Is decoupling GDP growth from environmental impact possible?

© 2016 Ward et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The argument that human society can decouple economic growth-defined as growth in Gross Domestic Product (GDP)-from growth in environmental impacts is appealing. If such decoupling is possible, it means that GDP growth is a sustainable societal goal. Here we show that the decoupling concept can be interpreted using an easily understood model of economic growth and environmental impact. The simple model is compared to historical data and modelled projections to demonstrate that growth in GDP ultimately cannot be decoupled from growth in material and energy use. It is therefore misleading to develop growth-oriented policy around the expectation that decoupling is possible. We also note that GDP is increasingly seen as a poor proxy for societal wellbeing. GDP growth is therefore a questionable societal goal. Society can sustainably improve wellbeing, including the wellbeing of its natural assets, but only by discarding GDP growth as the goal in favor of more comprehensive measures of societal wellbeing

Elevational Spatial Compounding for enhancing image quality in Echocardiography

INTRODUCTION: Echocardiography is commonly used in clinical practice for the real-time assessment of cardiac morphology and function. Nevertheless, due to the nature of the data acquisition, cardiac ultrasound images are often corrupted by a range of acoustic artefacts, including acoustic noise, speckle and shadowing. Spatial compounding techniques have long been recognised for their ability to suppress common ultrasound artefacts, enhancing the imaged cardiac structures. However, they require extended acquisition times as well as accurate spatio-temporal alignment of the compounded data. Elevational spatial compounding acquires and compounds adjacent partially decorrelated planes of the same cardiac structure. METHODS: This paper employs an anthropomorphic left ventricle phantom to examine the effect of acquisition parameters, such as inter-slice angular displacement and 3D sector angular range, on the elevational spatial compounding of cardiac ultrasound data. RESULTS AND CONCLUSION: Elevational spatial compounding can produce substantial noise and speckle suppression as well as visual enhancement of tissue structures even for small acquisition sector widths (2.5° to 6.5°). In addition, elevational spatial compounding eliminates the need for extended acquisition times as well as the need for temporal alignment of the compounded datasets. However, moderate spatial registration may still be required to reduce any tissue/chamber blurring side effects that may be introduced

The importance of adjusting for potential confounders in Bayesian hierarchical models synthesising evidence from randomised and non-randomised studies: an application comparing treatments for abdominal aortic aneurysms

<p>Abstract</p> <p>Background</p> <p>Informing health care decision making may necessitate the synthesis of evidence from different study designs (e.g., randomised controlled trials, non-randomised/observational studies). Methods for synthesising different types of studies have been proposed, but their routine use requires development of approaches to adjust for potential biases, especially among non-randomised studies. The objective of this study was to extend a published Bayesian hierarchical model to adjust for bias due to confounding in synthesising evidence from studies with different designs.</p> <p>Methods</p> <p>In this new methodological approach, study estimates were adjusted for potential confounders using differences in patient characteristics (e.g., age) between study arms. The new model was applied to synthesise evidence from randomised and non-randomised studies from a published review comparing treatments for abdominal aortic aneurysms. We compared the results of the Bayesian hierarchical model adjusted for differences in study arms with: 1) unadjusted results, 2) results adjusted using aggregate study values and 3) two methods for downweighting the potentially biased non-randomised studies. Sensitivity of the results to alternative prior distributions and the inclusion of additional covariates were also assessed.</p> <p>Results</p> <p>In the base case analysis, the estimated odds ratio was 0.32 (0.13,0.76) for the randomised studies alone and 0.57 (0.41,0.82) for the non-randomised studies alone. The unadjusted result for the two types combined was 0.49 (0.21,0.98). Adjusted for differences between study arms, the estimated odds ratio was 0.37 (0.17,0.77), representing a shift towards the estimate for the randomised studies alone. Adjustment for aggregate values resulted in an estimate of 0.60 (0.28,1.20). The two methods used for downweighting gave odd ratios of 0.43 (0.18,0.89) and 0.35 (0.16,0.76), respectively. Point estimates were robust but credible intervals were wider when using vaguer priors.</p> <p>Conclusions</p> <p>Covariate adjustment using aggregate study values does not account for covariate imbalances between treatment arms and downweighting may not eliminate bias. Adjustment using differences in patient characteristics between arms provides a systematic way of adjusting for bias due to confounding. Within the context of a Bayesian hierarchical model, such an approach could facilitate the use of all available evidence to inform health policy decisions.</p

Bayesian Hierarchical Models Combining Different Study Types and Adjusting for Covariate Imbalances: A Simulation Study to Assess Model Performance

BACKGROUND: Bayesian hierarchical models have been proposed to combine evidence from different types of study designs. However, when combining evidence from randomised and non-randomised controlled studies, imbalances in patient characteristics between study arms may bias the results. The objective of this study was to assess the performance of a proposed Bayesian approach to adjust for imbalances in patient level covariates when combining evidence from both types of study designs. METHODOLOGY/PRINCIPAL FINDINGS: Simulation techniques, in which the truth is known, were used to generate sets of data for randomised and non-randomised studies. Covariate imbalances between study arms were introduced in the non-randomised studies. The performance of the Bayesian hierarchical model adjusted for imbalances was assessed in terms of bias. The data were also modelled using three other Bayesian approaches for synthesising evidence from randomised and non-randomised studies. The simulations considered six scenarios aimed at assessing the sensitivity of the results to changes in the impact of the imbalances and the relative number and size of studies of each type. For all six scenarios considered, the Bayesian hierarchical model adjusted for differences within studies gave results that were unbiased and closest to the true value compared to the other models. CONCLUSIONS/SIGNIFICANCE: Where informed health care decision making requires the synthesis of evidence from randomised and non-randomised study designs, the proposed hierarchical Bayesian method adjusted for differences in patient characteristics between study arms may facilitate the optimal use of all available evidence leading to unbiased results compared to unadjusted analyses

Reporting of prognostic markers: current problems and development of guidelines for evidence-based practice in the future

Prognostic markers help to stratify patients for treatment by identifying patients with different risks of outcome (e.g. recurrence of disease), and are important tools in the management of cancer and many other diseases. Systematic review and meta-analytical approaches to identifying the most valuable prognostic markers are needed because (sometimes conflicting) evidence relating to markers is often published across a number of studies. To investigate the practicality of this approach, an empirical investigation of a systematic review of tumour markers for neuroblastoma was performed; 260 studies of prognostic markers were identified, which considered 130 different markers

Large scale patterns in vertical distribution and behavior of mesopelagic scattering layers

Recent studies suggest that previous estimates of mesopelagic biomasses are severely biased, with the new, higher estimates underlining the need to unveil behaviourally mediated coupling between shallow and deep ocean habitats. We analysed vertical distribution and diel vertical migration (DVM) of mesopelagic acoustic scattering layers (SLs) recorded at 38 kHz across oceanographic regimes encountered during the circumglobal Malaspina expedition. Mesopelagic SLs were observed in all areas covered, but vertical distributions and DVM patterns varied markedly. The distribution of mesopelagic backscatter was deepest in the southern Indian Ocean (weighted mean daytime depth: WMD 590 m) and shallowest at the oxygen minimum zone in the eastern Pacific (WMD 350 m). DVM was evident in all areas covered, on average ~50% of mesopelagic backscatter made daily excursions from mesopelagic depths to shallow waters. There were marked differences in migrating proportions between the regions, ranging from ~20% in the Indian Ocean to ~90% in the Eastern Pacific. Overall the data suggest strong spatial gradients in mesopelagic DVM patterns, with implied ecological and biogeochemical consequences. Our results suggest that parts of this spatial variability can be explained by horizontal patterns in physical-chemical properties of water masses, such as oxygen, temperature and turbidity.En prensa2,927

Methods for specifying the target difference in a randomised controlled trial : the Difference ELicitation in TriAls (DELTA) systematic review

Peer reviewedPublisher PD

Histopathological grading of pediatric ependymoma: reproducibility and clinical relevance in European trial cohorts

<p>Abstract</p> <p>Background</p> <p>Histopathological grading of ependymoma has been controversial with respect to its reproducibility and clinical significance. In a 3-phase study, we reviewed the pathology of 229 intracranial ependymomas from European trial cohorts of infants (2 trials - SFOP/CNS9204) and older children (2 trials - AIEOP/CNS9904) to assess both diagnostic concordance among five neuropathologists and the prognostic utility of histopathological variables, particularly tumor grading.</p> <p>Results</p> <p>In phase 1, using WHO criteria and without first discussing any issue related to grading ependymomas, pathologists assessed and independently graded ependymomas from 3 of 4 trial cohorts. Diagnosis of grade II ependymoma was less frequent than grade III, a difference that increased when one cohort (CNS9204) was reassessed in phase 2, during which the pathologists discussed ependymoma grading, jointly reviewed all CNS9204 tumors, and defined a novel grading system based on the WHO classification. In phase 3, repeat independent review of two cohorts (SFOP/CNS9904) using the novel system was associated with a substantial increase in concordance on grading. Extent of tumor resection was significantly associated with progression-free survival (PFS) in SFOP and AIEOP, but not in CNS9204 and CNS9904. Strength of consensus on grade was significantly associated with PFS in only one trial cohort (AIEOP). Consensus on the scoring of individual histopathological features (necrosis, angiogenesis, cell density, and mitotic activity) correlated with PFS in AIEOP, but in no other trial.</p> <p>Conclusions</p> <p>We conclude that concordance on grading ependymomas can be improved by using a more prescribed scheme based on the WHO classification. Unfortunately, this appears to have utility in limited clinical settings.</p