Modelling Patient Behaviour Using IoT Sensor Data: a Case Study to Evaluate Techniques for Modelling Domestic Behaviour in Recovery from Total Hip Replacement Surgery

The UK health service sees around 160,000 total hip or knee replacements every year and this number is expected to rise with an ageing population. Expectations of surgical outcomes are changing alongside demographic trends, whilst aftercare may be fractured as a result of resource limitations. Conventional assessments of health outcomes must evolve to keep up with these changing trends. Health outcomes may be assessed largely by self-report using Patient Reported Outcome Measures (PROMs), such as the Oxford Hip or Oxford Knee Score, in the months up to and following surgery. Though widely used, many PROMs have methodological limitations and there is debate about how to interpret results and definitions of clinically meaningful change. With the development of a home-monitoring system, 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. In this paper, we discuss the motivation and technology used in long-term continuous observation of movement, sleep and domestic routine for healthcare applications, such as the HEmiSPHERE project for hip and knee replacement patients. In this case study, we evaluate trends evident in data of two patients, collected over a 3-month observation period post-surgery, by comparison with scores from PROMs for sleep and movement quality, and by comparison with a third control home. We find that accelerometer and indoor localisation data correctly highlight long-term trends in sleep and movement quality and can be used to predict sleep and wake times and measure sleep and wake routine variance over time, whilst indoor localisation provides context for the domestic routine and mobility of the patient. Finally, we discuss a visual method of sharing findings with healthcare professionals

Genetic polymorphisms of the RAS-cytokine pathway and chronic kidney disease

Chronic kidney disease (CKD) in children is irreversible. It is associated with renal failure progression and atherosclerotic cardiovascular (CV) abnormalities. Nearly 60% of children with CKD are affected since birth with congenital or inherited kidney disorders. Preliminary evidence primarily from adult CKD studies indicates common genetic risk factors for CKD and atherosclerotic CV disease. Although multiple physiologic pathways share common genes for CKD and CV disease, substantial evidence supports our attention to the renin angiotensin system (RAS) and the interlinked inflammatory cascade because they modulate the progressions of renal and CV disease. Gene polymorphisms in the RAS-cytokine pathway, through altered gene expression of inflammatory cytokines, are potential factors that modulate the rate of CKD progression and CV abnormalities in patients with CKD. For studying such hypotheses, the cooperative efforts among scientific groups and the availability of robust and affordable technologies to genotype thousands of single nucleotide polymorphisms (SNPs) across the genome make genome-wide association studies an attractive paradigm for studying polygenic diseases such as CKD. Although attractive, such studies should be interpreted carefully, with a fundamental understanding of their potential weaknesses. Nevertheless, whole-genome association studies for diabetic nephropathy and future studies pertaining to other types of CKD will offer further insight for the development of targeted interventions to treat CKD and associated atherosclerotic CV abnormalities in the pediatric CKD population

CKD-MBD after kidney transplantation

Successful kidney transplantation corrects many of the metabolic abnormalities associated with chronic kidney disease (CKD); however, skeletal and cardiovascular morbidity remain prevalent in pediatric kidney transplant recipients and current recommendations from the Kidney Disease Improving Global Outcomes (KDIGO) working group suggest that bone disease—including turnover, mineralization, volume, linear growth, and strength—as well as cardiovascular disease be evaluated in all patients with CKD. Although few studies have examined bone histology after renal transplantation, current data suggest that bone turnover and mineralization are altered in the majority of patients and that biochemical parameters are poor predictors of bone histology in this population. Dual energy X-ray absorptiometry (DXA) scanning, although widely performed, has significant limitations in the pediatric transplant population and values have not been shown to correlate with fracture risk; thus, DXA is not recommended as a tool for the assessment of bone density. Newer imaging techniques, including computed tomography (quantitative CT (QCT), peripheral QCT (pQCT), high resolution pQCT (HR-pQCT) and magnetic resonance imaging (MRI)), which provide volumetric assessments of bone density and are able to discriminate bone microarchitecture, show promise in the assessment of bone strength; however, future studies are needed to define the value of these techniques in the diagnosis and treatment of renal osteodystrophy in pediatric renal transplant recipients

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

FinnGen provides genetic insights from a well-phenotyped isolated population

Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10–11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.publishedVersionPeer reviewe

Genetic architecture of human plasma lipidome and its link to cardiovascular disease

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 x10(-8)), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD

Algorithmic multiparameterised verification of safety properties:process algebraic approach

Abstract Due to increasing amount of concurrency, systems have become difficult to design and analyse. In this effort, formal verification, which means proving the correctness of a system, has turned out to be useful. Unfortunately, the application domain of the formal verification methods is often indefinite, tools are typically unavailable, and most of the techniques do not suit especially well for the verification of software systems. These are the questions addressed in the thesis. A typical approach to modelling systems and specifications is to consider them parameterised by the restrictions of the execution environment, which results in an (infinite) family of finite-state verification tasks. The thesis introduces a novel approach to the verification of such infinite specification-system families represented as labelled transition systems (LTSs). The key idea is to exploit the algebraic properties of the correctness relation. They allow the correctness of large system instances to be derived from that of smaller ones and, in the best case, an infinite family of finite-state verification tasks to be reduced to a finite one, which can then be solved using existing tools. The main contribution of the thesis is an algorithm that automates the reduction method. A specification and a system are given as parameterised LTSs and the allowed parameter values are encoded using first order logic. Parameters are sets and relations over these sets, which are typically used to denote, respectively, identities of replicated components and relationships between them. Because the number of parameters is not limited and they can be nested as well, one can express multiply parameterised systems with a parameterised substructure, which is an essential property from the viewpoint of modelling software systems. The algorithm terminates on all inputs, so its application domain is explicit in this sense. Other proposed parameterised verification methods do not have both these features. Moreover, some of the earlier results on the verification of parameterised systems are obtained as a special case of the results presented here. Finally, several natural and significant extensions to the formalism are considered, and it is shown that the problem becomes undecidable in each of the cases. Therefore, the algorithm cannot be significantly extended in any direction without simultaneously restricting some other aspect

Refinement checking parameterised quorum systems

Abstract Many fault-tolerant algorithms are based on decisions made by a quorum of nodes. Since the algorithms are utilised in safety critical applications such as distributed databases, it is necessary to make sure that they operate reliably under every possible scenario. We introduce a generic compositional formalism, based on parameterised labelled transition systems, which allows us to express safety properties of parameterised quorum systems. We prove that any parameterised verification task expressible in the formalism collapses into finitely many finite state refinement checking problems. The technique is implemented in a tool, which performs the verification completely automatically. As an example, we prove the leader election phase of the Raft consensus algorithm correct for an arbitrary number of terms and for a cluster of any size

An optimal cut-off algorithm for parameterised refinement checking

Abstract The verification of contemporary distributed software systems is challenging, because they are heavily parameterised, containing components whose number and connections cannot be a priori fixed. In this work, we consider the multi-parameterised verification of safety properties by refinement checking in the context of labelled transition systems (LTSs). The LTSs are parameterised by using first-order constructs, sorts, variables, and predicates, while preserving compositionality. This allows us to parameterise not only the number of replicated components but also the communication topology of the system. Our approach to solving a verification task in the parameterised LTS formalism is to determine a finite cut-off set of parameter values such that in order to prove a parameterised system implementation correct with respect to its specification, it is sufficient to consider only finitely many instances of the parameterised system generated by the parameter values in the cut-off set. In the conference version of this work, we converted the problem of determining a finite cut-off set into the unsatisfiability of a first-order formula and provided a satisfiability modulo theories (SMT)-based semi-algorithm for dynamically, i.e., iteratively, computing a cut-off set. In this article, we present a new version of the algorithm and prove that the cut-off sets computed by this new algorithm are optimal. Hence, we call the new version the optimal cut-off algorithm. The algorithm will always terminate for system topologies expressible in the ∃∗∀∗ fragment of first-order logic. It also enables us to consider systems with topologies beyond this fragment, but for these systems, the algorithm is not guaranteed to terminate. We have implemented the approach on top of the Z3 SMT solver and successfully applied it to several system models. As a running example, we consider the leader election phase of the generalised (Byzantine) Raft consensus algorithm and prove the optimal cut-off set of six (respectively, thirteen) parameter values corresponding to instances up to three (respectively, four) servers. To the best of our knowledge, this is the first time a Byzantine variant of the parameterised Raft leader election is automatically verified