Overview of literature and information on "khat-related" mortality: a call for recognition of the issue and further research

During the past 20 years or so, more has become known about the properties of khat, its pharmacology, physiological and psychological effects on humans. However, at the same time its reputation of social and recreational use in traditional contexts has hindered the dissemination of knowledge about its detrimental effects in terms of mortality. This paper focuses on this particular deficit and adds to the knowledge-base by reviewing the scant literature that does exist on mortality associated with the trade and use of khat. We sought all peer-reviewed papers relating to deaths associated with khat. From an initial list of 111, we identified 15 items meeting our selection criteria. Examination of these revealed 61 further relevant items. These were supplemented with published reports, newspaper and other media reports. A conceptual framework was then developed for classifying mortality associated with each stage of the plant's journey from its cultivation, transportation, consumption, to its effects on the human body. The model is demonstrated with concrete examples drawn from the above sources. These highlight a number of issues for which more substantive statistical data are needed, including population-based studies of the physiological and psychological determinants of khat-related fatalities. Khat-consuming communities, and health professionals charged with their care should be more aware of the physiological and psychological effects of khat, together with the risks for morbidity and mortality associated with its use. There is also a need for information to be collected at international and national levels on other causes of death associated with khat cultivation, transportation, and trade. Both these dimensions need to be understood.

Affective and linguistic processing of speech prosody: DC potential studies

Speech melody or prosody subserves linguistic, emotional, and pragmatic functions in speech communication. Prosodic perception is based on the decoding of acoustic cues with a predominant function of frequency-related information perceived as speaker's pitch. Evaluation of prosodic meaning is a cognitive function implemented in cortical and subcortical networks that generate continuously updated affective or linguistic speaker impressions. Various brain-imaging methods allow delineation of neural structures involved in prosody processing. In contrast to functional magnetic resonance imaging techniques, DC (direct current, slow) components of the EEG directly measure cortical activation without temporal delay. Activation patterns obtained with this method are highly task specific and intraindividually reproducible. Studies presented here investigated the topography of prosodic stimulus processing in dependence on acoustic stimulus structure and linguistic or affective task demands, respectively. Data obtained from measuring DC potentials demonstrated that the right hemisphere has a predominant role in processing emotions from the tone of voice, irrespective of emotional valence. However, right hemisphere involvement is modulated by diverse speech and language-related conditions that are associated with a left hemisphere participation in prosody processing. The degree of left hemisphere involvement depends on several factors such as (i) articulatory demands on the perceiver of prosody (possibly, also the poser), (ii) a relative left hemisphere specialization in processing temporal cues mediating prosodic meaning, and (iii) the propensity of prosody to act on the segment level in order to modulate word or sentence meaning. The specific role of top-down effects in terms of either linguistically or affectively oriented attention on lateralization of stimulus processing is not clear and requires further investigations.

Graphical presentation of diagnostic information

BACKGROUND: Graphical displays of results allow researchers to summarise and communicate the key findings of their study. Diagnostic information should be presented in an easily interpretable way, which conveys both test characteristics (diagnostic accuracy) and the potential for use in clinical practice (predictive value). METHODS: We discuss the types of graphical display commonly encountered in primary diagnostic accuracy studies and systematic reviews of such studies, and systematically review the use of graphical displays in recent diagnostic primary studies and systematic reviews. RESULTS: We identified 57 primary studies and 49 systematic reviews. Fifty-six percent of primary studies and 53% of systematic reviews used graphical displays to present results. Dot-plot or box-and- whisker plots were the most commonly used graph in primary studies and were included in 22 (39%) studies. ROC plots were the most common type of plot included in systematic reviews and were included in 22 (45%) reviews. One primary study and five systematic reviews included a probability-modifying plot. CONCLUSION: Graphical displays are currently underused in primary diagnostic accuracy studies and systematic reviews of such studies. Diagnostic accuracy studies need to include multiple types of graphic in order to provide both a detailed overview of the results (diagnostic accuracy) and to communicate information that can be used to inform clinical practice (predictive value). Work is required to improve graphical displays, to better communicate the utility of a test in clinical practice and the implications of test results for individual patients.

Cord entanglement in monoamniotic twins: 2D and 3D colour Doppler studies

Cord entanglement affects the majority of monoamniotic (MA) twins, accounting for the high proportion of intrauterine deaths of MA twins, and it is often present from early gestation. 3D ultrasound can be used to acquire volume data comprising information on umbilical colour Doppler flow, providing a very graphic depiction of cord entanglement. We have used 2D, "conventional" and a novel 3D display of colour Doppler ultrasound showing cord entanglement.

Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine

BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. METHODS/DESIGN: Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests and development of clinical prediction rules for the individual patients. These will be made accessible for clinicians. DISCUSSION: The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic and prognostic research.

Multivariable adjustments counteract spectrum and test review bias in accuracy studies

OBJECTIVES: The STAndards for Reporting studies of Diagnostic accuracy (STARD) for investigators and editors and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) for reviewers and readers offer guidelines for the quality and reporting of test accuracy studies. These guidelines address and propose some solutions to two major threats to validity: spectrum bias and test review bias. STUDY DESIGN AND SETTING: Using a clinical example, we demonstrate that these solutions fail and propose an alternative solution that concomitantly addresses both sources of bias. We also derive formulas that prove the generality of our arguments. RESULTS: A logical extension of our ideas is to extend STARD item 23 by adding a requirement for multivariable statistical adjustment using information collected in QUADAS items 1, 2, and 12 and STARD items 3-5, 11, 15, and 18. CONCLUSION: We recommend reporting not only variation of diagnostic accuracy across subgroups (STARD item 23) but also the effects of the multivariable adjustments on test performance. We also suggest that the QUADAS be supplemented by an item addressing the appropriateness of statistical methods, in particular whether multivariable adjustments have been included in the analysis.

When one depends on the other: reporting of interaction in case-control and cohort studies

BACKGROUND: Interaction refers to the situation in which the effect of 1 exposure on an outcome differs across strata of another exposure. We did a survey of epidemiologic studies published in leading journals to examine how interaction is assessed and reported. METHODS: We selected 150 case-control and 75 cohort studies published between May 2001 and May 2007 in leading general medicine, epidemiology, and clinical specialist journals. Two reviewers independently extracted data on study characteristics. RESULTS: Of the 225 studies, 138 (61%) addressed interaction. Among these, 25 (18%) presented no data or only a P value or a statement of statistical significance; 40 (29%) presented stratum-specific effect estimates but no meaningful comparison of these estimates; and 58 (42%) presented stratum-specific estimates and appropriate tests for interaction. Fifteen articles (11%) presented the individual effects of both exposures and also their joint effect or a product term, providing sufficient information to interpret interaction on an additive and multiplicative scale. Reporting was poorest in articles published in clinical specialist articles and most adequate in articles published in general medicine journals, with epidemiology journals in an intermediate position. CONCLUSIONS: A majority of articles reporting cohort and case-control studies address possible interactions between exposures. However, in about half of these, the information provided was unsatisfactory, and only 1 in 10 studies reported data that allowed readers to interpret interaction effects on an additive and multiplicative scale.

STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement

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.

STrengthening the REporting of Genetic Association Studies (STREGA)--an extension of the STROBE statement

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.

Strengthening the reporting of genetic association studies (STREGA): an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement

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.

STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement

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.

STrengthening the REporting of Genetic Association studies (STREGA): an extension of the STROBE Statement

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.