Impact of donor lung quality on post-transplant recipient outcome in the Lung Allocation Score era in Eurotransplant - a historical prospective study.

The aim of this study was to investigate whether there is an impact of donation rates on the quality of lungs used for transplantation and whether donor lung quality affects post-transplant outcome in the current Lung Allocation Score era. All consecutive adult LTx performed in Eurotransplant (ET) between January 2012 and December 2016 were included (N = 3053). Donors used for LTx in countries with high donation rate were younger (42% vs. 33% ≤45 years, P < 0.0001), were less often smokers (35% vs. 46%, P < 0.0001), had more often clear chest X-rays (82% vs. 72%, P < 0.0001), had better donor oxygenation ratios (20% vs. 26% with PaO2 /FiO2  ≤ 300 mmHg, P < 0.0001), and had better lung donor score values (LDS; 28% vs. 17% with LDS = 6, P < 0.0001) compared with donors used for LTx in countries with low donation rate. Survival rates for the groups LDS = 6 and ≥7 at 5 years were 69.7% and 60.9% (P = 0.007). Lung donor quality significantly impacts on long-term patient survival. Countries with a low donation rate are more oriented to using donor lungs with a lesser quality compared to countries with a high donation rate. Instead of further stretching donor eligibility criteria, the full potential of the donor pool should be realized.

Lung allocation score: the Eurotransplant model versus the revised US model - a cross-sectional study.

Both Eurotransplant (ET) and the US use the lung allocation score (LAS) to allocate donor lungs. In 2015, the US implemented a new algorithm for calculating the score while ET has fine-tuned the original model using business rules. A comparison of both models in a contemporary patient cohort was performed. The rank positions and the correlation between both scores were calculated for all patients on the active waiting list in ET. On February 6th 2017, 581 patients were actively listed on the lung transplant waiting list. The median LAS values were 32.56 and 32.70 in ET and the US, respectively. The overall correlation coefficient between both scores was 0.71. Forty-three per cent of the patients had a < 2 point change in their LAS. US LAS was more than two points lower for 41% and more than two points higher for 16% of the patients. Median ranks and the 90th percentiles for all diagnosis groups did not differ between both scores. Implementing the 2015 US LAS model would not significantly alter the current waiting list in ET.

Heart re-transplantation in Eurotransplant.

Internationally 3% of the donor hearts are distributed to re-transplant patients. In Eurotransplant, only patients with a primary graft dysfunction (PGD) within 1 week after heart transplantation (HTX) are indicated for high urgency listing. The aim of this study is to provide evidence for the discussion on whether these patients should still be allocated with priority. All consecutive HTX performed in the period 1981-2015 were included. Multivariate Cox' model was built including: donor and recipient age and gender, ischaemia time, recipient diagnose, urgency status and era. The study population included 18 490 HTX, of these 463 (2.6%) were repeat transplants. The major indications for re-HTX were cardiac allograft vasculopathy (CAV) (50%), PGD (26%) and acute rejection (21%). In a multivariate model, compared with first HTX hazards ratio and 95% confidence interval for repeat HTX were 2.27 (1.83-2.82) for PGD, 2.24 (1.76-2.85) for acute rejection and 1.22 (1.00-1.48) for CAV (P < 0.0001). Outcome after cardiac re-HTX strongly depends on the indication for re-HTX with acceptable outcomes for CAV. In contrast, just 47.5% of all hearts transplanted in patients who were re-transplanted for PGD still functioned at 1-month post-transplant. Alternative options like VA-ECMO should be first offered before opting for acute re-transplantation.

Pediatric heart allocation and transplantation in Eurotransplant.

Pediatric heart allocation in Eurotransplant (ET) has evolved over the past decades to better serve patients and improve utilization. Pediatric heart transplants (HT) account for 6% of the annual transplant volume in ET. Death rates on the pediatric heart transplant waiting list have decreased over the years, from 25% in 1997 to 18% in 2011. Within the first year after listing, 32% of all infants (<12 months), 20% of all children aged 1-10 years, and 15% of all children aged 11-15 years died without having received a heart transplant. Survival after transplantation improved over the years, and in almost a decade, the 1-year survival went from 83% to 89%, and the 3-year rates increased from 81% to 85%. Improved medical management of heart failure patients and the availability of mechanical support for children have significantly improved the prospects for children on the heart transplant waiting list.

Then there were seven: a commentary on creating a public involvement strategy group for a policy research unit in behavioural science.

The National Institute for Health and Care Research (NIHR) Policy Research Unit in Behavioural Science (PRU-BS) was funded to inform government on the application of behavioural science in health and social care policy. What makes this unit different to other topic specific ones, was the wide range of its brief. Because of this, the PPI group would need to include a wide range of experience and expertise and be prepared to learn. We were a different type of public group for a different type of task. This paper deals with how we approached this. In this paper we outline how the PPI plan in the funding proposal for the PRU-BS was adapted to real world challenges. We describe the stages in the formation of the PPI Strategy Group and how a virtual platform was created to ensure good communication. We discuss our pragmatic approach of developing Terms of Reference and a PPI strategy document. Given the restrictions imposed by the Covid-19 pandemic we explain how we tackled PPI SG member induction sessions, meetings and training sessions. To illustrate how the group operates we provide an example of our involvement in a PRU-BS project. Central to our paper is the lessons we learned. We hope the challenges we met in forming the unique PPI SG, how these were overcome, and our recommendations will help others faced with a similar task.

The Policy Research Unit in Behavioural Science (PRU-BS) was formed in early 2019, funded by the National Institute for Health and Care Research (NIHR). The aim of the unit is to advise the government on the use of behavioural science (the study of human behaviour) to inform health and social care policy. From the outset the aim was to embed PPI in all aspects of the unit's work from the governance and direction of the unit to the individual research projects it conducts. As behavioural science cuts across all aspects of health, recruiting members of the public to work within the PRU-BS required careful thought. In this paper we describe the processes of recruiting to our PPI Strategy Group, the induction and training, and the ways in which we worked to develop the group and become embedded within the unit. Lastly, we present several recommendations based on our experiences of forming the PPI Strategy Group. Although this is aimed primarily at those contemplating setting up a group whose remit extends beyond a single research project, we hope this will be a useful resource for the public, researchers and others working in PPI.

The London low emission zone baseline study.

On February 4, 2008, the world's largest low emission zone (LEZ) was established. At 2644 km2, the zone encompasses most of Greater London. It restricts the entry of the oldest and most polluting diesel vehicles, including heavy-goods vehicles (haulage trucks), buses and coaches, larger vans, and minibuses. It does not apply to cars or motorcycles. The LEZ scheme will introduce increasingly stringent Euro emissions standards over time. The creation of this zone presented a unique opportunity to estimate the effects of a stepwise reduction in vehicle emissions on air quality and health. Before undertaking such an investigation, robust baseline data were gathered on air quality and the oxidative activity and metal content of particulate matter (PM) from air pollution monitors located in Greater London. In addition, methods were developed for using databases of electronic primary-care records in order to evaluate the zone's health effects. Our study began in 2007, using information about the planned restrictions in an agreed-upon LEZ scenario and year-on-year changes in the vehicle fleet in models to predict air pollution concentrations in London for the years 2005, 2008, and 2010. Based on this detailed emissions and air pollution modeling, the areas in London were then identified that were expected to show the greatest changes in air pollution concentrations and population exposures after the implementation of the LEZ. Using these predictions, the best placement of a pollution monitoring network was determined and the feasibility of evaluating the health effects using electronic primary-care records was assessed. To measure baseline pollutant concentrations before the implementation of the LEZ, a comprehensive monitoring network was established close to major roadways and intersections. Output-difference plots from statistical modeling for 2010 indicated seven key areas likely to experience the greatest change in concentrations of nitrogen dioxide (NO2) (at least 3 microg/m3) and of PM with an aerodynamic diameter < or = 10 microm (PM10) (at least 0.75 microg/m3) as a result of the LEZ; these suggested that the clearest signals of change were most likely to be measured near roadsides. The seven key areas were also likely to be of importance in carrying out a study to assess the health outcomes of an air quality intervention like the LEZ. Of the seven key areas, two already had monitoring sites with a full complement of equipment, four had monitoring sites that required upgrades of existing equipment, and one required a completely new installation. With the upgrades and new installations in place, fully ratified (verified) pollutant data (for PM10, PM with an aerodynamic diameter < or = 2.5 microm [PM2.5], nitrogen oxides [NOx], and ozone [O3] at all sites as well as for particle number, black smoke [BS], carbon monoxide [CO], and sulfur dioxide [SO2] at selected sites) were then collected for analysis. In addition, the seven key monitoring sites were supported by other sites in the London Air Quality Network (LAQN). From these, a robust set of baseline air quality data was produced. Data from automatic and manual traffic counters as well as automatic license-plate recognition cameras were used to compile detailed vehicle profiles. This enabled us to establish more precise associations between ambient pollutant concentrations and vehicle emissions. An additional goal of the study was to collect baseline PM data in order to test the hypothesis that changes in traffic densities and vehicle mixes caused by the LEZ would affect the oxidative potential and metal content of ambient PM10 and PM2.5. The resulting baseline PM data set was the first to describe, in detail, the oxidative potential and metal content of the PM10 and PM2.5 of a major city's airshed. PM in London has considerable oxidative potential; clear differences in this measure were found from site to site, with evidence that the oxidative potential of both PM10 and PM2.5 at roadside monitoring sites was higher than at urban background locations. In the PM10 samples this increased oxidative activity appeared to be associated with increased concentrations of copper (Cu), barium (Ba), and bathophenanthroline disulfonate-mobilized iron (BPS Fe) in the roadside samples. In the PM2.5 samples, no simple association could be seen, suggesting that other unmeasured components were driving the increased oxidative potential in this fraction of the roadside samples. These data suggest that two components were contributing to the oxidative potential of roadside PM, namely Cu and BPS Fe in the coarse fraction of PM (PM with an aerodynamic diameter of 2.5 microm to 10 microm; PM(2.5-10)) and an unidentified redox catalyst in PM2.5. The data derived for this baseline study confirmed key observations from a more limited spatial mapping exercise published in our earlier HEI report on the introduction of the London's Congestion Charging Scheme (CCS) in 2003 (Kelly et al. 2011a,b). In addition, the data set in the current report provided robust baseline information on the oxidative potential and metal content of PM found in the London airshed in the period before implementation of the LEZ; the finding that a proportion of the oxidative potential appears in the PM coarse mode and is apparently related to brake wear raises important issues regarding the nature of traffic management schemes. The final goal of this baseline study was to establish the feasibility, in ethical and operational terms, of using the U.K.'s electronic primary-care records to evaluate the effects of the LEZ on human health outcomes. Data on consultations and prescriptions were compiled from a pilot group of general practices (13 distributed across London, with 100,000 patients; 29 situated in the inner London Borough of Lambeth, with 200,000 patients). Ethics approvals were obtained to link individual primary-care records to modeled NOx concentrations by means of post-codes. (To preserve anonymity, the postcodes were removed before delivery to the research team.) A wide range of NOx exposures was found across London as well as within and between the practices examined. Although we observed little association between NOx exposure and smoking status, a positive relationship was found between exposure and increased socioeconomic deprivation. The health outcomes we chose to study were asthma, chronic obstructive pulmonary disease, wheeze, hay fever, upper and lower respiratory tract infections, ischemic heart disease, heart failure, and atrial fibrillation. These outcomes were measured as prevalence or incidence. Their distributions by age, sex, socioeconomic deprivation, ethnicity, and smoking were found to accord with those reported in the epidemiology literature. No cross-sectional positive associations were found between exposure to NOx and any of the studied health outcomes; some associations were significantly negative. After the pilot study, a suitable primary-care database of London patients was identified, the General Practice Research Database responsible for giving us access to these data agreed to collaborate in the evaluation of the LEZ, and an acceptable method of ensuring privacy of the records was agreed upon. The database included about 350,000 patients who had remained at the same address over the four-year period of the study. Power calculations for a controlled longitudinal analysis were then performed, indicating that for outcomes such as consultations for respiratory illnesses or prescriptions for asthma there was sufficient power to identify a 5% to 10% reduction in consultations for patients most exposed to the intervention compared with patients presumed to not be exposed to it. In conclusion, the work undertaken in this study provides a good foundation for future LEZ evaluations. Our extensive monitoring network, measuring a comprehensive set of pollutants (and a range of particle metrics), will continue to provide a valuable tool both for assessing the impact of LEZ regulations on air quality in London and for furthering understanding of the link between PM's composition and toxicity. Finally, we believe that in combination with our modeling of the predicted population-based changes in pollution exposure in London, the use of primary-care databases forms a sound basis and has sufficient statistical power for the evaluation of the potential impact of the LEZ on human health.

AMUC: Associated Motion capture User Categories.

The AMUC (Associated Motion capture User Categories) project consisted of building a prototype sketch retrieval client for exploring motion capture archives. High-dimensional datasets reflect the dynamic process of motion capture and comprise high-rate sampled data of a performer's joint angles; in response to multiple query criteria, these data can potentially yield different kinds of information. The AMUC prototype harnesses graphic input via an electronic tablet as a query mechanism, time and position signals obtained from the sketch being mapped to the properties of data streams stored in the motion capture repository. As well as proposing a pragmatic solution for exploring motion capture datasets, the project demonstrates the conceptual value of iterative prototyping in innovative interdisciplinary design. The AMUC team was composed of live performance practitioners and theorists conversant with a variety of movement techniques, bioengineers who recorded and processed motion data for integration into the retrieval tool, and computer scientists who designed and implemented the retrieval system and server architecture, scoped for Grid-based applications. Creative input on information system design and navigation, and digital image processing, underpinned implementation of the prototype, which has undergone preliminary trials with diverse users, allowing identification of rich potential development areas.