Psychosis is a heterogeneous psychiatric condition for which a multitude of risk and protective factors have been suggested. This umbrella review aimed to classify the strength of evidence for the associations between each factor and psychotic disorders whilst controlling for several biases. The Web of Knowledge database was searched to identify systematic reviews and meta‐analyses of observational studies which examined associations between socio‐demographic, parental, perinatal, later factors or antecedents and psychotic disorders, and which included a comparison group of healthy controls, published from 1965 to January 31, 2017. The literature search and data extraction followed PRISMA and MOOSE guidelines. The association between each factor and ICD or DSM diagnoses of non‐organic psychotic disorders was graded into convincing, highly suggestive, suggestive, weak, or non‐significant according to a standardized classification based on: number of psychotic cases, random‐effects p value, largest study 95% confidence interval, heterogeneity between studies, 95% prediction interval, small study effect, and excess significance bias. In order to assess evidence for temporality of association, we also conducted sensitivity analyses restricted to data from prospective studies. Fifty‐five meta‐analyses or systematic reviews were included in the umbrella review, corresponding to 683 individual studies and 170 putative risk or protective factors for psychotic disorders. Only the ultra‐high‐risk state for psychosis (odds ratio, OR=9.32, 95% CI: 4.91‐17.72) and Black‐Caribbean ethnicity in England (OR=4.87, 95% CI: 3.96‐6.00) showed convincing evidence of association. Six factors were highly suggestive (ethnic minority in low ethnic density area, second generation immigrants, trait anhedonia, premorbid IQ, minor physical anomalies, and olfactory identification ability), and nine were suggestive (urbanicity, ethnic minority in high ethnic density area, first generation immigrants, North‐African immigrants in Europe, winter/spring season of birth in Northern hemisphere, childhood social withdrawal, childhood trauma, Toxoplasma gondii IgG, and non‐right handedness). When only prospective studies were considered, the evidence was convincing for ultra‐high‐risk state and suggestive for urbanicity only. In summary, this umbrella review found several factors to be associated with psychotic disorders with different levels of evidence. These risk or protective factors represent a starting point for further etiopathological research and for the improvement of the prediction of psychosis.
Meta-analysis has evolved as a primary tool for evidence-based medicine. Initially, meta-analysis was seenas a technique that could improve statistical power in a research world of small, underpowered studies.We increasingly recognize that meta-analysis is a critical tool that can help us measure and understand notonly summary effects, but also heterogeneity (diversity) and bias. Here I discuss some key themes and chal-lenges for “meta-epidemiology”. These include the contrast between randomized and observational evi-dence; the evolutionary nature of biomedical evidence; the contrast between small and larger studies; thedifficulties in appraising study “quality” and its potential impact on the study effects; and the scandal ofmissing even minimal, key information on the harms of interventions that are otherwise postulated to beeffective. I discuss a general outlook about the validity of the evidence in medicine and public health. I sug-gest that we should learn to live with uncertainty, since the evidence that is available is often limited, biased,or both. This means that we should be prepared to dismiss big chunks of biomedical dogma, including per-haps whole specialties and sub-specialties of current medicine, as false, erroneous, irrelevant or even poten-tially dangerous for the health of individuals and populations. An effort should be made to shift the accu-mulation and synthesis of evidence towards answering critical public health-related questions.This paper is based on a lecture presented at the European Public Health Association 2005 annual confer-ence in Graz, Austria
The ratio of false-positive to false-negative findings (FP:FN ratio) is an informative metric that warrants further evaluation. The FP:FN ratio varies greatly across different epidemiologic areas. In genetic epidemiology, it has varied from very high values (possibly even >100:1) for associations reported in candidate-gene studies to very low values (1:100 or lower) for associations with genome-wide significance. The substantial reduction over time in the FP:FN ratio in human genome epidemiology has corresponded to the routine adoption of stringent inferential criteria and comprehensive, agnostic reporting of all analyses. Most traditional fields of epidemiologic research more closely follow the practices of past candidate gene epidemiology, and thus have high FP:FN ratios. Further, FP and FN results do not necessarily entail the same consequences, and their relative importance may vary in different settings. This ultimately has implications for what is the acceptable FP:FN ratio and for how the results of published epidemiologic studies should be presented and interpreted.
We present circuits for a high-efficiency low-swing interconnect scheme suitable for the Smart Memories reconfigurable architecture. By using a separate supply, global clocking, and differential signaling, we reduce design complexity; and by using overdrive circuits, equalization techniques, and sense-amplifiers we retain high performance. A testchip built in a 1.8 V 0.18-/spl mu/m technology consumed <1pJ/bit for a 10 mm bus at 1 GHz, a power savings over full-swing signaling of up to 10 x, and demonstrated amplifier input offset voltages of under 100 mV.
Abstract : This investigation considers the relationship between the physical failures that occur during fabrication and the resulting faulty behavior of the circuit. Fault models are used to describe the operation of integrated circuits containing physical failures introduced during fabrication. The effectiveness of fault models is dependent upon both the accuracy of the model and the occurrence of the underlying failure mechanism. A specially designed static RAM provides the size, design style, and testability required of a fault model test bed. An actual RAM implementation is described which was used for evaluation of fault models.
Abstract Strategies for the use of COVID‐19 vaccines in children and young adults (in particular university students) are hotly debated and important to optimize. As of late August 2021, recommendations on the use of these vaccines in children vary across different countries. Recommendations are more uniform for vaccines in young adults, but vaccination uptake in this age group shows a large range across countries. Mandates for vaccination of university students are a particularly debated topic with many campuses endorsing mandates in the USA in contrast to European countries, at least as of August 2021. The commentary discusses the potential indirect impact of vaccination of youth on the COVID‐19 burden of disease for other age groups and societal functioning at large, estimates of direct impact on reducing fatalities and nonlethal COVID‐19‐related events in youth, estimates of potential lethal and nonlethal adverse events from vaccines and differential considerations that may exist in the USA, European countries and nonhigh‐income countries. Decision‐making for deploying COVID‐19 vaccines in young people is subject to residual uncertainty on the future course of the pandemic and potential evolution towards endemicity. Rational recommendations would also benefit from better understanding of the clinical and sociodemographic features of COVID‐19 risk in young populations and from dissecting the role of re‐infections and durability of natural vs. vaccine‐induced immunity.
In the first article of this series, we reviewed the basic genetics concepts necessary to understand genetic association studies. In this second article, we enumerate the major issues in judging the validity of these studies, framed as critical appraisal questions. Was the disease phenotype properly defined and accurately recorded by someone blind to the genetic information? Have any potential differences between disease and nondisease groups, particularly ethnicity, been properly addressed? In genetic studies, one potential cause of spurious associations is differences between cases and controls in ethnicity, a situation termed population stratification. Was measurement of the genetic variantsunbiasedandaccurate?MethodsfordeterminingDNAsequencevariation are not perfect and may have some measurement error. Do the genotype proportions observe Hardy-Weinberg equilibrium? This simple mathematic rule about the distribution of genetic groups may be one way to check for errors in reading DNA information. Have the investigators adjusted their inferencesformultiplecomparisons?Giventhethousandsofgeneticmarkerstested in genome-wide association studies, the potential for false-positive and falsenegative results is much higher than in traditional medical studies, and it is particularly important to look for replication of results.
