48 resultados para Chucking the Checklist
Resumo:
Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
Resumo:
Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
Resumo:
Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
Resumo:
Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
Resumo:
Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
Resumo:
Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
Resumo:
BACKGROUND There is evidence for the efficacy of psycho-oncological interventions (POI) in randomized controlled trials for cancer patients. Our objective was to explore, under naturalistic conditions (using propensity score matching), whether POI are effective to decrease anxiety, depression, distress and overall psychopathological symptoms within cancer patients and their partners. METHODS This study was conducted in the Oncology and Hematology Center of a University clinic in Switzerland with a group of 186 patients and 117 partners. Outcome measures of mental health were the Hospital Anxiety and Depression Scale and the Symptom Checklist (SCL-9-K). Repeated-measures ANOVAs were used to analyze change over time and group effects between individuals with POI vs. without POI. RESULTS Highly distressed patients and their partners participating in POI reported better mental health over time. Among moderately distressed patients, a decrease over time emerged in depression and distress independent of POI. No effectiveness of POI could be demonstrated in moderately distressed patients and partners. CONCLUSION Most of the highly distressed patients receive additional POI and therefore conclusions about the efficacy of POI are difficult. For moderately distressed individuals, POI as implemented in Switzerland does not improve mental health in such patients and their partners, which may be caused by very time limited POI treatments. Studies with more intense POI treatments are needed.
Resumo:
Molecular data are now widely used in epidemiological studies to investigate the transmission, distribution, biology, and diversity of pathogens. Our objective was to establish recommendations to support good scientific reporting of molecular epidemiological studies to encourage authors to consider specific threats to valid inference. The statement Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) builds upon the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) initiative. The STROME-ID statement was developed by a working group of epidemiologists, statisticians, bioinformaticians, virologists, and microbiologists with expertise in control of infection and communicable diseases. The statement focuses on issues relating to the reporting of epidemiological studies of infectious diseases using molecular data that were not addressed by STROBE. STROME-ID addresses terminology, measures of genetic diversity within pathogen populations, laboratory methods, sample collection, use of molecular markers, molecular clocks, timeframe, multiple-strain infections, non-independence of infectious-disease data, missing data, ascertainment bias, consistency between molecular and epidemiological data, and ethical considerations with respect to infectious-disease research. In total, 20 items were added to the 22 item STROBE checklist. When used, the STROME-ID recommendations should advance the quality and transparency of scientific reporting, with clear benefits for evidence reviews and health-policy decision making.
Resumo:
Purpose We hypothesized that reduced arousability (Richmond Agitation Sedation Scale, RASS, scores −2 to −3) for any reason during delirium assessment increases the apparent prevalence of delirium in intensive care patients. To test this hypothesis, we assessed delirium using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Intensive Care Delirium Screening Checklist (ICDSC) in intensive care patients during sedation stops, and related the findings to the level of sedation, as assessed with RASS score. Methods We assessed delirium in 80 patients with ICU stay longer than 48 h using CAM-ICU and ICDSC during daily sedation stops. Sedation was assessed using RASS. The effect of including patients with a RASS of −2 and −3 during sedation stop (“light to moderate sedation”, eye contact less than 10 s or not at all, respectively) on prevalence of delirium was analyzed. Results A total of 467 patient days were assessed. The proportion of CAM-ICU-positive evaluations decreased from 53 to 31 % (p < 0.001) if assessments from patients at RASS −2/−3 (22 % of all assessments) were excluded. Similarly, the number of positive ICDSC results decreased from 51 to 29 % (p < 0.001). Conclusions Sedation per se can result in positive items of both CAM-ICU and ICDSC, and therefore in a diagnosis of delirium. Consequently, apparent prevalence of delirium is dependent on how a depressed level of consciousness after sedation stop is interpreted (delirium vs persisting sedation). We suggest that any reports on delirium using these assessment tools should be stratified for a sedation score during the assessment.
Resumo:
Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. 18 items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the Web sites of PLoS Medicine, Annals of Internal Medicine, and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.
Resumo:
Much medical research is observational. The reporting of observational studies is often of insufficient quality. Poor reporting hampers the assessment of the strengths and weaknesses of a study and the generalisability of its results. Taking into account empirical evidence and theoretical considerations, a group of methodologists, researchers, and editors developed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations to improve the quality of reporting of observational studies. The STROBE Statement consists of a checklist of 22 items, which relate to the title, abstract, introduction, methods, results and discussion sections of articles. Eighteen items are common to cohort studies, case-control studies and cross-sectional studies and four are specific to each of the three study designs. The STROBE Statement provides guidance to authors about how to improve the reporting of observational studies and facilitates critical appraisal and interpretation of studies by reviewers, journal editors and readers. This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the STROBE Statement. The meaning and rationale for each checklist item are presented. For each item, one or several published examples and, where possible, references to relevant empirical studies and methodological literature are provided. Examples of useful flow diagrams are also included. The STROBE Statement, this document, and the associated Web site (http://www.strobe-statement.org/) should be helpful resources to improve reporting of observational research.
Resumo:
OBJECTIVES Accurate trial reporting facilitates evaluation and better use of study results. The objective of this article is to investigate the quality of reporting of randomized controlled trials (RCTs) in leading orthodontic journals, and to explore potential predictors of improved reporting. METHODS The 50 most recent issues of 4 leading orthodontic journals until November 2013 were electronically searched. Reporting quality assessment was conducted using the modified CONSORT statement checklist. The relationship between potential predictors and the modified CONSORT score was assessed using linear regression modeling. RESULTS 128 RCTs were identified with a mean modified CONSORT score of 68.97% (SD = 11.09). The Journal of Orthodontics (JO) ranked first in terms of completeness of reporting (modified CONSORT score 76.21%, SD = 10.1), followed by American Journal of Orthodontics and Dentofacial Orthopedics (AJODO) (73.05%, SD = 10.1). Journal of publication (AJODO: β = 10.08, 95% CI: 5.78, 14.38; JO: β = 16.82, 95% CI: 11.70, 21.94; EJO: β = 7.21, 95% CI: 2.69, 11.72 compared to Angle), year of publication (β = 0.98, 95% CI: 0.28, 1.67 for each additional year), region of authorship (Europe: β = 5.19, 95% CI: 1.30, 9.09 compared to Asia/other), statistical significance (significant: β = 3.10, 95% CI: 0.11, 6.10 compared to non-significant) and methodologist involvement (involvement: β = 5.60, 95% CI: 1.66, 9.54 compared to non-involvement) were all significant predictors of improved modified CONSORT scores in the multivariable model. Additionally, median overall Jadad score was 2 (IQR = 2) across journals, with JO (median = 3, IQR = 1) and AJODO (median = 3, IQR = 2) presenting the highest score values. CONCLUSION The reporting quality of RCTs published in leading orthodontic journals is considered suboptimal in various CONSORT areas. This may have a bearing in trial result interpretation and use in clinical decision making and evidence- based orthodontic treatment interventions.
Resumo:
AIM Abstracts of randomized clinical trials are extremely important as trial appraisal is often based on the information included here. The objective of this study was to assess the quality of the reporting of RCT abstracts in journals of Oral Implantology. MATERIAL AND METHODS Six leading Implantology journals were screened for RCTs between years 2008 and 2012. A 21-item modified CONSORT for abstracts checklist was used to examine the completeness of abstract reporting. Descriptive statistics and linear regression modeling were employed for data analysis. RESULTS One hundred and sixty three RCT abstracts were included in this study. The majority of the RCTs were published in the Clinical Oral Implants Research (42.9%). The mean overall reporting quality score was 58.6% (95% CI: 57.6-59.7). The highest score was noted in the European Journal of Oral Implantology (63.8%; 95% CI: 61.8-65.8). Multivariate analysis demonstrated that abstract quality score was related to publication journal and number of research centers involved. Most abstracts adequately reported interventions (89.0%), objectives (77.9%) and conclusions (74.8%) while failed to report randomization procedures, allocation concealment, effect estimate, confidence intervals, and funding. Registration of RCTs was not reported in any of the abstracts. CONCLUSIONS The reporting quality in abstracts of RCTs published in Oral Implantology journals needs to be improved. Editors and authors should be encouraged to endorse the CONSORT for abstracts guidelines in order to achieve optimal quality in abstract reporting.
Resumo:
OBJECTIVE To provide guidance on standards for reporting studies of diagnostic test accuracy for dementia disorders. METHODS An international consensus process on reporting standards in dementia and cognitive impairment (STARDdem) was established, focusing on studies presenting data from which sensitivity and specificity were reported or could be derived. A working group led the initiative through 4 rounds of consensus work, using a modified Delphi process and culminating in a face-to-face consensus meeting in October 2012. The aim of this process was to agree on how best to supplement the generic standards of the STARD statement to enhance their utility and encourage their use in dementia research. RESULTS More than 200 comments were received during the wider consultation rounds. The areas at most risk of inadequate reporting were identified and a set of dementia-specific recommendations to supplement the STARD guidance were developed, including better reporting of patient selection, the reference standard used, avoidance of circularity, and reporting of test-retest reliability. CONCLUSION STARDdem is an implementation of the STARD statement in which the original checklist is elaborated and supplemented with guidance pertinent to studies of cognitive disorders. Its adoption is expected to increase transparency, enable more effective evaluation of diagnostic tests in Alzheimer disease and dementia, contribute to greater adherence to methodologic standards, and advance the development of Alzheimer biomarkers.
Resumo:
OBJECTIVE Although protocol registration for systematic reviews is still not mandatory, reviewers should be strongly encouraged to register the protocol to identify the methodological approach, including all outcomes of interest. This will minimize the likelihood of biased decisions in reviews, such as selective outcome reporting. A group of international experts convened to address issues regarding the need to develop hierarchical lists of outcome measurement instruments for a particular outcome for metaanalyses. METHODS Multiple outcome measurement instruments exist to measure the same outcome. Metaanalysis of knee osteoarthritis (OA) trials, and the assessment of pain as an outcome, was used as an exemplar to assess how Outcome Measures in Rheumatology (OMERACT), the Cochrane Collaboration, and other international initiatives might contribute in this area. The meeting began with formal presentations of background topics, empirical evidence from the literature, and a brief introduction to 2 existing hierarchical lists of pain outcome measurement instruments recommended for metaanalyses of knee OA trials. RESULTS After discussions, most participants agreed that there is a need to develop a methodology for generation of hierarchical lists of outcome measurement instruments to guide metaanalyses. Tools that could be used to steer development of such a prioritized list are the COSMIN checklist (Consensus-based Standards for the selection of health status Measurement Instruments) and the OMERACT Filter 2.0. CONCLUSION We list meta-epidemiological research agenda items that address the frequency of reported outcomes in trials, as well as methodologies to assess the best measurement properties (i.e., truth, discrimination, and feasibility).