Physical Sciences Research Council Research Articles

Markov Decision Processes with Observation Costs: Framework and Computation with a Penalty Scheme

We consider Markov decision processes where the state of the chain is only given at chosen observation times and of a cost. Optimal strategies involve the optimization of observation times as well as the subsequent action values. We consider the finite horizon and discounted infinite horizon problems as well as an extension with parameter uncertainty. By including the time elapsed from observations as part of the augmented Markov system, the value function satisfies a system of quasivariational inequalities (QVIs). Such a class of QVIs can be seen as an extension to the interconnected obstacle problem. We prove a comparison principle for this class of QVIs, which implies the uniqueness of solutions to our proposed problem. Penalty methods are then utilized to obtain arbitrarily accurate solutions. Finally, we perform numerical experiments on three applications that illustrate our framework. Funding: J. Tam is supported by the Engineering and Physical Sciences Research Council [Grant 2269738].

Correlated Equilibria for Mean Field Games with Progressive Strategies

In a discrete space and time framework, we study the mean field game limit for a class of symmetric N-player games based on the notion of correlated equilibrium. We give a definition of correlated solution that allows us to construct approximate N-player correlated equilibria that are robust with respect to progressive deviations. We illustrate our definition by way of an example with explicit solutions. Funding: O. Bonesini acknowledges financial support from Engineering and Physical Sciences Research Council [Grant EP/T032146/1]. M. Fischer acknowledges partial support through the University of Padua [Research Project BIRD229791 “Stochastic mean field control and the Schrödinger problem”].

Submodular Functions and Perfect Graphs

We give a combinatorial polynomial-time algorithm to find a maximum weight independent set in perfect graphs of bounded degree that do not contain a prism or a hole of length four as an induced subgraph. An even pair in a graph is a pair of vertices all induced paths between which are even. An even set is a set of vertices every two of which are an even pair. We show that every perfect graph that does not contain a prism or a hole of length four as an induced subgraph has a balanced separator which is the union of a bounded number of even sets, where the bound depends only on the maximum degree of the graph. This allows us to solve the maximum weight independent set problem using the well-known submodular function minimization algorithm. Funding: This work was supported by the Engineering and Physical Sciences Research Council [Grant EP/V002813/1]; the National Science Foundation [Grants DMS-1763817, DMS-2120644, and DMS-2303251]; and Alexander von Humboldt-Stiftung.

A New Simheuristic Approach for Stochastic Runway Scheduling

We consider a stochastic, dynamic runway scheduling problem involving aircraft landings on a single runway. Sequencing decisions are made with knowledge of the estimated arrival times (ETAs) of all aircraft due to arrive at the airport, and these ETAs vary according to continuous-time stochastic processes. Time separations between consecutive runway landings are modeled via sequence-dependent Erlang distributions and are affected by weather conditions, which also evolve continuously over time. The resulting multistage optimization problem is intractable using exact methods, and we propose a novel simheuristic approach based on the application of methods analogous to variable neighborhood search in a high-dimensional stochastic environment. Our model is calibrated using flight tracking data for over 98,000 arrivals at Heathrow Airport. Results from numerical experiments indicate that our proposed simheuristic algorithm outperforms an alternative based on deterministic forecasts under a wide range of parameter values, with the largest benefits seen when the underlying stochastic processes become more volatile and also when the on-time requirements of individual flights are given greater weight in the objective function. Funding: This work was supported by the Engineering and Physical Sciences Research Council [Grant EP/M020258/1]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/trsc.2022.0400 .

QUANTIFICATION OF THE ACCURACY OF IN VIVO TIBIOFEMORAL KINEMATICS CALCULATED USING MAGNETIC RESONANCE IMAGING AND BIPLANE VIDEO X-RAY

AbstractObjectivesInvestigate Magnetic Resonance Imaging (MRI) as an alternative to Computerised Tomography (CT) when calculating kinematics using Biplane Video X-ray (BVX) by quantifying the accuracy of a combined MRI-BVX methodology by comparing with results from a gold-standard bead-based method.MethodsWritten informed consent was given by one participant who had four tantalum beads implanted into their distal femur and proximal tibia from a previous study. Three-dimensional (3D) models of the femur and tibia were segmented (Simpleware Scan IP, Synopsis) from an MRI scan (Magnetom 3T Prisma, Siemens). Anatomical Coordinate Systems (ACS) were applied to the bone models using automated algorithms1. The beads were segmented from a previous CT and co-registered with the MRI bone models to calculate their positions. BVX (60 FPS, 1.25 ms pulse width) was recorded whilst the participant performed a lunge. The beads were tracked, and the ACS position of the femur and tibia were calculated at each frame (DSX Suite, C-Motion Inc.). The beads were digitally removed from the X-rays (MATLAB, MathWorks) allowing for blinded image-registration of the MRI models to the radiographs. The mean difference and standard deviation (STD) between bead-generated and image-registered bone poses were calculated for all degrees of freedom (DOF) for both bones. Using the principles defined by Grood and Suntay2, 6 DOF kinematics of the tibiofemoral joint were calculated (MATLAB, MathWorks). The mean difference and STD between these two sets of kinematics were calculated.ResultsThe absolute mean femur and tibia ACS position differences (Table 1) between the bead and image-registered poses were found to be within 0.75mm for XYZ, with all STD within ±0.5mm. Mean rotation differences for both bones were found to be within 0.2º for XYZ (Table 1). The absolute mean tibiofemoral joint translations (Table 1) were found to be within ±0.7mm for all DOF, with the smallest absolute mean in compression-distraction. The absolute mean tibiofemoral rotations were found to be within 0.25º for all DOF (Table 1), with the smallest mean was found in abduction-adduction. The largest mean and STD were found in internal-external rotation due to the angle of the X-rays relative to the joint movement, increasing the difficulty of manual image registration in that plane.ConclusionThe combined MRI-BVX method produced bone pose and tibiofemoral kinematics accuracy similar to previous CT results3. This allows for confidence in future results, especially in clinical applications where high accuracy is needed to understand the effects of disease and the efficacy of surgical interventions. Acknowledgements: This research was supported by the Engineering and Physical Sciences Research Council (EPSRC) doctoral training grant (EP/T517951/1).Declaration of Interest(b) declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported:I declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.

In the Lab: Heterogeneous Catalysis Mediated Interconversion between NAD(P)+ and NAD(P)H Accompanied by Consumption and Generation of Hydrogen

Dr. Wang is a Senior Lecturer in Chemical Engineering at Lancaster University. Prior to this, he was a Lecturer in Chemical Engineering at the University of Aberdeen, Postdoctoral Research Associate at Heriot-Watt University, where he also obtained his PhD (2014). He completed both MSc and BEng studies at Tianjin University. Wang has been the author of over 50 peer-reviewed publications, an editorial board member of Chinese Chemical Letters and his research has mainly been funded by the Engineering and Physical Sciences Research Council (EPSRC), Royal Society, UK Catalysis Hub and industry. Wang’s research interest ranges from reaction engineering, green energy and materials to chemicals, where heterogeneous catalysis is the core discipline. His recent work has focused on the innovative use of heterogeneous catalysts (e.g., supported metals) in enzymatic transformations via cofactor regeneration,1,2 paving the way to a potential new regeneration technology.

Urban–rural disparity in global estimation of PM2·5 household air pollution and its attributable health burden

Polluting fuels and inefficient stove technologies are still a leading cause of premature deaths worldwide, particularly in low-income and middle-income countries. Previous studies of global household air pollution (HAP) have neither considered the estimation of PM2·5 at national level nor the corresponding attributable mortality burden. Additionally, the effects of climate and ambient air pollution on the global estimation of HAP-PM2·5 exposure for different urban and rural settings remain largely unknown. In this study, we include climatic effects to estimate the HAP-PM2·5 exposure from different fuel types and stove technologies in rural and urban settings separately and the related attributable global mortality burden. Bayesian hierarchical models were developed to estimate an annual average HAP-PM2·5 personal exposure and HAP-PM2·5 indoor concentration (including both outdoor and indoor sources). Model variables were selected from sample data in 282 peer-reviewed studies drawn and updated from the WHO Global HAP dataset. The PM2·5 exposure coefficients from the developed model were applied to the external datasets to predict the HAP-PM2·5 exposure globally (personal exposure in 62 countries and indoor concentration in 69 countries). Attributable mortality rate was estimated using a comparative risk assessment approach. Using weighted averages, the national level 24 h average HAP-PM2·5 exposure due to polluting and clean fuels and related death rate per 100 000 population were estimated. In 2020, household use of polluting solid fuels for cooking and heating led to a national-level average personal exposure of 151 μg/m3 (95% CI 133-169), with rural households having an average of 171 μg/m3 (153-189) and urban households an average of 92 μg/m3 (77-106). Use of clean fuels gave rise to a national-level average personal exposure of 69 μg/m3 (62-76), with a rural average of 76 μg/m3 (69-83) and an urban average of 49 μg/m3 (46-53). Personal exposure-attributable premature mortality (per 100 000 population) from the use of polluting solid fuels at national level was on average 78 (95% CI 69-87), with a rural average of 82 (73-90) and an urban average of 66 (57-75). The average attributable premature mortality (per 100 000 population) from the use of clean fuels at the national level is 62 (54-70), with a rural average of 66 (58-74) and an urban average of 52 (47-57). The estimated HAP-PM2·5 indoor concentration shows that the use of polluting solid fuels resulted in a national-level average of 412 μg/m3 (95% CI 353-471), with a rural average of 514 μg/m3 (446-582) and an urban average of 149 μg/m3 (126-173). The use of clean fuels (gas and electricity) led to an average PM2·5 indoor concentration of 135 μg/m3 (117-153), with a rural average of 174 μg/m3 (154-195) and an urban average of 71 μg/m3 (63-80). Using time-weighted HAP-PM2·5 indoor concentrations, the attributable premature death rate (per 100 000 population) from the use of polluting solid fuels at the national level is on average 78 (95% CI 72-84), the rural average being 84 (78-91) and the urban average 60 (54-66). From the use of clean fuels, the average attributable premature death rate (per 100 000 population) at the national level is 59 (53-64), the rural average being 68 (62-74) and the urban average 45 (41-50). A shift from polluting to clean fuels can reduce the average PM2·5 personal exposure by 53% and thereby lower the death rate. For all fuel types, the estimated average HAP-PM2·5 personal exposure and indoor concentrations exceed the WHO's Interim Target-1 average annual threshold. Policy interventions are urgently needed to greatly increase the use of clean fuels and stove technologies by 2030 to achieve the goal of affordable clean energy access, as set by the UN in 2015, and address health inequities in urban-rural settings. Wellcome Trust, The Lancet Countdown, the Engineering and Physical Sciences Research Council, and the Natural Environment Research Council.

Nontruthful Position Auctions Are More Robust to Misspecification

We consider the classical model of sponsored search due to Edelman et al. and Varian and examine how robust standard position auctions are to a misspecification of the position-dependent quality factors used by this model. We show that under both complete and incomplete information a nontruthful position auction admits an efficient equilibrium for a strictly broader range of parameter values than the Vickrey-Clarke-Groves (VCG) mechanism, which would be truthful if the parameters were specified correctly. Our result for complete information concerns the generalized second-price (GSP) mechanism and is driven by a detailed understanding of the Nash equilibrium polytopes of the VCG mechanism and the GSP mechanism. Our result for incomplete information concerns the generalized first-price (GFP) mechanism and uses a surprising connection between the unique candidate equilibrium bidding functions of the VCG mechanism and the GFP mechanism. Funding: F. Fischer was supported by the Engineering and Physical Sciences Research Council [Grant EP/T015187/1] and Einstein Stiftung Berlin.

Similar‐to‐me effects in the grant application process: Applicants, panellists, and the likelihood of obtaining funds

We analyse if and how the characteristics of grant research panels affect the applicants' likelihood of obtaining funding and, especially, if particular types of panels favour particular types of applicants. We use the UK's Engineering and Physical Sciences Research Council (EPSRC) award decisions to test the similar‐to‐me hypothesis for the first time in the grant context. Our main results indicate that panel members tend to favour more (or penalise less) applicants with similar characteristics to them, as the similar‐to‐me hypothesis suggests. We show, for instance, that the quality of the applicants is more critical for panels of high quality than for panels of relatively lower quality, that basic‐oriented panels tend to penalise applied‐oriented applicants, and that panels with fewer female members tend to penalise teams with more female applicants. As a whole, we show that similar‐to‐me effects are simultaneously at work for a wide variety of functional, job‐related research characteristics as well as for more well‐known demographic attributes.

Physical activity in young children across developmental and health states: the ActiveCHILD study.

Evidence about physical activity of young children across developmental and health states is very limited. Using data from an inclusive UK cohort, ActiveCHILD, we investigated relationships between objectively measured physical activity, child development, social context, and health-related quality of life (HRQoL). Children (12-36 months), purposively sampled across health pathways, developmental abilities, and sociodemographic factors, were recruited through thirteen National Health Service organisations in England. Data were collected from 07/2017 to 08/2019 on: weekly physical activity (3-7 days) using waist-worn accelerometer (ActiGraph 3GTX); sociodemographics, parent actions, child HRQoL, and child development using questionnaires; and child health conditions using clinical records. A data-driven, unsupervised method, called hidden semi-Markov model (HSMM) segmented the accelerometery data and provided estimates of the total time spent active (any intensity) and very active (greater intensity) for each child. Relationships with the explanatory factors were investigated using multiple linear regression. Physical activity data were obtained for 282 children (56% females, mean age 21 months, 37.5% with a health condition) covering all index of multiple deprivation deciles. The patterns of physical activity consisted of two daily peaks, children spending 6.44 (SD=1.39) hours active (any intensity), of which 2.78 (SD=1.38) hours very active, 91% meeting WHO guidelines. The model for total time active (any intensity) explained 24% of variance, with mobility capacity the strongest predictor (β=0.41). The model for time spent very active explained 59% of variance, with mobility capacity again the strongest predictor (β=0.76). There was no evidence of physical activity explaining HRQoL. The findings provide new evidence that young children across developmental states regularly achieve mainstream recommended physical activity levels and challenges the belief that children with development problems need lower expectations for daily physical activity compared to peers. Advancing the rights of all children to participate in physical activity requires inclusive, equally ambitious, expectations for all. Niina Kolehmainen, HEE/NIHR Integrated Clinical Academic Senior Clinical Lecturer, NIHR ICA-SCL-2015-01-00, was funded by the NIHR for this research project. Christopher Thornton, Olivia Craw, Laura Kudlek, and Laura Cutler were also funded from this award. Tim Rapley is a member of the NIHR Applied Research Collaboration North East and North Cumbria, with part of his time funded through the related award (NIHR200173). The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR, NHS, or the UK Department of Health and Social Care. The work of Kianoush Nazarpour is supported by Engineering and Physical Sciences Research Council (EPSRC), under grant number EP/R004242/2.

Fibrosis entropy is associated with life-threatening arrhythmia in non-ischaemic cardiomyopathy

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): This work was supported by the National Institute for Health Research Biomedical Research Centre at Guy’s and St. Thomas’ Trust and King’s College, the Centre of Excellence in Medical Engineering funded by the Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC; WT088641/Z/09/Z). M.J.B. is supported by a Medical Research Council New Investigator Grant (MR/N011007/1) and British Heart Foundation (Project grant PG/18/74/34077). This work was supported by EPSRC 2018/19 DTP - EP/R513064/1 grant. This work was supported by a National Heart and Lung Institute Foundation grant awarded to Professor Sanjay Prasad and Dr Richard Jones. Background Enhanced risk stratification for implanted defibrillator requirement represents an important area of research in patients with non-ischemic cardiomyopathy (NICM). Myocardial fibrosis represents the major underlying arrhythmic substrate in this population, and its identification on late-gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) is associated with life-threatening arrhythmia (LTA). Fibrosis entropy, a measure of scar texture heterogeneity, may confer important information regarding the underlying pro-arrhythmic mechanisms of both core scar and areas of intermediate signal intensity (Gray Zone [GZ]). Purpose We sought to: 1) evaluate whether LGE-CMR assessment of left ventricular (LV) tissue entropy had incremental utility to fibrosis presence for arrhythmic risk stratification of patients with NICM; 2) quantify the added utility of GZ entropy in such analysis. Methods This study involved a prospective observational cohort of consecutive patients with NICM and myocardial fibrosis detected on LGE-CMR. Epicardial and endocardial contours obtained from LGE-CMR data were used with a FWHM method to delineate core fibrosis (≥50% maximum signal intensity) and GZ fibrosis (≥35%-<50% signal intensity). Fibrotic masks were subsequently used, along with native dicom LGE-CMR images to compute tissue entropy, defined by the standard Shannon Entropy for core fibrosis, GZ fibrosis, and combined core+GZ fibrosis. Patients underwent adjudicated long-term follow-up for LTA (composite of sudden cardiac death, aborted sudden cardiac death or sustained ventricular tachycardia). Results Of 291 patients with NICM and mid-wall/subepicardial fibrosis, 38 patients (13.1%) experienced LTA over median follow-up of 6.3 years (interquartile range 4.6-9.1 years). On Cox regression analysis, core fibrosis entropy (Hazard ratio [HR] 1.77, 95% CI 1.25-2.54, p=0.001), GZ fibrosis entropy (HR 1.74, 95% CI 1.20-2.54, p=0.004) and combined fibrosis entropy (HR 1.98, 95% CI 1.30-2.52, p=0.001) were associated LTA after adjustment for variables used to guide ICD implantation (LVEF <35% and NYHA class >1) and remained associated in multivariable models accounting separately for core and GZ fibrosis mass. The addition of core fibrosis entropy, GZ fibrosis entropy and combined fibrosis entropy to a baseline clinical model improved the C-statistic from 0.49 to 0.59, 0.62 and 0.62, respectively. LVEF <35% was not associated with LTA (HR 1.45, 95% CI 0.77-2.74, p=0.25) on multivariable analysis. Conclusions Fibrosis entropy on LGE-CMR offers incremental utility to LVEF and fibrosis presence for arrhythmic risk prediction in patients with NICM. The combination of core and GZ fibrosis entropy offers the highest association with risk.

Left ventricular shape remodelling predicts major arrhythmic events in stable coronary artery disease

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): This work was supported by the National Institute for Health Research Biomedical Research Centre at Guy’s and St. Thomas’ Trust and King’s College, the Centre of Excellence in Medical Engineering funded by the Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC; WT088641/Z/09/Z). M.J.B. is supported by a Medical Research Council New Investigator Grant (MR/N011007/1) and British Heart Foundation (Project grant PG/18/74/34077). This work was supported by EPSRC 2018/19 DTP - EP/R513064/1 grant. This work was supported by a National Heart and Lung Institute Foundation grant awarded to Professor Sanjay Prasad and Dr Richard Jones. Background Arrhythmic risk stratification of patients with stable coronary artery disease (CAD) for defibrillator implantation remains imprecise. Current clinical guidelines center on a basic assessment of adverse cardiac remodelling, an approach with well documented limitations. More advanced analysis of intricate and regional LV remodelling in these patients may shed new insight for enhanced risk prediction of life-threatening arrhythmia in stable CAD. Objective We explored a novel computational 3D LV shape analysis strategy to accurately represent, and quantify, arrhythmogenic LV remodelling patterns in late gadolinium enhancement cardiovascular magnetic resonance images (LGE-CMR) in patients with stable CAD. We assess the utility of our patient-specific 3D LV arrhythmic shape (LVAS) score predicting major arrhythmic event; comparing to the current clinical benchmark of severely reduced LVEF and NYHA functional class. Methods Patients with stable CAD were prospectively recruited into a CMR registry and followed up for a composite endpoint of major arrhythmic events (MAE) consisting of sudden cardiac death (SCD), aborted SCD or haemodynamically unstable VT. Time-to-event data was also recorded. 2D LGE-CMR images were contoured and used as input to an advanced computational shape-analysis approach (Figure 1A). Reconstructed 3D LV shape models were analysed using Principle Component Analysis and Cox-Lasso to characterise the average arrhythmogenic LV shape, which was then used to quantitatively define a patient-specific LV arrhythmic shape (LVAS) score. Results Of 397 patients (mean [SD] LVEF% 45.4 ± 16.0) followed for a median (IQR) of 6 (3) years, 55 (14%) experienced a major arrhythmic event (MAE). The mean (SD) LVEF for patients who experienced MAE was lower than for those that did not (37.1% ± 13.2 vs 46.7% ± 16.0), yet there was no difference in NYHA class. LVAS mean (95% confidence interval [CI]) score was different between event and event-free patients: 2.98 (0.48-6.44) vs 19.83 (10.66-29), P<0.001. On univariate Cox regression analysis both LVAS score (hazard ratio [HR] 2.1, 95% CI 1.6-2.7, P<0.001) and LVEF<35% (HR 2.9, 95% CI 1.6-5.0, P<0.01) were associated with the primary endpoint. NYHA Class >I was not associated with the primary endpoint (HR 1.5, 95% CI 0.8-2.7, P=0.221). In multivariate Cox regression analysis, LVAS remained independently associated with the primary endpoint after adjusting for LVEF<35% and NYHA>Class I: LVAS score HR 2.1, 95% CI 1.5-3.0, P<0.001; LVEF<35% HR 1.0, 95% CI 0.5-2.2, P=0.923; NYHA>Class I HR 1.3, 95% CI 0.7-2.5, P=0.443 (Figure 1 B, C). The addition of the LVAS score increased the C-statistic from 0.6 to 0.75 between models. Conclusion A Left Ventricle Arrhythmic Shape score improved arrhythmic risk stratification compared to guideline-based clinical parameters, highlighting a potentially novel approach to identifying candidates for implantable cardioverter defibrillators in stable CAD.

Advanced 3D analysis of fibrotic ring-like pattern in non-ischemic cardiomyopathy predicts major arrhythmic events

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): This work was supported by the National Institute for Health Research Biomedical Research Centre at Guy’s and St. Thomas’ Trust and King’s College, the Centre of Excellence in Medical Engineering funded by the Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC; WT088641/Z/09/Z). M.J.B. is supported by a Medical Research Council New Investigator Grant (MR/N011007/1) and British Heart Foundation (Project grant PG/18/74/34077). This work was supported by EPSRC 2018/19 DTP - EP/R513064/1 grant. This work was supported by a National Heart and Lung Institute Foundation grant awarded to Professor Sanjay Prasad and Dr Richard Jones. This work was supported by a National Heart and Lung Institute Foundation grant awarded to SKP, DJH, REJ, UT and BPH. Additionally, the study was supported by an Intermediate Clinical Research Fellowship awarded to BPH (FS/ICRF/21/26019). Background The presence of ring-like patterns of mid-wall fibrosis identified on late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) is associated with an increased risk of major arrhythmic events (MAE) in non-ischemic cardiomyopathy (NICM). Analysis of tissue bordering core fibrosis and healthy myocardium (Gray Zone [GZ]) has been suggested as an important pro-arrhythmic substrate in this population. Purpose To investigate refined anatomical definitions of the fibrotic ring pattern, including the importance of GZ inclusion in the association with MAE in NICM. Methods LGE CMR data from 292 NICM patients were analysed to delineate both core and GZ fibrosis. Fibrosis quantification masks for each 2D image slice were used, along with AHA 17-segment maps, to identify fibrotic ring patterns: defined by fibrosis extending by 3 or more continuous AHA-segments for any individually-contiguous fibrotic component within each slice (Fig 1A). Ring patterns were assessed separately for core fibrosis and core + GZ, as well as individually in basal, mid-basal and mid-apical regions. In separate analysis, LGE contours were aligned, interpolated, and used to generate 3D computational volumetric models (Fig 1B). Individually-connected scar components were extracted and the 3D circumferential angular variation (3DCAV) of each separate fibrotic structure quantified as a continuous variable (Fig 1C). Association of the presence of ring patterns and 3DCAV with a composite MAE were investigated. Results Of 292 patients, 67(23%) had core fibrotic ring patterns (54 basal, 28 mid-cavity level, 6 apical). Over a median(IQR) of 6(4) years, 16(24%) patients experienced MAE. On univariate Cox analysis, ring pattern core fibrosis was a strong predictor of MAE (Hazard ratio [HR] 2.2, 95% confidence interval [CI] 1.13-4.31, p=0.021). Apical-basal region analysis showed that basal ring pattern was associated with MAE (HR 2.25, 95%CI, 1.13-4.51, p=0.022). Multivariate Cox analysis including raised NYHA Class and severely reduced LVEF, overall ring (HR 2.14, 95%CI, 1.05-4.33, p=0.035) and basal ring pattern (HR 2.9, 95%CI 1.39-6.02, P=0.004) continued to show independent association with the MAE. Analysis of the full 3D geometry of the individual scar components also showed that our novel 3DCAV metric was associated with the MAE on both univariate (HR 1.31, 95%CI 1.08-1.59, P=0.007) and multivariate (HR 1.3, 95%CI, 1.06-1.60, P=0.013). Analysis of core ring patterns outperformed analysis of core+GZ patterns in all cases. Conclusions Our study confirms that ring-like patterns of fibrosis in NICM are strongly associated with MAE in NICM, with patterns predominantly at the basal regions conferring enhanced risk relative to mid-basal and mid-apical regions. Inclusion of GZ quantification in ring-pattern analysis did not enhance risk prediction. Our novel 3D analysis of circumferential fibrosis patterns may provide a more robust quantitative metric for stratification.

No time for complacency on COVID-19 in Europe

No time for complacency on COVID-19 in Europe

Profiling post-COVID-19 condition across different variants of SARS-CoV-2: a prospective longitudinal study in unvaccinated wild-type, unvaccinated alpha-variant, and vaccinated delta-variant populations

Self-reported symptom studies rapidly increased understanding of SARS-CoV-2 during the COVID-19 pandemic and enabled monitoring of long-term effects of COVID-19 outside hospital settings. Post-COVID-19 condition presents as heterogeneous profiles, which need characterisation to enable personalised patient care. We aimed to describe post-COVID-19 condition profiles by viral variant and vaccination status. In this prospective longitudinal cohort study, we analysed data from UK-based adults (aged 18-100 years) who regularly provided health reports via the Covid Symptom Study smartphone app between March 24, 2020, and Dec 8, 2021. We included participants who reported feeling physically normal for at least 30 days before testing positive for SARS-CoV-2 who subsequently developed long COVID (ie, symptoms lasting longer than 28 days from the date of the initial positive test). We separately defined post-COVID-19 condition as symptoms that persisted for at least 84 days after the initial positive test. We did unsupervised clustering analysis of time-series data to identify distinct symptom profiles for vaccinated and unvaccinated people with post-COVID-19 condition after infection with the wild-type, alpha (B.1.1.7), or delta (B.1.617.2 and AY.x) variants of SARS-CoV-2. Clusters were then characterised on the basis of symptom prevalence, duration, demography, and previous comorbidities. We also used an additional testing sample with additional data from the Covid Symptom Study Biobank (collected between October, 2020, and April, 2021) to investigate the effects of the identified symptom clusters of post-COVID-19 condition on the lives of affected people. We included 9804 people from the COVID Symptom Study with long COVID, 1513 (15%) of whom developed post-COVID-19 condition. Sample sizes were sufficient only for analyses of the unvaccinated wild-type, unvaccinated alpha variant, and vaccinated delta variant groups. We identified distinct profiles of symptoms for post-COVID-19 condition within and across variants: four endotypes were identified for infections due to the wild-type variant (in unvaccinated people), seven for the alpha variant (in unvaccinated people), and five for the delta variant (in vaccinated people). Across all variants, we identified a cardiorespiratory cluster of symptoms, a central neurological cluster, and a multi-organ systemic inflammatory cluster. These three main clusers were confirmed in a testing sample. Gastrointestinal symptoms clustered in no more than two specific phenotypes per viral variant. Our unsupervised analysis identified different profiles of post-COVID-19 condition, characterised by differing symptom combinations, durations, and functional outcomes. Our classification could be useful for understanding the distinct mechanisms of post-COVID-19 condition, as well as for identification of subgroups of individuals who might be at risk of prolonged debilitation. UK Government Department of Health and Social Care, Chronic Disease Research Foundation, The Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value-Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation, UK Alzheimer's Society, and ZOE.

Effects of sleep disturbance on dyspnoea and impaired lung function following hospital admission due to COVID-19 in the UK: a prospective multicentre cohort study

Sleep disturbance is common following hospital admission both for COVID-19 and other causes. The clinical associations of this for recovery after hospital admission are poorly understood despite sleep disturbance contributing to morbidity in other scenarios. We aimed to investigate the prevalence and nature of sleep disturbance after discharge following hospital admission for COVID-19 and to assess whether this was associated with dyspnoea. CircCOVID was a prospective multicentre cohort substudy designed to investigate the effects of circadian disruption and sleep disturbance on recovery after COVID-19 in a cohort of participants aged 18 years or older, admitted to hospital for COVID-19 in the UK, and discharged between March, 2020, and October, 2021. Participants were recruited from the Post-hospitalisation COVID-19 study (PHOSP-COVID). Follow-up data were collected at two timepoints: an early time point 2-7 months after hospital discharge and a later time point 10-14 months after hospital discharge. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire and a numerical rating scale. Sleep quality was also assessed with an accelerometer worn on the wrist (actigraphy) for 14 days. Participants were also clinically phenotyped, including assessment of symptoms (ie, anxiety [Generalised Anxiety Disorder 7-item scale questionnaire], muscle function [SARC-F questionnaire], dyspnoea [Dyspnoea-12 questionnaire] and measurement of lung function), at the early timepoint after discharge. Actigraphy results were also compared to a matched UK Biobank cohort (non-hospitalised individuals and recently hospitalised individuals). Multivariable linear regression was used to define associations of sleep disturbance with the primary outcome of breathlessness and the other clinical symptoms. PHOSP-COVID is registered on the ISRCTN Registry (ISRCTN10980107). 2320 of 2468 participants in the PHOSP-COVID study attended an early timepoint research visit a median of 5 months (IQR 4-6) following discharge from 83 hospitals in the UK. Data for sleep quality were assessed by subjective measures (the Pittsburgh Sleep Quality Index questionnaire and the numerical rating scale) for 638 participants at the early time point. Sleep quality was also assessed using device-based measures (actigraphy) a median of 7 months (IQR 5-8 months) after discharge from hospital for 729 participants. After discharge from hospital, the majority (396 [62%] of 638) of participants who had been admitted to hospital for COVID-19 reported poor sleep quality in response to the Pittsburgh Sleep Quality Index questionnaire. A comparable proportion (338 [53%] of 638) of participants felt their sleep quality had deteriorated following discharge after COVID-19 admission, as assessed by the numerical rating scale. Device-based measurements were compared to an age-matched, sex-matched, BMI-matched, and time from discharge-matched UK Biobank cohort who had recently been admitted to hospital. Compared to the recently hospitalised matched UK Biobank cohort, participants in our study slept on average 65 min (95% CI 59 to 71) longer, had a lower sleep regularity index (-19%; 95% CI -20 to -16), and a lower sleep efficiency (3·83 percentage points; 95% CI 3·40 to 4·26). Similar results were obtained when comparisons were made with the non-hospitalised UK Biobank cohort. Overall sleep quality (unadjusted effect estimate 3·94; 95% CI 2·78 to 5·10), deterioration in sleep quality following hospital admission (3·00; 1·82 to 4·28), and sleep regularity (4·38; 2·10 to 6·65) were associated with higher dyspnoea scores. Poor sleep quality, deterioration in sleep quality, and sleep regularity were also associated with impaired lung function, as assessed by forced vital capacity. Depending on the sleep metric, anxiety mediated 18-39% of the effect of sleep disturbance on dyspnoea, while muscle weakness mediated 27-41% of this effect. Sleep disturbance following hospital admission for COVID-19 is associated with dyspnoea, anxiety, and muscle weakness. Due to the association with multiple symptoms, targeting sleep disturbance might be beneficial in treating the post-COVID-19 condition. UK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council.

IN VIVO PILOT STUDY OF TIBIOFEMORAL KINEMATICS DURING LOADED DYNAMIC ACTIVITIES

Biplane video X-ray (BVX) – with models segmented from magnetic resonance imaging (MRI) – is used to directly track bones during dynamic activities. Investigating tibiofemoral kinematics helps to understand effects of disease, injury, and possible interventions.Develop a protocol and compare in-vivo kinematics during loaded dynamic activities using BVX and MRI.BVX (60 FPS) was captured whilst three healthy volunteers performed three repeats of lunge, stair ascent and gait. MRI scans were performed (Magnetom 3T Prisma, Siemens). 3D bone models of the tibia and femur were segmented (Simpleware Scan IP, Synopsis). Bone poses were obtained by manually matching bone models to X-rays (DSX Suite, C-Motion Inc.). Mean range of motion (ROM) of the contact points on the medial and lateral tibial plateau were calculated using custom MATLAB code (MathWorks). Results were filtered using an adaptive low pass Butterworth filter (Frequency range: 5-29Hz).Gait and Stair ascent activities from one participant's data showed increased ROM for medial-lateral (ML) translation in the medial compartment but decreased ROM in anterior-posterior (AP) translation when comparing against the same translations on the lateral compartment of the tibial plateau. Lunge activity showed increased ROM for both ML and AP translation in the medial compartment when compared with the lateral compartment.These results highlight the variability in condylar translations between different activities. Understanding healthy in-vivo kinematics across different activities allows the determination of suitable activities to best investigate the kinematic changes due to disease or injury and assess the efficacy of different interventions.Acknowledgements: This research was supported by the Engineering and Physical Sciences Research Council (EPSRC) doctoral training grant (EP/T517951/1).

Gender diversity and publication activity—an analysis of STEM in the UK

Abstract Gender diversity in STEM remains a significant issue, as the field continues to be a male dominated one, despite increased attention on the subject. This article examines the interplay between gender diversity on projects funded by a major UK research council, the Engineering and Physical Sciences Research Council, and the publication activity of a project, as measured by the average journal quality of project publication output, over a 10-year period. The proportion of female representation and leadership on these projects remains very low. For the projects examined as part of this study, over 70% of these projects have no female representation, and less than 15% have a female lead. This study does not find a significant relationship between gender diversity and journal quality output. This study highlights that an important avenue for future work is the development of alternative metrics to assess the performance of research projects in a discipline characterized by very low levels of gender diversity, to fully unpack the impact of project team gender diversity on project output activity.

Genetic Validation of Psoriasis Phenotyping in UK Biobank Supports the Utility of Self-Reported Data and Composite Definitions for Large Genetic and Epidemiological Studies

Genetic Validation of Psoriasis Phenotyping in UK Biobank Supports the Utility of Self-Reported Data and Composite Definitions for Large Genetic and Epidemiological Studies

ClinCirc identifies alterations of the circadian peripheral oscillator in critical care patients.

BackgroundAssessing circadian rhythmicity from infrequently sampled data is challenging; however, these types of data are often encountered when measuring circadian transcripts in hospitalized patients.MethodsWe present ClinCirc. This method combines 2 existing mathematical methods (Lomb-Scargle periodogram and cosinor) sequentially and is designed to measure circadian oscillations from infrequently sampled clinical data. The accuracy of this method was compared against 9 other methods using simulated and frequently sampled biological data. ClinCirc was then evaluated in 13 intensive care unit (ICU) patients as well as in a separate cohort of 29 kidney-transplant recipients. Finally, the consequences of circadian alterations were investigated in a retrospective cohort of 726 kidney-transplant recipients.ResultsClinCirc had comparable performance to existing methods for analyzing simulated data or clock transcript expression of healthy volunteers. It had improved accuracy compared with the cosinor method in evaluating circadian parameters in PER2:luc cell lines. In ICU patients, it was the only method investigated to suggest that loss of circadian oscillations in the peripheral oscillator was associated with inflammation, a feature widely reported in animal models. Additionally, ClinCirc was able to detect other circadian alterations, including a phase shift following kidney transplantation that was associated with the administration of glucocorticoids. This phase shift could explain why a significant complication of kidney transplantation (delayed graft dysfunction) oscillates according to the time of day kidney transplantation is performed.ConclusionClinCirc analysis of the peripheral oscillator reveals important clinical associations in hospitalized patients.FundingUK Research and Innovation (UKRI), National Institute of Health Research (NIHR), Engineering and Physical Sciences Research Council (EPSRC), National Institute on Academic Anaesthesia (NIAA), Asthma+Lung UK, Kidneys for Life.