Umbrella review and meta‐analysis of antiplatelet therapy for peripheral artery disease

Background The literature on antiplatelet therapy for peripheral artery disease has historically been summarized inconsistently, leading to conflict between international guidelines. An umbrella review and meta‐analysis was performed to summarize the literature, allow assessment of competing safety risks and clinical benefits, and identify weak areas for future research. Methods MEDLINE, Embase, DARE, PROSPERO and Cochrane databases were searched from inception until January 2019. All meta‐analyses of antiplatelet therapy in peripheral artery disease were included. Quality was assessed using AMSTAR scores, and GRADE analysis was used to quantify the strength of evidence. Data were pooled using random‐effects models. Results Twenty‐eight meta‐analyses were included. Thirty‐three clinical outcomes and 41 antiplatelet comparisons in 72 181 patients were analysed. High‐quality evidence showed that antiplatelet monotherapy reduced non‐fatal strokes (3 (95 per cent c.i. 0 to 6) fewer per 1000 patients), In symptomatic patients, it reduced cardiovascular deaths (8 (0 to 16) fewer per 1000 patients), but increased the risk of major bleeding (7 (3 to 14) more events per 1000). In asymptomatic patients, monotherapy reduced non‐fatal strokes (5 (0 to 8) fewer per 1000), but had no other clinical benefit. Dual antiplatelet therapy caused more major bleeding after intervention than monotherapy (37 (8 to 102) more events per 1000), with very low‐quality evidence of improved endovascular patency (risk ratio 4·00, 95 per cent c.i. 0·91 to 17·68). Conclusion Antiplatelet monotherapy has minimal clinical benefit for asymptomatic peripheral artery disease, and limited benefit for symptomatic disease, with a clear risk of major bleeding. There is a lack of evidence to guide antiplatelet prescribing after peripheral endovascular intervention

Systematic review and narrative synthesis of surgeons’ perception of postoperative outcomes and risk

Background The accuracy with which surgeons can predict outcomes following surgery has not been explored in a systematic way. The aim of this review was to determine how accurately a surgeon's ‘gut feeling’ or perception of risk correlates with patient outcomes and available risk scoring systems. Methods A systematic review was undertaken in accordance with PRISMA guidelines. A narrative synthesis was performed in accordance with the Guidance on the Conduct of Narrative Synthesis In Systematic Reviews. Studies comparing surgeons' preoperative or postoperative assessment of patient outcomes were included. Studies that made comparisons with risk scoring tools were also included. Outcomes evaluated were postoperative mortality, general and operation‐specific morbidity and long‐term outcomes. Results Twenty‐seven studies comprising 20 898 patients undergoing general, gastrointestinal, cardiothoracic, orthopaedic, vascular, urology, endocrine and neurosurgical operations were included. Surgeons consistently overpredicted mortality rates and were outperformed by existing risk scoring tools in six of seven studies comparing area under receiver operating characteristic (ROC) curves (AUC). Surgeons' prediction of general morbidity was good, and was equivalent to, or better than, pre‐existing risk prediction models. Long‐term outcomes were poorly predicted by surgeons, with AUC values ranging from 0·51 to 0·75. Four of five studies found postoperative risk estimates to be more accurate than those made before surgery. Conclusion Surgeons consistently overestimate mortality risk and are outperformed by pre‐existing tools; prediction of longer‐term outcomes is also poor. Surgeons should consider the use of risk prediction tools when available to inform clinical decision‐making. Introduction Surgical procedures all carry associated risks. It is therefore important that surgeons are able to make accurate predictions of potential benefit and risk, including immediate mortality and morbidity, as well as long‐term outcomes, to enable balanced decision‐making and fully informed consent. Risks can also be estimated after surgery, based on additional perioperative and intraoperative data, which allows contemporary prediction of outcome. There are numerous risk prediction models that enable the surgeon to quantify risk based on measurable parameters1-5. However, there are inherent limitations in using a generalized risk prediction model, which may not include clinical data pertinent to the individual case in question, leading to variability in model accuracy6-10. As a result, risk prediction tools are generally used in tandem with the surgeon's ‘gut feeling’ of overall risk and anticipated outcome (‘clinical gestalt’). Several disparate factors influence surgeons' perception of outcome: patient factors, such as their perceived fitness, their pathology and planned procedure; setting factors, such as the experience of other members of staff; and surgeon factors, such as clinical knowledge, operative skill, previous significant surgical complications, and inclinations and attitudes11-13. Anticipating surgical risk is subject to multiple biases, which make it challenging. These include the natural tendency toward anecdotal recall and the availability heuristic (the likelihood of making a decision based on how easily the topic or examples come to mind)14, 15. Some studies16-18 support the accuracy and reproducibility of surgeons' predictions, whereas others19-22 demonstrate less favourable results. The complexity of synthesizing risk perceptions is significant and incompletely understood23, 24. The accuracy of surgeons' prediction has not been explored previously in a systematic manner. The aim of this review was thus to determine, from the available evidence, whether a surgeon's gut feeling or perception of risk correlates with postoperative outcomes, and to compare this prediction with currently available risk scoring systems, where available. Methods This systematic review was undertaken in accordance with the PRISMA guidelines25, 26. MEDLINE (via PubMed), Embase, the Cochrane Library Database, and the Cochrane Collaboration Central Register of Controlled Clinical Trials were searched with no date or language restrictions, with the last search date on 9 July 2018. The search term used was (‘Surgeons’[Mesh] OR ‘General Surgery/manpower*’ [MeSH]) AND (‘perception’ OR ‘intuition’ OR ‘predict*’ OR ‘decision making’ [mesh]). There was no restriction on publication type. This search was complemented by an exhaustive review of the bibliography of key articles, and also by using the Related Articles function in PubMed of included papers. Results were restricted to human research published in English. Inclusion and exclusion criteria All studies of patients undergoing surgery in which a preoperative or postoperative surgeon assessment (or proxy assessment) of a postoperative outcome was performed were included. This included articles that reported general risk (such as mortality) or a surgery‐specific risk (for example anastomotic leakage). Studies that made comparisons with established risk scoring tools were also included. Papers or abstracts in English, or non‐English papers with an English abstract, were included. Papers describing the risk assessment of ‘theoretical’ cases, or patient vignettes in a situation distant from clinical practice (such as a conference), were excluded, as were studies in which surgeons' assessment of risk was compared with an established risk scoring tool, without data on actual patient outcome. Data extraction and assessment of study quality Three authors independently extracted data and assessed the methodological quality of the studies, with all data extraction independently checked by the senior author. The following baseline data were extracted from each study: first author, year of publication, data collection period, geographical location, study design and type (single or multiple centres, number of surgeons involved in risk estimation, whether consecutive patients were enrolled), surgical specialty, whether other risk scoring systems were used for comparison and, if so, whether the assessor was blinded to this result. Data extracted regarding the assessment of risk included: risk outcome assessed; timing of risk estimation (preoperative or postoperative); type of risk assessment by surgeons (qualitative, quantitative, continuous scale such as a visual analogue scale (VAS), or composite score); absolute value of risk event predicted by surgeon and by scoring system; absolute value of risk occurrence rate; summary data on outcome reported, including area under the curve (AUC) of receiver operating characteristic (ROC) curves, observed : expected (O : E) or predicted : observed (P : O) ratios, or any other summary data. When data were available, AUCs were extracted with their 95 per cent confidence intervals. AUCs greater than 0·9 were considered as indicating high performance, 0·7–0·9 as moderate performance, 0·5–0·7 as low performance, and less than 0·5 as indicating risk assessment no better than chance alone27, 28. Risk predictions made by pre‐existing tools, such as the Physiological and Operative Severity Score for the enumeration of Mortality and morbidity (POSSUM)1, Portsmouth‐POSSUM (P‐POSSUM)4 or Continuous Improvement in Cardiac Surgery Program (CICSP)5, were compared with outcome when given. Internal prediction models, where authors would derive significant predictive co‐variables from their data set and assess the accuracy of these co‐variables within the same data set, were not evaluated as they lacked validity. Study quality was assessed using the Newcastle–Ottawa (NO) score29, 30. The NO score assigns points based on: the quality of patient selection (maximum 4 points); comparability of the cohort (maximum 2 points); and outcome assessment (maximum 3 points). Studies that scored 6 points or more were considered to be of higher quality. Outcome measures The following outcome measures were defined a priori and refined during data extraction: postoperative mortality (usually defined as 30 days after surgery); postoperative general morbidity (usually defined as 30 days after surgery); postoperative procedure‐specific morbidity; and long‐term outcome (typically operation‐specific). Further comparative analyses of outcomes included comparison of preoperative and postoperative predictions, and of predictions made by consultants and surgical trainees. Narrative synthesis Given the marked heterogeneity in study design, patient population included, method of assessing risk and outcomes assessed, meta‐analysis was deemed not appropriate. A narrative synthesis was therefore performed according to the Guidance on the Conduct of Narrative Synthesis In Systematic Reviews31. Three authors systematically summarized each article using bullet points to document key aspects of each study, focusing particularly on methods used and results obtained. The validity and certainty of the results were noted (whether appropriate statistical comparisons were used and, if so, their effect size and significance). The senior author identified and grouped common themes, divided larger themes into subthemes, tabulated a combined summary of the paper, and synthesized a common rubric for each theme. Consolidated reviewers' comments can be found in Table S1 (supporting information). Results A total of 584 articles were identified from the literature search, of which 48 were retrieved for evaluation. Papers were excluded on the basis of being duplicates (1) and being irrelevant based on the title (497) and abstract (38) (Fig. 1). Twenty‐seven studies16-24, 32-49 comprising 20 898 patients met the inclusion criteria and were included in the narrative synthesis (Appendix S1, supporting information)

Guidelines for negotiating social research in communities living adjacent to transboundary protected areas: Kruger National Park

The objective with these Guidelines is to assist local people and social researchers to negotiate equitable research agreements. This document lays out the purpose of the guidelines, provides some background information about the process that led to this document, and provides some general principles and practical guidelines for social research in local communities. The Guidelines have their origins in a long process of consultation, discussion and exchange between social researchers and local people, which took place in South Africa over a period of three years (2005-2008). It draws on the substantial experience of people living adjacent to the Kruger National Park with research and researchers; also on the collective experience of the informal network of researchers that participated in the development of the guidelines. Local people have experienced research in positive and negative ways. Some communities in the area adjacent to the Kruger National Park can justifiably feel over-exposed to researchers, while others feel that opportunities and insights potentially generated by research passes them by. Yet even these often feel that some guidelines are required to avoid duplication and negative engagement. Important is to mention that the engagement between social researchers and communities is not a matter of these two groups alone. Many facilitating, structurating stakeholders such as NGOs, parastatals conservation organisations and government organisations, are important influencing players in this engagement. Therefore, while the guidelines focus specifically on researcher-community interactions, these other players should not be forgotten and should themselves be aware of their effects in these interactions. The guidelines outline opportunities and constraints that arise when local people and social researchers engage one another. The guidelines are not prescriptive, but raise issues and suggest ways in which these can be dealt with

Dairy Development Forum—Quo Vadis?

Irish Ai

How climate change affects extremes in maize and wheat yield in two cropping regions

Author Posting. © American Meteorological Society, 2015. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 28 (2015): 4653–4687, doi:10.1175/JCLI-D-13-00326.1.Downscaled climate model projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were used to force a dynamic vegetation agricultural model (Agro-IBIS) and simulate yield responses to historical climate and two future emissions scenarios for maize in the U.S. Midwest and wheat in southeastern Australia. In addition to mean changes in yield, the frequency of high- and low-yield years was related to changing local hydroclimatic conditions. Particular emphasis was on the seasonal cycle of climatic variables during extreme-yield years and links to crop growth. While historically high (low) yields in Iowa tend to occur during years with anomalous wet (dry) growing season, this is exacerbated in the future. By the end of the twenty-first century, the multimodel mean (MMM) of growing season temperatures in Iowa is projected to increase by more than 5°C, and maize yield is projected to decrease by 18%. For southeastern Australia, the frequency of low-yield years rises dramatically in the twenty-first century because of significant projected drying during the growing season. By the late twenty-first century, MMM growing season precipitation in southeastern Australia is projected to decrease by 15%, temperatures are projected to increase by 2.8°–4.5°C, and wheat yields are projected to decline by 70%. Results highlight the sensitivity of yield projections to the nature of hydroclimatic changes. Where future changes are uncertain, the sign of the yield change simulated by Agro-IBIS is uncertain as well. In contrast, broad agreement in projected drying over southern Australia across models is reflected in consistent yield decreases for the twenty-first century. Climatic changes of the order projected can be expected to pose serious challenges for continued staple grain production in some current centers of production, especially in marginal areas.This work was initiated at the Dissertations Initiative for the Advancement of Climate Change Research (DISCCRS) V Symposium, supported by the U.S. National Science Foundation through collaborative Grants SES-0932916 and SES-0931402. CCU was supported by a University of New South Wales Vice-Chancellor Fellowship and the Penzance Endowed Fund and John P. Chase Memorial Endowed Fund at WHOI. TET was supported by the U.S. Department of Energy Award DE-EE0004397. NC was funded by NSF Grant EAR-1204774. We are indebted to the FORMAS-funded Land Use Today and Tomorrow (LUsTT) project (Grant 211-2009-1682) for financial support

Robotic milking technologies and renegotiating situated ethical relationships on UK dairy farms

Robotic or automatic milking systems (AMS) are novel technologies that take over the labor of dairy farming and reduce the need for human-animal interactions. Because robotic milking involves the replacement of 'conventional' twice-a-day milking managed by people with a system that supposedly allows cows the freedom to be milked automatically whenever they choose, some claim robotic milking has health and welfare benefits for cows, increases productivity, and has lifestyle advantages for dairy farmers. This paper examines how established ethical relations on dairy farms are unsettled by the intervention of a radically different technology such as AMS. The renegotiation of ethical relationships is thus an important dimension of how the actors involved are re-assembled around a new technology. The paper draws on in-depth research on UK dairy farms comparing those using conventional milking technologies with those using AMS. We explore the situated ethical relations that are negotiated in practice, focusing on the contingent and complex nature of human-animal-technology interactions. We show that ethical relations are situated and emergent, and that as the identities, roles, and subjectivities of humans and animals are unsettled through the intervention of a new technology, the ethical relations also shift. © 2013 Springer Science+Business Media Dordrecht