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.
Null hypothesis significance testing (NHST) has several shortcomings that are likely contributing factors behind the widely debated replication crisis of (cognitive) neuroscience, psychology, and ...biomedical science in general. We review these shortcomings and suggest that, after sustained negative experience, NHST should no longer be the default, dominant statistical practice of all biomedical and psychological research. If theoretical predictions are weak we should not rely on all or nothing hypothesis tests. Different inferential methods may be most suitable for different types of research questions. Whenever researchers use NHST they should justify its use, and publish pre-study power calculations and effect sizes, including negative findings. Hypothesis-testing studies should be pre-registered and optimally raw data published. The current statistics lite educational approach for students that has sustained the widespread, spurious use of NHST should be phased out.
Studies using genome-wide platforms have yielded an unprecedented number of promising signals of association between genomic variants and human traits. This Review addresses the steps required to ...validate, augment and refine such signals to identify underlying causal variants for well-defined phenotypes. These steps include: large-scale exact replication across both similar and diverse populations; fine mapping and resequencing; determination of the most informative markers and multiple independent informative loci; incorporation of functional information; and improved phenotype mapping of the implicated genetic effects. Even in cases for which replication proves that an effect exists, confident localization of the causal variant often remains elusive.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Background
Estimates of community spread and infection fatality rate (IFR) of COVID‐19 have varied across studies. Efforts to synthesize the evidence reach seemingly discrepant conclusions.
Methods
...Systematic evaluations of seroprevalence studies that had no restrictions based on country and which estimated either total number of people infected and/or aggregate IFRs were identified. Information was extracted and compared on eligibility criteria, searches, amount of evidence included, corrections/adjustments of seroprevalence and death counts, quantitative syntheses and handling of heterogeneity, main estimates and global representativeness.
Results
Six systematic evaluations were eligible. Each combined data from 10 to 338 studies (9‐50 countries), because of different eligibility criteria. Two evaluations had some overt flaws in data, violations of stated eligibility criteria and biased eligibility criteria (eg excluding studies with few deaths) that consistently inflated IFR estimates. Perusal of quantitative synthesis methods also exhibited several challenges and biases. Global representativeness was low with 78%‐100% of the evidence coming from Europe or the Americas; the two most problematic evaluations considered only one study from other continents. Allowing for these caveats, four evaluations largely agreed in their main final estimates for global spread of the pandemic and the other two evaluations would also agree after correcting overt flaws and biases.
Conclusions
All systematic evaluations of seroprevalence data converge that SARS‐CoV‐2 infection is widely spread globally. Acknowledging residual uncertainties, the available evidence suggests average global IFR of ~0.15% and ~1.5‐2.0 billion infections by February 2021 with substantial differences in IFR and in infection spread across continents, countries and locations.
As the scientific enterprise has grown in size and diversity, we need empirical evidence on the research process to test and apply interventions that make it more efficient and its results more ...reliable. Meta-research is an evolving scientific discipline that aims to evaluate and improve research practices. It includes thematic areas of methods, reporting, reproducibility, evaluation, and incentives (how to do, report, verify, correct, and reward science). Much work is already done in this growing field, but efforts to-date are fragmented. We provide a map of ongoing efforts and discuss plans for connecting the multiple meta-research efforts across science worldwide.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The American College of Cardiology/American Heart Association (ACC/AHA) guidelines on assessment of cardiovascular risk and on treatment of blood cholesterol, which included recommendations for ...primary prevention with statins, came under intense criticism immediately with their release. Main concerns focused on flawed methods (problems with the risk calculation), ethics (conflicts of interest), and inferences (too many people offered treatment). The ACC and the AHA are among the most experienced organizations in medicine that develop guidelines. Their processes are meticulous, including transparent reporting of conflicts. Here, Ioannidis discusses the potential implications of the new cardiovascular guidelines.
Some of these deficiencies may be best solved by improving the RCT agenda rather than turning to RCD. For example, the cost of RCTs can be reduced substantially, allowing very large sample sizes and ...better representativeness of the enrolled populations, if simple, pragmatic megatrials are adopted and RCD are used for collecting outcome information.11,12 Nevertheless, such megatrials are uncommon, and thus observational RCD studies are used to fill the evidence gap. For uncommon conditions, even megatrials would have few patients to inform on outcomes in these subgroups. Studies using RCD can reach sample sizes that are 100- to 1000-fold bigger than the sample sizes of large trials. However, the planning and reporting for claims of subgroup differences in clinical research have been dismal, and most claims are not validated.13 For example, it remains unknown whether the treatment effect suggested by RCD studies involving patients over 80 years of age with modest renal impairment, hypertension and taking three other drugs would be more reliable than the average treatment effect suggested by an RCT that involved patients with none or few of these characteristics. Given the limited funds for RCTs, many important health care questions are not studied. Such evidence gaps could be addressed by a better RCT research agenda that prioritizes the use of pragmatic, patient-important outcomes14 and relevant head-to-head comparisons.5,15,16 Some comparative effectiveness evidence may also be accommodated by network meta-analyses of RCTs.5,15,17 However, even then, an exhaustive evaluation of treatment effects on mortality and other patientimportant outcomes (including major harms) with RCTs alone is unrealistic. Here, RCD could fill many evidence gaps. One may then decide that the RCD evidence is strong enough to lead to policy or guideline changes, or the RCD evidence may be used to guide the design of future RCTs. There are also situations where conducting RCTs would be unrealistic or perceived as unethical.18 We recently conducted an empirical analysis on how RCD studies try to complement RCTs to understand treatment effects.24 We assessed 337 RCD studies that investigated the comparative effectiveness of medical treatments on mortality. Seventy percent of these studies were incremental research that supplemented existing RCTs but did not fill fundamental knowledge gaps (i.e., questions never evaluated in RCTs). In only six (1.8%) of these RCD studies did the authors state that conducting RCTs on their research topic would be unethical, and in only 18 (5.3%) did they state that it would be difficult. Typically, investigators conducting the RCDs reasoned that RCT results had limited generalizability (37.6%), did not adequately address specific outcomes (31.9%) or certain populations (23.5%), or were inconclusive or inconsistent (25.8%).
The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study ...publication bias has been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. Until recently, outcome reporting bias has received less attention.
We review and summarise the evidence from a series of cohort studies that have assessed study publication bias and outcome reporting bias in randomised controlled trials. Sixteen studies were eligible of which only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Eleven of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7). In comparing trial publications to protocols, we found that 40-62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies.
Recent work provides direct empirical evidence for the existence of study publication bias and outcome reporting bias. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Measuring the seroprevalence of antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is central to understanding infection risk and fatality rates. We studied Coronavirus ...Disease 2019 (COVID-19)-antibody seroprevalence in a community sample drawn from Santa Clara County.
On 3 and 4 April 2020, we tested 3328 county residents for immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies to SARS-CoV-2 using a rapid lateral-flow assay (Premier Biotech). Participants were recruited using advertisements that were targeted to reach county residents that matched the county population by gender, race/ethnicity and zip code of residence. We estimate weights to match our sample to the county by zip, age, sex and race/ethnicity. We report the weighted and unweighted prevalence of antibodies to SARS-CoV-2. We adjust for test-performance characteristics by combining data from 18 independent test-kit assessments: 14 for specificity and 4 for sensitivity.
The raw prevalence of antibodies in our sample was 1.5% exact binomial 95% confidence interval (CI) 1.1-2.0%. Test-performance specificity in our data was 99.5% (95% CI 99.2-99.7%) and sensitivity was 82.8% (95% CI 76.0-88.4%). The unweighted prevalence adjusted for test-performance characteristics was 1.2% (95% CI 0.7-1.8%). After weighting for population demographics, the prevalence was 2.8% (95% CI 1.3-4.2%), using bootstrap to estimate confidence bounds. These prevalence point estimates imply that 53 000 95% CI 26 000 to 82 000 using weighted prevalence; 23 000 (95% CI 14 000-35 000) using unweighted prevalence people were infected in Santa Clara County by late March-many more than the ∼1200 confirmed cases at the time.
The estimated prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that COVID-19 was likely more widespread than indicated by the number of cases in late March, 2020. At the time, low-burden contexts such as Santa Clara County were far from herd-immunity thresholds.
To examine whether the age distribution of COVID-19 deaths and the share of deaths in nursing homes changed in the second versus the first pandemic wave.
We considered all countries that had at least ...4000 COVID-19 deaths occurring as of January 14, 2021, at least 200 COVID-19 deaths occurring in each of the two epidemic wave periods; and which had sufficiently detailed information available on the age distribution of these deaths. We also considered countries with data available on COVID-19 deaths of nursing home residents for the two waves.
Change in the second wave versus the first wave in the proportion of COVID-19 deaths occurring in people <50 years (“young deaths”) among all COVID-19 deaths and among COVID-19 deaths in people <70 years old; and change in the proportion of COVID-19 deaths in nursing home residents among all COVID-19 deaths.
Data on age distribution were available for 14 eligible countries. Individuals <50 years old had small absolute difference in their share of the total COVID-19 deaths in the two waves across 13 high-income countries (absolute differences 0.0–0.4%). Their proportion was higher in Ukraine, but it decreased markedly in the second wave. The proportion of young deaths was lower in the second versus the first wave (summary prevalence ratio 0.81, 95% CI 0.71–0.92) with large between-country heterogeneity. The proportion of young deaths among deaths <70 years did not differ significantly across the two waves (summary prevalence ratio 0.96, 95% CI 0.86–1.06). Eligible data on nursing home COVID-19 deaths were available for 11 countries. The share of COVID-19 deaths that were accounted by nursing home residents decreased in the second wave significantly and substantially in 8 countries (prevalence ratio estimates: 0.36 to 0.78), remained the same in Denmark and Norway and markedly increased in Australia.
In the examined countries, age distribution of COVID-19 deaths has been fairly similar in the second versus the first wave, but the contribution of COVID-19 deaths in nursing home residents to total fatalities has decreased in most countries in the second wave.
•Age distribution of COVID-19 deaths was fairly similar in the second vs first wave.•COVID-19 deaths in people <50 were uncommon and became more rare in the second wave.•Share of COVID-19 deaths among nursing home residents decreased in most countries.
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