George Davey Smith

Bio: George Davey Smith is an academic researcher from University of Bristol. The author has contributed to research in topics: Population & Mendelian randomization. The author has an hindex of 224, co-authored 2540 publications receiving 248373 citations. Previous affiliations of George Davey Smith include Keele University & Western Infirmary.

Effect of conjugal bereavement on mortality of the bereaved spouse in participants of the Renfrew/Paisley Study

Abstract: Objectives: To investigate how loss of a spouse affects mortality risk in the bereaved partner. Design and setting: Prospective cohort study in Renfrew and Paisley in Scotland. Participants: 4395 married couples aged 45–64 years when the study was carried out between 1972 and 1976. Methods: The date of bereavement for the bereaved spouse was the date of death of his or her spouse. Bereavement could occur at any time during the follow-up period, so it was considered as a time-dependent exposure variable and the Cox proportional hazards model for time-dependent variables was used. The relative rate (RR) of mortality was calculated for bereaved versus non-bereaved spouses and adjusted for confounding variables. Main outcome measures: Causes of death to 31 March 2004. Results: Bereaved participants were at higher risk than non-bereaved participants of dying from any cause (RR 1.27; 95% CI 1.2 to 1.35). These risks remained but were attenuated after adjustment for confounding variables. There were raised RRs for bereaved participants dying of cardiovascular disease, coronary heart disease, stroke, all cancer, lung cancer, smoking-related cancer, and accidents or violence. After adjustment for confounding variables, RRs remained higher for bereaved participants for all these causes except for mortality from lung cancer. There was no strong statistical evidence that the increased risks of death associated with bereavement changed with time after bereavement. Conclusions: Conjugal bereavement, in addition to existing risk factors, is related to mortality risk for major causes of death.

New Measurements of High-Momentum Nucleons and Short-Range Structures in Nuclei

Abstract: We present new measurements of electron scattering from high-momentum nucleons in nuclei. These data allow an improved determination of the strength of two-nucleon correlations for several nuclei, including light nuclei where clustering effects can, for the first time, be examined. The data also include the kinematic region where three-nucleon correlations are expected to dominate.

Evolutionary constructive induction

Abstract: Feature construction in classification is a preprocessing step in which one or more new attributes are constructed from the original attribute set, the object being to construct features that are more predictive than the original feature set. Genetic programming allows the construction of nonlinear combinations of the original features. We present a comprehensive analysis of genetic programming (GP) used for feature construction, in which four different fitness functions are used by the GP and four different classification techniques are subsequently used to build the classifier. Comparisons are made of the error rates and the size and complexity of the resulting trees. We also compare the overall performance of GP in feature construction with that of GP used directly to evolve a decision tree classifier, with the former proving to be a more effective use of the evolutionary paradigm.

GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI.

Abstract: Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.

Prevention indicators for evaluating the progress of national AIDS programmes.

Abstract: Major interventions to reduce HIV transmission involve increasing knowledge about preventing HIV transmission for sustained behavioral changes; and enhancing the control of sexually transmitted diseases (STD) which increase the probability of HIV transmission. Activities have also been developed to prevent the transmission of HIV by blood donor selection and more rational use of transfusions. Behavioral changes among injecting drug users have also been promoted. Recommendations are made for the evaluation of AIDS programs focusing on prevention of sexual transmission of HIV and outlining the approach developed by the Global Program on AIDS (GPA; Geneva Switzerland) for use by national programs. Based on the feasibility accuracy reliability and validity of the quantitative assessment of programs 10 indicators of progress and outcomes of prevention activities have been developed by GPA. These include indicators of population knowledge regarding preventive practices reported sexual behavior and use of condoms in the general population STD service evaluation and indicators of program impact. The latter are measured through the reported STD incidence in the general male population and syphilis and HIV prevalence in women. The four methods are proposed for measuring the 10 core prevention indicators (PI). Five PIs are measured during a population survey: reported knowledge of preventive practices (PI-1) condom availability at peripheral level (PI-3) reported frequency of nonregular sexual partners (PI-4) reported condom use during nonregular sexual encounters (PI-5) and reported STD incidence among men (PI-9). Condom availability at central level (PI-2) is assessed through key-informant interviews with major distributors. Structured health facility surveys allow assessment of the appropriateness of STD case management (PI-6 and PI-7). A serosurvey among antenatal clinic attenders aged 15-24 years allows the measurement of HIV and syphilis seroprevalence in that population (PI-8 and PI-10). GPA recommends that such surveys be repeated after a period of 1 to several years.

Measuring inconsistency in meta-analyses

Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …

Bias in meta-analysis detected by a simple, graphical test

Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure

The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration

Abstract: Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement—a reporting guideline published in 1999—there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

Abstract: Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate