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Phenome-wide association of physical activity with morbidity and mortality risk in China: A prospective cohort study.
Research in high-income countries has established the health benefits of physical activity (PA), but evidence from low- and middle-income countries, including China, where PA patterns vary from those in high-income countries, remains limited. Moreover, previous research, mainly focused on specific diseases, failing to fully capture the health impacts of PA. We investigated the associations of PA with 425 distinct diseases and 53 causes of death using data from 511,088 participants aged 30-79 years in the China Kadoorie Biobank. Baseline PA was assessed using a questionnaire between 2004 and 2008, and usual PA levels were estimated using the resurvey data in 2013-2014. Cox regression was employed to estimate the associations between PA and outcomes, adjusting for potential confounders. During a median follow-up time of 12 years, 722,183 incident events and 39,320 deaths were recorded across 18 chapters of the International Classification of Diseases, 10th Revision (ICD-10). Total PA was significantly and inversely associated with incidence risks of 14 ICD-10 chapters, specifically 65 diseases and 19 causes of death, with the highest quintile group of PA showing a 14% lower disease incidence and 40% lower all-cause mortality compared with the lowest group. Of these diseases, 54 were not highlighted in World Health Organization PA guidelines. Dose-response analyses revealed L-shaped associations for most PA types, except moderate-to-vigorous intensity PA, which showed a U-shaped relationship. In this population, physical inactivity accounted for 12.8% of PA-related deaths. The findings underscore the broad health benefits of PA across a variety of body systems and the significant disease burden due to inactivity in China, highlighting the urgent need for PA promotion.
Translational genomics of osteoarthritis in 1,962,069 individuals.
Osteoarthritis is the third most rapidly growing health condition associated with disability, after dementia and diabetes1. By 2050, the total number of patients with osteoarthritis is estimated to reach 1 billion worldwide2. As no disease-modifying treatments exist for osteoarthritis, a better understanding of disease aetiopathology is urgently needed. Here we perform a genome-wide association study meta-analyses across up to 489,975 cases and 1,472,094 controls, establishing 962 independent associations, 513 of which have not been previously reported. Using single-cell multiomics data, we identify signal enrichment in embryonic skeletal development pathways. We integrate orthogonal lines of evidence, including transcriptome, proteome and epigenome profiles of primary joint tissues, and implicate 700 effector genes. Within these, we find rare coding-variant burden associations with effect sizes that are consistently higher than common frequency variant associations. We highlight eight biological processes in which we find convergent involvement of multiple effector genes, including the circadian clock, glial-cell-related processes and pathways with an established role in osteoarthritis (TGFβ, FGF, WNT, BMP and retinoic acid signalling, and extracellular matrix organization). We find that 10% of the effector genes express a protein that is the target of approved drugs, offering repurposing opportunities, which can accelerate translation.
Refined selection of individuals for preventive cardiovascular disease treatment with a transformer-based risk model.
BACKGROUND: Although statistical models have been commonly used to identify patients at risk of cardiovascular disease for preventive therapy, these models tend to over-recommend therapy. Moreover, in populations with pre-existing diseases, the current approach is to indiscriminately treat all, as modelling in this context is currently inadequate. This study aimed to develop and validate the Transformer-based Risk assessment survival (TRisk) model, a novel deep learning model, for predicting 10-year risk of cardiovascular disease in both the primary prevention population and individuals with diabetes. METHODS: An open cohort of 3 million adults aged 25-84 years was identified using linked electronic health records from 291 general practices, for model development, and 98 general practices, for validation, across England from 1998 to 2015. Comparison against the QRISK3 score and a deep learning derivation of it was done. Additional analyses compared discriminatory performance in other age groups, by sex, and across categories of socioeconomic status. FINDINGS: TRisk showed superior discrimination (C index in the primary prevention population 0·910; 95% CI 0·906-0·913). TRisk's performance was found to be less sensitive to population age range than the benchmark models and outperformed other models also in analyses stratified by age, sex, or socioeconomic status. All models were overall well calibrated. In decision curve analyses, TRisk showed a greater net benefit than benchmark models across the range of relevant thresholds. At the widely recommended 10% risk threshold and the higher 15% threshold, TRisk reduced both the total number of patients classified at high risk (by 20·6% and 34·6%, respectively) and the number of false negatives as compared with recommended strategies. TRisk similarly outperformed other models in patients with diabetes. Compared with the widely recommended treat-all policy approach for patients with diabetes, TRisk at a 10% risk threshold would lead to deselection of 24·3% of individuals, with a small fraction of false negatives (0·2% of the cohort). INTERPRETATION: TRisk enabled a more targeted selection of individuals at risk of cardiovascular disease in both the primary prevention population and cohorts with diabetes, compared with benchmark approaches. Incorporation of TRisk into routine care could potentially reduce the number of treatment-eligible patients by approximately one-third while preventing at least as many events as with currently adopted approaches. FUNDING: None.
Acceptability of improved cook stoves-a scoping review of the literature.
Improved cooking stoves (ICS) are intended to reduce indoor air pollution and the inefficient use of fuel yet there is often reticence to shift permanently to ICS. Drawing on a scoping review, this article aims to provide a comprehensive overview of factors affecting the acceptability of ICS. A scoping review was carried out using a systematic search strategy of literature. All articles identified in three major databases that included Pubmed/Medline, Scopus and Web of Science underwent screening followed by content analysis to generate major and minor themes using a structured social level analysis. The analysis identified factors at micro, meso, and macro-social levels that potentially contribute to an adoption of an improved cooking stove (ICS). The findings from the review were discussed and refined among a group of experts identified based on their prior academic or commercial contributions related to ICS. Adoption of ICS was dependent on functional outputs (e.g. cleanliness, and cooking efficiency) while meeting local social and cultural demands (e.g. cooking large meals, traditional meals, and taste). Health and cost benefits played an important role in the adoption and sustained use of ICS. The adoption of ICS was enabled by use among neighbors and other community members. Sustained use of ICS depended on fuel supply, fuel security and policies promoting its use. Policies offering subsidies in support of supply-chain garnered institutional trust among community members and resulted in the sustained use of ICS. In addition to design attributes of ICS that could meet both scientific and social demands, policies supporting promotion of clean energy, subsidies and supplies can substantially enhance the adoption of ICS.
Genetic Risk and Prognosis of the First Incident Stroke Survivors: Findings from China Kadoorie Biobank and UK Biobank.
BACKGROUND AND OBJECTIVES: Stroke is known for its poor prognosis. Although genetic instruments have shown promise in stratifying first stroke risk in the general population, it is unknown whether they are associated with stroke prognosis. Our study aims to explore the role of genetic risk of stroke in the progression from stroke-free to first stroke and then to recurrent stroke, subsequent coronary heart disease (CHD), and death in China and the United Kingdom. METHODS: We used data from 2 prospective population-based cohorts, China Kadoorie Biobank (CKB) and UK Biobank (UKB). Participants who were unrelated and free of stroke and CHD at baseline were included. Genetic risks of stroke were quantified using integrative polygenic risk scores (iPRSs), which incorporated summary statistics from multiple genome-wide association studies for stroke outcomes and its subtypes, and vascular-risk traits. We used a multistate model to analyze the roles of genetic risk in the transitions from baseline to first incident stroke and then to recurrent stroke, subsequent CHD, and death. RESULTS: Our study included 80,908 CKB participants and 380,348 UKB participants, with mean ages (% female) of 54.0 years (58.6%) and 56.1 years (55.4%). During median follow-ups of 11.9 years and 13.4 years in the CKB and UKB, respectively, 13,481 and 5,772 participants had their first stroke, neither experienced a CHD, or died within 28 days. These survivors had 5,707 and 943 recurrent strokes, as well as 1,196 and 418 CHD events, respectively. iPRSs were associated with recurrent stroke and CHD among stroke survivors in both populations. The corresponding hazard ratios (HRs) and 95% CIs per SD of iPRSs were 1.08 (1.05-1.11) and 1.08 (1.02-1.15) in CKB and 1.11 (1.03-1.19) and 1.23 (1.10-1.37) in UKB, respectively. There was no association between iPRSs and mortality risk. When we further divided the first stroke into 4 pathologic subtypes, both populations revealed statistically significant associations between iPRSs and the transitions from first ischemic stroke to recurrent stroke and CHD. DISCUSSION: Our study shows that the genetic risk of first stroke also influences the prognosis of stroke survivors, indicating that PRS has the potential to improve stroke prognosis.
Risk thresholds for soft versus hard cardiovascular disease outcome models for initiating statin therapy among Chinese adults: a cost-utility analysis.
BACKGROUND: Current guidelines for atherosclerotic cardiovascular disease (ASCVD) primary prevention mostly recommend risk scores that predict risk of non-fatal myocardial infarction, fatal ischemic heart disease (IHD), and fatal or non-fatal ischemic stroke (hard outcomes), ignoring the burden from other non-fatal IHD outcomes. We explored the optimal risk thresholds for statin initiation using non-laboratory-based soft and hard ASCVD outcome models and compared the cost-utility of such models in the Chinese population. METHODS: We constructed Markov cohort models to estimate the incidence of ASCVD events, costs, and quality-adjusted life years (QALYs) over a lifetime from a social perspective. The simulation cohort was constructed using data from the China Kadoorie Biobank (CKB). Input data included cost, utility, statin efficacy, and other parameters were derived from published literature. We used CKB-ASCVD models to predict 10-year risk and different risk thresholds to guide statin initiation. The incremental cost-effectiveness ratio (ICER) was estimated as cost per QALY gained. Sensitivity analyses were performed to explore the uncertainty in the models. RESULTS: The optimal risk threshold was 18% for the soft ASCVD model and 10% for the hard ASCVD model, with ICERs of $7013.48/QALY and $6540.71/QALY, respectively. The optimal thresholds were robust in stratified analyses by region and sex, and one-way sensitivity analyses over a wide range of input parameters. Probabilistic sensitivity analyses showed that these optimal thresholds had around 70% chance of being cost-effective. When analyzed by age group, above optimal thresholds were cost-effective in adults aged 30-59 years but not in those aged 60-75 years. The threshold strategies based on soft ASCVD model were mostly cost-saving compared with those based on hard models to treat the same proportions of the population. CONCLUSIONS: The risk threshold of 18% for soft ASCVD model and 10% for hard ASCVD model have acceptable cost-utility profiles in the Chinese population. The soft ASCVD model is more cost-effective than the hard model and should be used as a screening tool for ASCVD primary prevention.
A systematic review of evidence regarding the association between time to mobilization following hip fracture surgery and patient outcomes.
AIMS: Performance indicators are increasingly used to evaluate the quality of healthcare provided to patients following a hip fracture. In this systematic review, we investigated the association between 'early mobilization' after surgery and patient outcomes. METHODS: Evidence was searched through 12 electronic databases and other sources. The methodological quality of studies meeting the inclusion criteria was assessed. The protocol for this suite of related systematic reviews was registered at PROSPERO: ID = CRD42023417515. RESULTS: A total of 24,507 articles were reviewed, and 20 studies met the inclusion criteria for the review, involving a total of 317,173 patients aged over 60 years with a hip fracture. There were two randomized clinical trials, five prospective studies, and 13 retrospective cohort studies, conducted between January 1981 and June 2022. All but two studies came from high-income healthcare systems. The definition of early mobilization varied across studies and health systems; and weightbearing status was often not reported or ambiguously defined, making formal meta-analysis of the data impossible. Early mobilization (within 48 hours of surgery) was associated with improved outcomes in 29 of the 33 patient-reported outcomes, including improved mobility scores and improved assessments of daily activities of living. A total of 45 out of 51 clinical outcomes derived from hospital records showed a positive association with early mobilization, including reduced rates of postoperative complications, reduced length of acute hospital stay, and lower mortality. CONCLUSION: Early mobilization after surgery for hip fracture in older people is associated with improved patient-reported outcomes and reduced length of hospital stay. Standardization of the definition of early mobilization and consistent reporting of weightbearing status would improve future evidence synthesis.
Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011-2022: a modelling study.
BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne viral hemorrhagic fever with expanding geographical range. The determinants of the seasonal dynamics of SFTS remain poorly understood. METHODS: Monthly SFTS cases from 604 counties in five provinces with high-notification rate in China (2011-2022) were analyzed using hierarchical Bayesian spatiotemporal and distributed lag nonlinear models. Cumulative and month-specific effects of meteorological factors were assessed, with socioeconomic factors as modifiers. FINDINGS: The cumulative effect peaked at 21.97 °C (RR = 1.24, 95% CI: 1.10-1.40) and the month-specific effect peaked at 25.67 °C (RR = 1.38, 95% CI: 1.26-1.51) without time lag. Increased precipitation significantly amplified the risk of SFTS with a notable lag effect observed. Both drought and wet conditions heightened the risk of SFTS occurrence substantially, with cumulative RR peaking at 3.13 (95% CI: 1.58-6.23) for Standardized Precipitation Evapotranspiration Index (SPEI-1) of -2.5, indicating drought conditions, and peaking at 1.51 (95% CI: 1.00-2.27) for SPEI-1 of 2.16, indicating wet conditions. The highest month-specific RR was observed at an SPEI-1 of -2.5 with a 2-month lag and at 1.81 with a 1-month lag, respectively. The risk of SFTS was higher in low-urbanization areas during drought, while was higher in high-urbanization areas with wet conditions. INTERPRETATION: Climatic factors significantly influence SFTS dynamics, with socioeconomic conditions modifying these effects. Integrating climate factors into surveillance and early warning systems is essential for targeted prevention and control. FUNDING: National Natural Science Foundation of China (No. 82330103 and No. 42201497), Youth Innovation Promotion Association (No. 2023000117), and the Wellcome Trust [220211].
Long-term exposure to fine particulate matter interacting with individual conditions increase breast cancer incidence: a large-scale Chinese cohort
Background: Breast cancer is the most frequently diagnosed malignancy among women worldwide. This study aimed to investigate the impact of long-term fine particulate matter (PM2.5) exposure on breast cancer incidence in a cohort of 281,152 women from the China Kadoorie Biobank who were initially free of breast cancer. Results: PM2.5 concentrations were estimated using a high-resolution satellite-based model, and breast cancer cases were ascertained through national databases. Over a median follow-up of 11.12 years, 2393 new breast cancer cases were reported. Analyses using Cox proportional hazard and restricted cubic spline models demonstrated a non-linear association between PM2.5 exposure and breast cancer incidence, with a marked increase in risk observed once PM2.5surpassed 53.6 μg/m3. For every 10 μg/m3 increase in PM2.5, the hazard ratio for breast cancer incidence was 1.07 (95% confidence interval: 1.03–1.12). Furthermore, interactions were noted between PM2.5, physical activity, and life satisfaction, indicating that high pollution levels may diminish the protective benefits of exercise and positive psychological well-being. Conclusions: These findings highlight the need for stringent air pollution control measures and underscore the importance of integrated strategies that consider environmental, lifestyle, and psychological factors to reduce the burden of breast cancer.
The time-dependent reproduction number for epidemics in heterogeneous populations.
The time-dependent reproduction number [Formula: see text] can be used to track pathogen transmission and to assess the efficacy of interventions. This quantity can be estimated by fitting renewal equation models to time series of infectious disease case counts. These models almost invariably assume a homogeneous population. Individuals are assumed not to differ systematically in the rates at which they come into contact with others. It is also assumed that the typical time that elapses between one case and those it causes (known as the generation-time distribution) does not differ across groups. But contact patterns are known to widely differ by age and according to other demographic groupings, and infection risk and transmission rates have been shown to vary across groups for a range of directly transmitted diseases. Here, we derive from first principles a renewal equation framework which accounts for these differences in transmission across groups. We use a generalization of the classic M'Kendrick-von Foerster equation to handle populations structured into interacting groups. This system of partial differential equations allows us to derive a simple analytical expression for [Formula: see text], which involves only group-level contact patterns and infection risks. We show that the same expression emerges from both deterministic and stochastic discrete-time versions of the model and demonstrate through simulations that our [Formula: see text] expression governs the long-run fate of epidemics. Our renewal equation model provides a basis from which to account for more realistic, diverse populations in epidemiological models and opens the door to inferential approaches which use known group characteristics to estimate [Formula: see text].
Medium-term effects of SARS-CoV-2 infection on multiple vital organs, exercise capacity, cognition, quality of life and mental health, post-hospital discharge
AbstractBackgroundThe medium-term effects of Coronavirus disease (COVID-19) on multiple organ health, exercise capacity, cognition, quality of life and mental health are poorly understood.MethodsFifty-eight COVID-19 patients post-hospital discharge and 30 comorbidity-matched controls were prospectively enrolled for multiorgan (brain, lungs, heart, liver and kidneys) magnetic resonance imaging (MRI), spirometry, six-minute walk test, cardiopulmonary exercise test (CPET), quality of life, cognitive and mental health assessments.FindingsAt 2-3 months from disease-onset, 64% of patients experienced persistent breathlessness and 55% complained of significant fatigue. On MRI, tissue signal abnormalities were seen in the lungs (60%), heart (26%), liver (10%) and kidneys (29%) of patients. COVID-19 patients also exhibited tissue changes in the thalamus, posterior thalamic radiations and sagittal stratum on brain MRI and demonstrated impaired cognitive performance, specifically in the executive and visuospatial domain relative to controls. Exercise tolerance (maximal oxygen consumption and ventilatory efficiency on CPET) and six-minute walk distance (405±118m vs 517±106m in controls, p<0.0001) were significantly reduced in patients. The extent of extra-pulmonary MRI abnormalities and exercise tolerance correlated with serum markers of ongoing inflammation and severity of acute illness. Patients were more likely to report symptoms of moderate to severe anxiety (35% versus 10%, p=0.012) and depression (39% versus 17%, p=0.036) and a significant impairment in all domains of quality of life compared to controls.InterpretationA significant proportion of COVID-19 patients discharged from hospital experience ongoing symptoms of breathlessness, fatigue, anxiety, depression and exercise limitation at 2-3 months from disease-onset. Persistent lung and extra-pulmonary organ MRI findings are common. In COVID-19 survivors, chronic inflammation may underlie multiorgan abnormalities and contribute to impaired quality of life.FundingNIHR Oxford and Oxford Health Biomedical Research Centres, British Heart Foundation Centre for Research Excellence, UKRI, Wellcome Trust, British Heart Foundation.
Determinants of improvement trends in health workers' compliance with outpatient malaria case-management guidelines at health facilities with available "test and treat" commodities in Kenya.
BACKGROUND: Health workers' compliance with outpatient malaria case-management guidelines has been improving in Africa. This study examined the factors associated with the improvements. METHODS: Data from 11 national, cross-sectional health facility surveys undertaken from 2010-2016 were analysed. Association between 31 determinants and improvement trends in five outpatient compliance outcomes were examined using interactions between each determinant and time in multilevel logistic regression models and reported as an adjusted odds ratio of annual trends (T-aOR). RESULTS: Among 9,173 febrile patients seen at 1,208 health facilities and by 1,538 health workers, a higher annual improvement trend in composite "test and treat" performance was associated with malaria endemicity-lake endemic (T-aOR = 1.67 annually; p<0.001) and highland epidemic (T-aOR = 1.35; p<0.001) zones compared to low-risk zone; with facilities stocking rapid diagnostic tests only (T-aOR = 1.49; p<0.001) compared to microscopy only services; with faith-based/non-governmental facilities compared to government-owned (T-aOR = 1.15; p = 0.036); with a daily caseload of >25 febrile patients (T-aOR = 1.46; p = 0.003); and with under-five children compared to older patients (T-aOR = 1.07; p = 0.013). Other factors associated with the improvement trends in the "test and treat" policy components and artemether-lumefantrine administration at the facility included the absence of previous RDT stock-outs, community health workers dispensing drugs, access to malaria case-management and Integrated Management of Childhood Illness (IMCI) guidelines, health workers' gender, correct health workers' knowledge about the targeted malaria treatment policy, and patients' main complaint of fever. The odds of compliance at the baseline were variable for some of the factors. CONCLUSIONS: Targeting of low malaria risk areas, low caseload facilities, male and government health workers, continuous availability of RDTs, improving health workers' knowledge about the policy considering age and fever, and dissemination of guidelines might improve compliance with malaria guidelines. For prompt treatment and administration of the first artemether-lumefantrine dose at the facility, task-shifting duties to community health workers can be considered.
Incidence, outcomes and management of spontaneous haemoperitoneum in pregnancy: a UK population-based study.
BACKGROUND: Spontaneous haemoperitoneum in pregnancy (SHiP) is the occurrence during pregnancy of sudden intra-abdominal haemorrhage unrelated to extrauterine pregnancy, trauma or uterine rupture. SHiP is uncommon but is associated with preterm birth, high perinatal mortality and, more rarely, maternal mortality. We investigated the incidence of SHiP in the UK and its diagnosis, management and outcomes. METHODS: This two-year, prospective surveillance study used the UK Obstetric Surveillance System to collect anonymous data on all women who gave birth in a UK consultant-led maternity unit in 2016 and 2017 and who experienced SHiP. RESULTS: We confirmed 20 cases of SHiP, giving an estimated incidence of 1.3 cases per 100,000 maternities, or 1 per 75,614 maternities. The median gestational age at diagnosis was 35.7 weeks (IQR 29.9-38.4 weeks). A minority of affected women were receiving anticoagulant agents for prophylaxis (2/20) or treatment (4/20). The most common initial suspected diagnosis was placental abruption (7/20), followed by intra-abdominal bleeding, uterine rupture, or infection. SHiP was diagnosed using ultrasound in four women, using CT in five, and solely at surgery in 14. Aneurysms (4/20) and organ rupture or haematoma (5/20) were the most common bleeding source, and the condition was most commonly diagnosed and treated by laparotomy (11/20). Perinatal morbidity and mortality were high, with 16% of infants stillborn, an over 80% admission rate to the neonatal unit among the 16 live-born infants, major complications in a third of these infants, and one neonatal death. Maternal morbidity was also high, with 60% of women admitted to the intensive care unit, over half of whom experienced major morbidity, and one maternal death. CONCLUSIONS: SHiP is rare in the UK but when it occurs, it can be associated with major maternal morbidity and mortality, and perinatal outcomes are poor. International comparisons are complicated by differing definitions of SHiP.
The spatiotemporal distribution of human pathogens in ancient Eurasia.
Infectious diseases have had devastating effects on human populations throughout history, but important questions about their origins and past dynamics remain1. To create an archaeogenetic-based spatiotemporal map of human pathogens, we screened shotgun-sequencing data from 1,313 ancient humans covering 37,000 years of Eurasian history. We demonstrate the widespread presence of ancient bacterial, viral and parasite DNA, identifying 5,486 individual hits against 492 species from 136 genera. Among those hits, 3,384 involve known human pathogens2, many of which had not previously been identified in ancient human remains. Grouping the ancient microbial species according to their likely reservoir and type of transmission, we find that most groups are identified throughout the entire sampling period. Zoonotic pathogens are only detected from around 6,500 years ago, peaking roughly 5,000 years ago, coinciding with the widespread domestication of livestock3. Our findings provide direct evidence that this lifestyle change resulted in an increased infectious disease burden. They also indicate that the spread of these pathogens increased substantially during subsequent millennia, coinciding with the pastoralist migrations from the Eurasian Steppe4,5.
Sero-surveillance for IgG to SARS-CoV-2 at antenatal care clinics in three Kenyan referral hospitals: Repeated cross-sectional surveys 2020-21.
INTRODUCTION: The high proportion of SARS-CoV-2 infections that have remained undetected presents a challenge to tracking the progress of the pandemic and estimating the extent of population immunity. METHODS: We used residual blood samples from women attending antenatal care services at three hospitals in Kenya between August 2020 and October 2021and a validated IgG ELISA for SARS-Cov-2 spike protein and adjusted the results for assay sensitivity and specificity. We fitted a two-component mixture model as an alternative to the threshold analysis to estimate of the proportion of individuals with past SARS-CoV-2 infection. RESULTS: We estimated seroprevalence in 2,981 women; 706 in Nairobi, 567 in Busia and 1,708 in Kilifi. By October 2021, 13% of participants were vaccinated (at least one dose) in Nairobi, 2% in Busia. Adjusted seroprevalence rose in all sites; from 50% (95%CI 42-58) in August 2020, to 85% (95%CI 78-92) in October 2021 in Nairobi; from 31% (95%CI 25-37) in May 2021 to 71% (95%CI 64-77) in October 2021 in Busia; and from 1% (95% CI 0-3) in September 2020 to 63% (95% CI 56-69) in October 2021 in Kilifi. Mixture modelling, suggests adjusted cross-sectional prevalence estimates are underestimates; seroprevalence in October 2021 could be 74% in Busia and 72% in Kilifi. CONCLUSIONS: There has been substantial, unobserved transmission of SARS-CoV-2 in Nairobi, Busia and Kilifi Counties. Due to the length of time since the beginning of the pandemic, repeated cross-sectional surveys are now difficult to interpret without the use of models to account for antibody waning.
The influence of metformin treatment on the circulating proteome.
BACKGROUND: Metformin is one of the most used drugs worldwide. Given the increasing use of proteomics in trials, bioresources, and clinics, it is crucial to understand the influence of metformin on the levels of the circulating proteome. METHODS: We analysed a combined longitudinal proteomics dataset from the IMPOCT, RAMP and S3WP-T2D clinical trials in 98 participants before and after metformin exposure. This discovery analysis contained 372 proteins measured by proximity extension assays (Olink). We followed up experiment-wise statistically significant findings in two cross-sectional cohorts of people with type 2 diabetes comparing metformin treated and untreated individuals: IMI-DIRECT (784 participants, 372 proteins, Olink) and IMI-RHAPSODY (1175 participants, 1195 proteins, SomaLogic). FINDINGS: Overall, 23 protein analytes were robustly associated with exposure to metformin in the discovery and replication. This includes 11 protein-metformin associations that replicated in both replication sets and platforms (REG4, GDF15, REG1A, t-PA, TFF3, CDH5, CNTN1, OMD, NOTCH3, THBS4 and CD93), with the remaining 12 protein-metformin associations replicated using the Olink platform (EPCAM, SPINK1, SAA-4, COMP, ITGB2, ADGRG2, FAM3C, MERTK, COL1A1, HAOX1, VCAN, TIMD4) but not measured on the SomaLogic platform. Gene-set enrichment analysis revealed that the metformin exposure was associated with intestinal associated proteins. INTERPRETATION: These data highlight the need to account for exposure to metformin, and potentially other drugs, in proteomic studies and where protein biomarkers are used for clinical care. FUNDING: Innovative Medicines Initiative Joint Undertaking 2, under grant agreement no. 115881 (RHAPSODY) and the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution as well as the Swiss State Secretariat for Education Research' and Innovation (SERI), under contract no. 16.0097 (RHAPSODY).
Digitally Enabled Care in Diverse Environments (DECIDE): protocol for a programme of rapid evaluation of technology-enabled remote monitoring in health and social care
Background There is considerable interest in technology-enabled remote monitoring in the UK. The aim is to respond to system pressures and improve access, experience and quality of care. There is an urgent need for process, outcome and impact evaluations of interventions at various stages of development and implementation to address evidence gaps around adoption, spread, sustainability and inequalities. Aim DECIDE (Digitally Enabled Care in Diverse Environments) is a centre for rapid evaluation of technology-enabled remote monitoring funded by the National Institute for Health and Care Research (2023 to 2026). It aims to support service users, service commissioners and providers of remote monitoring services, to enable high quality care. Example questions include: Is the technology-enabled remote monitoring innovation needed and, if so, for whom? How are technology-enabled care pathways implemented, and what are associated outcomes and impacts? What are the opportunities and challenges for sustainability, scale-up and spread? Methods A range of qualitative, quantitative and economic methods will be used. Exact methods and questions will be dependent on the focus, scope and scale of each evaluation. Evaluations will be informed by relevant theory, including the Non-Adoption, Abandonment and the challenges to Spread, Scale-up and Sustainability of technological innovation in health and care (NASSS) framework. A User Advisory Group and External Steering Committee, both with diverse voices, will help shape evaluation design, implementation and dissemination. Project-led dissemination will ensure timely sharing of insights and support impact. Conclusion Evaluations will advance understanding of when and for whom technology-enabled remote monitoring innovation is needed; how it works and how factors related to the intervention, implementation process and wider context influence adoption; associated outcomes and impacts, whether and how these tackle inequalities; and potential challenges to scale and spread. We aim to inform decision-making by policymakers, commissioners, providers, patients/service users and researchers.