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As discussed in the introduction, there were many differences in the diet heart trials that were not related to SFA or mostly n-6 PUFA intake. In all of the diet heart trials the dietary advice or foods provided to participants would be expected to result in a lower TFA intake in the experimental group compared to the control group, particularly in ODHS, NDHS and HDAT. However, it is debated whether the experimental group in SDHS may have had a higher intake of TFA due to the use of a margarine that was potentially high in TFA. Furthermore, ODHS and STARS used a multifactorial dietary intervention, the control group in LAVAT had an insufficient vitamin E intake that was also 9.4-fold lower than the experimental group, and the control group in FMHS was prescribed more cardiotoxic medication on average. Therefore, to account for these differences, the clinical trials in this meta-analysis were categorised as ‘adequately controlled’ or ‘inadequately controlled’ and were subject to different subgroup analyses. Clinical trials categorised as adequately controlled are those that most accurately test the effect of replacing SFA with mostly n-6 PUFA, while the clinical trials categorised as inadequately controlled have too many dietary and/or non-dietary differences between the groups to be considered a valid test of replacing SFA with mostly n-6 PUFA. The clinical trials categorised as inadequately controlled include ODHS, NDHS, LAVAT, FMHS, HDAT, and STARS due to reasons discussed in the introduction and summarised above. The remaining trials, including RCOT, MRCT, SDHS, MCS, and DART, were categorised as adequately controlled. Due to debate over whether TFA intake in the SDHS experimental group was higher or lower than the control group, this trial was excluded in a sensitivity analysis of the adequately controlled trials.

MCS and FMHS reported their results as the number of events/deaths per 1000 person years, or per age-adjusted 1000 person years in the case of CHD mortality and total mortality in FMHS. Calculating the risk ratio (RR) using person years is important to do as the participants in those trials were patients in mental hospitals who could be discharged and readmitted, and any events/deaths that occurred during their absence would go unreported. The difference between calculating the RR using number of participants in each group rather than using person years is quite low in MCS [ 26 ], whereas in FMHS calculating the RR using the number of participants in each group often substantially underestimates the RR [ 30 , 57 ]. The RevMan software automatically calculates the RR using the number of events and participants in each group that has been entered. Therefore the value entered for number of participants in each group has been altered to produce the correct RR when measured using person years or age-adjusted person years, but equal to the total number of participants in the trial so as to not affect the weighting of the trial. This was done by using the following equations. The equation for the RR using person years, where E is events/deaths and PY is person years, is: RR = (E∕PY)∕(E∕PY). To not affect the weighting, the total number of person years needs to equal the total number of participants: PY + PY = N + N. Therefore: PY = (N + N)∕(1 + (RR x E∕E)); and PY = (N + N)∕(1 + (E∕(E x RR)))

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Worldwide emergence of resistance to antifungal drugs challenges human health and food security

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18 May 2018: Vol. 360, Issue 6390, pp. 739-742 DOI: 10.1126/science.aap7999
Matthew C. Fisher
MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London W2 1PG, UK.
Nichola J. Hawkins
Department of Biointeractions and Crop Protection, Rothamsted Research, Harpenden AL5 2JQ, UK.
Dominique Sanglard
Institute of Microbiology, University of Lausanne and University Hospital, Lausanne CH-1011, Switzerland.
Sarah J. Gurr
Department of BioSciences, University of Exeter, Exeter EX4 4QD, UK. Department of BioSciences, Utrecht University, Paduallaan 8, Netherlands.

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Abstract

The recent rate of emergence of pathogenic fungi that are resistant to the limited number of commonly used antifungal agents is unprecedented. The azoles, for example, are used not only for human and animal health care and crop protection but also in antifouling coatings and timber preservation. The ubiquity and multiple uses of azoles have hastened the independent evolution of resistance in many environments. One consequence is an increasing risk in human health care from naturally occurring opportunistic fungal pathogens that have acquired resistance to this broad class of chemicals. To avoid a global collapse in our ability to control fungal infections and to avoid critical failures in medicine and food security, we must improve our stewardship of extant chemicals, promote new antifungal discovery, and leverage emerging technologies for alternative solutions.

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Vol 360, Issue 639018 May 2018

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Worldwide emergence of resistance to antifungal drugs challenges human health and food security

By Matthew C. Fisher , Nichola J. Hawkins , Dominique Sanglard , Sarah J. Gurr

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