Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study

BACKGROUND

Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies.

OBJECTIVE

The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors.

METHODS

Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors.

RESULTS

The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids.

CONCLUSIONS

Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health.

TRIAL REGISTRATION

ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2021-050785.

Developing a novel dual-injection FDG-PET imaging methodology to study the functional neuroanatomy of gait

Gait is an excellent indicator of physical, emotional, and mental health. Previous studies have shown that gait impairments in ageing are common, but the neural basis of these impairments are unclear. Existing methodologies are suboptimal and novel paradigms capable of capturing neural activation related to real walking are needed. In this study, we used a hybrid PET/MR system and measured glucose metabolism related to both walking and standing with a dual-injection paradigm in a single study session. For this study, 15 healthy older adults (10 females, age range: 60.5-70.7 years) with normal cognition were recruited from the community. Each participant received an intravenous injection of [18F]-2-fluoro-2-deoxyglucose (FDG) before engaging in two distinct tasks, a static postural control task (standing) and a walking task. After each task, participants were imaged. To discern independent neural functions related to walking compared to standing, we applied a bespoke dose correction to remove the residual 18F signal of the first scan (PETSTAND) from the second scan (PETWALK) and proportional scaling to the global mean, cerebellum, or white matter (WM). Whole-brain differences in walking-elicited neural activity measured with FDG-PET were assessed using a one-sample t-test. In this study, we show that a dual-injection paradigm in healthy older adults is feasible with biologically valid findings. Our results with a dose correction and scaling to the global mean showed that walking, compared to standing, increased glucose consumption in the cuneus (Z = 7.03), the temporal gyrus (Z = 6.91) and the orbital frontal cortex (Z = 6.71). Subcortically, we observed increased glucose metabolism in the supraspinal locomotor network including the thalamus (Z = 6.55), cerebellar vermis and the brainstem (pedunculopontine/mesencephalic locomotor region). Exploratory analyses using proportional scaling to the cerebellum and WM returned similar findings. Here, we have established the feasibility and tolerability of a novel method capable of capturing neural activations related to actual walking and extended previous knowledge including the recruitment of brain regions involved in sensory processing. Our paradigm could be used to explore pathological alterations in various gait disorders.

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device

This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987.

Therapeutic advances in rheumatoid arthritis

Rheumatoid arthritis (RA) is one of the most common immune mediated inflammatory diseases. People with rheumatoid arthritis present with pain, swelling, and stiffness that typically affects symmetrically distributed small and large joints. Without effective treatment, significant joint damage, disability, and work loss develop, owing to chronic inflammation of the joint lining (synovium). Over the past 25 years, the management of this condition has been revolutionized, resulting in substantially higher levels of disease remission and better long term outcomes. This improvement reflects a paradigm shift towards early and aggressive pharmacological intervention coupled with a proliferation in treatment choice, in turn related to enhanced pathobiological understanding and the advent of new drugs for rheumatoid arthritis. Following an overview of these developments from a historical perspective, and with a general audience in mind, this review focuses on newer, targeted treatments in an ever evolving landscape. The review highlights ongoing areas of debate and unmet need, including the proportion of patients with persistent, difficult-to-treat disease, despite recent advances. Also discussed are personalized, strategic approaches to individual patients, the role for imaging in clinical decision making, and the goal of sustained, drug free remission and disease prevention in the future.

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases

Introduction

The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings.

Methods

Here, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data.

Results and discussion

The results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of -0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, -0.07, and <0.01 s for stance, swing, and stride time, respectively. Thus, the DL algorithm is considered successful in detecting gait events in ecologically valid environments across different mobility-limiting diseases.

Laboratory and free-living gait performance in adults with COPD and healthy controls

Background

Gait characteristics are important risk factors for falls, hospitalisations and mortality in older adults, but the impact of COPD on gait performance remains unclear. We aimed to identify differences in gait characteristics between adults with COPD and healthy age-matched controls during 1) laboratory tests that included complex movements and obstacles, 2) simulated daily-life activities (supervised) and 3) free-living daily-life activities (unsupervised).

Methods

This case-control study used a multi-sensor wearable system (INDIP) to obtain seven gait characteristics for each walking bout performed by adults with mild-to-severe COPD (n=17; forced expiratory volume in 1 s 57±19% predicted) and controls (n=20) during laboratory tests, and during simulated and free-living daily-life activities. Gait characteristics were compared between adults with COPD and healthy controls for all walking bouts combined, and for shorter (≤30 s) and longer (>30 s) walking bouts separately.

Results

Slower walking speed (-11 cm·s-1, 95% CI: -20 to -3) and lower cadence (-6.6 steps·min-1, 95% CI: -12.3 to -0.9) were recorded in adults with COPD compared to healthy controls during longer (>30 s) free-living walking bouts, but not during shorter (≤30 s) walking bouts in either laboratory or free-living settings. Double support duration and gait variability measures were generally comparable between the two groups.

Conclusion

Gait impairment of adults with mild-to-severe COPD mainly manifests during relatively long walking bouts (>30 s) in free-living conditions. Future research should determine the underlying mechanism(s) of this impairment to facilitate the development of interventions that can improve free-living gait performance in adults with COPD.

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

BACKGROUND

Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates.

METHODS

Twenty healthy older adults, 20 people with Parkinson's disease, 20 with multiple sclerosis, 19 with proximal femoral fracture, 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 h in the real-world, using a single wearable device worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the single wearable device. We assessed and validated three algorithms for gait sequence detection, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated.

RESULTS

We identified two cohort-specific top performing algorithms for gait sequence detection and CAD, and a single best for ICD and SL. Best gait sequence detection algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors < 11% for ICD and < 8.5% for CAD. The best identified SL algorithm showed lower performances than other DMOs (absolute error < 0.21 m). Lower performances across all DMOs were found for the cohort with most severe gait impairments (proximal femoral fracture). Algorithms' performances were lower for short walking bouts; slower gait speeds (< 0.5 m/s) resulted in reduced performance of the CAD and SL algorithms.

CONCLUSIONS

Overall, the identified algorithms enabled a robust estimation of key DMOs. Our findings showed that the choice of algorithm for estimation of gait sequence detection and CAD should be cohort-specific (e.g., slow walkers and with gait impairments). Short walking bout length and slow walking speed worsened algorithms' performances. Trial registration ISRCTN - 12246987.

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions

Introduction: Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity. Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72-4.87 steps/min, stride length 0.04-0.06 m, walking speed 0.03-0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

Imagined places of the past: the interplay of time and memory in the maintenance of place attachment

Place attachment describes the emotional connection that people hold with a physical space, and such bonds have been shown to be associated with higher levels of life satisfaction, as well as physical and mental well-being. Although a temporal element of place attachment is acknowledged, the exact nature of time’s role in such relationships is yet to be fully understood. The current study addressed this using qualitative interviews with nine long-term residents of an urban centre in Northwest England. Interpretative phenomenological analysis was applied to explore the underlying mechanisms through which time asserts its influence on place attachment. Analysis developed three interrelated super-ordinate themes: what time brings, accumulated attachment, and time as a dialectic. As time passes, life events, cultural changes, and physical transformation to the environment affect individuals’ interactions with place, and thus their relationship with it. Continued inhabitation leads to an accumulation of emotional salience. Ultimately, time interacts with human memory, offering individuals multiple perspectives through which to make sense of their present environment. Issues may then arise, as memory is heavily influenced by the passing of time. Consequently, present-day perceptions of the place’s past are often viewed through a prism of nostalgia, with implications for the person-place bond.

Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease

Introduction

Parkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management. This study investigates the feasibility and usability of a multi-component DHTS to remotely assess self-reported medication adherence and monitor mobility in people with Parkinson's (PwP).

Methods

Thirty participants with PD [Hoehn and Yahr stage I (n = 1) and II (n = 29)] were recruited for this cross-sectional study. Participants were required to wear, and where appropriate, interact with a DHTS (smartwatch, inertial measurement unit, and smartphone) for seven consecutive days to assess medication adherence and monitor digital mobility outcomes and contextual factors. Participants reported their daily motor complications [motor fluctuations and dyskinesias (i.e., involuntary movements)] in a diary. Following the monitoring period, participants completed a questionnaire to gauge the usability of the DHTS. Feasibility was assessed through the percentage of data collected, and usability through analysis of qualitative questionnaire feedback.

Results

Adherence to each device exceeded 70% and ranged from 73 to 97%. Overall, the DHTS was well tolerated with 17/30 participants giving a score &gt; 75% [average score for these participants = 89%, from 0 (worst) to 100 (best)] for its usability. Usability of the DHTS was significantly associated with age (ρ = −0.560, BCa 95% CI [−0.791, −0.207]). This study identified means to improve usability of the DHTS by addressing technical and design issues of the smartwatch. Feasibility, usability and acceptability were identified as key themes from PwP qualitative feedback on the DHTS.

Conclusion

This study highlighted the feasibility and usability of our integrated DHTS to remotely assess medication adherence and monitor mobility in people with mild-to-moderate Parkinson's disease. Further work is necessary to determine whether this DHTS can be implemented for clinical decision-making to optimise management of PwP.

Micro-CT Imaging and Mechanical Properties of Ovine Ribs

The use of ovine animal models in the study of injury biomechanics and modeling is increasing, due to their favorable size and other physiological characteristics. Along with this increase, there has also been increased interest in the development of in silico ovine models for computational studies to compliment physical experiments. However, there remains a gap in the literature characterizing the morphological and mechanical characteristics of ovine ribs. The objective of this study therefore is to report anatomical and mechanical properties of the ovine ribs using microtomography (micro-CT) and two types of mechanical testing (quasi-static bending and dynamic tension). Using microtomography, young ovine rib samples obtained from a local abattoir were cut into approximately fourteen 38 mm sections and scanned. From these scans, the cortical bone thickness and cross-sectional area were measured, and the moment of inertia was calculated to enhance the mechanical testing data. Based on a standard least squares statistical model, the cortical bone thickness varied depending on the region of the cross-section and the position along the length of the rib (p < 0.05), whereas the cross-sectional area remained consistent (p > 0.05). Quasi-static three-point bend testing was completed on ovine rib samples, and the resulting force-displacement data was analyzed to obtain the stiffness (44.67 ± 17.65 N/mm), maximum load (170.54 ± 48.28 N) and displacement at maximum load (7.19 ± 2.75 mm), yield load (167.81 ± 48.12 N) and displacement at yield (6.10 ± 2.25 mm), and the failure load (110.90 ± 39.30 N) and displacement at failure (18.43 ± 2.10 mm). The resulting properties were not significantly affected by the rib (p > 0.05), but by the animal they originated from (p < 0.05). For the dynamic testing, samples were cut into coupons and tested in tension with an average strain rate of 18.9 strain/sec. The resulting dynamic testing properties of elastic modulus (5.16 ± 2.03 GPa), failure stress (63.29 ± 14.02 MPa), and failure strain (0.0201 ± 0.0052) did not vary based on loading rate (p > 0.05).

Acceptability of wearable devices for measuring mobility remotely: Observations from the Mobilise-D technical validation study

Background

This study aimed to explore the acceptability of a wearable device for remotely measuring mobility in the Mobilise-D technical validation study (TVS), and to explore the acceptability of using digital tools to monitor health.

Methods

Participants (N = 106) in the TVS wore a waist-worn device (McRoberts Dynaport MM + ) for one week. Following this, acceptability of the device was measured using two questionnaires: The Comfort Rating Scale (CRS) and a previously validated questionnaire. A subset of participants (n = 36) also completed semi-structured interviews to further determine device acceptability and to explore their opinions of the use of digital tools to monitor their health. Questionnaire results were analysed descriptively and interviews using a content analysis.

Results

The device was considered both comfortable (median CRS (IQR; min-max) = 0.0 (0.0; 0-20) on a scale from 0-20 where lower scores signify better comfort) and acceptable (5.0 (0.5; 3.0-5.0) on a scale from 1-5 where higher scores signify better acceptability). Interviews showed it was easy to use, did not interfere with daily activities, and was comfortable. The following themes emerged from participants' as being important to digital technology: altered expectations for themselves, the use of technology, trust, and communication with healthcare professionals.

Conclusions

Digital tools may bridge existing communication gaps between patients and clinicians and participants are open to this. This work indicates that waist-worn devices are supported, but further work with patient advisors should be undertaken to understand some of the key issues highlighted. This will form part of the ongoing work of the Mobilise-D consortium.

Homes and health in the Outer Hebrides: A social prescribing framework for addressing fuel poverty and the social determinants of health

Health services are increasingly being reshaped with reference to addressing social determinants of health (SDoH), with social prescribing a prominent example. We examine a project in the Outer Hebrides that reshaped and widened the local health service, framing fuel poverty as a social determinant of health and mobilising a cross-sector support pathway to make meaningful and substantive improvements to islanders' living conditions. The 'Moving Together' project provided support to almost 200 households, ranging from giving advice on home energy, finances and other services, to improving the energy efficiency of their homes. In so doing, the project represents an expansion of the remit of social prescribing, in comparison with the majority of services currently provided under this banner, and can be seen as a more systemic approach that engages with the underlying conditions of a population's health. We present a framework through which to understand and shape initiatives to address fuel poverty through a social prescribing approach.

Leveraging an established neighbourhood-level, open access wastewater monitoring network to address public health priorities: a population-based study

BACKGROUND

Before the COVID-19 pandemic, the US opioid epidemic triggered a collaborative municipal and academic effort in Tempe, Arizona, which resulted in the world's first open access dashboard featuring neighbourhood-level trends informed by wastewater-based epidemiology (WBE). This study aimed to showcase how wastewater monitoring, once established and accepted by a community, could readily be adapted to respond to newly emerging public health priorities.

METHODS

In this population-based study in Greater Tempe, Arizona, an existing opioid monitoring WBE network was modified to track SARS-CoV-2 transmission through the analysis of 11 contiguous wastewater catchments. Flow-weighted and time-weighted 24 h composite samples of untreated wastewater were collected at each sampling location within the wastewater collection system for 3 days each week (Tuesday, Thursday, and Saturday) from April 1, 2020, to March 31, 2021 (Area 7 and Tempe St Luke's Hospital were added in July, 2020). Reverse transcription quantitative PCR targeting the E gene of SARS-CoV-2 isolated from the wastewater samples was used to determine the number of genome copies in each catchment. Newly detected clinical cases of COVID-19 by zip code within the City of Tempe, Arizona were reported daily by the Arizona Department of Health Services from May 23, 2020. Maricopa County-level new positive cases, COVID-19-related hospitalisations, deaths, and long-term care facility deaths per day are publicly available and were collected from the Maricopa County Epidemic Curve Dashboard. Viral loads of SARS-CoV-2 (genome copies per day) measured in wastewater from each catchment were aggregated at the zip code level and city level and compared with the clinically reported data using root mean square error to investigate early warning capability of WBE.

FINDINGS

Between April 1, 2020, and March 31, 2021, 1556 wastewater samples were analysed. Most locations showed two waves in viral levels peaking in June, 2020, and December, 2020-January, 2021. An additional wave of viral load was seen in catchments close to Arizona State University (Areas 6 and 7) at the beginning of the fall (autumn) semester in late August, 2020. Additionally, an early infection hotspot was detected in the Town of Guadalupe, Arizona, starting the week of May 4, 2020, that was successfully mitigated through targeted interventions. A shift in early warning potential of WBE was seen, from a leading (mean of 8·5 days [SD 2·1], June, 2020) to a lagging (-2·0 days [1·4], January, 2021) indicator compared with newly reported clinical cases.

INTERPRETATION

Lessons learned from leveraging an existing neighbourhood-level WBE reporting dashboard include: (1) community buy-in is key, (2) public data sharing is effective, and (3) sub-ZIP-code (postal code) data can help to pinpoint populations at risk, track intervention success in real time, and reveal the effect of local clinical testing capacity on WBE's early warning capability. This successful demonstration of transitioning WBE efforts from opioids to COVID-19 encourages an expansion of WBE to tackle newly emerging and re-emerging threats (eg, mpox and polio).

FUNDING

National Institutes of Health's RADx-rad initiative, National Science Foundation, Virginia G Piper Charitable Trust, J M Kaplan Fund, and The Flinn Foundation.

Design and validation of a multi-task, multi-context protocol for real-world gait simulation

BACKGROUND

Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a protocol for simulating real-world gait accounting for all these factors within a single set of observations, while ensuring minimisation of participant burden and safety.

METHODS

The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants' strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohorts that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson's disease (PD), multiple sclerosis (MS), proximal femoral fracture (PFF), chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks.

RESULTS

The protocol proved to be safe and feasible (all participants could complete it and no adverse events were recorded) and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a representation of a variety of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life.

CONCLUSIONS

The protocol allowed for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy.

TRIAL REGISTRATION

ISRCTN-12246987.

A personal journey to build leadership skills through collaboration to support radiography research and evidence-based practice

Introduction

The Covid-19 pandemic continues to impact on how radiotherapy is delivered, how staff do their job and how patients are cared for. Part of the UK NHS response to the covid-19 crisis was to accelerate final year radiotherapy students into work as therapeutic radiographers. The study objective is to explore the experiences of a cohort of new registrants who started work in May 2020.

Methods

In depth interviews were conducted remotely with newly qualified therapeutic radiography registrants regarding their first 12 months working in UK NHS cancer centres. Data were analysed within and across cases using a framework analysis and synthesised thematically.

Results

Eleven radiographers were interviewed, working across six different sites. Key generated themes are the risk of impaired professional socialisation due to incongruence between students’ expectations and the reality in clinical departments. We use Bridges Transitional Model to show how a combination of the disrupted/undefined end to university and a perceived lack of recognition of professional knowledge, skills and values evident in our data may leave participants stuck in a middle stage of the transition process. Slower than expected professional development led to demotivation, which was also associated with rising covid-19 case numbers.

Conclusion

The covid-19 pandemic accentuated and heightened the existing challenge of professional integration and socialisation faced by new therapeutic radiography staff. Demotivation and potentially attrition are more likely in this environment. Compassionate leadership that fosters the mentorship of junior cohorts as part of a flexible preceptorship package could mitigate these risks.

Auditory rhythmical cueing to improve gait in community-dwelling stroke survivors (ACTIVATE): a pilot randomised controlled trial

Background

Gait impairment limiting mobility and restricting activities is common after stroke. Auditory rhythmical cueing (ARC) uses a metronome beat delivered during exercise to train stepping and early work reports gait improvements. This study aimed to establish the feasibility of a full scale multicentre randomised controlled trial to evaluate an ARC gait and balance training programme for use by stroke survivors in the home and outdoors.

Methods

A parallel-group observer-blind pilot randomised controlled trial was conducted. Adults within 2 years of stroke with a gait-related mobility impairment were recruited from four NHS stroke services and randomised to an ARC gait and balance training programme (intervention) or the training programme without ARC (control). Both programmes consisted of 3x30 min sessions per week for 6 weeks undertaken at home/nearby outdoor community. One session per week was supervised and the remainder self-managed. Gait and balance performance assessments were undertaken at baseline, 6 and 10 weeks. Key trial outcomes included recruitment and retention rates, programme adherence, assessment data completeness and safety.

Results

Between November 2018 and February 2020, 59 participants were randomised (intervention n=30, control n=29), mean recruitment rate 4/month. At baseline, 6 weeks and 10 weeks, research assessments were conducted for 59/59 (100%), 47/59 (80%) and 42/59 (71%) participants, respectively. Missing assessments were largely due to discontinuation of data collection from mid-March 2020 because of the UK COVID-19 pandemic lockdown. The proportion of participants with complete data for each individual performance assessment ranged from 100% at baseline to 68% at 10 weeks. In the intervention group, 433/540 (80%) total programme exercise sessions were undertaken, in the control group, 390/522 (75%). Falls were reported by five participants in the intervention group, six in the control group. Three serious adverse events occurred, all unrelated to the study.

Conclusion

We believe that a definitive multicentre RCT to evaluate the ARC gait and balance training programme is feasible. Recruitment, programme adherence and safety were all acceptable. Although we consider that the retention rate and assessment data completeness were not sufficient for a future trial, this was largely due to the UK COVID-19 pandemic lockdown.

Trial registration

ISRCTN, ISRCTN10874601, Registered on 05/03/2018,

Supplementary Information

The online version contains supplementary material available at 10.1186/s40814-022-01193-y.

Variability in Opioid-Related Drug Overdoses, Social Distancing, and Area-Level Deprivation during the COVID-19 Pandemic: a Bayesian Spatiotemporal Analysis

Monitoring the spatial and temporal course of opioid-related drug overdose mortality is a key public health determinant. Despite previous studies exploring the evolution of drug-related fatalities following the stay-at-home mandates during the COVID-19 pandemic, little is known about the spatiotemporal dynamics that mitigation efforts had on overdose deaths. The purpose of this study was to describe the spatial and temporal dynamics of overdose death relative risk using a 4-week interval over a span of 5 months following the implementation of the COVID-19 lockdown in the city of Chicago, IL. A Bayesian space-time model was used to produce posterior risk estimates and exceedance probabilities of opioid-related overdose deaths controlling for measures of area-level deprivation and stay-at-home mandates. We found that area-level temporal risk and inequalities in drug overdose mortality increased significantly in the initial months of the pandemic. We further found that a change in the area-level deprivation from the first to the fourth quintile increased the relative risk of a drug overdose risk by 44.5%. The social distancing index measuring the proportion of persons who stayed at home in each census block group was not associated with drug overdose mortality. We conclude by highlighting the importance of contextualizing the spatial and temporal risk in overdose mortality for implementing effective and safe harm reduction strategies during a global pandemic.

Solidarity, not charity: Learning the lessons of the COVID-19 pandemic to reconceptualise the radicality of mutual aid

The COVID-19 pandemic has significantly ruptured our global society. We have seen health care systems, governments and commerce buckle under the strain of disease, lockdowns and unrest, but the rupture has also created space for radical (and anarchist) politics of mutual aid, as societal organising principles, to move into a more prominent position (and offers potential for this shift to remain after the crisis has subsided). However, in the short time since mutual aid has been thrust into the limelight, we have seen a multiplicity and spectrum of geographies, applications and approaches. Indeed, we have also seen its appropriation by government(s) that takes advantage of mutual aid's rallying cry of "solidarity not charity"; absolving the state's responsibilities to sufficiently fund social welfare when good neighbours will do it for free. In this paper we map out how mutual aid has been enacted during the COVID-19 pandemic by charity, contributory and radical groups to address specific and novel forms of vulnerabilities, and the opportunities and challenges this offers for the future. In particular we highlight potential tensions between the enacting of mutual aid practices and the political activism (or not) of the mutual aid actors. Our contribution is to reconceptualise mutual aid to (i) show where the real "mutualism" of mutual aid is, and (ii) create a better understanding of how mutual aid can be mobilised in future emergencies which will inevitably arise in the current climate emergency.

Locked down: Ontological security and the experience of COVID-19 while living in poor-quality housing

The aim of the paper is to illustrate how the housing system in the United Kingdom (UK) has contributed to creating vulnerabilities during the COVID-19 pandemic. Drawing on the concept of ontological security we look at how living with housing insecurity whilst enduring poor housing conditions has impacted the lives of those living in households. The paper draws on semi-structured interviews with 50 residents and 8 housing professionals. The findings outline the grinding impact of the pandemic on the ontological security of residents and the coping strategies adopted by a wider range of households who are now increasingly vulnerable. A number of people went into lockdown in vulnerable situations, experiencing deep inequalities and living in poorly maintained homes. This has weakened the ontological security experienced by many households. These represent significant failings of the housing system and housing policy impacting on the health and wellbeing of a wider cohort of people creating additional vulnerabilities.

A Rapid Non-Destructive Hyperspectral Imaging Data Model for the Prediction of Pungent Constituents in Dried Ginger

Ginger is best known for its aromatic odour, spicy flavour and health-benefiting properties. Its flavour is derived primarily from two compound classes (gingerols and shogaols), with the overall quality of the product depending on the interaction between these compounds. Consequently, a robust method for determining the ratio of these compounds would be beneficial for quality control purposes. This study investigated the feasibility of using hyperspectral imaging to rapidly determine the ratio of 6-gingerol to 6-shogoal in dried ginger powder. Furthermore, the performance of several pre-processing methods and two multivariate models was explored. The best-performing models used partial least squares regression (PSLR) and least absolute shrinkage and selection operator (LASSO), using multiplicative scatter correction (MSC) and second derivative Savitzky–Golay (2D-SG) pre-processing. Using the full range of wavelengths (~400–1000 nm), the performance was similar for PLSR (R² ≥ 0.73, RMSE ≤ 0.29, and RPD ≥ 1.92) and LASSO models (R² ≥ 0.73, RMSE ≤ 0.29, and RPD ≥ 1.94). These results suggest that hyperspectral imaging combined with chemometric modelling may potentially be used as a rapid, non-destructive method for the prediction of gingerol-to-shogaol ratios in powdered ginger samples.

Efficacy and safety of leadless pacemaker: A systematic review, pooled analysis and meta-analysis

Background

Leadless pacemakers have been designed as an alternative to transvenous systems which avoid some of the complications associated with transvenous devices. We aim to perform a systematic review of the literature to report the safety and efficacy findings of leadless pacemakers.

Methods

We searched MEDLINE and EMBASE to identify studies reporting the safety, efficacy and outcomes of patients implanted with a leadless pacemaker. The pooled rate of adverse events was determined and random-effects meta-analysis was performed to compare rates of adverse outcomes for leadless compared to transvenous pacemakers.

Results

A total of 18 studies were included with 2496 patients implanted with a leadless pacemaker and success rates range between 95.5 and 100%. The device or procedure related death rate was 0.3% while any complication and pericardial tamponade occurred in 3.1% and 1.4% of patients, respectively. Other complications such as pericardial effusion, device dislodgement, device revision, device malfunction, access site complications and infection occurred in less than 1% of patients. Meta-analysis of four studies suggests that there was no difference in hematoma (RR 0.67 95%CI 0.21–2.18, 3 studies), pericardial effusion (RR 0.59 95%CI 0.15–2.25, 3 studies), device dislocation (RR 0.33 95%CI 0.06–1.74, 3 studies), any complication (RR 0.44 95%CI 0.17–1.09, 4 studies) and death (RR 0.45 95%CI 0.15–1.35, 2 studies) comparing patients who received leadless and transvenous pacemakers.

Conclusion

Leadless pacemakers are safe and effective for patients who have an indication for single chamber ventricular pacing and the findings appear to be comparable to transvenous pacemakers.

Technical validation of real-world monitoring of gait: a multicentric observational study

INTRODUCTION

Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real-world, however, is still limited in patient populations. Rigorous validation procedures should cover the device metrological verification, the validation of the algorithms for the DMOs computation specifically for the population of interest and in daily life situations, and the users' perspective on the device.

METHODS AND ANALYSIS

This protocol was designed to establish the technical validity and patient acceptability of the approach used to quantify digital mobility in the real world by Mobilise-D, a consortium funded by the European Union (EU) as part of the Innovative Medicine Initiative, aiming at fostering regulatory approval and clinical adoption of DMOs.After defining the procedures for the metrological verification of an IMU-based device, the experimental procedures for the validation of algorithms used to calculate the DMOs are presented. These include laboratory and real-world assessment in 120 participants from five groups: healthy older adults; chronic obstructive pulmonary disease, Parkinson's disease, multiple sclerosis, proximal femoral fracture and congestive heart failure. DMOs extracted from the monitoring device will be compared with those from different reference systems, chosen according to the contexts of observation. Questionnaires and interviews will evaluate the users' perspective on the deployed technology and relevance of the mobility assessment.

ETHICS AND DISSEMINATION

The study has been granted ethics approval by the centre's committees (London-Bloomsbury Research Ethics committee; Helsinki Committee, Tel Aviv Sourasky Medical Centre; Medical Faculties of The University of Tübingen and of the University of Kiel). Data and algorithms will be made publicly available.

TRIAL REGISTRATION NUMBER

ISRCTN (12246987).

ChromeBat: A Bio-Inspired Approach to 3D Genome Reconstruction

With the advent of Next Generation Sequencing and the Hi-C experiment, high quality genome-wide contact data are becoming increasingly available. These data represents an empirical measure of how a genome interacts inside the nucleus. Genome conformation is of particular interest as it has been experimentally shown to be a driving force for many genomic functions from regulation to transcription. Thus, the Three Dimensional-Genome Reconstruction Problem (3D-GRP) seeks to take Hi-C data and produces a complete physical genome structure as it appears in the nucleus for genomic analysis. We propose and develop a novel method to solve the Chromosome and Genome Reconstruction problem based on the Bat Algorithm (BA) which we called ChromeBat. We demonstrate on real Hi-C data that ChromeBat is capable of state-of-the-art performance. Additionally, the domain of Genome Reconstruction has been criticized for lacking algorithmic diversity, and the bio-inspired nature of ChromeBat contributes algorithmic diversity to the problem domain. ChromeBat is an effective approach for solving the Genome Reconstruction Problem.

Two Epidemics and a Pandemic: The Collision of Prescription Drug Misuse and Racism during COVID-19

The present study investigated the relationship between perceived racial discrimination and prescription drug misuse (PDM) among Asian, Black, and Latinx Americans during the COVID-19 crisis. U.S. racial/ethnic minorities may have been uniquely affected by two national and one global pandemic: the opioid crisis, racism, and COVID-19. Opioid death rates increased among many groups prior to the pandemic. This country witnessed an increase in racialized acts against people of color across the spectrum in the spring and summer months of the world's COVID-19 outbreak. While studies have shown a clear link between perceived racial discrimination and substance abuse outside of the global pandemic, no identified studies have done so against the backdrop of a global health pandemic. Separate hierarchical regressions revealed a significant association between perceived racial discrimination and PDM for Black Americans, Asian Americans, and Latinx individuals. Findings build on the scant literature on PDM in diverse samples and establish a relationship between perceived racial discrimination and PDM, as previously identified for other abused substances. Future post-pandemic substance misuse interventions should consider the influence of perceived racial discrimination as they help individuals recover from the aftermath of this stressful trifecta.

High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were "novel" SNVs that had not yet been identified in the global clinical-derived data as of 17^th June 2020 (the day after our last wastewater sampling date). However, between 17^th of June 2020 and 20^th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were "novel" SNVs that had not yet been identified in the global clinical-derived data as of 17^th June 2020 (the day after our last wastewater sampling date). However, between 17^th of June 2020 and 20^th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

Use of spatio-temporal habitat suitability modelling to prioritise areas for common carp biocontrol in Australia using the virus CyHV-3

Common carp (Cyprinus carpio) are an invasive species of the rivers and waterways of south-eastern Australia, implicated in the serious decline of many native fish species. Over the past 50 years a variety of control options have been explored, all of which to date have proved either ineffective or cost prohibitive. Most recently the use of cyprinid herpesvirus 3 (CyHV-3) has been proposed as a biocontrol agent, but to assess the risks and benefits of this, as well as to develop a strategy for the release of the virus, a knowledge of the fundamental processes driving carp distribution and abundance is required. To this end, we developed a novel process-based modelling framework that integrates expert opinion with spatio-temporal datasets via the construction of a Bayesian Network. The resulting weekly networks thus enabled an estimate of the habitat suitability for carp across a range of hydrological habitats in south-eastern Australia, covering five diverse catchment areas encompassing in total a drainage area of 132,129 km² over a period of 17-27 years. This showed that while suitability for adult and subadult carp was medium-high across most habitats throughout the period, nevertheless the majority of habitats were poorly suited for the recruitment of larvae and young-of-year (YOY). Instead, high population abundance was confirmed to depend on a small number of recruitment hotspots which occur in years of favourable inundation. Quantification of the underlying ecological drivers of carp abundance thus makes possible detailed planning by focusing on critical weaknesses in the population biology of carp. More specifically, it permits the rational planning for population reduction using the biocontrol agent, CyHV-3, targeting areas where the total population density is above a "damage threshold" of approximately 100 kg/ha.

OP0033 REGULATORY T CELL CD39 EXPRESSION AS A PREDICTOR OF EARLY REMISSION-INDUCTION WITH METHOTREXATE IN NEW-ONSET RHEUMATOID ARTHRITIS

Background:

The long term outcomes for patients with rheumatoid arthritis (RA) depend on early and effective disease control. Methotrexate remains the key first line disease modifying therapy for the majority of patients, with 40% achieving an ACR50 on monotherapy(1). There are at present no effective biomarkers to predict treatment response, preventing effective personalisation of therapy. A putative mechanism of action of methotrexate, the potentiation of anti-inflammatory adenosine signalling, may inform biomarker discovery. By antagonism of the ATIC enzyme in the purine synthesis pathway, methotrexate has been proposed to increase the release of adenosine moieties from cells, which exert an anti-inflammatory effect through interaction with ADORA2 receptors(2). Lower expression of CD39 (a cell surface 5-’ectonucleotidase required for the first step in the conversion of ATP to adenosine) on circulating regulatory T-Lymphocytes (Tregs) was previously identified in patients already established on methotrexate who were not responding (DAS28 >4.0 vs <3.0)(3). We therefore hypothesised that pre-treatment CD39 expression on these cells may have clinical utility as a predictor of early methotrexate efficacy.

Objectives:

To characterise CD39 expression in peripheral blood mononuclear cells in RA patients naïve to disease modifying therapy commencing methotrexate, and relate this expression to 4 variable DAS28CRP remission (<2.6) at 6 months.

Methods:

68 treatment naïve early RA patients starting methotrexate were recruited from the Newcastle Early Arthritis Clinic and followed up for 6 months. Serial blood samples were taken before and during methotrexate therapy with peripheral blood mononuclear cells isolated by density centrifugation. Expression of CD39 by major immune subsets (CD4+ and CD8+ T-cells, B-lymphocytes, natural killer cells and monocytes) was determined by flow cytometry. The statistical analysis used was binomial logistic regression with baseline DAS28CRP used as a covariate due to the significant association of baseline disease activity with treatment response.

Results:

Higher pre-treatment CD39 expression was observed in circulating CD4+ T-cells of patients who subsequently achieved clinical remission at 6 months versus those who did not (median fluorescence 4854.0 vs 3324.2; p = 0.0108; Figure 1-A). This CD39 expression pattern was primarily accounted for by the CD4+CD25 high sub-population (median fluorescence 9804.7 vs 6455.5; p = 0.0065; Figure 1-B). These CD25 high cells were observed to have higher FoxP3 and lower CD127 expression than their CD39 negative counterparts, indicating a Treg phenotype. No significant associations were observed with any other circulating subset. A ROC curve demonstrates the discriminative utility of differential CD39 expression in the CD4+CD25 high population for the prediction of DAS28CRP remission in this cohort, showing greater specificity than sensitivity for remission prediction(AUC: 0.725; 95% CI: 0.53 - 0.92; Figure 1-C). Longitudinally, no significant induction or suppression of the CD39 marker was observed amongst patients who did or did not achieve remission over the 6 months follow-up period.

Figure 1.

Six month DAS28CRP remission versus pre-treatment median fluorescence of CD39 expression on CD4+ T-cells (A); CD25 High expressing CD4+ T-cells (B); and ROC curve of predictive utility of pre-treatment CD39 expression on CD25 High CD4+ T-cells (C).

Conclusion:

These findings support the potential role of CD39 in the mechanism of methotrexate response. Expression of CD39 on circulating Tregs in treatment-naïve RA patients may have particular value in identifying early RA patients likely to respond to methotrexate, and hence add value to evolving multi-parameter discriminatory algorithms.

References:

[1]Hazlewood GS, et al. BMJ. 2016 21;353:i1777

[2]Brown PM, et al. Nat Rev Rheumatol. 2016;12(12):731-742

[3]Peres RS, et al. Proc Natl Acad Sci U S A. 2015;112(8):2509-2514

Disclosure of Interests:

None declared

POS0348 GENETIC SUSCEPTIBILITY VARIANTS FOR RHEUMATOID ARTHRITIS ARE NOT ASSOCIATED WITH EARLY REMISSION; A MULTI-COHORT STUDY

Background:

Patients who achieve remission promptly could have a specific genetic risk profile that supports regaining immune tolerance. The identification of these genes could provide novel drug targets.

Objectives:

To test the association between RA genetic risk variants with achieving remission at 6 months.

Methods:

We computed genetic risk scores (GRS) comprising of the RA susceptibility variants1 and HLA-SE status separately in 4425 patients across eight datasets from inception cohorts. Remission was defined as DAS28CRP<2.6 at 6 months. Missing DAS28CRP values in patients were imputed using predictive mean matching by MICE. We first tested whether baseline DAS28CRP changed with increasing GRS using linear regression. Next, we calculated odds ratios for GRS and HLA-SE on remission using logistic regression. Heterogeneity of the outcome between datasets was mitigated by running inverse variance meta-analysis.

Results:

Evaluation of the complete dataset, baseline clinical variables did not differ between patients achieving remission and those who did not (Table 1). Distribution of GRS was consistent between datasets. Neither GRS nor HLA-SE was associated with baseline DAS2DAS (OR1.01; 95% CI 0.99-1.04). A fixed effect meta-analysis (Figure 1.) showed no significant effect of the GRS (OR 0.99; 95% CI 0.94-1.03) or HLA-SE (OR 0.8CRP87; 95% CI 0.75-1.01) on remission at 6 months.

Table 1.

Summary of the data separated by disease activity after 6 months.

allRemission at 6 monthsNo remission at 6 monthsN4425*15582430Age, mean (sd)55.38 (13.87)5517 (14.09)55.62 (13.59)Female %68.98%65.43%70.73%ACPA+ %61.94%63.53%61.67%Baseline DAS28, mean (sd)4.76 (1.22)4.47 (1.23)5.1 (1.15)

*not all patients had 6 months data

Conclusion:

In these combined cohorts, RA genetics risk variants are not associated with early disease remission. At baseline there was no difference in genetic risk between patients achieving remission or not. Studies encompassing other genetic variants are needed to elucidate the genetics of RA remission.

References:

[1]Knevel R et al. Sci Transl Med. 2020;12(545):eaay1548.

Acknowledgements:

This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777357, RTCure.

This project has received funding from Pfizer Inc.

Disclosure of Interests:

Samantha Jurado Zapata: None declared, Marc Maurits: None declared, Yann Abraham Employee of: Pfizer, Erik van den Akker: None declared, Anne Barton: None declared, Philip Brown: None declared, Andrew Cope: None declared, Isidoro González-Álvaro: None declared, Carl Goodyear: None declared, Annette van der Helm - van Mil: None declared, Xinli Hu Employee of: Pfizer, Thomas Huizinga: None declared, Martina Johannesson: None declared, Lars Klareskog: None declared, Dennis Lendrem: None declared, Iain McInnes: None declared, Fraser Morton: None declared, Caron Paterson: None declared, Duncan Porter: None declared, Arthur Pratt: None declared, Luis Rodriguez Rodriguez: None declared, Daniela Sieghart: None declared, Paul Studenic: None declared, Suzanne Verstappen: None declared, Leonid Padyukov: None declared, Aaron Winkler Employee of: Pfizer, John D Isaacs: None declared, Rachel Knevel Grant/research support from: Pfizer

Expectations of therapeutic radiography students in Wales about transitioning to practice during the Covid-19 pandemic as registrants on the HCPC temporary register

INTRODUCTION

The Covid-19 crisis continues to profoundly impact on radiotherapy practice in the UK. We explore the views of therapeutic radiographer students on entering their first post in unique circumstances as a means to evaluate the support that may minimise negative impacts on their transition to practitioners.

METHOD

Focus groups were conducted outside of students' final year educational programme and immediately prior to them starting work. Qualitative data were analysed using a framework analysis.

RESULTS

Emergent themes from the eleven participants were: Covid-19 as a layer on top of underlying anxieties; Degree of readiness for imminent psychological, emotional and practical challenges; Feeling valued as a health professional/radiographer at this time; A mixed student and qualified staff professional identity as HCPC temporary registrants.

CONCLUSION

Uncertainties related to Covid-19 were seen to add a destabilising component to existing anxieties and challenges. In this context, there are significant risks of impaired professional socialisation due to incongruence between students' expectations and the reality in clinical departments.

IMPLICATIONS FOR PRACTICE

Informed academic support and flexible clinical preceptorship that address anxieties and congruence barriers are vital to guide new practitioners through a health crisis that presents significant challenges but also opportunity for professional development.

Abstract SP020: Beyond Hormones: Newer Pharmacologic Approaches

It is now possible to prevent many breast cancers inhigh-risk women using anti-estrogen hormonal drugs. Several Phase III breast cancer preventiontrials demonstrated that hormonal drugs such as the “selective estrogenreceptor modulators” tamoxifen and raloxifene, and aromatase inhibitors preventthe development of 50% of ER-positive breast cancers in women. However, mostwomen at high risk of breast cancer do not use these cancer preventive drugsdue to concerns about their side effects. To overcome this problem, recent studies havefocused on testing novel approaches for the prevention of breast cancer. Results of preclinical and clinical studiestesting targeted drugs and vaccines for breast cancer prevention show that itis possible to prevent breast cancer with reduced toxicity. Studies seeking to prevent all forms ofbreast cancer, including ER-positive, HER2-positive, and “triple-negative”breast cancer, will be presented and discussed. Novel approaches testing targeted therapies including signalinginhibitors, combinations of preventive agents, and vaccines, will be presented. Many of these interventions prevent breastcancer in animal models, and are now being tested in human clinicaltrials. Results from studies testing novel drugdelivery approaches will also be discussed. Topical gels containing anti-estrogen drugs are being used to reducebreast cell growth and mammographic density in Phase II clinical trials. This topical approach has the potential toprevent ER-positive breast cancers without the toxicity of oral hormonaldrugs. All of these novel preventive measuresoffer great promise to effectively prevent all forms of breast cancer withminimal toxicity.

Citation Format: P Brown. Beyond Hormones: Newer Pharmacologic Approaches [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr SP020.

Survey of research participation amongst UK radiology trainees: aspirations, barriers, solutions and the Radiology Academic Network for Trainees (RADIANT)

AIM

To inform the activity of the newly formed Radiology Academic Network for Trainees (RADIANT) regarding the current level of interest, engagement, and barriers experienced by UK radiology trainees to undertake research.

MATERIALS AND METHODS

A web-based survey containing nine questions was sent to the UK radiology training programme directors for distribution to trainees. The survey was also distributed to all trainee members of the RADIANT network. This led to 224 responses over a period of 2 months.

RESULTS

A large proportion of respondents indicated a desire to participate in research in the next 12 months 72.3% (n=162). The most frequently reported barriers to research were lack of time (60.7%, n=136), lack of awareness of local/departmental opportunities (53.6%, n=120), and limited experience in research statistics (46%, n=103). The most favoured factor that would improve access to research was structured research training opportunities, qualified as a project with clear goals and timeline (71%, n=159), protected time for research (68.8%, n=154), and local or national trainee research networks (40.2%, n=90 and 37.1%, n=83, respectively).

CONCLUSION

Many radiology trainees would like to participate in research, but multiple barriers exist. The formation of RADIANT is seen as a key part of a multifaceted approach to improving access to quality research activity alongside support from local and regional training bodies.

Risk stratification and prognostic value of CMR in DCM; parametric mapping and GLS- value beyond EF and LGE?

Funding Acknowledgements

Type of funding sources: Private company. Main funding source(s): Dr Pamela Brown was suppoerted by funding from Alliance Medical.

Background; Arrhythmia risk stratification and device implantation in dilated cardiomyopathy (DCM) poses significant challenges and as demonstrated by the DANISH trial appears to have reached the asymptote of clinical efficacy. A body of evidence now demonstrates that risk stratification of and device selection for DCM patients may be enhanced by inclusion of patients" LGE-status. Furthermore, it has been suggested that CMR based parametric mapping and strain analysis may further advance risk stratification.

Methods; 703 patients with DCM undergoing clinically indicated CMR scans and prospectively enrolled into the UHSM-CMR study (NCT02326324) between 03/2015-12/2018 were analysed. Multivariable Cox proportional hazard models and Youden index driven C-statistics were used to assess additive prognostic value of GLS, T1 and ECV mapping on the combined endpoint of cardiovascular death, cardiac transplantation, LVAD  insertion  or hospitalisation for heart failure in models incorporating NHYA class, EF and LGE status. Additionally. the value of GLS, T1, and ECV on predicting significant arrhythmic events (SAV) (ventricular arrhythmia (VA), resuscitated cardiac arrest (rCA) or sudden cardiac death (SCD)) was assessed.

Results; Patients (mean age 59, 66% male, 60% ≥NYHA II, mean EF 42%, mean GLS -12%, mean ECV 27%) were on good medical therapy (beta blocker 74%%, ACE 79%, MRA 38%, Entresto 5%, CRT 23%). Mean follow-up was 21 months; the combined endpoint occurred in 34 patients (5%). On univariate analysis NYHA class (HR 2.44 (1.67-3.57), p &lt; 0.001), ECV (HR 1.14 (1.05-1.22), p &lt; 0.001), GLS% (HR 1.14 (1.07-1.21) p &lt; 0.001,) T1 (HR 1.06 (1.005-1.1), p = 0.03), RVEF (HR 0.95 (0.93-0.98), p &lt; 0.001), LVEF (HR 0.92 (0.9-0.95), p &lt; 0.001) were all significantly associated with outcome. On multivariate analysis only EF and NYHA class was associated with outcome.

SAV occurred as the first manifestation of disease or during follow up in 27 patients (4%). At univariate analysis LGE, ECV, GLS, EF and NYHA class were all associated with SAV. However, on multivariable analysis only EF, LGE  and ECV (HR 1.11 (1.01-1.22), p = 0.03) but not GLS remained independently predictive in a model already incorporating EF, NYHA and LGE.

Conclusion

Optimally treated DCM populations have very low event rates. CMR based assessment of fibrosis status/burden with both LGE and ECV assessment has the potential to enhance patient selection for ICD therapy. Whilst GLS is increasingly recognised as a sensitive imaging biomarker of early disease detection it provides no additive value,  likely because of it’s high co-linearity with EF, in models already containing EF, NYHA class and LGE status.

High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 5680 were novel SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.