To examine primary school and local authority characteristics associated with registration for The Daily Mile (TDM), an active mile initiative aimed at increasing physical activity in children.A cross-sectional linkage study using routinely collected data.All state-funded primary schools in England from 2012 to 2018 .3,502 of all 15,815 (22.1%) state-funded primary schools in England were registered to do TDM, ranging from 16% in the East Midlands region to 31% in Inner London. Primary schools registered for TDM had larger mean pupil numbers compared with schools that had not registered . There was a higher proportion of TDM-registered schools in urban areas compared with non-urban areas. There was local authority variation in the likelihood of school registration (intraclass correlation coefficient: 0.094). After adjusting for school and local authority characteristics, schools located in a major urban conurbation (OR 1.46 (95% CI 1.24 to 1.71) urban vs rural) and schools with a higher proportion of disadvantaged pupils had higher odds of being registered for TDM (OR 1.16 (95% CI 1.02 to 1.33)). Area-based physical activity and schools’ educational attainment were not significantly associated with registration to TDM.One in five primary schools in England has registered for TDM since 2012. TDM appears to be a wide-reaching school-based physical activity intervention that is reaching more disadvantaged primary school populations in urban areas where obesity prevalence is highest. TDM-registered schools include those with both high and low educational attainment and are in areas with high and low physical activity. There is potential for all children to take part, especially those who tend to be less physically active than their peers, such as girls, those residing in deprived areas and some minority ethnic groups.3The WHO and the UK government recommend that children aged 5 to 17 years should accumulate at least 60 minutes of moderate to vigorous physical activity (MVPA) daily.4 It is a teacher-led activity that involves primary school children jogging or running for 15 min during curriculum time within the school grounds.5 Its core features are that it is simple, inclusive and has flexible delivery that can be adapted to different primary school settings.5 Since 2018, the UK’s Child Obesity Strategy specifically mentioned TDM in outlining a national ambition for every primary school to achieve physical activity targets.6 Since then, there have been considerable efforts to promote and implement TDM. This includes 1.5 million pounds of investment by the UK government into funding co-ordinators in 10 areas of England to encourage schools to register for TDM.7 8 TDM Foundation has run numerous campaigns to promote TDM such as TV advertisements and a running event for primary school children called ‘GORunforFun’ which engaged 2,400 children from 45 schools across London.9 10 Qualitative research suggests there is considerable adaptation that occurs in areas where TDM has been successfully implemented.11 These features could be a key to its success in implementation and explain why more complex school-based interventions have failed.12 13 A growing evidence base suggests that TDM increases physical activity and fitness over the first 12 months of its adoption,14 15 but evidence of its impact on educational performance, well-being or maintaining healthy weight is limited.16 17The Daily Mile (TDM) is an active mile initiative that began in Scotland in 2012 and has grown as an organic grass-roots movement. TDM has reportedly had a large uptake that has spread across the UK and Europe, with an estimated 10,000 schools and nurseries taking part across 77 countries worldwide.Many schools, particularly those in urban areas, have limited access to outdoor space or have concerns about the risks of exposing children to air or traffic pollution, which could act as disincentives for uptake of TDM and other active mile interventions that involve running or jogging outside. Key performance indicators of educational attainment in UK schools are firmly tied to performance in reading and writing scores. Thus, it is possible that primary schools that lag in performance league tables do not prioritise activities such as TDM that may compete with curricular time. The purpose of this study was to link multiple routine data sources to examine sociodemographic, health and educational profiles of primary schools registered for TDM and the local authority areas in which they are located in England.This was a cross-sectional study of all state-funded primary schools in England. We created a database linking health and education data from the School Census, the National Pupil Database, Active Lives Surveys and the National Child Measurement Programme, with TDM registration data provided by TDM Foundation.18 It holds data on pupil characteristics including pupil numbers, ethnicity, if they are disadvantaged, or whether they have any special educational needs  entering and leaving primary school in England each year.22 The Active Lives Adult Survey collects data on physical activity and reported weight status of adults, and the Active Lives Children and Young People Survey contains reported data on children’s physical activity in England.23 We linked population profiles of obesity prevalence and physical activity in each local authority to our schools’ database.There are a total of 152 counties and unitary authorities in England which include metropolitan districts, London boroughs, unitary authorities and county councils which were defined as local authorities for our study.We compared school and local authority characteristics of primary schools registered for TDM with those that did not register. We also examined the local authority health profiles of child and adult physical activity and obesity prevalence in areas in which primary schools were located. We used t-tests to compare continuous variables  and ᵡ² tests to compare categorical variables .Due to the hierarchical nature of the data, multilevel models were used to determine the association between school and local authority characteristics associated with TDM registration and to assess variation at school and local authority levels. To investigate the variation explained at different levels, a sequential series of models were built .In order to establish the need to account for clustering, we fitted logistic regression models with school and local authority characteristics .After checking the need to account for clustering, we fitted a multilevel model with intercept only to examine the variability of TDM registration between local authorities (model 1). Next, to test whether school characteristics explained variation in registration, we extended model 1, adding school-level characteristics (model 2). Finally, we extended model 2 adding local authority characteristics  (model 3) to determine the extent of variation.2 test, to test the multilevel logistic regression model against the corresponding non-hierarchical logistic regression model to assess the goodness-of-fit. Results of the log-likelihood ratio χ2 test, along with the Akaike Information Criterion values, showed that multilevel models were preferred. Model 3 was chosen as the best fit for the data.Models 1, 2 and 3 were run as logistic regressions, without the local authority–level random effect. This was in order to obtain a log-likelihood ratio χ10.1136/jech-2020-214203.supp3Supplementary dataTo examine primary school and local authority characteristics associated with registration for TDM, we selected 10 candidate variables that are proxy indicators of school and pupil health and well-being. These were identified from the literature and by consensus among authors . These vThis study design and background were informed by extensive knowledge exchange with health professional, educational stakeholder representatives including head teachers, parents, policy-makers, TDM Foundation, and experts and academics including TDM Research Advisory Group.Between 2012 and 2018, there were 15,815 state-funded primary schools in England . Of thesTDM schools had greater mean pupil numbers compared to non-TDM schools . The proportion of disadvantaged children in TDM schools was higher than non-TDM schools . In line with our sample, which was all state-funded primary schools across England, 72% of TDM schools were under local authority control and 28% were academies (including free schools). A greater proportion of TDM schools were located in urban areas, especially the major conurbations of London, the West Midlands, West Yorkshire, Tyneside, Merseyside and Greater Manchester . FurtherAfter adjusting for school-level characteristics (model 2), schools in a major urban conurbation showed almost 50% higher odds of being registered for TDM (OR 1.46 (95% CI 1.24 to 1.71)). Additionally, schools with a higher proportion of disadvantaged pupils had higher odds of being registered as a TDM school compared with schools with a lower proportion of disadvantaged pupils, whereby an increase of 1 SD (19%) in the proportion of disadvantaged pupils produces, on average, a 16% increase in the odds of being a TDM school ). In the fully adjusted model (model 3), no significant associations were found between registration with TDM and child and adult physical activity, child and adult excess weight status, educational attainment measures and pupils whose first language was not classified as English.We found that 9.4% of the residual variance in TDM registration by schools is explained by local authority effects and 90.6% is explained by the schools’ characteristics. When school characteristics were added to the intercept only model, only part of the variation observed in model 1(2.6%) was explained (model 2 ICC=0.068). The ICC for model 3 is 0.064, dropping only very marginally from model 2, even after adding local authority prevalence of excess weight status and physical activity variables for children and adults, suggesting that the adult and child physical activity and excess weight status account for only ~0.4% of the variation seen in TDM registration.One in five primary schools across England has registered with TDM since 2012. The distribution varies across the 10 English regions, but it is much higher in London and major urban conurbations where over a third of primary schools are registered.After adjusting for school and local authority characteristics, larger primary schools in urban areas and a higher proportion of disadvantaged children were more likely to have registered for TDM. We found no association between TDM registration and area-based physical activity or excess weight status, or schools’ educational attainment. Additionally, there was evidence of variation in registration of TDM in different local authorities that was not accounted for by characteristics of schools and its pupils.25 reducing selection bias. The use of multilevel models allowed us to account for the clustering of pupil data within schools, and population health indicators in local authorities, as well as adjust for important confounders.To our knowledge, this study is the first national study to characterise primary school uptake of a whole school-based physical activity intervention. Its strengths are its size and use of routine data that is nationally representative of around 4.7 million children in over 15,000 state-funded primary schools and all local authorities in England,26 27 We were unable to obtain physical activity for individual children or schools and have instead relied on reported area-based measures of children’s physical activity and is subject to recall bias.However, there are a number of important limitations to our study. The models included 12,214 of the 15,815 schools due to missing data. However, the sensitivity analysis  shows th28 29 There is mixed evidence surrounding the association between children’s physical activity and living in urban or rural areas.30 31 Some studies31 32 have found that children in urban areas are less physically active compared with rural areas. This is unsurprising, given the multiplicity of ways in which attributes of the physical and built environment affect physical activity in children and adults.33 Nevertheless, our findings may be evidence of a successful movement to drive up physical activity among children in urban areas. This is important since 33.5% of the UK population lives in major urban conurbations.34 Additionally, we found that after adjusting for rurality and ethnicity, having a higher proportion of disadvantaged pupils in a school increased the odds of adopting TDM. This is inconsistent with previous studies,35 which have found that people from lower socioeconomic groups are less likely to be physically active compared with those from higher socioeconomic groups. Further, a recent study of TDM in Wales showed similar benefits in fitness among children from both low and high socioeconomic groups.15Our findings that more TDM-registered schools were located in major urban conurbations like London could be a result of media campaigns and promotion of TDM and public health endorsement of TDM in some local authorities.16 36 Previous studies of school-based physical activity interventions have not shown they are effective in increasing MVPA in children.12 13 37 Possible reasons for this may lie in difficulties implementing complex interventions at scale. Qualitative research suggests there is considerable adaptation that occurs in areas where TDM has been successfully implemented11 and may underpin TDM’s success as a growing grass-roots movement.Our finding that schools registering for TDM have similar educational attainment to the wider population of schools also suggests it is a wide-reaching intervention that reaches both high-performing and low-performing schools. The evidence base about the effect of school-based physical activity interventions, active miles and TDM itself on cognition and educational attainment is limited.et al found significant and distinctive variation in physical activity across local authorities in England in adults.38 In England, where almost 65% of state schools are local authority–controlled, local authority commitment to school-based physical activity interventions is vital in helping children reach physical activity recommendations. This lack of association with area-based measures does not preclude a school-level or pupil-level effect.After adjustment, we found that local authority health profiles of TDM-registered schools were comparable to non-registered schools with respect to child and adult excess weight, and child and adult physical activity. We found no studies examining the impact of local authority on adoption of school-based physical activity interventions in children, but Rind 14 15 17 then our findings that it is taken up by urban schools serving disadvantaged school populations suggest added value from TDM over other interventions, that when scaled have failed to reach populations of children most in need.39Our findings that TDM is potentially reaching over 1 million children in England are evidence of the appeal to schools. It appears to be a wide-reaching intervention reaching high-performing and low-performing primary schools alike and local authority areas with better and poorer health. If it can be assumed that the physical fitness benefits of TDM seen in small trials to date are sustainable,5 Our findings support the idea that TDM being ‘simple and free’ might make it a more accessible intervention. If school-based physical activity interventions are embedded in the school curriculum, they are more likely to be effective and sustainable40 and TDM could be a vehicle to help children achieve physical activity recommendations. A previous study reporting a process evaluation in the East Midlands region has demonstrated high rates of implementation of TDM during the adoption phase.41TDM is promoted as a ‘simple and free’ and ‘sustainable’ intervention.15 If TDM can improve cardiorespiratory fitness equally and be an accessible solution to reduce the growing inactivity in children, it is important to understand whether TDM is an equitable intervention reaching varied high-risk populations. We recommend further research to explain variation among local authority areas in registration to TDM. There is extensive variation in child obesity prevalence locally and nationally.42 43 Since increasing physical activity levels in children is part of the solution for obesity prevention and reduction in children,6 it is of interest to understand how inputs from certain local authorities may influence child obesity trends.A recent study found that TDM increases cardiorespiratory fitness in children from both deprived and affluent backgrounds.One in five primary schools in England has registered for TDM since 2012. TDM appears to be a wide-reaching school-based physical activity intervention that is reaching more disadvantaged primary school populations in urban areas where obesity prevalence is highest. TDM-registered schools include those with both high and low educational attainment and areas with high and low physical activities.A large proportion of children in the United Kingdom and the world do not meet physical activity recommendations.The Daily Mile has been taken up in many countries and has shown to increase physical fitness in children, but there is limited evidence of its distribution within countries or of the characteristics of school populations it is reaching.More than one in five primary schools in England is registered for The Daily Mile.The Daily Mile appears to be a wide-reaching school-based physical activity intervention that is reaching more disadvantaged primary school populations in urban areas where obesity prevalence is highest.The Daily Mile registered schools include those with both high and low educational attainment and are located in areas with high and low physical activities.


GSN and KRT15. The interfollicular epidermis expressed predominately genes encoding for proteins associated with differentiation. All sample groups express genes encoding for proteins involved in cellular growth and signal transduction. The expression pattern of skin-associated genes in dogs is similar to humans. Differences in expression compared to mice and humans include BMP2 expression mainly in telogen and high KRT17 expression in the interfollicular epidermis of dogs. Our data provide the basis for the investigation of the structure and function of canine skin or skin disease and support the use of dogs as a model for human cutaneous disease by assigning gene expression to specific tissue states.The transcriptome profile and differential gene expression in telogen and late anagen microdissected hair follicles and the interfollicular epidermis of healthy dogs was investigated by using RNAseq. The genes with the highest expression levels in each group were identified and genes known from studies in other species to be associated with structure and function of hair follicles and epidermis were evaluated. Transcriptome profiling revealed that late anagen follicles expressed mainly keratins and telogen follicles expressed  The skin is the largest organ, with various essential functions, including protection/barrier against outside influences and thermoregulation. The epidermis and its appendages form the outer layer of the skin and are the first shield of the body from external harm . To fulfIn all species, the interfollicular epidermis (IFE) is composed of a squamous, stratified, multilayered epithelium that frequently self-renews, involving epidermal stem and progenitor cells that reside in the basal layer of the epidermis ,3. AfterThe disturbance of this process can have a devastating impact, such as excessive water loss, invasion of pathogens and development of cancer, which may become life-threatening. The main role of HFs is the production of hair shafts to maintain the hair essential for a variety of functions, such as sensation and the dispersion of sebum and pheromones. In animals, the fur also has life-preserving functions, such as thermal regulation, visual communication and protection from solar radiation and physical trauma.In contrast to the continuous renewal of the IFE, HFs renew periodically, going through life-long recurrent phases of growth (anagen), regression (catagen) and rest (telogen) ,8. The hThe maintenance of the protective function of the skin is not only dependent on a functional stem cell compartment but also on proteins involved in the structural and functional integrity. Examples are keratin intermediate filaments and proteins involved in cell–cell adhesion such as adherens junctions and desmosomes ,25.The immune function of the epidermis is maintained by the presence of specialized antigen presenting cells (Langerhans cells) and of numerous pattern recognition receptors, such as Toll-like receptors ,27. HFs SUV39H2 variants in nasal parakeratosis or FAM83G variants in hereditary footpad hyperkeratosis .,48.47,48later at −20 °C until RNA extraction.The IFE was microdissected by cutting it off from the dermis and the HFs were removed with a scalpel blade. Between 20 and 30 small IFE pieces of 1–3 mm were collected. Microdissected HFs and IFE pieces were stored in RNAWhole skin, adjacent to skin used for microdissection, was collected and fixed immediately in 10% buffered formalin. The formalin-fixed tissue was embedded in paraffin, cut as a 4 µm section and stained with hematoxylin and eosin (H&E) using standard procedures. The histological specimens were evaluated to confirm that no pathologic changes were present and to confirm the hair cycle stages determined by microdissection.® 2.0 Fluorometer  and RNA quality was assessed with a Bioanalyzer . High quality RNA (RIN > 9) was reverse transcribed into cDNA with the SMART-Seq v4 Ultra Low Input RNA Kit  and libraries were constructed following the TruSeq® Nano DNA Library Prep  protocol for RNA sequencing. Multiplexed total cDNA libraries were sequenced on two lanes using an Illumina HiSq3000 instrument with 100 bp single-end sequencing cycles. On average, thirty million reads were collected, converted into FASTQ file format and demultiplexed.RNA for transcriptome sequencing was extracted from the 20 pooled microdissected HF of the same cycle stage and the IFE collected from each dog. RNA extraction, library preparation and RNA-seq were performed as described in a previous study ,36. In bThe data are available from the European Nucleotide Archive (ENA), study accession number PRJEB21761 and sample accessions SAMEA7016531-SAMEA7016551 .The reads were quality checked with fastqc . Low quaThe raw counts were subjected to a regularized-logarithm transformation and a principal component analysis (PCA) was performed using R software package “ggplot2”  to visuaTo take the gene length into account, raw counts were normalized using the Transcripts Per Million (TPM) method to examine the most expressed genes in each group.Gene descriptions and functions were identified using the National Center for Biotechnology Information (NCBI) Gene database .p-values were calculated according to the Benjamini Hochberg method. Transcripts were considered to be differentially expressed with a false discovery rate (FDR) of <0.01 and log2 fold change of 1.5 as the threshold. A heatmap was drawn for the top 30 DEGs sorted based on log2 fold change. The heat map was obtained using DESeq2 normalized gene counts and “heatmap.2” function of “gplots” R package.DEGs between late anagen and telogen samples were analyzed by using a generalized linear model (GLM) of DESeq2 R Package  to the pCanis lupus familiaris) was selected as the background parameter. The upregulated and downregulated DE gene sets comparing late anagen and telogen were used to extract functional gene sets by “functional annotation chart” analyses. Annotations whose Benjaminin corrected p-value were lower than 0.05 were considered statistically significant.Gene Ontology (GO) analysis was applied to analyze the functional enrichment and significant pathways associated with DEGs using the Database for Annotation Visualization and Integrated Discovery (DAVID) ,58. The In skin samples from six dogs, either anagen or telogen HF stages predominated. However, in samples from two dogs, both hair cycle stages were present in roughly equal proportions (dogs 4 and 8).Histological examination revealed that, while in most skin samples, both anagen and telogen hair cycle stages were present, one of the stages predominated and corresponded to the stage recognized during microdissection. No pathologic changes were present in the samples included in this study and the epidermis was of normal thickness in all samples.Transcriptome sequencing revealed the expression of 21,790 genes  were highly expressed. The LOC gene is predicted to encode keratin-associated protein 4-12-like In telogen HFs, gelsolin (GSN) was highly expressed, which encodes a calcium-regulated protein that functions in the assembly and disassembly of actin filaments and therefore plays a role in cellular structure. KRT15, a gene encoding for a stem cell marker described to be present in anagen and telogen hair cycle stages in dogs [The genes with the highest expression in anagen and telogen HFs and in the IFE were identified and are presented in a Venn diagram using GeneVenn  Figure . A high KRT1, KRT10, LOR and ITM2B). One of the most expressed genes in the epidermis, LOC106559288, is predicted to encode a long non-coding RNA (lncRNA).Most genes that are highly expressed in the IFE are known to be associated with differentiation of human keratinocytes or encode for proteins in the human epidermis , as well as MIR8858, ACTG1 and ANXA2, which encode for structural proteins or for proteins associated with cellular growth and signal transduction. The basal cell markers, n = 32), stem cell markers (n = 12), HF (n = 25) and IFE (n = 12) structure/function and immune function (n = 11), respectively) and used for further analyses. Genes that were expressed at a very low level in all three groups  were not included in further investigations. The average expression of each gene was calculated for IFE, anagen and telogen samples  and were further analyzed. They were assigned to a specific biological function . PMEL encodes for melanogenic proteins. As melanogenesis takes place in the inferior portion of HFs, which is only present in anagen HFs, it is not surprising that PMEL is highly expressed in late anagen HFs. The other genes expressed higher in anagen were associated with the hair cycle .Genes expressed at least four-fold higher  in one group compared to the others are mentioned in the following. Genes expressed higher in anagen than in the other groups were mainly associated with HF structure , but also with stem cell marker (KRT15) or follicular structure (KRT17).In contrast, genes expressed higher in telogen were associated mostly with the hair cycle . Some of the hair cycle-associated genes (DKK3 and WNT3) are highly expressed in the IFE. Selected genes that expressed strongly in all three groups  were associated with epidermal and HF structure and function, such as DSP, KRT5, KRT14, KRT16 and KRT17, as well as the stem cell marker KRT15.The selected genes that showed higher expression in the IFE are encoding for epidermal structure . KRT75, IVL and LOR were strongly expressed by both hair cycle stages, but KRT75 and IVL were expressed significantly more in late anagen and LOR in telogen.From the 92 preselected genes known to be associated with HF structure and function, hair cycle, stem cells and immune function, 46 genes were differentially expressed comparing late anagen versus telogen hair cycle stages . As presp value < 0.05 are shown in Differentially expressed genes of three GO categories  were either up- or down-regulated in anagen. Upregulated and downregulated DEGs enriched GO terms with a Benjamini adjusted We studied the gene expression profile of canine microdissected HFs in telogen and late anagen and in the IFE to gain information about the canine-specific expression pattern. It is well known that gene expression in different species varies and our data provide the basis to interpret studies involving gene expression in canine skin disorders, either inherited or acquired, in more detail and with more confidence.DSP, KRT1, KRT5, KRT10, KRT14, KRT15, KRT17 and LOR).A comparative analysis of the 100 most highly expressed skin-associated genes in human and mouse transcriptomes revealed a 30.2% identity and thus highlights the significant differences between these two species . To inveWNT3 seems to be the most prominent WNT ligand, whereas in the mouse, Wnt10a is one of the most prominent WNT ligands [WNT3 is the most prominently expressed WNT ligand in our anagen samples in dogs.These results support that the dog is a good model for human skin disease, as we show in this study that the canine gene expression in IFE and HFs is much more similar to human follicular and epidermal gene expression, as compared to the mouse. Furthermore, our results emphasize the similarity between human and dog signaling associated with hair growth and highlight a more different gene expression pattern in mice. Similarity in the gene expression patterns of dogs and humans, as opposed to mice, can be seen, for example, in WNT expression. In the human anagen HFs,  ligands ,87. SimiKRT17 and BMP2. KRT17 was highly expressed in all our samples .In the IFE, the genes that are expressed highest are associated with keratinocyte differentiation. One of the most expressed genes in canine IFE, DKK3 and WNT3) are also highly expressed in the IFE, similar to mice and humans [DKK3, in contrast to other members of the Dickkopf family, does not interfere with the WNT signaling pathway and is proposed to be a tumor suppressor gene.Some of the hair cycle-associated genes  is HOXC13. It has been suggested previously that FOXN1 and HOXC13 are required for hair keratin expression in mice and humans [HOXC13 was also shown to be highly expressed in human anagen HFs [FOXN1  is known to be predominantly expressed in hair matrix keratinocytes, the hair cortex, and in outer root sheath keratinocytes and is known, together with Msx-2, to maintain anagen in mice [Analyzing genes in our data sets known to be associated with HF and IFE structure and function, stem cell markers and immune function, we found that, in anagen, the hair cycle-associated genes that are most upregulated are d humans ,97 and H in mice ,99. The FGF18 and MMP7. FGF18 is an important indicator of stem cell quiescence. In mice, Fgf18 was found to be expressed in the bulge and FGF18 peaked during telogen [Fgf18 in mice results in a shorter telogen phase [FGF18 is a telogen marker. While not much is known about the expression of matrix metalloproteinase 7 (MMP7) in HFs, Mmp2 and Mmp9 expression was shown in all structures of murine HFs and in the sebaceous glands of different hair cycle stages, respectively [MMP7 seems to be predominantly expressed in telogen HFs, suggesting a role in the hair cycle of dogs.In telogen, the most significantly DEGs associated with the hair cycle were  telogen . The delen phase ,101. Ourectively . In our LHX2 and NFATC1 were differentially expressed [NFATC1 was expressed in both late anagen and telogen, whereas LHX2 was expressed strongly in telogen only  and canine MHC class I molecules  were expressed at very low levels in late anagen HFs and much higher in telogen HFs and the IFE  had a hFATP4 , which cBMP2 expression mainly in telogen in dogs but not mice, and KRT17 expression in the IFE in dogs, while absent in mice and humans. Our data provide the basis for research investigating the structure and function of canine skin or skin disease, but also for scientists using a canine model for human disease, by assigning genes to specific tissue types. We presented the gene expression pattern of canine IFE and microdissected HFs in different hair cycle stages (late anagen and telogen). We found that the gene expression patterns of skin-associated genes in dogs are more similar to those in humans as compared to mice, further corroborating that the dog is a good model for human skin diseases. We also found gene expression that differs from what is known in mice and humans, such as


Young adults with mobility disability report lower health-related quality of life (HRQoL) than their able-bodied peers. This study aims to examine potential differences between the effects of mobile app versus supervised training and the association of cardiorespiratory fitness change with HRQoL in young adults with mobility disability.n = 55) and a supervised health program (n = 55) that was provided for 12 weeks to 110 adults (18–45 years) with self-perceived mobility disability. Recruitment took place at rehabilitation centers in Stockholm, Sweden. Cardiorespiratory fitness was estimated from the results of a submaximal cycle ergometer test and HRQoL was assessed with the SF-36 questionnaire. Follow up was at 6 weeks, 12 weeks, and 1-year and all examinations were performed by blinded investigators. Between group differences of changes in HRQoL at follow up were estimated in intention-to-treat analysis using linear regression models. Crude and adjusted mixed-effects models estimated the associations between cardiorespiratory fitness change and HRQoL. Stratified analysis by intervention group was also performed.This is a secondary analysis of a parallel randomized controlled trial of a mobile app  and emotional role functioning  domains of SF-36. After stratification, the associations with general health  and emotional role functioning  were present only in the supervised group.This study found positive associations between cardiorespiratory fitness change and HRQoL in young adults with mobility disability who received supervised training. The effects of mobile app versus supervised training on HRQoL remain unclear.ISRCTN22387524; Prospectively registered on February 4th, 2018.International Standard Randomized Controlled Trial Number (ISRCTN) registry  Disability is a condition that any person might encounter at some point in life as a consequence of health conditions . It can The presence of mobility disability during early adulthood might lead to adverse consequences in the affected individuals. More specifically, young adults with acquired mobility limitations are more likely to increase their body weight  and follHRQoL constitutes a universal measurement for assessing self-perceived health covering several physical and mental health domains . In the Physical activity interventions are generally effective in improving HRQoL among adults –18. Two Previous research suggests that physical activity interventions which target people with disabilities should consider the use of technological means . Mobile Level of cardiorespiratory fitness is another more or less modifiable individual characteristic with known health benefits , 25, whiTo the best of our knowledge, there is a lack of evidence regarding effective interventions in improving HRQoL in young adults with mobility disability. To date, the majority of interventions with this aim has been focused on older adults , 32. MorThis is a secondary analysis of a parallel randomized controlled trial of two multicomponent interventions, with primary aim to compare the effects of a mobile app versus a supervised health program on physical activity levels in young adults with mobility disability . A protohttp://www.isrctn.com/ISRCTN22387524) [For the current study, the initial randomized controlled trial design was retained in order to compare the effects of the two interventions on HRQoL, which was among the pre-specified secondary outcomes of the trial (2387524) , using aThis study included young adults (18–45 years) that had acquired mobility disability over the past 3 years and had participated in the randomized controlled trial . Individn = 55) or a supervised health program (n = 55) for 12 weeks [During recruitment at the rehabilitation centers and before the first examination, staff from the TWITCH Health Capital in Stockholm randomly assigned participants to one of the two intervention groups. Participants were randomized to receive either a mobile app program , which was the primary outcome of the randomized controlled trial . For thiBoth intervention groups had multiple components designed based on behavior change techniques, including the use of intrinsic motivation, self-monitoring, and goal setting, which have deemed to be effective in increasing physical activity levels in adults .The mobile app program combined the use of three mobile apps, including a widely used walking app called Acupedo, a home-based body weight based training app, and a food photography app named LogMyFood . The traIn the supervised group, participants received health coaching and an individualized weekly personal training session for 1 h . They weHealth related quality of life (HRQoL) was assessed at baseline and at the follow up examinations with the SF-36 health survey which is a widely used instrument . It cons2max in ml/kg/min using sex specific equations that account for age [2max is an objective measure of cardiorespiratory fitness and represents the maximum volume of oxygen that the body can utilize per unit of time during intensive exercise [Cardiorespiratory fitness was estimated at all examination points from the results of the Ekblom-Bak test, which is a submaximal cycle ergometer test that estimates V˙O for age . V˙O2maxexercise .Demographic and clinical information including age, sex, and chronic conditions was collected at baseline through a self-reported questionnaire . Due to Smoking status was assessed at baseline through three Yes/No questions including whether they were daily smokers, occasional smokers, and if they ever used to smoke daily for at least 6 months . ParticiBody mass index (BMI) was calculated as body weight in kg divided by the square of height in meters. Height and weight were measured without shoes and were rounded to the nearest 0.5 cm and 0.1 kg respectively, using validated scales .Moderate to vigorous physical activity (MVPA) was measured at each examination point with the use of accelerometers (Actigraph GT3X+) for seven consecutive days . In orde2max and the SF-36 domain scores between baseline and each follow up examination, two tailed t-tests were applied. The results are presented as mean changes ± SD between baseline and each follow up examination.Statistical analyses were performed using Stata/IC 15. A significance level of < 0.05 was set for all statistical tests. Baseline characteristics of all participants and within each intervention group are presented in Table The effects of the mobile app program compared to the supervised health program on the SF-36 scores were examined using intention-to-treat analysis. Between group differences in the mean changes of SF-36 scores from baseline to midpoint, endpoint, and 1-year were estimated using simple linear regression models, with the supervised group chosen as referent.2max at midpoint, endpoint, and 1 year from baseline, with changes in the SF-36 scores. Mixed-effects linear regression is an extension of the generalized linear model and was suitable for this analysis, as it accounts for correlations between repeated measurements within participants and can model both mixed and random effects [2max and changes in the SF-36 scores.Mixed-effects linear regression models were fitted for estimating the association of changes in V˙O effects . The int effects  and HRQo effects . In addi2max, MVPA and SF-36 scores from the midpoint to the endpoint of the intervention, were compared between those who attended the 1-year follow up and those who did not. Two-tailed t-tests and chi-squared tests were used for these comparisons with level of significance α = 0.05.Sensitivity analysis was also performed for comparing baseline characteristics between those who attended the 1-year follow up and those who did not. In addition, changes in V˙OThe flow-chart of study participants is presented in Fig. In total, 40/55 participants from the mobile app and 49/55 from the supervised health program were included in the intention-to-treat analysis, as they had completed the SF-36 questionnaire in at least one follow-up examination. Between the two intervention groups there were not significant differences in the mean changes of SF-36 scores from baseline to each follow up. , general health , vitality , and emotional role functioning  domains of SF-36  and emotional role functioning  remained statistically significant. When measuring these associations within each intervention group, changes in V˙O2max were significantly associated with changes in the SF-36 scores only in the supervised health program. More specifically, both crude and adjusted models in the supervised group indicated associations between changes in V˙O2max and changes in the general health  and emotional role functioning  domains.The mixed-effects linear regression models indicated that changes in V˙O2max from midpoint to endpoint, compared to those who attended the last follow up .Sensitivity analyses indicated that participants who did not attend the 1-year follow up did not differ from the participants who attended the 1-year follow up regarding the baseline characteristics. Among the participants that did not attend the 1-year follow-up, 65% were from the mobile app group. In the mobile app group, 7 participants were dissatisfied with the allocation and dropped out before receiving the intervention. During the follow up, the attrition rates were similar in both groups. In addition, those who did not attend the 1-year follow up but had attended the endpoint follow up, had smaller increases in their V˙OThis study found no significant differences in the mean change of HRQoL scores from baseline to each follow up between a mobile app and a supervised health program delivered to young adults with mobility disability. Positive associations were observed between changes in cardiorespiratory fitness over 1 year and changes in the physical role functioning, general health, vitality, and emotional role functioning domains of HRQoL. After adjusting for potential confounders, the observed associations with physical role functioning and vitality did not remain statistically significant. Moreover, stratification by intervention group resulted in associations between changes in cardiorespiratory fitness and general health and emotional role functioning, only in the supervised health program.A small number of previous studies focused on clinical populations has evaluated the effects of mobile app training on HRQoL –47. AmonAssociations between cardiorespiratory fitness and specific domains of HRQoL have been previously observed in cross-sectional studies, however showing partially inconsistent results. More specifically, a study of healthy young males that looked into the different domains of HRQoL found positive associations only with the general health domain , whereasThis study also supports previous evidence regarding the possible benefits of supervised training on HRQoL. Two studies of older adults with mobility limitations reported higher increases in general health  and emotThis study has several strengths. Most importantly, to the best of our knowledge this is the first study to compare the effects of mobile app training to supervised training on HRQoL as well as to examine the association of changes in cardiorespiratory fitness with HRQoL, in people with mobility disability. In addition, the methods chosen had several benefits. Most importantly, the randomized controlled trial study design using intention to treat analysis, was allowing to compare the effects of the two interventions on HRQoL with a very low risk for confounding as all the characteristics of the participants were randomized in each group. Moreover, studying the population longitudinally allowed us to assess whether changes in cardiorespiratory fitness were associated with changes in HRQoL on an individual level over 1-year period, accounting for possible correlations between the repeated measurements with the use of mixed effects models. Finally, cardiorespiratory fitness was estimated with a submaximal cycle ergometer test, minimizing the risk of exposure misclassification, while HRQoL was measured with a widely used questionnaire , which aNevertheless, there are also some limitations that need to be considered. A threat for the internal validity of this study is the high attrition rates. Especially when comparing the effects of the two interventions on HRQoL, it is likely that the estimates have been affected by selection bias. As the sensitivity analysis showed, higher proportion of the dropouts was from the mobile app group. Although there were no differences regarding changes in HRQoL from midpoint to the endpoint between those who attended the 1-year follow up and those who did not, it is possible that participants who did not attend the midpoint or endpoint follow up had small or negative changes. This might have led to the underestimation of the differences in the mean change of HRQoL scores between the two groups, having the supervised group as reference. Regarding the estimates of the association of changes in cardiorespiratory fitness with HRQoL, mixed effects regression models use the maximum likelihood method to handle missing data by estimating the mean values from the available data at each time point . HoweverThe generalizability of this study might have also been limited due to the high attrition rates and the exclusion criteria. Certain characteristics of the study population such as higher proportion of females than males, were representative of young adults with mobility disability living in Stockholm , 4. HoweFurther limitations of this study lay on the interpretation of the results. More specifically the sample size of the study was probably not adequate to detect differences in the effects of the mobile app compared to the supervised program on HRQoL, since it was calculated based on the primary outcome. However, equivalence of these effects cannot be implied, as such inference would require a larger sample size . FurtherMore evidence is needed regarding the effects of mobile app training on HRQoL in adults with mobility disability. Future research could include larger samples and compare these effects not only with supervised training but also with usual treatment. In addition, further studies in young adults with mobility disability are needed in order to replicate the associations between changes in cardiorespiratory fitness and HRQoL, to investigate the existence of a causal relationship, and to better understand the role of supervised training in this association.This study found positive associations between cardiorespiratory fitness and the general health and emotional role functioning domains of HRQoL in young adults with mobility disability who received supervised training. It remains unclear whether mobile app training has similar effects with supervised health programs on HRQoL in people with mobility disability. Further studies are needed to better understand these effects.


In UK Biobank (UKB), a large population-based prospective study, cases of many diseases are ascertained through linkage to routinely collected, coded national health datasets. We assessed the accuracy of these for identifying incident strokes.In a regional UKB subpopulation , we identified all participants with ≥1 code signifying a first stroke after recruitment (incident stroke-coded cases) in linked hospital admission, primary care, or death record data. Stroke physicians reviewed their full electronic patient records (EPRs) and generated reference standard diagnoses. We evaluated the number and proportion of cases that were true-positives  for all codes combined and by code source and type.Of 232 incident stroke-coded cases, 97% had EPR information available. Data sources were 30% hospital admission only, 39% primary care only, 28% hospital and primary care, and 3% death records only. While 42% of cases were coded as unspecified stroke type, review of EPRs enabled a pathologic type to be assigned in >99%. PPVs  were 79% (73%–84%) for any stroke  and 83% (74%–90%) for ischemic stroke. PPVs for small numbers of death record and hemorrhagic stroke codes were low but imprecise.Stroke and ischemic stroke cases in UKB can be ascertained through linked health datasets with sufficient accuracy for many research studies. Further work is needed to understand the accuracy of death record and hemorrhagic stroke codes and to develop scalable approaches for better identifying stroke types. It is an open-access resource, established to facilitate research into the determinants of a wide range of health outcomes, particularly those of relevance in middle and older age.3UK Biobank (UKB) is a prospective population-based cohort study with extensive phenotypic and genotypic information on >500,000 participants from England, Scotland, and Wales , compared with diagnoses assigned following adjudication by clinical experts with access to the full free-text electronic patient records (EPRs).We conducted the study in a subpopulation of 17,249 UKB participants in the Lothian region of southeast Scotland, all of whom are linked to national administrative health datasets . This region encompasses the city of Edinburgh, where one of UKB's recruitment centers was located. Within this subpopulation, we identified all those with at least one code in their linked health data that indicated a stroke diagnosis after their recruitment to UKB.5We defined stroke according to the WHO definition: “rapidly developing clinical signs of focal  disturbance of cerebral function, lasting more than 24 hours or leading to death, with no apparent cause other than that of vascular origin.”We selected and included relevant codes from hospital admission, primary care, and death records up to the end of September 2015, the date at which data were complete for all sources at the time of this study.In the United Kingdom, hospital admissions and death records are coded by specialized medical coders, who use the International Classification of Diseases  coding system to assign a primary code to the main condition resulting in a particular admitted episode of care, and secondary codes to other conditions. Primary care data are coded by general practice clinical or administrative staff during clinical encounters or on receipt of information from elsewhere .Primary care data in the United Kingdom currently use the Read coding system (version 2 in Scotland during the time period of relevance in this study).4 browsing of the Technology Reference Data Update Distribution Service (isd.hscic.gov.uk/trud3/user/guest/group/0/home), the Secure Anonymised Information Linkage databank cerebrovascular diseases dictionary,6 the Quality Outcomes Framework indicator sets for stroke , and the CALIBER online data portal , as well as manual review of code lists by experts .We selected relevant stroke codes from the ICD-10 and Read version 2 coding systems, aiming to ascertain cases of stroke with a high positive predictive value (PPV) , while aiming to ascertain as many as possible of the true cases . Our code selections were informed by the results of a systematic review,We only validated diagnoses for cases with their first incident stroke, defined as the first-ever-in-a-lifetime occurrence of a WHO-defined stroke according to codes from linked national administrative datasets. We excluded participants who self-reported a stroke at baseline recruitment or who had a stroke code in their linked health care data predating recruitment to UKB. This was because (1) incident disease cases  are of most research interest in a prospective, population-based study recruiting mainly healthy volunteers and (2) a large proportion of stroke cases identified through codes or self-reported stroke status arising prior to recruitment  predated the EPR system used for validation. We based our analyses on the earliest code(s) for each participant from any data source.dryad.org/10.5061/dryad.w9ghx3fk0). We considered information relevant if it was associated with a hospital admission leading to the code, or if it was within 2 months before or after the date of a relevant primary care code. A 2-month window was chosen to reflect local clinical practice during the time period of the study: patients in NHS Lothian with a suspected stroke or TIA not requiring hospital admission would have been referred to the neurovascular specialist outpatient clinic, where they would usually be seen within 1 week, in keeping with national guidelines .For each included participant with a stroke code, we extracted, anonymized, and created a single document (hereafter referred to as a “vignette”) from all available relevant medical information from the secondary care EPR system, including outpatient clinic letters, hospital discharge summaries, and formal radiologic investigation reports .We developed an adjudication form, which included a summary for adjudicators of criteria for the diagnosis of stroke, its pathologic types , and subtypes  completed adjudication forms based on the information in the EPR-derived vignettes. They did not have access to review the brain imaging themselves, but formal scan reports were included in the vignettes. One adjudicator (K.R.) completed the forms for all participants and 5 other adjudicators  independently completed the forms (each for a subset) to allow assessment of interadjudicator agreement. All adjudicators were blinded to which specific codes had led to ascertainment of any case and to each other's diagnoses. The first adjudicator's diagnoses were used as the reference standard for the primary analyses in this study.We summarized participants' sex and median age at recruitment and at the time the code was assigned.We calculated the number and proportion of stroke-coded participants arising from each data source. We also stratified the codes into those specifying a stroke type (ischemic vs ICH vs SAH) vs those indicating an unspecified type of stroke, and calculated the numbers and proportions of these arising from each source. We compared these findings with the same analyses for the larger subset of all UKB participants with linkage to the relevant data sources in England, Scotland, and Wales.7 to measure interadjudicator agreement, comparing one adjudicator's (K.R.) diagnoses with a second  for the following: stroke vs not; stroke/TIA vs not; and, in cases where both adjudicators agreed that the diagnosis was stroke, ischemic stroke vs ICH vs SAH vs uncertain stroke type.We used percent agreement and Cohen kappa (ĸ)The main measure of accuracy assessed in this study was PPV . While we could not directly assess sensitivity, we were able to assess the effects on both PPV and the number of true-positive cases (a higher number of true-positives indicates higher sensitivity) of different code combination strategies for ascertaining cases. We categorized the stroke-coded cases as true-or false-positives based on adjudicators' diagnoses. We calculated the PPV and its 95% confidence interval (CI) using the Clopper Pearson exact method, considering both (1) only an adjudicator diagnosis of stroke a true-positive and (2) an adjudicator diagnosis of stroke or TIA a true-positive. To understand the contribution of each source of codes, we calculated PPVs for each code source separately  and for their combinations, and explored the effect (both on PPV and on true-positive case numbers) of including only codes in the primary position for hospital admission data.We also calculated PPVs for ischemic and hemorrhagic stroke types, and explored the effect (both on PPV and on true-positive case numbers) of restricting hospital data to codes in the primary position and of treating all unspecified stroke type codes as ischemic stroke codes.4 We refer to this as the administrative accuracy of the code. Clinicians will, however, appreciate that assessing the accuracy of a diagnostic code is more nuanced. A patient's true diagnosis may emerge over time after encounters with several different clinicians with varying levels of expertise and with access to different amounts of relevant information; hence, the EPR can contain inconsistencies, which may require specialist clinical knowledge to detect and/or resolve. Hence a specialist physician's review of all relevant parts of the complete EPR will give a more accurate picture of the true diagnosis and so of the code accuracy, which we refer to as the overall accuracy. We assessed administrative accuracy by having a primary care physician in our team review the EPR-derived vignettes for mentions of stroke diagnoses. We assessed overall accuracy by having expert adjudicators  review the EPR-derived vignettes and derive reference standard diagnoses based on all available information and their clinical interpretation of this information (see Process of assigning an expert diagnosis). We then assessed whether, and by how much, the administrative vs overall accuracy (PPV) differed for our selected stroke codes.In further analyses, we assessed administrative vs overall code accuracy and the effect on resulting PPVs, as we hypothesized that this may explain some of the variability of the results among previous validation studies. Some validation studies are based on the assumption that if the diagnostic code reflects the diagnosis mentioned somewhere in the EPR , then this is sufficient to confirm the accuracy of the code.r-project.org).We performed all statistical analyses in R  and more detailed subtype by the stroke specialist adjudicator, and their frequency distributions.All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. As part of the UKB recruitment process, informed consent was obtained from all individual participants included in the study.ukbiobank.ac.uk).Anonymized summary data based on this study not published within this article can be shared  on request from any qualified investigator unless limited by ethical or legal restrictions. Any bona fide researcher can access the UKB resource for research that aims to benefit the public's health  had available information in their EPR to create a vignette and were included in the study analyses .Of the 225 stroke-coded cases, 111 (49%) were female. Median age at recruitment to UKB was 63 years (range 41–70 years) and at time of the stroke code was 67 years (range 45–76 years) .dryad.org/10.5061/dryad.w9ghx3fk0). For the larger subset of all UKB participants with linkage to the relevant data sources, these proportions were similar for Scotland, but a higher proportion of participants in England and Wales had hospital-only codes  received a code from hospital admission data only, 87 (39%) from primary care data only, 64 (28%) from both hospital admission and primary care data, 6 (3%) from death records only, and one from both hospital admission data and death records (ly codes .dryad.org/10.5061/dryad.w9ghx3fk0). Among the larger subset of all UKB participants with relevant linked data, the proportion of cases with an unspecified stroke code was similar for Scotland, but lower for England and Wales   of stroke-coded cases had a stroke type-specific code , while the remaining 94 (42%) had unspecified stroke codes. The proportion of cases with unspecified stroke type codes was higher among those ascertained from primary care (105/151 [70%]) than from hospital admission data (38/132 [29%]), and all death record codes were stroke-type specific  (ctively) .All vignettes were independently reviewed by 2 adjudicators. For assigning a diagnosis of stroke vs not, interadjudicator agreement was 91% and Cohen kappa very good at 0.7 ; for stroke/TIA vs not, agreement was 93% and Cohen kappa very good at 0.7 . Agreement for assigning a stroke type (ischemic stroke vs ICH vs SAH vs uncertain stroke type) was 99% and Cohen kappa excellent at 0.98 .The overall PPV of case ascertainment for all 225 stroke-coded cases from all sources combined was 79% . When broken down by code source, PPV was highest for the 132 cases with hospital admission codes , and higher still when limiting analyses to primary position hospital codes only , at the expense of losing a few (<10%) true-positive cases. PPV for the 151 cases with primary care codes was 80% . Only 7 cases had death record codes, with PPV 57% , the wide CIs indicating limited precision of this estimate. For cases with both a hospital admission and a primary care code, PPV was very high , but only a third of the cases fell into this category .As regards the accuracy of identifying stroke pathologic type , PPV among the 88 participants with an ischemic stroke code was 83% ; restricting to primary position codes  increased this to 86% , with loss of <10% of true-positive cases . Given tPPV when measuring only administrative accuracy was 93%, decreasing to 79% when measuring overall accuracy. This demonstrates the importance of expert-led adjudication in validation studies, as ignoring it would lead to falsely inflated PPVs .The 47 false-positive stroke-coded cases had a similar proportion of unspecified codes and median age (at date of recruitment or first stroke code) as true-positives. False-positive cases were more likely to have a primary care code and to have died by the end of follow-up, and were slightly more likely to be female, to have a hemorrhagic stroke code, and to have an earlier first stroke code date .Alternative diagnoses for the 47 false-positives included TIA ; secondary intracranial bleed not due to SAH or ICH  (11/47 [23%]); radiologic finding of a suspected old vascular lesion  (8/47 [17%]); and possible or probable alternative diagnosis  (14/47 [30%]).Among the 15 participants with a false-positive ICH code, 7/15 had another primary stroke type ± secondary ICH, 4/15 intratumor bleed, 3/15 traumatic or other intracranial bleed, and 1/15 no obvious reason for an ICH code. Among the 7 participants with a false-positive SAH code, 4/7 were traumatic intracranial bleed, 2/7 another primary stroke type ± secondary SAH component, and 1/7 asymptomatic aneurysm.Because performance for hemorrhagic stroke codes was suboptimal, having observed that the more common alternative diagnoses were traumatic and intratumor bleeds or stroke complicated by a bleed, we performed additional analyses to explore the effects of different code inclusion criteria on numbers of cases, numbers of true-positives, and PPV for ICH and SAH. For both ICH and SAH, we could increase PPV but at the expense of failing to detect some true-positive cases. However, numbers of cases were too small to draw firm conclusions .dryad.org/10.5061/dryad.w9ghx3fk0).With information from the EPR, a stroke specialist was able to assign a pathologic stroke type to 177 of the 178 true-positive stroke cases: 149 (84%) were ischemic, 11 (6%) ICH, and 17 (10%) SAH. Depending on the subclassification system used, an ischemic subtype could be determined for 37%–87% of cases, an ICH subtype for 27%–100% of cases, and SAH subtype for 94% of cases  may give falsely inflated PPVs.8 UKB is primarily used for research into the genetic and nongenetic determinants of disease.3 In such analyses, it is important to ensure that a high proportion of participants identified as disease cases truly do have the disease (high PPV) to minimize bias in effect estimates, while aiming to optimize statistical power by ascertaining as many true-positive cases as possible . A high specificity (the proportion of participants without the disease that do not receive a stroke code) is crucial in obtaining a high PPV, but is not sufficient in and of itself. In population-based prospective cohorts where the proportion of all participants who are true-positives for the disease (in this case stroke) is generally low, the proportion of all participants incorrectly classified as having stroke  will generally be low (giving high specificity), even if the absolute number of false-positives is high compared to the absolute number of true-positives (low PPV).8 Providing appropriate codes are used, both the specificity and negative predictive value of routinely collected health care data to identify disease cases in population-based studies are usually very high (96%–100%).4 For these reasons, we focused on estimating the PPV of using routinely collected health care data to identify stroke cases in UKB, and on assessing the effects of different code and source selections on both PPV and number of true-positive cases.Acceptable levels of accuracy, and the relative importance of different accuracy metrics, depend on the context.Strengths of this study include (1) the overall large number of participants; (2) inclusion of primary care and death record codes for which accuracy data have previously been limited; (3) creation of vignettes using preset criteria from the EPR for 97% of otherwise eligible stroke-coded cases, thus avoiding the bias of selecting participants with a higher prior probability of having had a stroke; (4) blinding of adjudicators to codes and each other's diagnoses; (5) assessment of interadjudicator reliability; (6) further analysis of false-positive codes; and (7) assessment of both administrative and overall accuracy, demonstrating the importance of an expert-led reference standard in validation studies.There are some limitations: (1) small numbers precluded robust conclusions about the accuracy of death record and hemorrhagic stroke codes; (2) our lack of access to the full free text EPRs held exclusively by the primary care system may have led to slightly more conservative PPV estimates , as almost all stroke cases have acute inpatient or outpatient management in secondary care (in keeping with this is that we were able to find secondary care records for 97% of the cases) and information provided from primary to secondary care was available in the hospital EPR; (3) the potential difficulty in differentiating between definite false-positive and uncertain cases from retrospective review of medical records, which may have further reduced the estimated PPVs; and (4) the restriction of the current study to a Scottish subpopulation of the UKB participants .9 would not be readily ascertained by the linked, coded health care data sources used to follow the health of UKB participants, but can be detected through brain imaging conducted as part of the UKB multimodal imaging study of 100,000 of its participants.The present study is limited to validating the accuracy of codes for symptomatic stroke (as defined by the WHO). Subclinical cerebrovascular disease (such as that detected by brain imaging), which is more common, particularly in older people,4 where PPVs for stroke-specific ICD-10 hospital admission codes ranged from 79% to 83%,11 and for ischemic stroke from 86% to 88%.13 Our results for ICH and SAH code accuracy among a small number of participants were worse than those from the 2 previous United Kingdom–based studies of ICD-10 or Read codes.14 This may be in part because these studies checked only (or mainly) for administrative accuracy, hence inflating the PPVs. Our results were similar to a Danish study, which also used an expert review of medical records to check for overall accuracy.10 To our knowledge, there are no previous validation studies of stroke-specific UK primary care Read codes or death record codes for diagnosis of all types of stroke, nor of the effect of combining primary care and hospital admission coded data.These results are largely consistent with those from our earlier systematic review,Further work will be required to further explore the accuracy of hemorrhagic stroke and death record codes in larger numbers of cases by expanding this work to other UKB recruitment locations, which will also enable assessment of the generalizability of these results to other regions of the United Kingdom. In our Scottish subpopulation, while over one-third of the codes were not specific for a stroke type, expert adjudication allowed a stroke type to be assigned for almost all cases. Future studies should investigate ways of automating this process, as well as methods for determining more detailed stroke subtypes.Our results suggest that stroke and ischemic stroke cases in UKB can be identified through linked coded data with sufficient accuracy for many genetic and epidemiologic studies, while there are currently insufficient data to draw definite conclusions about the accuracy of hemorrhagic stroke codes.


P < 0.0001; 6 months, r = 0.59, P < 0.0001; 12 months, r = 0.62, P < 0.0001) and between the PD at 1 month and retinal sensitivity at 12 months . Unlike in areas that showed a mild to moderate decline in PD, retinal sensitivity in areas where the decrease in PD was severe at baseline did not show significant improvement with treatment over time. These findings suggest that the PD value measured using optical coherence tomography angiography at or soon after the baseline can predict retinal sensitivity after 1 year of anti-VEGF treatment.In this study, we investigated the longitudinal correlation between macular sensitivity and perfusion density (PD) in retinas affected by branch retinal vein occlusion. Retinal sensitivity was measured using microperimetry and PD was measured by optical coherence tomography angiography. We also investigated the possibility that the PD, 1 month after anti-vascular endothelial growth factor (VEGF) treatment, is a predictor of retinal sensitivity after 1 year of successful macular oedema management with anti-VEGF. The correlation between measurements of retinal sensitivity and PD at baseline (1 M) and at 6 and 12 months were investigated. There was a significant positive correlation between retinal sensitivity and PD at all time points (baseline (1 M), r = 0.67,  One subtype is the branch retinal vein occlusion (BRVO), which is thought to be caused by thrombosis at the level of the branch retinal vein where it is crossed by a sclerotic artery4. Occlusion of this vein leads to disturbance of haemodynamics and vascular autoregulation, resulting in retinal haemorrhage, venous dilatation, macular oedema, serous retinal detachment, and intraocular neovascularisation6.Retinal vein occlusion (RVO) is a common cause of retinal vascular disease. It can be classified according to the anatomical location and retinal ischaemia and has multiple predisposing and precipitating factors9.In approximately 80% of cases, BRVO is accompanied by macular oedema. One-third of patients show spontaneous resolution of macular oedema; however, if left untreated, BRVO can cause permanent impairment of vision in the residual patients11. Several anti-VEGF agents are available to attenuate this pathology and can significantly reduce macular oedema and improve vision14. The effectiveness of ranibizumab has been confirmed in several studies, including BRAVO study15.Although the underlying cause of macular oedema has not been clearly established, some hypotheses have been advocated. Accumulation of fluid in macular oedema seems to be associated with a response to vascular endothelial growth factor (VEGF) derived from the hypoxic retinal tissue17. OCTA is also more useful than the fluorescein angiography which has a limited ability to capture the topography and condition of the vessels accurately, not only because of the intraretinal haemorrhages during the acute stage of the disease but also due to the fluorescein dye leakage18. OCTA has enabled clinicians to determine macular vessel density in the superficial and deep retinal layers, and to quantitatively evaluate the areas with microvascular dropout at any stage of the disease20.Non-invasive diagnostic tools, including the optical coherence tomography angiography (OCTA), have been developed to allow us to perform an instant three-dimensional vascular mapping of the retina and choroidal vascularisation without the need for dye injection21. In a study using fluorescein angiography, retinal sensitivity was lower in the retinal non-perfusion areas22. If the macular vascular density measured by OCTA at an early stage of treatment can predict retinal sensitivity after treatment, it would be useful for explaining the prognosis to patients when starting the treatment. In this study, the retinal sensitivity and vessel density were compared in a point by point manner, but not as an overall average of the affected retina by BRVO. Their longitudinal correlation was investigated in the affected retina where macular oedema was well treated by anti-VEGF injections. We also investigated whether vessel density measured by OCTA at the beginning of treatment showed a correlation with macular sensitivity after one year of treatment.It has been reported that ranibizumab improves overall retinal sensitivity in the affected retina as well as visual acuity in patients with BRVOThe final study group comprised of 4 men and 4 women aged 61–80 years. The 12 months mean number of ranibizumab injection was 4.4. Mean baseline retinal sensitivity was 9.6 dB and the perfusion density (PD) at 1 month after treatment was 28% . In contrast, when compared to the baseline, the moderate and mild groups showed a significant improvement in the retinal sensitivity after 6 months  and 12 months , the survival of retinal neuronal cells depends on the oxygen and nutrients in the oedema fluid that consists of serum leaked from remaining capillaries. Anti-VEGF treatment reduces macular oedema and improves vision, but this may also cause more damage to the retinal neuronal cells in the area where PD is low. Thus, overall retinal sensitivity improved in the affected area, but the point by point evaluation shows that the retinal sensitivity remains low in the area with low PD. If the oxygen supply from the retinal circulation is impaired and neuronal cells are damaged, the retinal sensitivity will not improve even if oedema and haemorrhage are resolved.Provided that anti-VEGF treatment is available for a patient with BRVO and that macular oedema can be successfully suppressed, it is likely that there would be a correlation between retinal sensitivity at 12 months and PD evaluated one month after the first anti-VEGF injection when investigated in a point-by-point manner.27, were not investigated. Hayreh et al. reported that the prognosis of visual acuity differs between macular BRVO and major BRVO so that they are different entities, therefore, in this study only patients with major BRVO were enrolled28. In addition, the average retinal thickness in the measurement points where PD and retinal sensitivity were evaluated could not be measured in this experiment due to the limitations of the function of the measuring device. Therefore, the relationship between the retinal thickness and the PD or retinal sensitivity was not evaluated in a point-by-point manner. The investigation of the correlation between the haemorrhage and retinal sensitivity or between oedema and sensitivity was also not feasible.The limitations of this study are that only the eyes with major BRVO were included and that the number of patients was small. Other subtypes, including macular BRVO and BRVO that occurs in the optic disc29. In addition to the treatment of retinal oedema and haemorrhage, development of a treatment to improve macular perfusion itself is warranted in future research.OCTA evaluation of the foveal circulation using PD would be useful when explaining the vision prognosis to the patients since foveal sensitivity directly correlates with the central vision. As this study lacked controls, we cannot exclude the possibility of the natural/spontaneous healing; however, we observed an overall retinal sensitivity improvement after anti-VEGF treatment independent of the retinal perfusion improvement. In the future, substances that have the potential to induce reperfusion or physiologic retinal neovascularization into the nonperfusion areas may become therapeutic targets30. At 6 and 12 months, macular oedema was absent in all patients. The study was approved by the Shinshu University Institutional Review Board for Clinical Research and carried out in accordance with the tenets of the Declaration of Helsinki. Informed consent was obtained from all study participants.Patients with major BRVO who were treated at Shinshu University Hospital in 2017–2018, had MP3 measurement points recorded in the affected temporal region within 10 degrees of the fovea, and visited each month for 1 + pro re nata (PRN) intravitreal injections of ranibizumab 0.5 mg/0.05 ml  were identified and enrolled in the study. Patients with macular BRVO, who refused the injection, who failed to fulfil the monthly visit requirement, who had any ocular or periocular inflammation, and with artefacts in OCTA images precluding clear visualisation of the vessel were excluded. The foveal thickness was measured using OCT  as the average thickness of the retina in the 1 mm circle centred on the foveolar. After the first injection, ranibizumab was administered when the foveal thickness was found to be ≥300 μm measured by OCT at the time of a visit and when it increased by 20% over the thinnest foveal thickness. Swept-source OCTA  was performed, and the retinal sensitivity  for retinal sensitivity was measured at the time of the first injection and 6 and 12 months later. As described in the previous report, the baseline used for OCTA was one month after injection32, the PD was calculated for an area of 600 μm × 600 μm around each of the 17 measurement points of MP3 in the affected temporal region  Fig. . After tion Fig. . The PD 33. After obtaining the sensitivity response, this machine acquires a colour fundus photograph then automatically superimposes these 2 sets of data into 1 image . A two-tailed p-value <0.05 was considered statistically significant.Supplementary Figure.


Insufficient insulin secretion is a key component of both type 1 and type 2 diabetes. Since insulin is released by the islets of Langerhans, obtaining viable and functional islets is critical for research and transplantation. The effective and efficient isolation of these small islands of endocrine cells from the sea of exocrine tissue that is the rest of the pancreas is not necessarily simple or quick. Choosing and administering the digestive enzyme, separation of the islets from acinar tissue, and culture of islets are all things that must be considered. The purpose of this review is to provide a history of the development of islet isolation procedures and to serve as a practical guide to rodent islet research for newcomers to islet biology. We discuss key elements of mouse islet isolation including choosing collagenase, the digestion process, purification of islets using a density gradient, and islet culture conditions. In addition, this paper reviews techniques for assessing islet viability and function such as visual assessment, glucose-stimulated insulin secretion and intracellular calcium measurements. A detailed protocol is provided that describes a common method our laboratory uses to obtain viable and functional mouse islets for in vitro study. This review thus provides a strong foundation for successful procurement and purification of high-quality mouse islets for research purposes.The online version contains supplementary material available at 10.1186/s12575-021-00143-x. In early 1869, with his mention of “small cells of almost perfect homogeneous content, and of perfect polygonal form … lying together in twos or in small groups,” , 3. At t It was hypothesized that the exocrine tissue would impair the vitality and function of the endocrine pancreas , 6. In 1Figure Islet isolation was pioneered in a very narrow range of species, specifically guinea pigs , 27, 28 The primary goal of islet isolation, whether for in vitro studies or for transplantation, is to obtain purified islets that are both viable and responsive to stimulation in a manner consistent with their function in vivo. To this end, we highlight three key elements of a successful islet isolation procedure: 1) Digesting the tissues connecting the islets to the exocrine tissue, 2) separating islets from non-islet tissue, and 3) culturing islets in an environment that maintains viability and function  i) in response to glucose or other stimuli [2+]i including fluo-3, fluo-4, and fura red. Improved versions of some of these fluorophores have reduced leakage and photobleaching [Another important method to assess islet function is measuring changes in intracellular calcium  as a means to record and compare test groups side-by-side with control groups of islets. The basic approach was first described by Corbin et al. [2+]i signal from all islets is imaged (G). Data sets can be separated based on the red fluorescence image, with islets that are not visible belonging to the well 1 control and islets with red fluorescence belonging to the well 2 test condition.To extend the value of [Can et al.  and is s2+]i traces from a set of islets that were isolated from a diabetic db/db mouse and loaded with CTR and Fura-2. In Fig. 2+]i traces from the heterozygous controls that were loaded with Fura-2 only. As shown in Fig. 2+]i [2+]i responses to glucose stimulation. Although [Ca2+]i can be a convenient and insightful indicator of islet health and function, it is important to also measure insulin secretion due to many facets of the insulin secretory pathway that are separate from changes in [Ca2+]i [This CTR-labeling approach is displayed in Fig. ig. 2+]i  by exami [Ca2+]i –128.FigAs stated previously, islet isolation is an intricate process, but the ability to consistently procure viable and functional islets is crucial to effectively study the physiology and pathophysiology of islets. In this review, we have addressed the key factors to consider in both the isolation and assessment processes to obtain healthy islets. We provide a method of isolation developed by integrating the reports of many others in the research field with careful experimentation to optimize the islet isolation process for our laboratory. While this protocol provides a start for islet isolation, any procedure must be optimized to the capabilities of the laboratory and the specific goals of the study.Additional file 1: Supplemental Fig. S1 Hypoxic cell death as an unwanted variable in PI/AnnV studies. Due to loss of vascular connection during isolation, islets can become severely hypoxic, resulting in necrosis, especially in the core of an islet. Identifying and removing such islets from experiments helps in acquiring accurate data. (A) Brightfield image of untreated (control) islets (top) and cytokine-treated islets . The smaller islets in both images have no evidence of hypoxia while the larger islets have clearly defined dark centers. (B) All cytokine treated islets show a distinct ring of AnnV staining indicative of cytokine-induced apoptosis on the outermost layer of cells. Note the dark centers do not stain for AnnV. (C) PI staining showing both cytokine -associated and hypoxia-associated cell death. The only islet in the control showing PI staining is the large, dark centered islet while the cytokine treated islets show both cytokine-induced and hypoxia-associated cell death. The small cytokine treated islets on the left show several distinct punctate PI- stained nuclei typical of cytokine effects. The larger islets show varying degrees of punctate surface staining indicative of cytokine-induced cell death, but a large central mass of PI staining corresponding to the dark centers observed in the brightfield image.