psychologist's interview for confirmation of response. After recovery, screening was continued every 3 months for detection of recurrence throughout the study period. Out of the women who had declined counseling 12 agreed to retake AKUADS after 4 and 8 weeks of diagnosis. Independent samples t-test, chi-square test, Repeated Measures ANOVA and Kaplan Meier technique were used for the analysis.</p> <p>Results</p> <p>A significant decline in level of anxiety/depression was found in both the counseled and the non-counseled groups at 4 and 8 weeks (p-value < 0.001) but the counseled group fared better than the non-counseled for recovery, reduction in the rate of recurrence and increase in the duration before relapse.</p> <p>Conclusions</p> <p>As our results cannot be generalized; further studies need to be carried out, to assess the benefit of incorporating minimal counseling skills in the training of community health workers.</p

Predicting prognosis for adults with depression using individual symptom data:a comparison of modelling approaches

BACKGROUND: This study aimed to develop, validate and compare the performance of models predicting post-treatment outcomes for depressed adults based on pre-treatment data. METHODS: Individual patient data from all six eligible randomised controlled trials were used to develop (k = 3, n = 1722) and test (k = 3, n = 918) nine models. Predictors included depressive and anxiety symptoms, social support, life events and alcohol use. Weighted sum scores were developed using coefficient weights derived from network centrality statistics (models 1-3) and factor loadings from a confirmatory factor analysis (model 4). Unweighted sum score models were tested using elastic net regularised (ENR) and ordinary least squares (OLS) regression (models 5 and 6). Individual items were then included in ENR and OLS (models 7 and 8). All models were compared to one another and to a null model (mean post-baseline Beck Depression Inventory Second Edition (BDI-II) score in the training data: model 9). Primary outcome: BDI-II scores at 3-4 months. RESULTS: Models 1-7 all outperformed the null model and model 8. Model performance was very similar across models 1-6, meaning that differential weights applied to the baseline sum scores had little impact. CONCLUSIONS: Any of the modelling techniques (models 1-7) could be used to inform prognostic predictions for depressed adults with differences in the proportions of patients reaching remission based on the predicted severity of depressive symptoms post-treatment. However, the majority of variance in prognosis remained unexplained. It may be necessary to include a broader range of biopsychosocial variables to better adjudicate between competing models, and to derive models with greater clinical utility for treatment-seeking adults with depression

Life events and treatment prognosis for depression: A systematic review and individual patient data meta-analysis

Objective: To investigate associations between major life events and prognosis independent of treatment type: (1) after adjusting for clinical prognostic factors and socio-demographics; (2) amongst patients with depressive episodes at least six-months long; and (3) patients with a first life-time depressive episode. // Methods: Six RCTs of adults seeking treatment for depression in primary care met eligibility criteria, individual patient data (IPD) were collated from all six (n = 2858). Participants were randomized to any treatment and completed the same baseline assessment of life events, demographics and clinical prognostic factors. Two-stage random effects meta-analyses were conducted. // Results: Reporting any major life events was associated with poorer prognosis regardless of treatment type. Controlling for baseline clinical factors, socio-demographics and social support resulted in minimal residual evidence of associations between life events and treatment prognosis. However, removing factors that might mediate the relationships between life events and outcomes reporting: arguments/disputes, problem debt, violent crime, losing one's job, and three or more life events were associated with considerably worse prognoses (percentage difference in 3–4 months depressive symptoms compared to no reported life events =30.3%(95%CI: 18.4–43.3)). // Conclusions: Assessing for clinical prognostic factors, social support, and socio-demographics is likely to be more informative for prognosis than assessing self-reported recent major life events. However, clinicians might find it useful to ask about such events, and if they are still affecting the patient, consider interventions to tackle problems related to those events (e.g. employment support, mediation, or debt advice). Further investigations of the efficacy of such interventions will be important

What factors indicate prognosis for adults with depression in primary care? A protocol for meta-analyses of individual patient data using the Dep-GP database [version 1; peer review: 1 approved, 1 approved with reservations]

BACKGROUND: Pre-treatment severity is a key indicator of prognosis for those with depression. Knowledge is limited on how best to encompass severity of disorders. A number of non-severity related factors such as social support and life events are also indicators of prognosis. It is not clear whether this holds true after adjusting for pre-treatment severity as a) a depressive symptom scale score, and b) a broader construct encompassing symptom severity and related indicators: “disorder severity”. In order to investigate this, data from the individual participants of clinical trials which have measured a breadth of “disorder severity” related factors are needed. AIMS: 1) To assess the association between outcomes for adults seeking treatment for depression and the severity of depression pre-treatment, considered both as i) depressive symptom severity only and ii) “disorder severity” which includes depressive symptom severity and comorbid anxiety, chronicity, history of depression, history of previous treatment, functional impairment and health-related quality of life. 2) To determine whether i) social support, ii) life events, iii) alcohol misuse, and iv) demographic factors (sex, age, ethnicity, marital status, employment status, level of educational attainment, and financial wellbeing) are prognostic indicators of outcomes, independent of baseline “disorder severity” and the type of treatment received. METHODS: Databases were searched for randomised clinical trials (RCTs) that recruited adults seeking treatment for depression from their general practitioners and used the same diagnostic and screening instrument to measure severity at baseline – the Revised Clinical Interview Schedule; outcome measures could differ between studies. Chief investigators of all studies meeting inclusion criteria were contacted and individual patient data (IPD) were requested. CONCLUSIONS: In total 13 RCTs were found to meet inclusion criteria. The Dep-GP database was formed from the 6271 participants. This protocol outlines how these data will be analysed. REGISTRATION: PROSPERO CRD42019129512 (01/04/2019)

CONSORT-SPI 2018 Explanation and Elaboration: guidance for reporting social and psychological intervention trials.

BACKGROUND: The CONSORT (Consolidated Standards of Reporting Trials) Statement was developed to help biomedical researchers report randomised controlled trials (RCTs) transparently. We have developed an extension to the CONSORT 2010 Statement for social and psychological interventions (CONSORT-SPI 2018) to help behavioural and social scientists report these studies transparently. METHODS: Following a systematic review of existing reporting guidelines, we conducted an online Delphi process to prioritise the list of potential items for the CONSORT-SPI 2018 checklist identified from the systematic review. Of 384 international participants, 321 (84%) participated in both rating rounds. We then held a consensus meeting of 31 scientists, journal editors, and research funders (March 2014) to finalise the content of the CONSORT-SPI 2018 checklist and flow diagram. RESULTS: CONSORT-SPI 2018 extends 9 items (14 including sub-items) from the CONSORT 2010 checklist, adds a new item (with 3 sub-items) related to stakeholder involvement in trials, and modifies the CONSORT 2010 flow diagram. This Explanation and Elaboration (E&E) document is a user manual to enhance understanding of CONSORT-SPI 2018. It discusses the meaning and rationale for each checklist item and provides examples of complete and transparent reporting. CONCLUSIONS: The CONSORT-SPI 2018 Extension, this E&E document, and the CONSORT website ( www.consort-statement.org ) are helpful resources for improving the reporting of social and psychological intervention RCTs