A consensus-based tool for ranking the risk of blood-transmissible infections.

BACKGROUND: Emerging infectious diseases (EIDs) pose a threat to blood transfusion safety. Despite a lack of evidence, safety interventions may be required. However, what should decision makers base their decisions on? A model was developed that allows valuing the perceived risk of an EID for blood safety as derived from a group of experts. The model requires estimates of four disease characteristics and the accuracy of these estimates. STUDY DESIGN AND METHODS: Sixteen selected experts ranked 24 hypothetical diseases, each comprising a quantitative estimate of four characteristics: transfusion transmissibility, proportion of asymptomatic infectious phase, prevalence of infection, and disease impact. Each of the characteristics was expressed at one of six predefined levels with varying ranges of uncertainty. The model was derived using probabilistic inversion and was applied to value the perceived risk of most currently known EIDs relevant to blood transfusion. RESULTS: The model demonstrated that transmissibility and prevalence are the most important risk drivers. However, disease impact and likelihood of transmission during the asymptomatic phase of infection are more important when the disease characteristics are unknown. In the ranking of currently known EIDs, diseases that have been identified previously as posing a serious risk to blood transfusion appear at the top of the list. CONCLUSION: With the current model, the perceived risk of EIDs for transfusion safety can be determined for both known and unknown diseases, even when little information is available. Extension of the expert base, further model development and validation, and continuous updating of the model are recommended.

Course of iron parameters in HFE-hemochromatosis patients during initial treatment with erythrocytapheresis compared to phlebotomy.

Current treatment for newly diagnosed patients with hereditary hemochromatosis (HH) and iron overload consist of weekly phlebotomy or less frequent and more personalized erythrocytapheresis. Previous observations during phlebotomy suggest an increase in intestinal iron uptake caused by lowering of hepcidin as a result of intensive bloodletting. It is not known whether such an effect is present or even more pronounced using erythrocytapheresis since a larger amount of iron is extracted per procedure. In this study we aimed to assess the effect of erythrocytapheresis on the course of iron parameters, with special focus on serum hepcidin. We performed a retrospective proof-of-principle observational study, comparing serum iron parameters in 12 males during the depletion phase using either phlebotomy (n = 6) or erythrocytapheresis (n = 6). Decreases in serum ferritin over time were similar for both treatments but more pronounced using erythrocytapheresis when expressed per treatment procedure. Hemoglobin did not change during erythrocytapheresis, whereas during phlebotomy decreased with 10%. Increase of erythropoietin and soluble transferrin receptor and decrease in transferrin saturation were similar for both treatments. Reduction in serum hepcidin was higher (50% versus 25% of initial value) and occurred more early using phlebotomy (10 versus 20 weeks after start). In aggregate, compared to phlebotomy, the less frequent and more personalized erythrocytapheresis leads to a more pronounced decrease in serum ferritin per treatment procedure, without a larger decrease in serum hepcidin. This may be clinically relevant and may prevent an increase in intestinal iron uptake and an ensuing vicious circle of more frequent treatment procedures. J. Clin. Apheresis 31:564-570, 2016. © 2015 Wiley Periodicals, Inc.

Using expert judgment to estimate marine ecosystem vulnerability in the California Current.

As resource management and conservation efforts move toward multi-sector, ecosystem-based approaches, we need methods for comparing the varying responses of ecosystems to the impacts of human activities in order to prioritize management efforts, allocate limited resources, and understand cumulative effects. Given the number and variety of human activities affecting ecosystems, relatively few empirical studies are adequately comprehensive to inform these decisions. Consequently, management often turns to expert judgment for information. Drawing on methods from decision science, we offer a method for eliciting expert judgment to (1) quantitatively estimate the relative vulnerability of ecosystems to stressors, (2) help prioritize the management of stressors across multiple ecosystems, (3) evaluate how experts give weight to different criteria to characterize vulnerability of ecosystems to anthropogenic stressors, and (4) identify key knowledge gaps. We applied this method to the California Current region in order to evaluate the relative vulnerability of 19 marine ecosystems to 53 stressors associated with human activities, based on surveys from 107 experts. When judging the relative vulnerability of ecosystems to stressors, we found that experts primarily considered two criteria: the ecosystem's resistance to the stressor and the number of species or trophic levels affected. Four intertidal ecosystems (mudflat, beach, salt marsh, and rocky intertidal) were judged most vulnerable to the suite of human activities evaluated here. The highest vulnerability rankings for coastal ecosystems were invasive species, ocean acidification, sea temperature change, sea level rise, and habitat alteration from coastal engineering, while offshore ecosystems were assessed to be most vulnerable to ocean acidification, demersal destructive fishing, and shipwrecks. These results provide a quantitative, transparent, and repeatable assessment of relative vulnerability across ecosystems to any ongoing or emerging human activity. Combining these results with data on the spatial distribution and intensity of human activities provides a systematic foundation for ecosystem-based management.

Mapping cumulative impacts to coastal ecosystem services in British Columbia.

Ecosystem services are impacted through restricting service supply, through limiting people from accessing services, and by affecting the quality of services. We map cumulative impacts to 8 different ecosystem services in coastal British Columbia using InVEST models, spatial data, and expert elicitation to quantify risk to each service from anthropogenic activities. We find that impact to service access and quality as well as impact to service supply results in greater severity of impact and a greater diversity of causal processes of impact than only considering impact to service supply. This suggests that limiting access to services and impacts to service quality may be important and understanding these kinds of impacts may complement our knowledge of impacts to biophysical systems that produce services. Some ecosystem services are at greater risk from climate stressors while others face greater risk from local activities. Prominent causal pathways of impact include limiting access and affecting quality. Mapping cumulative impacts to ecosystem services can yield rich insights, including highlighting areas of high impact and understanding causes of impact, and should be an essential management tool to help maintain the flow of services we benefit from.

Cost-Effectiveness of a Proactive Primary Care Program for Frail Older People: A Cluster-Randomized Controlled Trial.

BACKGROUND: A proactive integrated approach has shown to preserve daily functioning among older people in the community. The aim is to determine the cost-effectiveness of a proactive integrated primary care program. METHODS: Economic evaluation embedded in a single-blind, 3-armed, cluster-randomized controlled trial with 12 months' follow-up in 39 general practices in the Netherlands. General practices were randomized to one of 3 trial arms: (1) an electronic frailty screening instrument using routine medical record data followed by standard general practitioner (GP) care; (2) this screening instrument followed by a nurse-led care program; or (3) usual care. Health resource utilization data were collected using electronic medical records and questionnaires. Associated costs were calculated. A cost-effectiveness analysis from a societal perspective was undertaken. The incremental cost per quality-adjusted life-year was calculated comparing proactive screening arm with usual care, and screening plus nurse-led care arm with usual care, as well as the screening arm with screening plus nurse-led care arm. RESULTS: Out of 7638 potential participants, 3092 (40.5%) older adults participated. Whereas effect differences were minor, the total costs per patient were lower in both intervention groups compared with usual care. The probability of cost-effectiveness at €20,000 per QALY threshold was 87% and 91% for screening plus GP care versus usual care and for screening plus nurse-led care compared to usual care, respectively. For screening plus nurse-led care vs screening plus standard GP care, the probability was 55%. CONCLUSION: A proactive screening intervention has a high probability of being cost-effective compared to usual care. The combined intervention showed less value for money.

The Predictive Value of Discrete Choice Experiments in Public Health: An Exploratory Application.

OBJECTIVE: The objective of this study was to assess the predictive value of a discrete choice experiment (DCE) in public health by comparing stated preferences to actual behavior. METHODS: 780 Type 2 diabetes mellitus (T2DM) patients received a questionnaire, containing a DCE with five attributes related to T2DM patients' willingness to participate in a combined lifestyle intervention. Panel mixed-multinomial-logit models were used to estimate the stated preferences based on 206 completed DCE questionnaires. Actual participation status was retrieved for 54 respondents based on patients' medical records and a second questionnaire. Predicted and actual behavior data were compared at population level and at individual level. RESULTS: Based on the estimated utility function, 81.8% of all answers that individual respondents provided on the choice tasks were predicted correctly. The actual participation rate at the aggregated population level was minimally underestimated (70.1 vs. 75.9%). Of all individual choices, 74.1% were predicted correctly with a positive predictive value of 0.80 and a negative predictive value of 0.44. CONCLUSION: Stated preferences derived from a DCE can adequately predict actual behavior in a public health setting.