Parallel Recursive State Compression for Free

This paper focuses on reducing memory usage in enumerative model checking, while maintaining the multi-core scalability obtained in earlier work. We present a tree-based multi-core compression method, which works by leveraging sharing among sub-vectors of state vectors. An algorithmic analysis of both worst-case and optimal compression ratios shows the potential to compress even large states to a small constant on average (8 bytes). Our experiments demonstrate that this holds up in practice: the median compression ratio of 279 measured experiments is within 17% of the optimum for tree compression, and five times better than the median compression ratio of SPIN's COLLAPSE compression. Our algorithms are implemented in the LTSmin tool, and our experiments show that for model checking, multi-core tree compression pays its own way: it comes virtually without overhead compared to the fastest hash table-based methods.Comment: 19 page

JointCalc: A web-based personalised patient decision support tool for joint replacement

Background and purpose Health information systems (HIS) are expected to be effective and efficient in improving healthcare services, but empirical observation of HIS reveals that most perform poorly in terms of these metrics. Theoretical factors of HIS performance are widely studied, and solutions to mitigate poor performance have been proposed. In this paper we implement effective methods to eliminate some common drawbacks of HIS design and demonstrate the synergy between the methods. JointCalc, the first comprehensive patient-facing web-based decision support tool for joint replacement, is used as a case study for this purpose. Methods and results User-centred design and thorough end-user involvement are employed throughout the design and development of JointCalc. This is supported by modern software production paradigms, including continuous integration/continuous development, agile and service-oriented architecture. The adopted methods result in a user-approved application delivered well within the scope of project. Conclusion This work supports the claims of high potential efficiency of HIS. The methods identified are shown to be applicable in the production of an effective HIS whilst aiding development efficiency

Home health monitoring around the time of surgery: a qualitative study of patients’ experiences before and after joint replacement

Objectives: Hip and knee replacements are common major elective surgical interventions with over 200,000 performed annually in the UK. Not all patients achieve optimal outcomes or experience problems or delays in recovery. The number of patients needing these operations are set to increase and routine clinical monitoring is time and resource consuming for patients and healthcare providers, therefore innovative evaluation of surgical outcomes are needed. The aim of this qualitative study was to capture the patient experience of living with a novel home monitoring sensing system during the period around joint replacement. Setting: One secondary care hospital in the South West, UK Participants: 13 patients, (8 female, 63-89y) undergoing total hip or knee replacement enrolled into the study Design: Qualitative study with thematic analysis. The system remained in situ for up to 12 weeks after their surgery and comprised a group of low powered sensors monitoring the environment (temperature, light and humidity) and activity of people within the home. Patients were interviewed at two timepoints: before and after surgery. Interviews explored views about living with the technology, its acceptability as well as attitudes towards health technology. Results: Three main themes emerged: installation of home sensing technology on the journey to surgery; the home space and defining unobtrusiveness and pivotal role of social support networks Conclusions: Patients who agreed to the technology found living with it acceptable. A home sensing system that monitors the environment and activity of the people in the home could provide an innovative way of assessing patients’ surgical outcomes. At a time, characterised by reduced mobility, functional limitations and increased pain, patients in this study relied on informal and formal supportive networks to help maintain the system through the busy trajectory of the perioperative period. Strengths and limitations of this study • In-depth one-to-one interviews provided insight into patients’ real experiences and views as they lived with the technology in their own homes • Although the sample size was small, lacked ethnic diversity and only included people willing to have technology installed in their homes, there was good diversity in age and gender and some diversity in patients undergoing hip and knee replacement • Use of thematic analysis enabled robust analysis of data, including focus on the acceptability of the technology in real health-related circumstances

A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement : a cohort study of data from the National Joint Registry in England and Wales

Background The risk of mortality following elective total hip (THR) and knee replacements (KR) may be influenced by patients’ pre-existing comorbidities. There are a variety of scores derived from individual comorbidities that can be used in an attempt to quantify this. The aims of this study were to a) identify which comorbidity score best predicts risk of mortality within 90 days or b) determine which comorbidity score best predicts risk of mortality at other relevant timepoints (30, 45, 120 and 365 days). Patients and methods We linked data from the National Joint Registry (NJR) on primary elective hip and knee replacements performed between 2011–2015 with pre-existing conditions recorded in the Hospital Episodes Statistics. We derived comorbidity scores (Charlson Comorbidity Index—CCI, Elixhauser, Hospital Frailty Risk Score—HFRS). We used binary logistic regression models of all-cause mortality within 90-days and within 30, 45, 120 and 365-days of the primary operation using, adjusted for age and gender. We compared the performance of these models in predicting all-cause mortality using the area under the Receiver-operator characteristics curve (AUROC) and the Index of Prediction Accuracy (IPA). Results We included 276,594 elective primary THRs and 338,287 elective primary KRs for any indication. Mortality within 90-days was 0.34% (N = 939) after THR and 0.26% (N = 865) after KR. The AUROC for the CCI and Elixhauser scores in models of mortality ranged from 0.78–0.81 after THR and KR, which slightly outperformed models with ASA grade (AUROC = 0.77–0.78). HFRS performed similarly to ASA grade (AUROC = 0.76–0.78). The inclusion of comorbidities prior to the primary operation offers no improvement beyond models with comorbidities at the time of the primary. The discriminative ability of all prediction models was best for mortality within 30 days and worst for mortality within 365 days. Conclusions Comorbidity scores add little improvement beyond simpler models with age, gender and ASA grade for predicting mortality within one year after elective hip or knee replacement. The additional patient-specific information required to construct comorbidity scores must be balanced against their prediction gain when considering their utility

Using home sensing technology to assess outcome and recovery after joint replacement – findings from the hip and knee study of a sensor platform of healthcare in a residential environment

Purpose: Improving outcomes after joint replacement is a key research priority. After joint replacement, up to 30% of patients report minimal improvement or their symptoms get worse and not all patients are satisfied with their outcome. Poor outcomes include continuing pain, functional limitation and increased healthcare utilisation. Patient Reported Outcome Measures (PROMs) such as the Oxford Hip or Oxford Knee Score and the EQ-5D, a measure of health status, are widely used to assess outcome after joint replacement in practice and research. These measures can assess a variety of health outcomes including pain, function and health related quality of life. Though widely used, many PROMs have methodological limitations and there is debate about how to interpret results and definitions of clinically meaningful change. Previously, research has explored the relationship between PROMs and objective measures, such as timed walks or sit-to-stand tests. Such objective measures are administered in controlled, laboratory style settings, and may not reflect levels of activity in daily life. With the rapid development of monitoring technology, there is opportunity to characterise the relationship between PROMs and behaviour in a natural setting and to develop methods of passive monitoring of outcome and recovery after surgery. We are working with a multidisciplinary team which has developed a system of low powered sensors that can monitor the health-related behaviours of people living at home. The system includes: sensors for the home environment (measuring temperature, humidity, room occupancy, water and electricity usage) a wrist-band body-worn activity monitor and silhouette (body outline) sensors. The SPHERE system of sensors is now being installed in 100 homes belonging to the general population. Within this cohort we are installing the system in the homes of 20 patients who are about to undergo a total hip or knee replacement (THR/TKR). The study aims to: (a) determine to what extent the sensory data obtained from the SPHERE system is comparable to data obtained from routine clinical measures and PROMs in the assessment of patients' activity, function and recovery processes; (b) investigate whether the sensory data can detect meaningful changes in recovery. Methods: To assess the accuracy and usefulness of the sensory data, in this 1-year observational study, patients will be provided with the sensor system to monitor and record daily continuous measurements. We will make and refine appropriate data learning outcomes with the quantitative data e.g., daily measurements in the weeks parallel to the distribution of PROM assessments pre/post-operative (4–9 days, 6 and 12 weeks) and weekly measurements during the other months. The study will assess the relationships between environmental, behavioural and movement data and the parameters of interest from the PROMs assessments over time. Interviews and focus groups with patients and health professional will provide qualitative data and achieve depth in understanding the accuracy of the data, its usefulness for health professionals in decision making, and if the technology is acceptable. Results: The SPHERE sensor system has been installed in the homes of two patients. We aim to recruit up to 20 patients, (aged 18 years or over) whom are due to undergo a TKR or THR in the UK. Conclusions: This study will provide a unique understanding of home and wearable sensor technology in an orthopaedic population and will compare sensor data with current PROMs

Obesity and revision surgery, mortality, and patient-reported outcomes after primary knee replacement surgery in the National Joint Registry : a UK cohort study

BACKGROUND: One in 10 people in the United Kingdom will need a total knee replacement (TKR) during their lifetime. Access to this life-changing operation has recently been restricted based on body mass index (BMI) due to belief that high BMI may lead to poorer outcomes. We investigated the associations between BMI and revision surgery, mortality, and pain/function using what we believe to be the world's largest joint replacement registry. METHODS AND FINDINGS: We analysed 493,710 TKRs in the National Joint Registry (NJR) for England, Wales, Northern Ireland, and the Isle of Man from 2005 to 2016 to investigate 90-day mortality and 10-year cumulative revision. Hospital Episodes Statistics (HES) and Patient Reported Outcome Measures (PROMs) databases were linked to the NJR to investigate change in Oxford Knee Score (OKS) 6 months postoperatively. After adjustment for age, sex, American Society of Anaesthesiologists (ASA) grade, indication for operation, year of primary TKR, and fixation type, patients with high BMI were more likely to undergo revision surgery within 10 years compared to those with "normal" BMI (obese class II hazard ratio (HR) 1.21, 95% CI: 1.10, 1.32 (p < 0.001) and obese class III HR 1.13, 95% CI: 1.02, 1.26 (p = 0.026)). All BMI classes had revision estimates within the recognised 10-year benchmark of 5%. Overweight and obese class I patients had lower mortality than patients with "normal" BMI (HR 0.76, 95% CI: 0.65, 0.90 (p = 0.001) and HR 0.69, 95% CI: 0.58, 0.82 (p < 0.001)). All BMI categories saw absolute increases in OKS after 6 months (range 18-20 points). The relative improvement in OKS was lower in overweight and obese patients than those with "normal" BMI, but the difference was below the minimal detectable change (MDC; 4 points). The main limitations were missing BMI particularly in the early years of data collection and a potential selection bias effect of surgeons selecting the fitter patients with raised BMI for surgery. CONCLUSIONS: Given revision estimates in all BMI groups below the recognised threshold, no evidence of increased mortality, and difference in change in OKS below the MDC, this large national registry shows no evidence of poorer outcomes in patients with high BMI. This study does not support rationing of TKR based on increased BMI

Using home sensing technology to assess outcome and recovery after hip and knee replacement in the UK: the HEmiSPHERE study protocol

Abstract Introduction Over 160 000 people with severe hip or knee pain caused by osteoarthritis undergo total hip (THR) or knee replacement (TKR) surgery each year in the UK within the National Health Service (NHS), and this number is expected to increase. Innovative approaches to evaluating surgical outcomes will be needed to respond to the increasing burden of joint replacement surgery. The Sensor Platform for Healthcare in a Residential Environment, Interdisciplinary Research Collaboration (SPHERE-IRC) have developed a system of sensors that can monitor the health-related behaviours of people living at home. The system includes sensors for the home environment (measuring temperature, humidity, room occupancy, water and electricity usage), a wristband body-worn activity monitor and silhouette (body outline) sensors. The aim of HEmiSPHERE (Hip and knEe study of a Sensor Platform of HEalthcare in a Residential Environment) is to (1) determine the accuracy and feasibility of the sensory data as it compares with conventional assessment of health outcomes after surgery using patient self-reported questionnaires, and (2) to explore how the SPHERE system is useful for everyday clinical decision-making. Methods and analysis A feasibility study recruiting and installing the SPHERE system in the homes of up to 30 NHS adult patients as they undergo a THR or TKR. Through a mixed-methods design, the SPHERE system will monitor and record continuous measurements of daily behaviour. Main outcomes will assess the relationships between environmental, behavioural and movement data and the parameters of interest from the standard clinical assessments measuring patient outcomes over time. Patient interviews and focus groups with consultant orthopaedic surgeons will provide in-depth understanding of the acceptability, feasibility and accuracy of the data. Ethics and dissemination We aim to disseminate the findings through regional talks and seminars, international conferences and peer-reviewed journals and social media

Revision and 90-day mortality following hip arthroplasty in patients with inflammatory arthritis and ankylosing spondylitis enrolled in the National Joint Registry for England and Wales

Aim: To assess revision rates and postoperative mortality in patients undergoing hip arthroplasty (HA) for inflammatory arthritis compared to hip osteoarthritis (OA). Methods: The analysis was conducted among cases of HA that were recorded in the National Joint Registry for England and Wales (NJR) between April 2003 and December 2012 and linked to Office for National Statistics mortality records. Procedures were identified where the indication for surgery was listed as seropositive rheumatoid arthritis (RA), ankylosing spondylitis (AS), other inflammatory arthritis (otherIA), or OA. 5-year revision risk and 90-day postoperative mortality according to indication were compared using Cox regression models adjusted for age, sex, American Society of Anaesthesiologists (ASA) grade, year of operation, implant type, and surgical approach. Results: The cohort included 1457 HA procedures conducted for RA, 615 for AS, 1000 for otherIA, and 183,108 for OA. When compared with OA, there was no increased revision risk for any form of inflammatory arthritis (adjusted HRs: RA: 0.93 (0.64–1.35); AS: 1.14 (0.73–1.79); otherIA: 1.08 (0.73–1.59)). Postoperative 90-day mortality was increased for RA when compared with OA (adjusted HR: 2.86 (1.68–4.88)), but not for AS (adjusted HR: 1.56 (0.59–4.18)) or otherIA (adjusted HR: 0.64 (0.16–2.55)). Conclusions: The revision risk in HA performed for all types of inflammatory arthritis is similar to that for HA performed for OA. The 3-fold increased risk of 90-day mortality in patients with RA compared with OA highlights the need for active management of associated comorbidities in RA patients during the perioperative period