Prior to investing in a large, multicentre randomised controlled trial (RCT), the National Institute for Health Research in the UK called for an evaluation of the feasibility and value for money of undertaking a trial on intravenous immunoglobulin (IVIG) as an adjuvant therapy for severe sepsis/septic shock.In response to this call, this study assessed the clinical and cost-effectiveness of IVIG (using a decision model), and evaluated the value of conducting an RCT  analysis). The evidence informing such assessments was obtained through a series of systematic reviews and meta-analyses. Further primary data analyses were also undertaken using the Intensive Care National Audit & Research Centre Case Mix Programme Database, and a Scottish Intensive Care Society research study.We found a large degree of statistical heterogeneity in the clinical evidence on treatment effect, and the source of such heterogeneity was unclear. The incremental cost-effectiveness ratio of IVIG is within the borderline region of estimates considered to represent value for money, but results appear highly sensitive to the choice of model used for clinical effectiveness. This was also the case with EVI estimates, with maximum payoffs from conducting a further clinical trial between £137 and £1,011 million.Our analyses suggest that there is a need for a further RCT. Results on the value of conducting such research, however, were sensitive to the clinical effectiveness model used, reflecting the high level of heterogeneity in the evidence base. Sepsis is a clinical syndrome defined by the presence of both infection and a systemic inflammatory response; sepsis is defined as severe when associated with, or complicated by, organ dysfunction . Severe Intravenous immunoglobulin (IVIG) is a scarce blood product derived from human donor blood; it is currently subject to a Demand Management Programme by the United Kingdom (UK) Department of Health . This prPrior to investing in a large, multicentre RCT, the Health Technology Assessment (HTA) Programme of the National Institute for Health Research in the UK called for an evaluation of the feasibility and value for money of undertaking such a trial . The aim of this manuscript is to report our findings in response to this call by assessing the clinical and cost-effectiveness of IVIG in severe sepsis/septic shock in adults, and evaluating the value of conducting a large, multicentre RCT using an expected value of information (EVI) analysis. EVI offers a methodological framework that explicitly considers the uncertainty surrounding the decision by a healthcare system to adopt a health technology and values the additional information, which may be generated by further research, in a way that is consistent with the objectives and resource constraints of heathcare provision .A full technical report of this research is published elsewhere . Here, wWe conducted a series of formal systematic reviews and undertook additional primary data analysis to develop and populate a decision analytic model. Details of each review and data sources are presented in the full technical report . The decThe decision model evaluated costs from the perspective of the NHS and Personal Social Services (PSS), and expressed these in British pounds sterling at a 2009 price base. Outcomes were expressed in quality-adjusted life years (QALYs). Both costs and outcomes were discounted using a 3.5% annual discount rate, in line with current guidelines . The modThe probabilistic analysis also provided a formal approach to quantifying the consequences associated with the uncertainty surrounding the model results, which were then used to inform the EVI analyses. The maximum amount the NHS should be willing to invest to reduce uncertainty in the decision can be informed by the expected value of perfect information (EVPI) ,14. The n*, for the proposed trial is where the ENBS reaches its maximum. This optimal sample size thus indicates how many patients should be enrolled for the trial to provide the highest payoff.The EVPI estimates set an upper limit on the returns to further research. However, to fully inform the research decision, the most efficient research design also needs to be established, for example, the type of study, the optimal sample size, the appropriate duration of follow-up and appropriate end points. The same framework of analyses can be extended to establish the expected value of sample information (EVSI) for a particular research design. To obtain the societal payoff to the proposed research, the population EVSI needs to be compared with the costs of sampling: the difference between the EVSI and the costs of sampling gives the expected net benefit of sampling (ENBS). The ENBS provides a necessary and sufficient condition for deciding to conduct more research that is, if the ENBS is greater than zero for any sample size then the benefits of gathering the sample information exceed the costs, and further research is potentially justified. The ENBS also provides a framework for the efficient design of the clinical trial, where the optimal sample size, All stages of the work were informed through discussions with an expert clinical advisory group who provided feedback on specific aspects of the analyses including the model structure, inputs and assumptions.i.short-term: the short-term consequences of the initial severe sepsis episode reflected the initial acute hospitalisation period  and related to the probability of surviving the initial acute hospitalisation. Baseline data from the CMPD were used to estimate the risk of acute hospital mortality associated with SC and the results of a systematic review of the clinical effectiveness of IVIG were applied to estimate the risk of acute hospital mortality associated with IVIG.ii.longer-term: conditional on having survived the initial acute hospitalisation, a Markov structure was used to characterise the long-term prognosis over the remainder of a patient’s lifetime. Such a model represents disease progression by defining important mutually exclusive events/health states and characterising how patients may move between states over regular time intervals. Here, we used a simple structure to represent the possibility of patients being alive or dead . Annual cycles were employed to reflect the annual probability of death for each year after the initial severe sepsis episode. Duration of stay alive or transition to death can be associated with a quality of life score and with costs incurred, allowing for long-term QALYs and costs to be evaluated. If IVIG reduces the risk of mortality during the initial acute hospitalisation period, then the use of this longer-term model will allow differences in long-term costs and QALYs to be translated.A simplified schematic of the structure of the decision model is presented in Figure The model was developed in the statistical programming package R .Evidence on the effectiveness of IVIG was sought and used to inform the decision model and further analyses. A systematic review of the literature was conducted to inform the effect of IVIG in severe sepsis on all-cause mortality during the initial acute hospitalisation. Full details of the methods of the systematic review are reported in the full technical report . In summ2, and Cochrans Q test. Stata, version 11.0 , was used.The primary outcome measure extracted was all-cause mortality, summarised on the odds ratio (OR) scale. Fixed- and random-effects meta-analyses were fitted using inverse variance weights. Heterogeneity was assessed using Iet al. [Heterogeneity was further explored comparing model fit from meta-regressions, estimated through Bayesian  Markov cet al. . Resultset al. . The poset al. . For theData from the CMPD  were used to inform the baseline risk of acute hospital mortality applied to SC during the initial hospitalisation. Mortality risk was estimated by conditioning on characteristics of patients and the severity of illness at presentation: age and gender; Acute Physiology and Chronic Health Evaluation II (APACHE II) score; ICNARC physiology score and number of dysfunctional organ systems. Logistic regressions (robust standard errors (SEs) adjusting for clustering on critical care unit) were used.We undertook additional primary data analysis to inform the longer-term survival estimates for severe sepsis survivors based on a cohort of 345 subjects from the Scottish Intensive Care Society (SICS) prospective, observational, multicentre, epidemiological study of severe sepsis . Only paParametric survival analyses were undertaken to estimate longer-term mortality (goodness of fit was assessed using Akaike information criterion (AIC) statistics). Three separate models were fitted including additional covariates for: age; APACHE II score at admission; and organ system dysfunction. The covariates were included to adjust for potential imbalances between the baseline characteristics from the CMPD  and the SICS study cohort. Also, these covariates allowed for consideration of subgroup-specific estimates for longer-term survival.The length of stay (LOS) during the index severe sepsis episode (from the CMPD) was used to cost the acute hospital stay. Unit costs were derived from national databases. A summary of the information used is presented in Table Table I2 = 46.9%), a random-effects model fitted the data well while the fixed-effect model showed substantial lack of fit. The pooled OR from the random-effects model was 0.47 (95% CI 0.32 to 0.69), showing a stronger effect than the fixed-effect model .Seventeen studies were identified that met the inclusion criteria with a large degree of heterogeneity in treatment effect between studies -40. Figu−1 day−1), volume (ml kg−1 day−1)); and study quality . These two key covariates explained the majority of the heterogeneity in treatment effect across the studies. Further detail on these analyses is presented in the full technical report [From the meta-regression analyses, key covariates appearing to explain the existing heterogeneity between studies were: dosing regimen (duration of treatment (days), daily dose , the majority of results were fairly comparable and still showed a reduction in the odds of all-cause mortality in patients with severe sepsis treated with IVIG but the 95% CrI widened suggesting a larger degree of uncertainty. The only exception was model M4b, which reported an increase in the odds of all-cause mortality, albeit with very wide credible intervals. However, some caution should be applied to this result since it involves extrapolation beyond the available data. In the absence of a single best-fitting model that made clinical sense, sensitivity analyses were subsequently used in the cost-effectiveness modelling.Model input parameters and uncertainty around their estimates are described in Table With respect to resource use, we obtained estimates from the literature of total costs per annum and used these to describe costs after discharge from the index acute hospitalization . The eviTable For the alternative clinical effectiveness models, the ICER estimates vary between £16,177 per QALY to IVIG being dominated by SC alone (that is IVIG being both less effective and more costly). These results clearly demonstrate that any conclusions regarding the cost-effectiveness of IVIG appear highly sensitive to the choice of model used for clinical effectiveness. Furthermore, the level of decision uncertainty, expressed in terms of the probability that IVIG is cost-effective, remains high across all these scenarios.Table Figure n*, for a proposed trial are reported in Table The population ENBS and the optimal sample size, Despite the existence of a large number of RCTs and numerous previous systematic reviews and meta-analyses of the relative effectiveness of IVIG, there remains controversy surrounding the value of IVIG as an adjunctive treatment in severe sepsis. Our study is the first to combine a formal systematic review of clinical effectiveness together with other epidemiological, resource use and quality of life data in order to robustly assess both the cost-effectiveness of IVIG based on existing evidence as well as the value of conducting further research.Within this work, we re-analysed existing relative effectiveness RCT evidence and conducted a new meta-analysis, the first to simultaneously allow for type of IVIG (IVIG or IVIGAM), choice of control , study quality/publication bias and other potential covariates. Our results indicated that treatment with IVIG may be associated with lower mortality but the evidence base shows a large degree of heterogeneity between individual studies. Given it was unclear what was the relevant source of heterogeneity in the evidence base, alternative clinical effectiveness models were evaluated.Our results on the cost-effectiveness of IVIG appear within the borderline region of estimates considered to represent value for money in the NHS, but these results are associated with significant decision uncertainty and appear highly sensitive to the alternative clinical effectiveness models applied. Using an expected value of information framework, we established the value of collecting further information. Results show that a study collecting data on the relative effectiveness of IVIG (in comparison with standard care) appeared the most efficient research design to invest in. However, results on the value of conducting such research were also sensitive to the clinical effectiveness model used. Given that it was unclear what the clinical rationale for the effects explored was within each of the clinical effectiveness models and that the need for a further RCT exists, designing this study will be complex when uncertainties exist at this level.Our study did not find evidence that current guidance on the use of IVIG should change . Although the EVI analyses suggested substantial potential value from a large, multicentre RCT evaluating the clinical effectiveness of IVIG in this population, there remain significant uncertainties around the design of a study . Without greater understanding of the existing variation , there is a danger of investing in a large trial that is suboptimal (for example including a number of different dosing regimens), which may be a less efficient use of resources than deferring a definitive trial until we better understand the existing variation. Thus, our current recommendations are for research that focuses on filling the knowledge gaps that exist with a view to informing the design of a future multicentre RCT. These recommendations include: (i) research on the mechanism(s) of action of IVIG in severe sepsis (and on understanding the heterogeneity of the severe sepsis syndrome) - commencing with a rigorous review of existing research prior to embarking on any new studies and; (ii) dose-ranging/finding studies to identify dose, timing of dose and safety data to inform the intervention(s).In addition to clarifying the results on clinical effectiveness, it may be that research informing other parameters is also worthwhile, especially with respect to data on the longer-term survival and costs of severe sepsis. This research could be conducted using relatively cheaper, non-RCT designs, for example using record linkage between existing databases or conducting a prospective cohort study providing that the period for which patients are observed is sufficiently long enough to capture the impact on costs for several years after the initial episode.Our study examined the evidence for the clinical effectiveness of IVIG in severe sepsis (including septic shock) and found significant heterogeneity (variation) between studies. An in-depth look at the potential sources for the heterogeneity identified publication bias and dosing regimen as possible explanatory factors. The rationale for the latter being a relevant factor was unclear, and for this reason we examined the implications of the existing heterogeneity and concluded it affected both the potential clinical and cost-effectiveness of this treatment and, hence, current recommendations for its use.We assessed the value of a new, large, multicentre RCT to evaluate the clinical and cost-effectiveness of IVIG in this population and, while our analyses suggest that such research may be of value, there remains significant uncertainties around the design for such a study . We concluded that, prior to investing in a new RCT, further research is needed both into the mechanism(s) of action of IVIG and from a dose-ranging/finding study.Our work illustrates the use of an explicit framework to quantify the value of investing in new research. This work also highlights that explicit consideration of the sources of heterogeneity in the current evidence base is key to informing the design of new research.The effect of IVIG on mortality is associated with a large degree of heterogeneity between individual studies. It was unclear what the relevant source of heterogeneity in the evidence base was.The cost-effectiveness of IVIG appears within the borderline region of estimates considered to represent value for money in the NHS, but these results are associated with significant uncertainty and appear highly sensitive to the alternative clinical effectiveness models applied.Collecting data on the relative effectiveness of IVIG appears an efficient research design in which to invest. However, the unclear clinical rationale for the heterogeneity in the evidence base suggests that, despite the need for a further RCT, designing this study will be complex when uncertainties exist at this level.


Oxygenates formed as by-products of Fischer-Tropsch syntheses can be transformed into other Fischer-Tropsch derived oxygenates instead of treating them as unwanted chemicals. One-step direct synthesis of ethyl acetate from ethanol is feasible with the use of some heterogeneous catalysts. Despite their apparent simplicity, both transformations are discussed as targeted fields of research. Furthermore, the two concepts are justified due to the environmental protection. Arguments regarding the Fischer-Tropsch process are focused on the opportunities of the utilization of undesirable by-products. The effective striving for their utilization can make the oxygenates the targeted products of this process. Arguments regarding the one-step direct synthesis of ethyl acetate underline the environmental protection and sustainability as a less waste-generating method but, above all, highlight the possibility of reducing the glycerol overproduction problem. The production of ethyl acetate from bioethanol and then transesterification of fats and oils with the use of ethyl acetate allows managing all the renewable raw materials. Thus, the process enables the biosynthesis of biodiesel without glycerine by-product and potentially would result in the increase in the demand for ethyl acetate.The online version of this article (doi:10.1186/s13065-014-0077-9) contains supplementary material, which is available to authorized users. Oxygenates are organic oxygen compounds – common oxygenated hydrocarbon derivatives. Their definition is vague although intuitively obvious – e.g. simple ethers rather than sugars. Therefore, it can be thought that simple research on transformation of oxygenates is inexpedient as it has already been performed and is generally known while the research work has moved towards more advanced structures. It is true only to certain extent. The purposefulness of the studies on transformations of certain oxygenates into other ones is justified by dynamic changes in their interdependence. In order to visualize the purposefulness of studies on the catalytic conversion of oxygenates some examples are presented hereinafter.Here is a simple model showing why even advanced studies concerning a simple issue require some modifications over time.In the following sequence:aldehydes are more highly-processed and more highly-oxidized products than alcohols. Numerous methods of oxidation or dehydrogenation of alcohols to aldehydes have been developed, especially the key ones, including catalysts, some of which are almost perfect. However, the answer to the question whether it is worth to obtain all aldehydes from alcohols or, in other words, whether it is worth to convert all alcohols into aldehydes, is “no”.Accordingly, the research on the development of the catalytic transformations of simple oxygenates may have new motivation. The efforts to minimize the side formation of oxygenates as “unfavourable” for Fischer-Tropsch products may be abandoned in favor of the intentional exploitation of these compounds. Additionally, even uncomplicated methods of ethyl ethanoate synthesis can be replaced with even simpler, direct ones.n-butanol and isobutanol ..n-butanoThe purpose of the above examples is to illustrate the diversity of the seemingly similar situations and their specificity as well as to prove that "the only correct" direction of transformation of oxygenates does not exist.Hence, the purposefulness of the work on any particular transformation of oxygenates depends on a whole range of market factors. First of all, this work comes down to the development of an active and selective catalyst. The complexity of such an undertaking includes important concepts concerning the catalysis. Many factors are significant at the same time. There is no point in discussing them individually here or even in trying to rank them. Such complexity indicates that designing the optimal solution for a specific, desired transformation, i.e. both preparation of a catalyst and the course of this transformation, will not facilitate the execution of other tasks, even closely related ones, because of the multitude of significant factors and the multitude of interdependencies. The variation of such interdependencies does not have to be linear so extrapolations and interpolations are not always effective. Another conclusion is that the number of factors to define a specific process excludes a random selection of catalyst components.It may happen that the understanding of phenomena brings useful generalizations. In the 1920s Taylor deduced that since a catalyst can be completely poisoned by such a little amount of poison that it is able to cover only a small fraction of the catalyst surface it means that the active participants in the reaction are only certain groups of atoms on the surface . In suchThe above differentiated mechanisms relate to the catalyst per se. Catalytically active materials are often affixed to the catalyst support due to their high surface area and saving of the valuable materials. Additionally, quite a while ago, the boundary between the actual catalyst and the catalytic support began to blur. Tauster found the strong metal-support interaction (SMSI effect)  predicteComing back to the main problem of the dependence of the justification of transformation of oxygenates on variable conditions, a new attitude regarding the products of the Fischer-Tropsch synthesis should be noted. The F-T synthesis is a technology developed in the 1920s, which consists in producing liquid fuels from any carbon materials other than petroleum. This is a technology related to that used much earlier than F-T, in tar and charcoal manufactories by tar makers and charcoal burners. Disregarding the details of gas names definitions  from any carbon material: wood, coal, biomass, natural gas -32]  can be the sources of hydrogen.The WGSR is the most important side reaction of the Fischer-Tropsch synthesis ,88] of  of 88] o– The increase in demand for methanol is also an important trigger. In the chemical industry worldwide there is no other product with such a mass and multi-directional use as methanol. It is an irreplaceable intermediate product for the syntheses of many chemicals, in particular formaldehyde and various related products. Methanol is also the main base for the production of top quality petrol and diesel fuels. It can be added, blended, in significant volumes, directly to petrol fuels  or trans– The reason is also the return to the concept of using heavier fuels of natural origin. It is also a comeback, because the first diesel engine built by Rudolf Diesel was fuelled by peanut oil and such was the original intention.Despite these facts, the preparations for the return of the Fischer-Tropsch technology proceeded slowly. This was explained by the adverse financial situation resulting from the significant decline in oil prices, which reduced the competitiveness of coal fuels in relation to petroleum fuels. The current price fluctuations emphasize the purposefulness of long-term studies in this field. May the dim prospects for shale gas not overshadow this opportunity and not be the cause of another failure to develop chemical technologies based on coal resources.Another example of a new approach to transformation of a simple oxygenate is the concept of a single-stage production of ethyl acetate. Of course, the idea of primary alcohols transformation into esters had to appear during the development of organic chemistry  as a resn-1 carbon atoms in aliphatic chain ,, w, wn-1 caIn the reports in literature about this group of transformations there is a large divergence of views as to the route of the reaction. Among others, there are suggested pathways via aldol, via aldol and secondary alcohol, simultaneously via ester and aldol, via hemiacetal and ester, or aldol with a parallel hydrogen transfer reaction -128]. T. T128]. Most of the catalysts of dehydrogenative character transform primary alcohols only to aldehydes and less often to symmetric ketones. Excessive overrun of conversion optimal conditions leads to possible degradation products. Nevertheless, the proper selection of control parameters allows obtaining esters as major conversion products. Obviously, such a termination of the transformation at the ester stage is effective only with respect to specific catalysts.The important incentive, impetus to intensify the research on the termination of the course of bimolecular condensation of primary alcohols in the ester phase is the potential increase in the ethyl acetate demand. The major driving force for that demand originates from the search for new energy sources which would be renewable and “clean” – not causing additional carbon dioxide emission. Biomass derived fuels meet these expectations and can partly replace fossil fuels. Diesel oil substitute – biodiesel – is one of them. Ethyl acetate can be used in some methods of biodiesel production. Biodiesel synthesis with the use of ethyl acetate is an attractive option because of the possibility of reducing the glycerol overproduction problem . The majGlycerol overproduction as well as the problems with its utilization initiate the search for new methods of its management. The use of ethyl acetate instead of alcohol in the process of cross transesterification of triglycerides in the Gliperol process is an example of such projects .In this case the transformation of fats follows the scheme:p-toluenesulfonic acid, Tishchenko condensation of acetaldehyde – catalyst: aluminum triethoxide, condensation of acetic acid with ethylene – catalyst: bentonites, heteropolyacids)).Glycerol triacetate (triacetin) does not require the separation from the final product as it improves biofuel combustion conditions . BesidesChanges in the fuel market, including the strong drive towards the idea of using ethanol and, consequently, a large increase in the production of bioethanol, are consistent with this concept. Thus, ethyl alcohol can be a cheap, renewable resource for the production of ethyl acetate . The conResearch on the development of catalytic transformations of simple oxygenates is still justified. New market conditions make the production and processing of oxygenates as part of the Fischer-Tropsch synthesis purposeful. On the other hand, the increase in the potential demand for ethyl acetate against the background of high availability of ethanol justifies further research on a direct one-step catalytic synthesis of this ester.


This paper describes a device that allows for simultaneous tomographic imaging of samples on three independent rotational axes. This rotation axis demultiplexer (POLYTOM) is equipped with anti-backlash gears and placed on a standard sample rotation stage thus allowing for the transformation of the input rotation axis onto two additional parallel vertical axes. Consequently, three times the number of samples can be investigated within a given time period, thereby reducing the acquisition time of multiple sample tomographic investigations by a factor of three. The results of our pilot experiments using neutron tomographic imaging are presented. We foresee that the device will be of particular use for tomographic imaging of elongated samples at low-flux (e.g. neutron) sources; however, its use for the more widespread types of imaging techniques (e.g. X-rays) is not ruled out. The highlights of this new device for the purpose of the (neutron) computed tomography are:•Anti-backlash transformation of the input rotation onto two additional rotational axes.•Reduction of the acquisition time of the multiple sample tomographic investigations by a factor of three.•Low-cost. The temporal resolution of some imaging facilities (e.g. those for neutron imaging) is limited by the relatively low flux of its sources. Even with the most powerful neutron sources it is common that the acquisition time for neutron radiographies is on the order of many seconds to minutes, while the time required for acquisition of entire neutron tomographies is on the order of tens of hours e.g. . The neuWhile the size and shape of the field of view depend on a particular test arrangement, the typical field of view in (neutron) full-field imaging is given by the shape of the utilized detector. The routinely used charge-coupled devices (CCDs) or complementary metal-oxide-semiconductor (CMOS) cameras are usually in the shape of a square or low-aspect-ratio rectangle. Likewise, the available neutron beam profile at the detector position usually has similar vertical and horizontal dimensions.For tomographic imaging, samples are placed on a rotational stage and radiographs are acquired from various angular positions. In the case that the samples are significantly smaller than the field of view, it is possible, and indeed a common practice, to stack the samples above each other and perform the tomography investigation of multiple samples in the same tomographic run. However, even when stacked in the vertical direction, the samples often fill up only a limited part of the available field of view in the horizontal direction Tomographic sample stages are routinely equipped with a single rotational stage with its  axis of rotation parallel to the imaging plane . In this paper, we demonstrate that a rotation axis demultiplexer (POLYTOM) can be reliably used to transform the rotation from this single rotational axis onto two adjacent parallel axes. In this way, the field of view is divided into three independent vertical segments in which three tomographies can be run simultaneously. We tested the device using both neutron and X-ray imaging at the NEUTRA beamline, and we demonstrate that the three resulting tomographic datasets show no sign of any instability or irregularity artifacts due to its use.The POLYTOM device was designed with three actuated axes. In order to provide the highest possible precision, and hence obtain the highest resolution during tomography, two constraints were applied to the mechanical design: (i) minimization of tolerances, and (ii) no allowable backlash from the gears. It is worth pointing out here that the anti-backlash gears are particularly important for the tomographic experiments, during which the direction of the motion of the rotation stages changes  would have to be used.Given that the amount of time required for tomographic experiments increases with the enhancement in the spatial resolution, we foresee that a device similar to POLYTOM could be downscaled and also be used to create images at higher spatial resolutions Finally, even though the demultiplexer has been developed for the purpose of neutron tomographic imaging, it can naturally be used for other imaging types. This is especially true for imaging types that are not extensively limited by the low fluxes (e.g. X-ray tomography). Likewise, we expect that the POLYTOM device could be used to observe three different processes on three replicate samples simultaneously.We developed a rotation axis demultiplexer that permits simultaneous computed tomography of multiple samples. In the pilot experiments, we demonstrated that the device provides satisfactory results. We show that the stability of the adjacent axes of the device is sufficient to guarantee the same spatial resolution of the tomographic reconstructions for all the samples tested. As a consequence, we show that the demultiplexer is capable of reducing the beam-time allocation needs for a multiple sample imaging experiments by a factor of three.


CT by combining computed tomography angiographic (CTA) images and computational fluid dynamics (CFD) technique. Utilizing the method, this study explored the effects of diameter stenosis (DS), stenosis length, and location on FFRCT. The baseline left anterior descending (LAD) model was reconstructed from CTA of a healthy porcine heart. A series of models were created by adding an idealized stenosis . Through numerical simulations, it was found that FFRCT decreased (from 0.89 to 0.74), when DS increased (from 45% to 75%). Similarly, FFRCT decreased with the increase of stenosis length and the stenosis located at proximal position had lower FFRCT than that at distal position. These findings are consistent with clinical observations. Applying the same method on two patients' CTA images yielded FFRCT close to the FFR values obtained via invasive angiography. The proposed noninvasive computation of FFRCT is promising for clinical diagnosis of CAD.Fractional flow reserve (FFR) is the gold standard to guide coronary interventions. However it can only be obtained via invasive angiography. The objective of this study is to propose a noninvasive method to determine FFR As the most common type of cardiovascular disease, coronary artery disease (CAD) is caused by the build-up of plaques on the endothelial walls of coronary arteries, which leads to a reduction in arteries cross-sectional area and blood supply to the myocardium . PatholoThe rapid development of noninvasive imaging technologies, such as computed tomography angiography (CTA) and magnetic resonance imaging (MRI), has proven valuable to characterize the anatomic severity of CAD with fair cost and less complication. Diameter stenosis (DS) is commonly applied to quantify the anatomic severity of CAD. It expresses the ratio of the lumen diameter at a stenotic region over that of a “normal” segment. However, DS cannot characterize hemodynamic functional significance of coronary stenosis on myocardial blood supply. Among the stenoses discriminated with the threshold of 50% for DS, fewer than half are ischemic .In terms of hemodynamic indexes to quantify the functional significance of coronary stenosis, fractional flow reserve (FFR) is the gold standard to guide coronary interventions –6 becausIn view of the abundant hemodynamic information provided by computational fluid dynamics (CFD) simulations, considerable insights have been gained on understanding the physiology of CAD through CFD studies . TremendAs proper boundary conditions are necessary for CFD simulations of CAD, both prescribed profiles , 12 and CT from CT images by applying sophisticated reduced-ordered models as the boundary conditions for transient numerical simulations. Because the calculation of FFR is based on the time-averaged pressure over several cardiac cycles in clinics [CT with lower computational cost. The method is firstly applied on a left anterior descending (LAD) model reconstructed from CTA of a healthy porcine heart and then tested on two patient-specific left coronary artery trees reconstructed from patients' CTA images to examine whether the approach can be applied for noninvasively assessing the hemodynamic significance of coronary stenosis in clinics.With the development of CFD techniques, numerous CFD studies have been coupled with clinical imaging techniques to provide detailed hemodynamic information and link CAD with vortices , wall sh clinics , this stCT are investigated. The results may be useful to aid the clinician in making the decision of revascularization.As the anatomical severity of CAD is believed to be related not only to DS but also to the location and length of the stenosis, which can affect the hemodynamics , a serieCT distributions) for a series of stenosed porcine LAD models was provided to explore the effect of DS, stenosis length, and location on FFRCT. The results of two case studies were also presented to demonstrate the applicability of the current methodologies on clinical diagnosis of human CAD. Finally, the conclusions were drawn in This paper is organized as follows: the detailed computational methodologies were described in In this study, a left anterior descending (LAD) model was used as the baseline model, which was reconstructed from CTA of a healthy porcine heart. The detailed description on animal preparation, CTA, and image processing can be found in . As showAfter generating these LAD models with SpaceClaim, their computational domains were discretized with commercial software ANSYS workbench. Meshes near the branch junctions, at the stenosis and near the walls, were refined for adequate resolution of flow in the boundary layers  were the location in Cartesian coordinate and the Cartesian component of velocity, respectively. P represented the static pressure. ρ and μ were density and dynamic viscosity of the fluid, which were set as 1060 kg/m3 and 4.5 × 10−3 Pa·s, respectively, to mimic the blood properties in large epicardial arteries [Here arteries , 26.Proper boundary conditions are required for CFD simulations to closely mimic the real physiological condition . In geneAccording to the pulsatile pressure and flow velocity waveforms measured in vivo at the inlet of the porcine LAD , the timPi and Qi represent the pressure and flow rate at the ith outlet, respectively. Here, Ri is the resistance of the downstream vasculature and Pi0, is the back pressure at ith outlet.In order to derive the resistance values of downstream vasculatures, the steady-state simulations under two sets of boundary conditions were carried out on the baseline model prior to the simulation on stenosed LAD models. One of the simulations represents the peak phase of systole, when the inlet pressure is at the maximum . The othIn clinics, FFR measurement is done following vasodilation, which leads to the decrease of coronary resistance. To resemble this physiological situation, the resistance of downstream vasculature of each primary branch was assumed to be reduced to 0.21 times of its resting value, which was within the physiological range measured by Wilson et al. . Accordiω given asUser defined function (UDF) was compiled to supply the resistance boundary conditions at the outlets. In this manner, the downstream vasculature of the primary branches was coupled to the LAD model, and the static pressure at each outlet was solved iteratively. To ensure smooth convergence, the pressure gradient calculated at the outlet was attenuated several times to couple iterative underrelaxation-based resistance boundary conditions with those outlets; namely, an implicit algorithm was applied to the outlet with an underrelaxation factor of In addition, no-slip boundary condition was applied at the wall, as all these LAD models were assumed to be stationary and rigid. All the computations were executed in a Dell T7500 workstation and it took around half hour computational time for one case.To elucidate the role of stenosis on hemodynamics of coronary artery, Once there was a stenosis in the LAD trunk, the streamlines diverted into the center of the LAD main trunk due to the shrinking of the cross-sectional area from the beginning to the throat of the stenosis region. Downstream the throat of the stenosis, the cross-sectional area of the LAD main trunk increased gradually. Due to the inertia momentum, the fluid moved downstream with slight divergence of the streamlines. Hence flow recirculation region was formed near the wall downstream the stenosis, which was filled by vortices and reverse flow derived from the downstream streamlines as shown in An interesting phenomenon was found for the flow rate distribution among the primary branches. With the increase of DS, less blood flowed downstream to perfuse the myocardium downstream the first primary branch  owing to the limitation of the imaging resolution. With the development of medical imaging techniques, the breakthrough in this area should be achievable in the near future.


To answer the need for the rigorous protection of biomedical data, we organized the Critical Assessment of Data Privacy and Protection initiative as a community effort to evaluate privacy-preserving dissemination techniques for biomedical data. We focused on the challenge of sharing aggregate human genomic data  in a way that preserves the privacy of the data donors, without undermining the utility of genome-wide association studies (GWAS) or impeding their dissemination. Specifically, we designed two problems for disseminating the raw data and the analysis outcome, respectively, based on publicly available data from HapMap and from the Personal Genome Project. A total of six teams participated in the challenges. The final results were presented at a workshop of the iDASH  National Center for Biomedical Computing. We report the results of the challenge and our findings about the current genome privacy protection techniques. The biomedical community is evolving to benefit from and to contribute to big data science. This began with advances in high throughput and computing technologies and is expanding to include expected, as well as unexpected, sources of health-related data, such as electronic health records and social media. A large amount of biomedical data  are being rapidly generated in research and clinical laboratories and healthcare settings . Human gTo transform such data into knowledge that is applicable to biomedicine, new technologies for large-scale investigations and meta-analysis analysis  on genoHowever, further progress in this area has been impeded by the constraints in accessing human genome data, due in part to privacy concerns related to the disclosure of these data ,5. As huIt is well known that sharing raw DNA data  poses risks even after the removal of explicit identifiers , as the donor can be possibly re-identified through the genetic markers  in the data -8. Even In the past several years, there is growing interest in developing effective methodologies to analyze and disseminate sensitive data. Cryptographic protocols (such as homomorphic computation -17) wereA critical challenge of applying privacy technology on human genomic data is to balance data sharing  and privacy protection. To investigate the extent to which data perturbation technologies are practical, we organized the Critical Assessment of Data Privacy and Protection (CADPP) Workshop as a community effort to evaluate the effectiveness of these methodologies  for genWe devised a task for each of these two problems, based on publicly available data from the International HapMap Project  and the case group so that the resulting data are indistinguishable when any individual is present or absent in the case group. Below, we provide background on differential privacy, a framework developed by Dwork [For both tasks, we challenged teams to apply data perturbation techniques based on the differential privacy standard. These techniques attempt to add noise to the allele frequencies of the by Dwork , for reaDefinition 1  A randomized algorithm satisfies -differential privacy if for all adjacent datasets and , and any possible output in the output space of Note that echanism  is commoDefinition 2 For any , and all adjacent datasets  and , the sensitivity of isAnother popular method for achieving differential privacy is called the exponential mechanism, which was proposed by McSherry and Talwar . This meAs mentioned, we organized the challenge around two specific problems: i) sharing allele frequencies and ii) sharing the most significant single nucleotide variants (SNVs) in GWAS.http://www.personalgenomes.org/), which consisted of 411 participants whose genotypes were profiled on 29,757,319 SNVs across the whole genome. The control data consisted of 174 participants from the CEU population in HapMap (http://hapmap.ncbi.nlm.nih.gov/index.html.en).We devised one task for each problem. For each task, we constructed two datasets based on case and control groups of individuals. The case group was composed of the subjects from the Personal Genome Project . Each team was provided with the original allele frequencies for the case group, and was instructed to submit perturbed allele frequencies for this group. Note that, in the challenge, we assume the genotypes of the control group are publicly shared, and thus there is no need to protect them. In order for participating teams to evaluate the effectiveness of their data perturbation method, the control group data were made available.Numerous statistical attack models have been proposed to detect the presence of a participant in a case population. Homer et al. presented a statistical inference approach that computes the likelihood of a patient to participate in a case group whose aggregate allele frequencies on many SNV were shared . Followij, m is the total number of SNVs, j in the case group, and where i, representing the likelihood of that subject's presence in the case group. The probability that a subject in the case group will be re-identified is considered to be high if the LR test statistic from her SNVs is significantly greater than those of subjects who are not in the case group.A statistic χ2-association test [p-value threshold, e.g., 10−5) SNVs reported by the χ2-association test on perturbed data were true. In other words, these SNVs were identified as truly significant on the original data using the same statistical test and a majority of truly significant SNVs could be identified on the perturbed data.We used the LR test to evaluate the privacy risks in the submitted data after perturbation from participating teams. The submitted data were considered sufficiently protected if there were approximately the same number of individuals in the case group with LR statistics above the same threshold as those in a test group . The utility of the perturbed data were measured using the number of significant SNPs identified by the ion test , which ihttp://www.humangenomeprivacy.org/service.php) for participating teams to evaluate the privacy risks in their perturbed data. A team could upload perturbed allele frequencies in the case group, and the LR statistics were calculated for each case individual using his/her actual genotype, the uploaded allele frequencies in the case group, and the actual allele frequencies in the control group (from the HapMap project). For comparison, the LR statistics were also computed for a group of test individuals  who were not in either the case or control group. If the number of case individuals was not significantly larger than the number of test individuals who had a test statistic above a certain threshold, these case individuals were considered indistinguishable from any individuals outside the case group and the perturbed case group data were considered to be privacy-preserving.We implemented the likelihood ratio test as an online tool  using our baseline method (see below). The second dataset consisted of 600 SNV sites spanning a 1M bps genomic segment on human chromosome 10, which is a moderately challenging dataset whose re-identification risk can be fully mitigated by our baseline method.naïve and advanced algorithms. In the naïve algorithm, we treated the allele counts across multiple SNP sites as a histogram, and added Laplacian noise to the allele counts. Note that the sensitivity of the count function over N SNVs is 2N, which can be used inTo ensure the feasibility of the competition, we implemented two baseline algorithms for adding noise to data used in task 1, which we refer to as the As the name implies, the naïve algorithm is simple and straightforward. However, the sensitivity in this case is high because the dimensionality of the dataset, which corresponds to the number of SNVs, is large . The high sensitivity can resulting in adding a large amount of noise to the data, which may significantly damage the utility.haplotypes [haplotype blocks (or haploblocks); within each block, a specific combination of alleles across multiple adjacent SNV sites is called a haplotype. Due to linkage disequilibrium (LD) in human, SNVs within each block are likely inherited together. As a result, inter-haploblock SNVs are more highly correlated than intra-haploblock SNVs. Therefore, the number of potential SNV sequences in each haplotype block (across n SNV sites) is much smaller than the theoretical bound . Rather than adding noise to allele counts on individual SNV sites, the advanced data perturbation approach adds Laplacian noise to the haplotype counts, which are normalized within each haplotype block.Figure We derived the allele counts on each SNV site from counts of haplotypes containing the site. By using haplotypes, we can reduce the dimensionality of genomic data by one order of magnitude. In practice, we need to allocate the privacy budget (default 1) into haploblocks in an unequal manner to ensure it is not overspent. To do so, we employed an empirical method for budget allocation. Specifically, we allocated a budget to each haploblock proportionally to the number of haplotypes within that block. In doing so, a larger budget will be assigned to the blocks with a greater number of haplotypes (and thus less noise will be added to them). Similarly, a smaller budget will be assigned to the blocks with fewer haplotypes. Note that the total privacy budget across the entire dataset remains the same as in the naïve approach.We constructed two datasets for Challenge 1. The first case dataset consists of 311 SNVs from 200 PGP participants. As shown in Figure p-value distribution, based on a χ2 test, of all SNVs in this this case-control dataset. The upper and lower lines in the figure differentiate the top-5 and top-10 most significant SNVs, respectively, from the rest of the set, which correspond to the p-value cutoffs of 10−8 and 10−7, respectively. The practical p-value threshold used in GWAS is 10−5, indicating that there exist many significant SNVs in the dataset to be identified in typical GWAS analyses.Figure χ2-association test on this dataset. Figure http://www.humangenomeprivacy.org/competitiondata.php). The first line of the file consists of the IDs of human individuals, followed by the SNV ID and the genotypes in each individual, which themselves follow the order of SNV site locations. The allele frequencies for the SNVs can be derived from the input data. To evaluate the utility of the perturbed case data submitted by participating teams, we conducted a χ2 test on a combination of the submitted and unperturbed control data. The significant SNVs  were compared to the significant SNVs reported by the same test on the un-perturbed case data. A larger number of common SNVs between these sets indicates higher utility of the corresponding perturbation technique and vice versa.The second case dataset consists of 610 SNVs of the same 200 participants from the PGP as the first dataset. As shown in Figure K  most significant SNVs among all SNVs  across the genome. Again, we used the χ2 test statistic for utility evaluation in the case-control analysis. We expected the released GWAS results to achieve a given privacy standard: they should be differentially private with a privacy budget of 1. The utility of the anonymized GWAS results submitted by the participating groups was evaluated based on the proportion of SNVs in the released result that were among actual top-K most significant SNVs that would have been released if preserving privacy was not a concern.The goal of the second task was to evaluate the utility of competing data perturbation techniques in releasing privacy protected results of GWAS. We consider a typical GWAS, where the users are interested in knowing the identity of the top-valid 2,500,781 SNV sites genotyped in at least 174 PGP participants so that we could estimate the allele frequencies on these sites accurately. Next, we eliminated PGP participants from our constructed dataset who had fewer than 90,000 genotyped valid SNV sites. After these preprocessing steps, there were still genotypes missing for some PGP participants, which were imputed based on allele frequencies from the CEU population in HapMap using fastPHASE, a commonly utilized phasing tool [We first preprocessed the case data containing 29,755,199 SNV sites to make them compatible with the control data. Many SNV sites were genotyped for only a small portion of PGP individuals, and some other SNV sites genotyped in PGP were not genotyped in HapMap. We removed all unmatched SNV data between these two datasets and retained only the ing tool . FinallyWe constructed two datasets for this task. The large dataset consists of all valid 106,129 SNVs from 201 cases and 174 controls after the data pre-processing procedure, which was used to evaluate the utility of the perturbation algorithms submitted by participating teams. We also constructed a small dataset (a subset of the larger one) consisting of 5000 SNVs on the same case and control groups that were randomly sampled from the larger dataset. The SNVs in both datasets were evenly distributed in different human chromosomes  to dynamically compare the algorithms of participating teams that can be accessed at https://humangenomeprivacy.ucsd-dbmi.org. Using this webservice, a user can assess competing models in finer granularity than what is reported in this article. The figures below illustrate how WIDGET can be used to evaluate a model's performance for task 1 and task 2, respectively.We built a companion webservice using JavaScript and R Shiny server technology  for top-K SNV identification (Task 2), where the same privacy standard  SNV identification performance of a given method.In Figure A total of six teams participated in the competition. Three teams, from the University of Oklahoma, University of Texas (UT) Dallas, and McGill University, participated in the first task. The team from Indiana University collaborated with the UCSD organizers to design and implement the baseline methods, but they did not participate in the competition. Two teams, from UT Austin and Carnegie Mellon University, participated in the second task. The results of the challenge were presented at an iDASH  workshop on March 24, 2014 in La Jolla, California. All teams presented their methods and results at the workshop. The details of the methods used in the challenge are described in separate articles in this issue ,30. Belopower of the LR test; i.e., the fraction of case individuals who could be re-identified with confidence higher than a specified threshold. If the power was not significantly higher than 0.05, we considered the perturbed data to have a small privacy risk. From the results, we can see that in all cases except two (including the haplotype-based method on the second dataset), the privacy risk was sufficiently mitigated by the data perturbation techniques. We then measured the utility of the perturbed data based on the number of significant SNVs detected by using χ2 test (see above) under various p-value cutoffs  of a χ2test.Table The results of the SNV-based algorithm (the naïve baseline method) showed the least utility. It missed a substantial number of truly significant SNVs, while it generated a large number false positive SNVs. The haplotype-based algorithm exhibited better performance. Almost all truly significant SNVs were detected in both datasets, and the number of false positives was reduced. The results of UT Dallas and McGill University teams showed similar results on utility of perturbed data, and nearly all significant SNVs were detected, although both had a high false positive rate. Overall, the McGill University team performed the best in the task and won the task 1 challenge.K is set to be smaller than 15, both algorithms can correctly identify more than 80% of the top-K most significant SNVs. The performance is, however, inversely correlated with K, such that when K ≥ 15, both methods return only around 50% of the true top-K SNVs. Similarly, for the large dataset, when K < 10, both algorithms perform well.Table χ2 test statistics used by the CMU team. From the results of task 1, we observed that it remains a challenge to share aggregate human genomic data in a privacy-preserving manner while maintaining truthful associations between the SNV data and the case-control groups. Even for a single genomic locus consisting of a few hundreds of SNVs the association was largely broken after data perturbation.Overall, the UT Austin team generated the best results. One reason is that their Hamming distance based utility function had relatively smaller sensitivity (therefore reduced perturbation noise) when compared to that of the This problem will become more challenging as larger volumes of human genomic data are planned for dissemination. The performance of differential privacy-based data perturbation techniques heavily relies on the dimensionality of the data. Even though we can reduce the number of dimensions by utilizing unique semantics of genomic data, such as haplotype blocks, it is unlikely that current perturbation techniques will scale well for sharing whole human genomic data.On the other hand, the results in task 2 showed that privacy-preserving techniques work well for sharing analytical results (by using statistics commonly used in GWAS). High utility can be preserved when only a small number  of the most significant SNVs are of interest to the end users. Notably, this task is well aligned with the centralized computing model, in which a computing center hosts genomic data, as well as the service of customized analyses on these data, and will only release the results of these analyses .It is essential to develop new privacy-preserving techniques that enable the sharing of human genomic data in a way that preserves the privacy of the data donors, without undermining the utility of the data or impeding its convenient dissemination. This workshop only focused on technical aspects of privacy, but there are many other components, such as social and legal controls, that need to be accounted for when erecting privacy preserving infrastructures. As an initial step to assess existing techniques, we organized the first challenge with two tasks based on real-world human genomic data in GWAS. We discovered that differential privacy-based data perturbation techniques have limitations in sharing a large volume of human genomic data, but can be used to disseminate analytical results (by using GWAS-like statistics), through services like those offered by NCBI. We plan to organize this challenge annually, and hereby welcome suggestions and comments to improve the contest in upcoming years.The authors declare that they have no competing interests.XJ and HT drafted the majority of the manuscript and entire team edited and updated it accordingly. BM and LOM guided the experimental design and provided detailed edits to the manuscript. XW, HT and XJ designed the baseline methods. YZ and SW implemented the evaluation mechanisms for the competition.


For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST) with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects’ behavior and found that attention-like features in the behavioral model are essential for explaining subjects’ responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects. e.g. where to eat) we first have to identify a set of environmental features that are relevant for the decision . Although we are able to make such inferences almost effortlessly, this type of problems is computationally challenging, as we live in a complex environment that constantly changes and contains an immense number of features. Here we investigated the question of how the human brain solves this computational challenge. In particular, we designed a new experimental paradigm and derived novel behavioral models to test the hypothesis that attention modulates the formation of beliefs about the relevance of several environmental features. As each behavioral model accounted for a different hypothesis about the underlying computational mechanism we compared them in their ability to explain the measured behavior of human subjects performing the experimental task. The model comparison indicates that an attentional-focus mechanism is a key feature of behavioral models that accurately replicate subjects’ behavior. These findings suggest that the evolution of beliefs is modulated by a competitive attractor dynamics that forms prior expectation about future outcomes. Hence, the findings provide interesting and novel insights into the computational mechanisms underlying human behavior when making decisions in complex environments.When making decisions in our everyday life ( Depending on the fishing place  only some of these features will be relevant. To perfectly solve such tasks all possible features should be taken into account simultaneously. However, due to an apparent limitation in their cognitive resources, humans dynamically attend only to the most relevant environmental features when deciding what action to pursue .To find the mode of ch areas –77 and ich areas ,57. We uhttp://www.mathworks.de/matlabcentral/fileexchange/13490), MATLAB Central File Exchange. Retrieved 10. November 2013].Once the mode of the log-joint probability distribution  is foundN = 50 times per experimental block for each model. For each of the N solutions we estimated the Hessian matrix and computed the Laplace approximation to the log-evidence. Finally, we kept the solution with the largest log-evidence, therefore increasing the probability of finding the maximal lower bound to the log-evidence and thus the most likely model of a subject’s behavior. The numerically obtained S are used as the mean and the covariance matrix of the approximate posterior distribution Because of the stochastic nature of the CMA-ES algorithm we repeated the stochastic search We first estimated the log model evidence of the 17 generative models described above for each experimental block. To obtain a total per-subject log-evidence for each experimental condition, we summed the estimated log-evidences over experimental blocks of a single experimental condition. This gives us the log model evidence of each generative model for each subject per experimental condition. We used the obtained log-evidences to apply the hierarchical Bayesian model selection approach described in ,55. By uThus, the two computed quantities of interest are the expected probability (EP) and the exceedance probability (XP) of each model: The EP is defined as the probability that a given model generated the behavioral data of a randomly selected subject (see  for a dehttps://sites.google.com/site/jeandaunizeauswebsite/code/rfx-bms), retrieved January 2014]. In what follows we will describe the results obtained by applying the Bayesian model selection to the set of behavioral models that we used to approximate subjects’ behavior in the probabilistic WCST.We used the MATLAB implementation of the random-effect Bayesian model selection [, non-Bayesian The solution here is that instead of trying to answer which of the models provides the best description of behavioral data, we should ask which of the features of the perceptual and the response model are the most relevant for generating the data . Note thFrom the results of the four family-wise model comparisons, shown in Brdr see , whose und and 3rd level of the hierarchy, see Reduced structured and structure-free models for details) is an essential feature in both experimental conditions  with belief solicitation to show that, in a rather complex environment, update of beliefs is modulated by an attentional focus mechanism. We analyzed behavioral data of 22 subjects using a meta-Bayesian framework ,50. ThisThe variant of the WCST used here can be seen as a simple but representative task to which humans are often exposed, namely making decisions in situations where the relevant features of the environment are not obvious but need to be inferred first. What makes the WCST simpler when compared to natural environment is the reduced number of possible pre-learned hypotheses. However, the dynamic complexity is comparable to real world situations: (i) the rules of the environment can change, and (ii) in the specific WCST used here the experimenter occasionally ‘makes a mistake’ just as in the natural environment one often cannot know something with certainty. For the WCST task, these two naturally occurring sources of uncertainties make the necessary inference sufficiently complex to compute the subject’s uncertainty about the relevance of visual features. To better infer the hidden internal beliefs and uncertainties of subjects, we used belief solicitation in a form of a betting assignment, which reflect a subject’s hidden beliefs over the space of possible hypotheses. To our knowledge, such belief solicitation was not previously used in a WCST task, although similar experimental designs were used for simpler tasks ,79.To incorporate attentional-focus within the perceptual part of the behavioral model we modeled the dynamics of the hidden states of a probabilistic generative model with a winner-take-all (WTA) dynamics. This is a well-known type of dynamics applied to artificial neural networks –40,80–82For our purposes, the WTA neuronal network implemented a dynamic and self-regulated attention formation at the top level of a hierarchical representation of environmental features.In comparison to the classical connectionist approach, e.g. , the maiOur finding—that competitive inhibitory WTA dynamics as a model of attentional focus is required for describing the hidden update process of subjects’ beliefs—is in agreement with previous findings of Wilson and Niv . This suThe WTA dynamics introduces the following features in the evolution of beliefs: (i) faster convergence of beliefs to the working hypothesis; (ii) the beliefs are more inert to frequent changes in the environment, that is, to switch between the hypotheses sufficient amount of contradicting evidence has to accumulate. (iii) The beliefs change faster if the changes in the environment are rare, as after the fixed point is reached beliefs do not evolve further. In contrast, the diffusive dynamics of the SFM variants of the perceptual model is not bounded within finite volume of the belief space. Hence, as the posterior beliefs about a hypothesis’ relevance can be strongly separated if the environment is stable for a long period of time and, once the switch occurs it would take a very long time to adjust the beliefs as nothing constrains the separation of the posterior expectations.Consequently, as our results suggest, the proposed attractor dynamics modulate expectations. This would predict the following effects on behavior: (i) Even small amount of evidence can have a big impact on beliefs, (ii) if changes in the environment are too frequent they will have smaller impact on beliefs than expected from the diffusive dynamics, and (iii) if changes in the environment are rare it will take less contradicting evidence to change the working hypothesis than predicted by the diffusive and unconstrained dynamics.Although various studies have demonstrated that human behavior can approximate a Bayesian observer ,60–62,87In recent work Acerbi et al.  have demThus, to account for potential dependence of response variability on posterior uncertainty we considered two variants of the response model. In the first variant we assume that the response variability is constant over an experimental block. In the second variant we additionally allow for the variability of the modeled responses proportional to the posterior uncertainty (see Eqs  and 16)16)), whiDepending on the experimental condition both variants of the response model provide good accounts for the deviation of subjects’ responses from the optimal response. In the no-switch condition  and as a suppressor of the perceptual surprise  and also contains the results of the model comparison.(PDF)Click here for additional data file.S2 TextContains detailed derivation of the response model within the framework of Bayesian decision theory.(PDF)Click here for additional data file.S1 DataContains behavioral data, posterior and prior expectation (and covariance matrix) of the free model parameters, estimated log-model evidence for each behavioral model, and the model comparison results.(GZ)Click here for additional data file.S1 Figrcorr between the mean subject performance and the mean model performance, for each behavioral model in the switch (top) and no-switch condition (bottom).Pearson correlation coefficient (TIFF)Click here for additional data file.


The low quality of healthcare and the presence of user fees in Burkina Faso contribute to low utilization of healthcare and elevated levels of mortality. To improve access to high-quality healthcare and equity, national authorities are testing different intervention arms that combine performance-based financing with community-based health insurance and pro-poor targeting. There is a need to evaluate the implementation of these unique approaches. We developed a research protocol to analyze the conditions that led to the emergence of these intervention arms, the fidelity between the activities initially planned and those conducted, the implementation and adaptation processes, the sustainability of the interventions, the possibilities for scaling them up, and their ethical implications.n =18) representing different intervention arms and the district or regional hospital (n =3). We will select contrasted cases in relation to their initial performance . Over a period of 18 months, we will use quantitative and qualitative data collection and analytical tools to study these cases including in-depth interviews, participatory observation, research diaries, and questionnaires. We will give more weight to qualitative methods compared to quantitative methods.The study adopts a longitudinal multiple case study design with several embedded levels of analyses. To represent the diversity of contexts where the intervention arms are carried out, we will select three districts. Within districts, we will select both primary healthcare centers (Performance-based financing is expanding rapidly across low- and middle-income countries. The results of this study will enable researchers and decision makers to gain a better understanding of the factors that can influence the implementation and the sustainability of complex interventions aiming to increase healthcare quality as well as equity. Universal health coverage entails that everyone should have access to good quality healthcare services without experiencing financial hardship resulting from healthcare payment . DespiteRecently, numerous LMICs have introduced performance-based financing (PBF) to improve the delivery of healthcare services. The World Bank, for instance, supported the design and implementation of PBF in over 30 LMICs ,5. DiffeThe body of evidence on the implementation and effectiveness of PBF is not well established. In Rwanda, for instance, PBF increased the number of assisted deliveries, children's consultations, and perceived quality of care ,10. MeanResearchers have suggested that several dimensions must be taken into account when evaluating any PBF intervention, including the characteristics of the healthcare system. Most studies on PBF focus on primary healthcare facilities. Local stakeholders have highlighted the need to examine the implementation process of PBF in higher level health facilities. Other elements to be considered include the governance structure, organizational cultures, training activities, nature of contracts, redistribution of incentives, indicators of performance, mechanisms to monitor performance, means of dialogue between stakeholders, power relations, community involvement, and perceptions of stakeholders ,15–17.In addition, one must consider that PBF can also trigger unintended processes and effects. Financial incentives might erode intrinsic motivation  or lead Achieving universal health coverage will likely require a comprehensive approach that simultaneously tackles supply-side and demand-side barriers to effective healthcare coverage. Offering financial incentives to motivate healthcare providers may not be sufficient to tackle all the barriers that influence access to healthcare . Without making specific provisions for the poor, PBF is unlikely to produce the same benefits for all. To promote equitable access to healthcare, PBF could be combined with pro-poor targeting strategies and/or community-based health insurance (CBHI). Thus far, empirical evidence on the feasibility of combining PBF with other supply- or demand-side interventions that address social protection is scarce.In LMICs, pro-poor targeting has been implemented both on the supply side and the demand side. On the supply side, one strategy is to pay healthcare providers more for services offered to the poor compared to the rest of the population . On the On the demand side, CBHI could be combined with PBF to increase risk sharing among the population. Since the 1990s , severalAlthough CBHIs have adopted a wide range of initiatives involving various stakeholders, none of them have been able to resolve the issue of low membership on their own . To dateIt is essential to produce evidence on the feasibility of implementing combined interventions with synergetic potential, as a means to address equity concerns related to traditional PBF approaches. In Burkina Faso, the implementation of various intervention arms combining PBF with CBHI and pro-poor targeting offers a unique opportunity to explore existing gaps in knowledge.In Burkina Faso, nearly half of the population lives below the poverty line and more than 100,000 children under the age of 5 die each year . The proIn 2011, the Government of Burkina Faso launched a pilot PBF intervention targeting maternal and child healthcare services in three districts. In 2012, the evaluation of the pilot project  found a Performance-based financing only (PBF 1): Health facilities are paid according to the quantity and quality of healthcare services delivered. Patients are required to pay user fees. PBF performance agreements concluded between the MOH and the health center define the package of basic services to be provided and the indicators and targets to be reached in delivering these services. The results achieved against these targets are assessed by external reviewers every 3 months. Based on these verified results, each facility under a PBF contract receives payments in partial reimbursement for the services delivered. The payments are based on unit prices, based on a number of factors designed to achieve the desired results. This includes the basic cost of the inputs required (and not financed elsewhere) for services to be rendered, adjusted for quality of the service. This intervention group does not include any systematic targeting and subsidization of the poor.Performance-based financing + systematic targeting and subsidization for the poor (PBF 2): PBF is combined with a community-based selection of the poor (approximately 15%–20% of the population) who are entitled to benefit from user fee exemptions. A specific PBF indicator is introduced for purchasing services for the poor, using a fixed unit price for each consultation package (including services and drugs). The fixed unit price is higher than for non-targeted patients, taking into consideration the delivery of care without direct payments from patients. If issues of oversupply arise after the first few months of implementation, a cap may be established so that a maximum of about 10% of consultations can be reimbursed as consultations offered to the poor. In that case, health facilities would receive the normal rate for consultations offered to the poor exceeding the 10% cap.Performance-based financing + systematic targeting and subsidization for the poor + provider motivation (PBF 3): PBF is combined with a community-based selection of the poor who are entitled to benefit from user fee exemptions (approximately 15%–20% of the population). Healthcare providers are paid more for services provided to the poor than in PBF 2. The multiplication factor varies depending on the services. If issues of oversupply arise, a reimbursement cap of about 10% may be established. The higher reimbursement rate acts as a financial incentive for healthcare providers to take personal initiative to increase the utilization of healthcare by the poorest households.Performance-based financing + community-based health insurance (including targeting of the poor) (PBF 4): PBF is combined with CBHI offered to the general population. The insurance premiums of the poor (approximately 15%–20% of the population) are subsidized. Healthcare services are purchased at varying payment levels, as defined in PBF 3 (with higher payment levels for services provided to the poor). Thus, subsidization of services provided to the poor who do not pay the premiums will pass via the PBF mechanism at budget-neutral levels, while capitation payments will replace out-of-pocket payments for the general population.In 2013, the government decided to expand PBF to 12 districts in six regions, covering a population of approximately four million people. The operation is financed by the World Bank and carried out by the Ministry of Health's Technical Support Unit in charge of PBF (TSU- PBF). The objective remains that of improving the utilization and quality of maternal and child healthcare services. In comparison to the earlier pilot project, PBF will be combined with additional interventions directly targeting health equity: demand- and supply- side pro-poor targeting and CBHI. The objective of combining PBF with pro-poor targeting and CBHI is to ensure that healthcare improvements are accompanied by adequate measures to enhance equity in utilization rates and secure financial protection. Four intervention arms are being implemented to compare their outcomes:Primary healthcare facilities are randomly allocated to the different groups. All district and regional hospitals included will be allocated to PBF 2.The theory of the overall intervention combining PBF with pro-poor targeting and CBHI is presented in Figure The World Bank also finances the impact evaluation of the four intervention arms. The impact assessment adopts a blended experimental and quasi-experimental design. For the experimental portion of the design, facilities within PBF districts are randomly assigned to PBF intervention arms to test the effects of the additional components (pro-poor targeting - PBF 2 and 3 and CBHI - PBF 4) versus PBF alone (PBF 1). For the quasi-experimental portion, facilities are matched with other facilities in neighboring control districts to compare the effects of the intervention arms with the absence of any intervention . Two comparison districts in each of the six regions, where the intervention districts will take place, have been selected to act as comparison health facilities. The research protocol presented in this manuscript is not for this impact evaluation. Our protocol focuses exclusively on the implementation process and, as such, adopts a design that is complementary to the one used for the impact evaluation.Q1. How was the decision taken to combine PBF with CBHI and pro-poor targeting?Q2. Were the interventions' activities implemented as planned and why?Q3. How do social actors perceive the interventions?Q4. How were the interventions implemented?Q5. What adaptation/invention/innovation strategies did the interventions trigger?Q6. Did the interventions induce unintended effects? If so, which ones?Q7. How did the different contexts shape the way the interventions were deployed?Q8. Which specific activities or combination of activities produced changes in the performance of health centers? How were these changes produced over time?Q9. Will the implementation process of the interventions allow their sustainability?Q10. What is the potential for scaling-up the interventions nationwide?Q11. Which ethical considerations are associated with the interventions?The overall objective of this study is to analyze the emergence, the fidelity, the implementation process, the sustainability, the possibilities for scaling-up the intervention arms nationwide, and the ethical implications of the intervention arms. The research questions (Q) are:The current study is anchored in methodological pragmatism –55. WhenThe methodological strategy was developed during a pre-evaluative phase ,61 whichSeveral types of evaluations will be conducted as part of this study. Examples of typical questions representing each type of evaluation are presented in Table emergence (Q1) will examine the factors that led to the decision to combine PBF with pro-poor targeting and CBHI. An analytical framework derived from the multiple streams approach will be used to understand public policy agenda setting [The assessment of  setting .fidelity of implementation (Q2) is essential because stakeholders plan to implement a combination of interventions that they believe to be effective. But in order to be effective, the interventions must be either implemented as planned (to avoid type 3 errors [Assessing the 3 errors ), or the3 errors –67.processes (Q3–7) will focus on the internal dynamics of the intervention arms, the roles, perceptions and coping strategies of actors, the unintended effects, the evolution of actions, and the mediating effect of the context [The assessment of  context ,69. We a context ,68.performance assessment (Q8) will focus on activities related to the interventions in PHC and district or regional hospitals. It is related to an effectiveness analysis. Primary healthcare centers and hospitals will be considered to be effective when they are better than others (median) and they improve their score on indicators associated with the interventions' activities.The sustainability assessment (Q9) [The ent (Q9)  will focent (Q9) ,72: i) spotentially scale-up the interventions (Q10) will be studied by examining the characteristics of the innovation , the context, the host organization , the implementation strategy, and the support team  [The conditions to ld Bank) .ethical considerations (Q11) will involve analysis of the moral and political issues associated with the design and implementation of the intervention arms. The goal is to go beyond ethical considerations traditionally associated with procedural ethics in order to examine a wider scope of ethical implications pertinent to the interventions.The assessment of The design will be a longitudinal multiple case study with several nested levels of analyses –77.Since the social context and the district teams' leadership affect the performance of the PHC in Burkina Faso ,78,79, cn =21 cases). More specifically, in Diébougou and Ouahigouya, where three modalities are implemented , we will select two PHCs for each of the three intervention arms. In Diébougou, we will also select the district hospital (DH). In Ouahigouya, we will select the regional hospital (RH) because there is no district hospital. In Solenzo, where only two intervention arms have been implemented (PBF 1 and PBF 4), we will choose six PHCs, that is three for each of the two intervention arms, and the district hospital.The cases will be PHCs representing different intervention arms and the district or regional hospital located within each of the three selected districts. Figure The selected cases will be considered to be typical cases . For eacThis evaluative research will adopt a mixed methods approach . We willDuring the first month (M1) of the study, we will measure the initial performance levels of the PHCs to allow the selection of cases. Our previous work in Burkina Faso and that of other researchers have demonstrated the quality of the routine data ,77,82,83Three months M3) after the beginning of the study, we will collect data to measure the fidelity of the intervention arms' implementation and to understand the process of implementation. Under the supervision of a researcher in each district, research assistants will be present in each case for a 2-week period. This relatively long immersion will not only create a sense of trust with the stakeholders, but also provide a better understanding of the contextual issues. On site, research assistants will conduct non-participant observation . They will keep research diaries, take notes after informal interviews, and make ethnographic  summarie after thAfter 6 months (M6), a qualitative data collection round will be conducted on a national level to better understand the factors that contributed to the emergence of PBF with pro-poor targeting and CBHI. We will collect data from all of the available documentation and from approximately 20 in-depth interviews with key stakeholders. In-depth interviews will be conducted until we reach saturation of data.After 12 months (M12), a second data collection phase will take place in all of the selected healthcare facilities. In terms of performance, quantitative data will be collected using the same method as in M1. However, without waiting for the results of these analyses, we will conduct in-depth interviews with healthcare providers and members of the management committee to capture their perceptions of the evolution of this performance. Following the same method used during M3, we will analyze the evolution of the fidelity of the implementation and the processes using document analysis, observations, and in-depth interviews. In addition, the sustainability and conditions to potentially scale-up the intervention arms nationwide will be studied through interviews conducted on a national level. We will conduct interviews until we reach saturation of data (approximately 30 interviews) with stakeholders.At 18 months (M18), after analyzing the quantitative data on the evolution of the performance, research assistants will conduct a final 2-week field visit in each case. They will conduct interviews with key stakeholders to discuss and understand the quantitative performance data. Not only will we try to understand how the interventions are organized at M18 but, due to preliminary data analysis of M3 and M12, we will also conduct interviews on the evolution of the implementation and potential explanations for the challenges, modifications, and difficulties. We will also conduct the assessment of ethical considerations during this phase.Each case has a specific historical, social, environmental, and political context as well as relations between the populations and healthcare providers. The temporal dimension of these relations is essential to understand, as the intervention arms will certainly bring about changes that will evolve over time ,77. The The in-depth research strategy and use of multiple sources of evidence  reinforcA preparatory workshop between researchers (M1) will ensure a common understanding of concepts, analytical framework, and data collection strategy. An expert will give a workshop on the NVivo software to the research staff in order to establish a common platform for the data analyses throughout the study. We will record, transcribe, and code all interviews. We will conduct content analyses ,85. We wThere are no constraints or restrictions weighing on the autonomy and independence of the study or the publication of its results. Ethical committees in Burkina Faso and at the University of Montreal Hospital Research Center (CRCHUM) have approved the study. The study's objectives are aligned with Burkina Faso's national priorities. The Ministry of Health and donors have requested an evaluation of the four intervention arms. We will inform all relevant stakeholders and authorities about the purpose of the study and the presence of research assistants on the field. We will not disclose the performance of selected cases to the participants. We will obtain oral or written informed consent from the participants depending on their literacy level.The study is financed through the first author's (VR) programmatic research funds allocated by the Canadian Institutes of Health Research (CIHR). The data collection will begin during summer 2014. The data cleaning or analyses will not have begun at the time of submission of this protocol.An important strength of this protocol rests in its rigorous design. Langley et al.  have argMoreover, the context in Burkina Faso provides a unique opportunity to examine the interactional implementation process of combined interventions. This study has been designed so that we can disentangle and compare the distinct contributions of PBF, pro-poor targeting, and CBHI. This will allow us to understand the added value of each component.As with any population health intervention research, various methodological and operational challenges are likely to arise during the course of this study. One difficulty will be to avoid or control for the implementation of other studies or interventions overlapping with our area of interest. Health needs in Burkina Faso are urgent, so a number of prominent international health agencies are intervening with their own agendas or priorities at stake. The lack of coordination between all the actors makes it difficult to select cases with the assurance that no other confounding study or intervention will affect or contaminate our sample. Potentially confounding factors will be handled on a case-by-case basis, for example through negotiation with other stakeholders and adaptation of methodological strategies. Our close ties and constant communication with the country's Ministry of Health, funders, and local stakeholders will allow us to remain well informed throughout the study in order to take appropriate measures in a timely fashion, if needed.Another limitation of this study will be the difficulty in establishing a causal chain between the inputs, the processes, and the results. Inferring causality for interventions implemented in a real-life setting is more complex, but on the positive side, results tend to be more pertinent for decision making. Another concern for this study is that multiple stakeholders have been directly implicated in the implementation of the interventions and may have vested interests in its promotion. Although the perceptions and strategies of the actors are part of the object of the present study, we must be wary of the possibility that participants may introduce biases in the study. Overall, we will try to strengthen the validity of the results by using multiple sources of data and varied methods of data collection and analysis.www.equitesante.org). Moreover, we will present the results in local and international conferences. Lastly, we will publish scientific articles in open access journals to promote access to the findings.This evaluation study will promote the utilization of the results. Throughout the study, the research team will collaborate with key decision makers and stakeholders to ensure that the research questions are pertinent and that the results will be useful for evidence-based decision making. This collaboration will flourish without influencing the scientific independence of research. We will organize workshops to plan the study and share results locally. We will disseminate the results using reports, policy briefs, and lay publications distributed in French and in English. These will also be shared on our webpage (Independent evaluations of PBF in LMIC are rare and mainly examine impacts. To date, little research has helped to understand issues related to the implementation process and the coping strategies of actors that are at the heart of complex interventions. Moreover, it is urgent to clarify how PBF can be combined with other approaches to promote equitable access to healthcare services. The implementation of interventions with high synergistic potential in Burkina Faso provides a unique opportunity to respond to the existing knowledge gap. In this article, we have presented a comprehensive protocol that aims to study the emergence, the fidelity, the processes, the sustainability, the conditions that can influence scaling-up, and the ethical considerations of four intervention arms that combine PBF with pro-poor targeting and CBHI. The complex mixed methods design will allow researchers and decision makers to understand the evolution of these approaches over time. Ultimately, the scientific evidence produced should be used to promote access to high-quality healthcare for vulnerable groups.