Life expectancy in Duchenne Muscular Dystrophy : reproduced individual patient data meta-analysis

Objective: Duchenne Muscular Dystrophy (DMD) is a rare progressive disease, which is often diagnosed in early childhood, and leads to considerably reduced life-expectancy; due to its rarity, research literature and patient numbers are limited. To fully characterise the natural history, it is crucial to obtain appropriate estimates of the life-expectancy and mortality rates of patients with DMD. Methods: A systematic review of the published literature on mortality in DMD up until July 2020 was undertaken, specifically focusing on publications in which Kaplan-Meier (KM) survival curves with age as a time-scale were presented. These were digitised and individual patient data (IPD) reconstructed. The pooled IPD were analysed using the Kaplan-Meier estimator and parametric survival analysis models. Estimates were also stratified by birth cohort. Results: Of 1177 articles identified, 14 publications met the inclusion criteria and provided data on 2283 patients, of whom 1049 had died. Median life-expectancy was 22.0 years (95% CI: 21.2, 22.4). Analyses stratifying by three time-periods in which patients were born showed markedly increased life-expectancy in more recent patient populations; patients born after 1990 have a median life-expectancy of 28.1 years (95% CI 25.1, 30.3). Conclusions: This paper presents a full overview of mortality across the lifetime of a patient with DMD, and highlights recent improvements in survival. In the absence of large-scale prospective cohort studies or trials reporting mortality data for patients with DMD, extraction of IPD from the literature provides a viable alternative to estimating life-expectancy for this patient population

Natural history of Duchenne muscular dystrophy in the United Kingdom : a descriptive study using the Clinical Practice Research Datalink

Background Duchenne muscular dystrophy (DMD) is a rare, muscle-degenerative disease predominantly affecting males. Natural history models capture the full disease pathway under current care and combine with estimates of new interventions’ effects to assess cost-effectiveness by health technology decision-makers. These models require mortality estimates throughout a patient's lifetime, but rare disease datasets typically contain relatively few patients with short follow-ups. Alternative (published) sources of mortality data may therefore be required. Methods The Clinical Practice Research Datalink (CPRD) was evaluated as a source of mortality and natural history data for future economic evaluations of health technologies for DMD and rare diseases in general in the UK population. This retrospective longitudinal cohort study provides flexible parametric estimates of mortality rates and survival probabilities in the current UK DMD population through primary/secondary records in the CPRD since 1990. It also investigates clinically significant milestones such as corticosteroid use, spinal surgery, and cardiomyopathy in these patients. Results A total of 1121 male patients were included in the study, observed from 0.7 to 48.9 years. Median life expectancy was 25.64 years (95% confidence interval 24.73, 26.47), consistent with previous global estimates. This has improved to 26.47 (25.16, 27.89) years in patients born after 1990. The median ages at corticosteroid initiation, spinal surgery, ventilation, and cardiomyopathy diagnosis were 6.06 years (5.77, 6.29), 14.79 years (14.29, 15.09), 16.97 years (16.50, 18.31), and 15.26 years (14.22, 16.70), respectively. Conclusions Estimates of mortality in UK-based DMD patients are age-specific in a uniquely large and nationally representative sample from the CPRD

Incidence and prevalence of post-stroke insomnia: a systematic review and meta-analysis

Problems with sleep are reported to be common after stroke but the incidence and prevalence of insomnia and insomnia symptoms following stroke is not yet established. The aim of this review was to conduct a systematic review and meta-analysis of the incidence and prevalence of insomnia and insomnia symptoms in individuals affected by stroke. We searched seven main electronic databases to identify studies until September 25, 2018. No studies examining incidence of post-stroke insomnia were identified. Twenty-two studies on prevalence of insomnia or insomnia symptoms including individuals with stroke were included with fourteen studies suitable for inclusion in the meta-analysis. Meta-analysis indicated pooled prevalence of 38.2% (CI 30.1–46.5) with significantly higher prevalence estimates for studies using non-diagnostic tools, 40.70% (CI 30.96–50.82) compared to studies using diagnostic assessment tools 32.21% (CI 18.5–47.64). Greater insomnia symptoms were indicated in those with comorbid depression and anxiety. The prevalence of both insomnia and insomnia symptoms are considerably higher in stroke survivors compared to the general population. Studies investigating the incidence, insomnia symptom profile and changes in insomnia prevalence over time are needed to inform clinical practice and to encourage tailored interventions that consider this symptomatology. PROSPERO registration number CRD42017065670

The effect of nodal connectivity and strut density within stochastic titanium scaffolds on osteogenesis

Modern orthopaedic implants use lattice structures that act as 3D scaffolds to enhance bone growth into and around implants. Stochastic scaffolds are of particular interest as they mimic the architecture of trabecular bone and can combine isotropic properties and adjustable structure. The existing research mainly concentrates on controlling the mechanical and biological performance of periodic lattices by adjusting pore size and shape. Still, less is known on how we can control the performance of stochastic lattices through their design parameters: nodal connectivity, strut density and strut thickness. To elucidate this, four lattice structures were evaluated with varied strut densities and connectivity, hence different local geometry and mechanical properties: low apparent modulus, high apparent modulus, and two with near-identical modulus. Pre-osteoblast murine cells were seeded on scaffolds and cultured in vitro for 28 days. Cell adhesion, proliferation and differentiation were evaluated. Additionally, the expression levels of key osteogenic biomarkers were used to assess the effect of each design parameter on the quality of newly formed tissue. The main finding was that increasing connectivity increased the rate of osteoblast maturation, tissue formation and mineralisation. In detail, doubling the connectivity, over fixed strut density, increased collagen type-I by 140%, increased osteopontin by 130% and osteocalcin by 110%. This was attributed to the increased number of acute angles formed by the numerous connected struts, which facilitated the organization of cells and accelerated the cell cycle. Overall, increasing connectivity and adjusting strut density is a novel technique to design stochastic structures which combine a broad range of biomimetic properties and rapid ossification

Modeling the multi‐state natural history of rare diseases with heterogeneous individual patient data : a simulation study

Multi‐state survival models are used to represent the natural history of a disease, forming the basis of a health technology assessment comparing a novel treatment to current practice. Constructing such models for rare diseases is problematic, since evidence sources are typically much sparser and more heterogeneous. This simulation study investigated different one‐stage and two‐stage approaches to meta‐analyzing individual patient data (IPD) in a multi‐state survival setting when the number and size of studies being meta‐analyzed are small. The objective was to assess methods of different complexity to see when they are accurate, when they are inaccurate and when they struggle to converge due to the sparsity of data. Biologically plausible multi‐state IPD were simulated from study‐ and transition‐specific hazard functions. One‐stage frailty and two‐stage stratified models were estimated, and compared to a base case model that did not account for study heterogeneity. Convergence and the bias/coverage of population‐level transition probabilities to, and lengths of stay in, each state were used to assess model performance. A real‐world application to Duchenne Muscular Dystrophy, a neuromuscular rare disease, was conducted, and a software demonstration is provided. Models not accounting for study heterogeneity were consistently out‐performed by two‐stage models. Frailty models struggled to converge, particularly in scenarios of low heterogeneity, and predictions from models that did converge were also subject to bias. Stratified models may be better suited to meta‐analyzing disparate sources of IPD in rare disease natural history/economic modeling, as they converge more consistently and produce less biased predictions of lengths of stay

Measuring the effects of listening for leisure on outcome after stroke (MELLO):A pilot randomized controlled trial of mindful music listening

Background: Cognitive deficits and low mood are common post-stroke. Music listening is suggested to have beneficial effects on cognition, while mindfulness may improve mood. Combining these approaches may enhance cognitive recovery and improve mood early post-stroke. Aims: To assess the feasibility and acceptability of a novel mindful music listening intervention. Methods: A parallel group randomized controlled feasibility trial with ischemic stroke patients, comparing three groups; mindful music listening, music listening and audiobook listening (control group), eight weeks intervention. Feasibility was measured using adherence to protocol and questionnaires. Cognition (including measures of verbal memory and attention) and mood (Hospital Anxiety and Depression Scale) were assessed at baseline, end of intervention and at six-months post-stroke. Results: Seventy-two participants were randomized to mindful music listening (n = 23), music listening (n = 24), or audiobook listening (n = 25). Feasibility and acceptability measures were encouraging: 94% fully consistent with protocol; 68.1% completing ≥6/8 treatment visits; 80–107% listening adherence; 83% retention to six-month endpoint. Treatment effect sizes for cognition at six month follow-up ranged from d = 0.00 ([−0.64,0.64], music alone), d = 0.31, ([0.36,0.97], mindful music) for list learning; to d = 0.58 ([0.06,1.11], music alone), d = 0.51 ([−0.07,1.09], mindful music) for immediate story recall; and d = 0.67 ([0.12,1.22], music alone), d = 0.77 ([0.16,1.38]mindful music) for attentional switching compared to audiobooks. No signal of change was seen for mood. A definitive study would require 306 participants to detect a clinically substantial difference in improvement (z-score difference = 0.66, p = 0.017, 80% power) in verbal memory (delayed story recall). Conclusions: Mindful music listening is feasible and acceptable post-stroke. Music listening interventions appear to be a promising approach to improving recovery from stroke

Depression and anxiety symptoms post-stroke/TIA:prevalence and associations in cross-sectional data from a regional stroke registry

BACKGROUND: Mood disorders are commonly seen in those with cerebrovascular disease. Literature to-date has tended to focus on depression and on patients with stroke, with relatively little known about post-stroke anxiety or mood disorder in those with transient ischaemic attack (TIA). We aimed to describe prevalence of depression and anxiety symptoms in stroke and TIA cohorts and to explore association with clinical and socio-demographic factors. METHODS: We used a city wide primary care stroke registry (Glasgow Local Enhanced Service for Stroke - LES). All community dwelling stroke-survivors were included. We described cross-sectional prevalence of depression and anxiety symptoms using the Hospital Anxiety and Depression Scale (HADS). Data on clinical and demographic details was collected and univariable and multivariable analyses performed to describe associations with HADS scores. We examined those with a diagnosis of 'stroke' and 'TIA' as separate cohorts. RESULTS: From 13,283 potentially eligible stroke patients in the registry, we had full HADS data on 4,079. Of the 3,584 potentially eligible TIA patients, we had full HADS data on 1,247 patients. Across the stroke cohort, 1181 (29%) had HADS anxiety scores suggestive of probable or possible anxiety; 993 (24%) for depression. For TIA patients, 361 (29%) had anxiety and 254 (21%) had depression. Independent predictors of both depression and anxiety symptoms were female sex, younger age and higher socioeconomic deprivation score (all p < 0.001). CONCLUSION: Using HADS, we found a high prevalence of anxiety and depression symptoms in a community-based cohort of patients with cerebrovascular disease

Using technologies to support reminiscence

This paper is about the evolution of a system prototype called Pensieve whose goal is to support people’s reminiscing practices. A number of technologies exist to manage memory-related content; however, these technologies tend to take a model of memory as information that leads to a focus on capture and access. Pensieve is instead based on reusing memory-laden content people already create in social media services. This idea is supported by theories of autobiographical memory, insights from interviews with eight subjects, and experiences with two prototypes deployed to ten users. These interviews and experiences suggest that people value even simple tools that support reminiscence, as well as providing both design goals and research questions around the design of tools that support people in reminiscing