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Aims: Health education is integral to cardiometabolic disease (CMD) management. This study aimed to assess whether and how education preferences have changed over time, and whether trends differ by sociodemographic characteristics (education status, age, ethnicity, and sex). Methods: A cross‐sectional questionnaire was deployed across five counties in the East Midlands, UK between 2017 and 2022 to adults with CMD (type 2 diabetes, cardiovascular disease or cerebrovascular disease). Respondent demographic data were collected alongside health education preferences. Statistical analyses ascertained whether demographic characteristics influenced preferences. The distribution of preferences over time was charted to identify trends. Results: A total of 4301 eligible responses were collected. Face‐to‐face one‐to‐one education was preferred (first choice for 75.1% of participants) but popularity waned over the five‐year period. Trends were similar amongst demographic groups. Online education showed a U‐shaped trend: In 2017, 44% of respondents ranked it as acceptable, peaking at 53% in 2019, but declining again, to below base line, 43%, by 2022. This modality was more popular with participants aged younger than 65 years, but popularity in people older than 65 years increased over the study period. The popularity of printed information also declined over time across all demographic groups except those of South Asian ethnicity, for whom it remained static. Conclusions: The overwhelming preference for face‐to‐face one‐to‐one health education from a doctor or nurse highlights the importance of preserving access to this modality, even in the face of current NHS pressures and trends towards digitalisation. Trends are changing, and should continue to be monitored, including between different sociodemographic groups. [ABSTRACT FROM AUTHOR]

Background: Self‐management is a key component of successful chronic kidney disease (CKD) management. Here, we present the findings from the internal pilot of a multicentre randomised controlled trial (RCT) aimed to test the effect of a digital self‐management programme ('My Kidneys & Me' (MK&M)). Methods: Participants (aged ≥18 years and CKD stages 3‐4) were recruited from hospital kidney services across England. Study processes were completed virtually. Participants were randomised 2:1 to either intervention (MK&M) or control group. The first 60 participants recruited were included in a 10‐week internal pilot which assessed study feasibility and acceptability against pre‐specified progression criteria: 1) eligibility and recruitment, acceptability of 2) randomisation and 3) outcomes, 4) MK&M activation, and 5) retention and attrition rates. Semi‐structured interviews further explored views on trial participation. Results: Of the 60 participants recruited, 41 were randomised to MK&M and 19 to control. All participants completed baseline measures and 62% (n=37) completed post‐intervention outcome measures. All progression criteria met the minimum thresholds to proceed. Nine participants were interviewed. The themes identified were satisfaction with study recruitment processes (openness to participate, reading and agreeing to "terms and conditions"), acceptability of study design (remote study participation, acceptability of randomisation, completion of online assessment(s)), and methods to improve recruitment and retention (personalised approach, follow‐up communication). Conclusion: This internal pilot demonstrated the feasibility and acceptability of a virtually run RCT. Progression criteria thresholds to proceed to the definitive RCT were met. Areas for improvement were identified and protocol amendments were made to improve trial delivery. [ABSTRACT FROM AUTHOR]

Aims: To examine the impact of impaired glycaemic regulation (IGR) and exercise training on hepatic lipid composition in men with metabolic dysfunction‐associated steatotic liver disease (MASLD). Materials and Methods: In Part A (cross‐sectional design), 40 men with MASLD (liver proton density fat fraction [PDFF] ≥5.56%) were recruited to one of two groups: (1) normal glycaemic regulation (NGR) group (glycated haemoglobin [HbA1c] < 42 mmol∙mol−1 [<6.0%]; n = 14) or (2) IGR group (HbA1c ≥ 42 mmol∙mol−1 [≥6.0%]; n = 26). In Part B (randomized controlled trial design), participants in the IGR group were randomized to one of two 6‐week interventions: (1) exercise training (EX; 70%–75% maximum heart rate; four sessions/week; n = 13) or (2) non‐exercise control (CON; n = 13). Saturated (SI; primary outcome), unsaturated (UI) and polyunsaturated (PUI) hepatic lipid indices were determined using proton magnetic resonance spectroscopy. Additional secondary outcomes included liver PDFF, HbA1c, fasting plasma glucose (FPG), homeostatic model assessment of insulin resistance (HOMA‐IR), peak oxygen uptake (VO2 peak), and plasma cytokeratin‐18 (CK18) M65, among others. Results: In Part A, hepatic SI was higher and hepatic UI was lower in the IGR versus the NGR group (p = 0.038), and this hepatic lipid profile was associated with higher HbA1c levels, FPG levels, HOMA‐IR and plasma CK18 M65 levels (rs ≥0.320). In Part B, hepatic lipid composition and liver PDFF were unchanged after EX versus CON (p ≥ 0.257), while FPG was reduced and VO2 peak was increased (p ≤ 0.030). ΔVO2 peak was inversely associated with Δhepatic SI (r = −0.433) and positively associated with Δhepatic UI and Δhepatic PUI (r ≥ 0.433). Conclusions: Impaired glycaemic regulation in MASLD is characterized by greater hepatic lipid saturation; however, this composition is not altered by 6 weeks of moderate‐intensity exercise training. [ABSTRACT FROM AUTHOR]

Diabetic Foot Ulcers (DFUs) are a major complication of diabetes, with treatment requiring offloading. This study aimed to capture how the accelerometer-assessed physical activity profile differs in those with DFUs compared to those with diabetes but without ulceration (non-DFU). Participants were requested to wear an accelerometer on their non-dominant wrist for up to 8days. Physical activity outcomes included average acceleration (volume), intensity gradient (intensity distribution), the intensity of the most active sustained (continuous) 5–120 min of activity (MXCONT), and accumulated 5–120 min of activity (MXACC). A total of 595 participants (non-DFU = 561, DFU = 34) were included in the analysis. Average acceleration was lower in DFU participants compared to non-DFU participants (21.9 mg [95%CI:21.2, 22.7] vs. 16.9 mg [15.3, 18.8], p < 0.001). DFU participants also had a lower intensity gradient, indicating proportionally less time spent in higher-intensity activities. The relative difference between DFU and non-DFU participants was greater for sustained activity (MXCONT) than for accumulated (MXACC) activity. In conclusion, physical activity, particularly the intensity of sustained activity, is lower in those with DFUs compared to non-DFUs. This highlights the need for safe, offloaded modes of activity that contribute to an active lifestyle for people with DFUs. [ABSTRACT FROM AUTHOR]

OBJECTIVE: We evaluated baseline characteristics of participants with early-onset type 2 diabetes (T2D) from the SURPASS program and tirzepatide's effects on glycemic control, body weight (BW), and cardiometabolic markers. RESEARCH DESIGN AND METHODS: This post hoc analysis compared baseline characteristics and changes in mean HbA1c, BW, waist circumference (WC), lipids, and blood pressure (BP) in 3,792 participants with early-onset versus later-onset T2D at week 40 (A Study of Tirzepatide [LY3298176] in Participants With Type 2 Diabetes Not Controlled With Diet and Exercise Alone [SURPASS-1] and A Study of Tirzepatide [LY3298176] Versus Semaglutide Once Weekly as Add-on Therapy to Metformin in Participants With Type 2 Diabetes [SURPASS-2]) or week 52 (A Study of Tirzepatide [LY3298176] Versus Insulin Degludec in Participants With Type 2 Diabetes [SURPASS-3]). Analyses were performed by study on data from participants while on assigned treatment without rescue medication in case of persistent hyperglycemia. RESULTS: At baseline in SURPASS-2, participants with early-onset versus later-onset T2D were younger with longer diabetes duration (9 vs. 7 years, P < 0.001) higher glycemic levels (8.5% vs. 8.2%, P < 0.001), higher BW (97 vs. 93 kg, P < 0.001) and BMI (35 vs. 34 kg/m2, P < 0.001), and a similarly abnormal lipid profile (e.g., triglycerides 167 vs. 156 mg/dL). At week 40, similar improvements in HbA1c (−2.6% vs. −2.4%), BW (−14 vs. −13 kg), WC (−10 vs. −10 cm), triglycerides (−26% vs. −24%), HDL (7% vs. 7%), and systolic BP (−6 vs. −7 mmHg) were observed in both subgroups with tirzepatide. CONCLUSIONS: Despite younger age, participants with early-onset T2D from the SURPASS program had higher glycemic levels and worse overall metabolic health at baseline versus those with later-onset T2D. In this post hoc analysis, similar improvements in HbA1c, BW, and cardiometabolic markers were observed with tirzepatide, irrespective of age at T2D diagnosis. Future studies are needed to determine long-term outcomes of tirzepatide in early-onset T2D. [ABSTRACT FROM AUTHOR]

In a randomised controlled trial (RCT), the between-arm difference in the average probability of an event per unit of time (i.e., yearly incidence risk difference, YIRD) is an easy-to-interpret treatment effect metric. We aimed to quantify the YIRD in cardiorenal RCTs of GLP-1RAs or SGLT-2is. We digitally searched for RCTs published up to March 1st, 2023, including subjects with type 2 diabetes randomised to GLP-1RAs or SGLT-2is and investigating cardiorenal outcomes or death. We extracted information from Kaplan-Meier (KM) plots to obtain time-to-event individual data and estimate within-arm yearly incidence risk and YIRD. Data from 19 RCTs (28 kM plots) were analysed: comparing treatment to placebo, in GLP-1RA RCTs the YIRD ranged from 0.2 % (95 % CI: −0.7 %, 1.1 %) to −1.9 % (−3.1, −0.7), for primary outcome; and from −0.2 % (−0.5, 0.2) to −0.4 % (−0.7 %, −0.0 %), for mortality. With the exception of SOLOIST-WHF (YIRD 11.9 % for primary outcome), corresponding estimates in SGLT-2is RCTs were: from −0.1 % (−0.4, 0.1) to −5.0 % (−7.7, −2.6), for primary outcome; and from −0.1 % (−0.2, 0.1) to −1.9 % (−4.4 %, 0.6 %), for mortality. The YIRD metric complements other relative treatment effect estimates and helps quantify the absolute benefit of GLP-1RAs and SGLT-2is. • Yearly incidence risk difference (YIRD) can help interpreting treatment effect. • Using reconstructed time-to-event data, we estimated YIRD in cardiorenal trials. • YIRDs was estimated for primary outcomes and death in GLP1-RAs and SGLT2-is trials. • YIRD is easy-to-interpret and could add insights in clinical decision-making. [ABSTRACT FROM AUTHOR]

Background The updated European Working Group on Sarcopenia in Older People (EWGSOP2) recommends handgrip strength (HGS) and the chair stand test (CST) to assess muscle strength, with the CST being a convenient proxy for lower limb strength. However, adiposity may differentially influence these strength criteria and produce discrepant sarcopenia prevalence. Objective To determine the prevalence of sarcopenia using HGS or the CST, and to investigate the associations between these strength criteria and adiposity in adults with type 2 diabetes mellitus. Methods The EWGSOP2 definition was used to assess the prevalence of probable (low muscle strength), confirmed (plus low muscle mass) and severe (plus poor physical performance) sarcopenia. Linear regression models were used to study the association between different measures of muscle strength and adiposity. Results We used data from 732 adults with type 2 diabetes mellitus (35.7% female, aged 64 ± 8 years, body mass index 30.7 ± 5.0 kg/m2). Using the CST compared with HGS produced a higher prevalence of probable (31.7% vs. 7.1%), confirmed (5.6% vs. 1.6%) and severe (1.0% vs. 0.3%) sarcopenia, with poor agreement between strength criteria to identify probable sarcopenia. CST performance, but not HGS, was significantly associated with all measures of adiposity in unadjusted and adjusted models. Conclusions Higher levels of adiposity may impact CST performance, but not HGS, resulting in a higher prevalence of sarcopenia in adults with type 2 diabetes mellitus. Consideration should be paid to the most appropriate measure of muscle function in this population. [ABSTRACT FROM AUTHOR]

Background: Self-management education programmes are cost-effective in helping people with type 2 diabetes manage their diabetes, but referral and attendance rates are low. This study reports on the effectiveness of the Embedding Package, a programme designed to increase type 2 diabetes self-management programme attendance in primary care. Methods: Using a cluster randomised design, 66 practices were randomised to: (1) a wait-list group that provided usual care for nine months before receiving the Embedding Package for nine months, or (2) an immediate group that received the Embedding Package for 18 months. 'Embedders' supported practices and self-management programme providers to embed programme referral into routine practice, and an online 'toolkit' contained embedding support resources. Patient-level HbA1c (primary outcome), programme referral and attendance data, and clinical data from 92,977 patients with type 2 diabetes were collected at baseline (months − 3–0), step one (months 1–9), step 2 (months 10–18), and 12 months post-intervention. An integrated ethnographic study including observations, interviews, and document analysis was conducted using interpretive thematic analysis and Normalisation Process Theory. Results: No significant difference was found in HbA1c between intervention and control conditions (adjusted mean difference [95% confidence interval]: -0.10 [-0.38, 0.18] mmol/mol; -0.01 [-0.03, 0.02] %). Statistically but not clinically significantly lower levels of HbA1c were found in people of ethnic minority groups compared with non-ethnic minority groups during the intervention condition (-0.64 [-1.08, -0.20] mmol/mol; -0.06% [-0.10, -0.02], p = 0.004), but not greater self-management programme attendance. Twelve months post-intervention data showed statistically but not clinically significantly lower HbA1c (-0.56 [95% confidence interval: -0.71, -0.42] mmol/mol; -0.05 [-0.06, -0.04] %; p < 0.001), and higher self-management programme attendance (adjusted odds ratio: 1.13; 95% confidence interval: 1.02, 1.25; p = 0.017) during intervention conditions. Themes identified through the ethnographic study included challenges for Embedders in making and sustaining contact with practices and providers, and around practices' interactions with the toolkit. Conclusions: Barriers to implementing the Embedding Package may have compromised its effectiveness. Statistically but not clinically significantly improved HbA1c among ethnic minority groups and in longer-term follow-up suggest that future research exploring methods of embedding diabetes self-management programmes into routine care is warranted. Trial registration: ISRCTN23474120, registered 05/04/2018. [ABSTRACT FROM AUTHOR]

Aim: To investigate how 24‐h physical behaviours differ across type 2 diabetes (T2DM) subtypes. Materials and Methods: We included participants living with T2DM, enrolled as part of an ongoing observational study. Participants wore an accelerometer for 7 days to quantify physical behaviours across 24 h. We used routinely collected clinical data (age at onset of diabetes, glycated haemoglobin level, homeostatic model assessment index of beta‐cell function, homeostatic model assessment index of insulin resistance, body mass index) to replicate four previously identified subtypes (insulin‐deficient diabetes [INS‐D], insulin‐resistant diabetes [INS‐R], obesity‐related diabetes [OB] and age‐related diabetes [AGE]), via k‐means clustering. Differences in physical behaviours across the diabetes subtypes were assessed using generalized linear models, with the AGE cluster as the reference. Results: A total of 564 participants were included in this analysis (mean age 63.6 ± 8.4 years, 37.6% female, mean age at diagnosis 53.1 ± 10.0 years). The proportions in each cluster were as follows: INS‐D: n = 35, 6.2%; INS‐R: n = 88, 15.6%; OB: n = 166, 29.4%; and AGE: n = 275, 48.8%. Compared to the AGE cluster, the OB cluster had a shorter sleep duration (−0.3 h; 95% confidence interval [CI] −0.5, −0.1), lower sleep efficiency (−2%; 95% CI −3, −1), lower total physical activity (−2.9 mg; 95% CI −4.3, −1.6) and less time in moderate‐to‐vigorous physical activity (−6.6 min; 95% CI −11.4, −1.7), alongside greater sleep variability (17.9 min; 95% CI 8.2, 27.7) and longer sedentary time (31.9 min; 95% CI 10.5, 53.2). Movement intensity during the most active continuous 10 and 30 min of the day was also lower in the OB cluster. Conclusions: In individuals living with T2DM, the OB subtype had the lowest levels of physical activity and least favourable sleep profiles. Such behaviours may be suitable targets for personalized therapeutic lifestyle interventions. [ABSTRACT FROM AUTHOR]

Background Air pollution may be a risk factor for physical inactivity and sedentary behaviour (SED) through discouraging active lifestyles, impairing fitness and contributing to chronic diseases with potentially important consequences for population health. Methods Using generalized estimating equations, we examined the associations between long-term particulate matter with diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10) and nitrogen dioxide (NO2) and annual change in accelerometer-measured SED, moderate-to-vigorous physical activity (MVPA) and steps in adults at risk of type 2 diabetes within the Walking Away from Type 2 Diabetes trial. We adjusted for important confounders including social deprivation and measures of the built environment. Results From 808 participants, 644 had complete data (1605 observations; 64.7% men; mean age 63.86 years). PM2.5, NO2 and PM10 were not associated with change in MVPA/steps but were associated with change in SED, with a 1 ugm−3 increase associated with 6.38 (95% confidence interval: 0.77, 12.00), 1.52 (0.49, 2.54) and 4.48 (0.63, 8.34) adjusted annual change in daily minutes, respectively. Conclusions Long-term PM2.5, NO2 and PM10 exposures were associated with an annual increase in SED: ~11–22 min/day per year across the sample range of exposure (three standard deviations). Future research should investigate whether interventions to reduce pollution may influence SED. [ABSTRACT FROM AUTHOR]

For the first time, the latest American Diabetes Association/European Association for the Study of Diabetes (ADA/EASD) consensus guidelines have incorporated a growing body of evidence linking health outcomes associated with type 2 diabetes to the movement behavior composition over the whole 24-h day. Of particular note, the importance of sleep as a key lifestyle component in the management of type 2 diabetes is promulgated and presented using three key constructs: quantity, quality, and timing (i.e., chronotype). In this narrative review we highlight some of the key evidence justifying the inclusion of sleep in the latest consensus guidelines by examining the associations of quantity, quality, and timing of sleep with measures of glycemia, cardiovascular disease risk, and mortality. We also consider potential mechanisms implicated in the association between sleep and type 2 diabetes and provide practical advice for health care professionals about initiating conversations pertaining to sleep in clinical care. In particular, we emphasize the importance of measuring sleep in a free-living environment and provide a summary of the different methodologies and targets. In summary, although the latest ADA/EASD consensus report highlights sleep as a central component in the management of type 2 diabetes, placing it, for the first time, on a level playing field with other lifestyle behaviors (e.g., physical activity and diet), the evidence base for improving sleep (beyond sleep disorders) in those living with type 2 diabetes is limited. This review should act as a timely reminder to incorporate sleep into clinical consultations, ongoing diabetes education, and future interventions. [ABSTRACT FROM AUTHOR]

In the primary care setting providers have more tools available than ever before to impact positively obesity, diabetes, and their complications, such as renal and cardiac diseases. It is important to recognise what is available for treatment taking into account diabetes heterogeneity. For those who develop type 2 diabetes (T2DM), effective treatments are available that for the first time have shown a benefit in reducing mortality and macrovascular complications, in addition to the well‐established benefits of glucose control in reducing microvascular complications. Some of the newer medications for treating hyperglycaemia have also a positive impact in reducing heart failure (HF). Technological advances have also contributed to improving the quality of care in patients with diabetes. The use of technology, such as continuous glucose monitoring systems (CGM), has improved significantly glucose and glycated haemoglobin A1c (HbA1c) values, while limiting the frequency of hypoglycaemia. Other technological support derives from the use of predictive algorithms that need to be refined to help predict those subjects who are at great risk of developing the disease and/or its complications, or who may require care by other specialists. In this review we also provide recommendations for the optimal use of the new medications; sodium‐glucose co‐transporter‐2 inhibitors (SGLT2i) and Glucagon‐like peptide‐receptor agonists 1 (GLP1RA) in the primary care setting considering the relevance of these drugs for the management of T2DM also in its early stage. [ABSTRACT FROM AUTHOR]

Background: This study assesses the temporal responses of cardiovascular function, fibro-inflammation, and glucometabolic profiles in asymptomatic adults with type 2 diabetes, following a low-energy meal replacement plan (MRP) or exercise training. Methods: Secondary analysis of DIASTOLIC: a randomised, open-label, blinded-endpoint trial of 12 weeks MRP (~810 kcal/day) or exercise training. Cardiac magnetic resonance, plasma fibroinflammatory, and metabolic markers were undertaken at baseline, 4, and 12 weeks. Results: Out of 24 participants in the MRP group and 22 in exercise training, 18 and 11 completed all three visits. MRP resulted in early (0–4 weeks) improvement in insulin resistance (HOMA-IR: 10.82 to 4.32), decrease in FABP-4 (4.87 ± 0.19 to 5.15 ± 0.32 mg/L), and improvement in left ventricular remodelling LV mass: volume (0.86 ± 0.14 to 0.78 ± 0.11), all with large effect sizes. MMP8 levels increased moderately at 4–12 weeks. Peak early diastolic strain rate (cPEDSR) initially decreased, then improved. Exercise training led to minor improvements in insulin resistance and MMP-8 levels, with no significant changes in cPEDSR or LV remodelling. Conclusions: MRP resulted in early improvements in insulin resistance, cardiac remodelling, and inflammation, but with an initial decrease in diastolic function, improving by 12 weeks. Exercise training showed minor early benefits in insulin resistance and inflammation, but no significant cardiac changes. [ABSTRACT FROM AUTHOR]

Aim: Despite global recommendations for type 2 diabetes mellitus treatment to maintain optimal glycaemic targets, a significant proportion of people remain in suboptimal glycaemic control. Our objective was to investigate the impact of intensification delay after basal insulin (BI) initiation on long‐term complications in people with suboptimal glycaemia. Materials and Methods: We conducted a retrospective cohort study in individuals with type 2 diabetes mellitus initiated on BI. Those with suboptimal glycaemia (glycated haemoglobin ≥7% or ≥53 mmol/mol) within 12 months of BI initiation were divided into early (treatment intensified within 5 years), or late (≥5 years) intensification groups. We estimated the age‐stratified risks of micro‐ and macrovascular complications among these groups compared with those with optimal glycaemia (glycated haemoglobin <7%). Results: Of the 13 916 people with suboptimal glycaemia, 52.5% (n = 7304) did not receive any treatment intensification. In those aged <65 years, compared with the optimal glycaemia group late intensification was associated with a 56% higher risk of macrovascular complications (adjusted hazard ratio 1.56; 95% confidence intervals 1.08, 2.26). In elderly people (≥65 years), late intensification was associated with a higher risk of cardiovascular‐related death (1.62; 1.03, 2.54) and a lower risk of microvascular complications (0.26; 0.08, 0.83). Conclusions: Those who had late intensification were at an increased risk of cardiovascular death if they were ≥65 years and an increased risk of macrovascular complications if they were <65 years. These findings highlight the critical need for earlier intensification of treatment and adopting personalized treatment strategies to improve patient outcomes. [ABSTRACT FROM AUTHOR]

Background: In patients with coronavirus disease 2019 (COVID-19) requiring supplemental oxygen, dexamethasone reduces acute severity and improves survival, but longer-term effects are unknown. We hypothesised that systemic corticosteroid administration during acute COVID-19 would be associated with improved health-related quality of life (HRQoL) 1 year after discharge., Methods: Adults admitted to hospital between February 2020 and March 2021 for COVID-19 and meeting current guideline recommendations for dexamethasone treatment were included using two prospective UK cohort studies (Post-hospitalisation COVID-19 and the International Severe Acute Respiratory and emerging Infection Consortium). HRQoL, assessed by the EuroQol-Five Dimensions-Five Levels utility index (EQ-5D-5L UI), pre-hospital and 1 year after discharge were compared between those receiving corticosteroids or not after propensity weighting for treatment. Secondary outcomes included patient-reported recovery, physical and mental health status, and measures of organ impairment. Sensitivity analyses were undertaken to account for survival and selection bias., Findings: Of the 1888 participants included in the primary analysis, 1149 received corticosteroids. There was no between-group difference in EQ-5D-5L UI at 1 year (mean difference 0.004, 95% CI -0.026-0.034). A similar reduction in EQ-5D-5L UI was seen at 1 year between corticosteroid exposed and nonexposed groups (mean±sd change -0.12±0.22 versus -0.11±0.22). Overall, there were no differences in secondary outcome measures. After sensitivity analyses modelled using a cohort of 109 318 patients admitted to hospital with COVID-19, EQ-5D-5L UI at 1 year remained similar between the two groups., Interpretation: Systemic corticosteroids for acute COVID-19 have no impact on the large reduction in HRQoL 1 year after hospital discharge. Treatments to address the persistent reduction in HRQoL are urgently needed., Competing Interests: Conflict of interest: O.C. Leavy declares that their institute received joint funding from UKRI and NIHR (MR/V027859/1 and COV0319) to complete this work. A.B. Docherty declares that they were awarded funding from a Wellcome Clinical Research Career Development Fellowship (216606/Z/19/Z) to complete this work. A Sheikh declares that their institute was awarded grant funding from NIHR and UKRI to complete this work; participation on a Data Safety Monitoring Board or Advisory Board for AstraZeneca's Thrombotic Thrombocytopenic Taskforce; and leadership or fiduciary roles for UK and Scottish Government COVID-19 advisory groups. C.E. Bolton declares that their institute received grant funding from NIHR/UKRI and NIHR to complete this work; and their institute received grant funding from Nottingham Hospitals Charity and University of Nottingham. G. Choudhury declares funding from GlaxoSmithKline and AstraZeneca; received honoraria for delivering talks from GSK, AZ, Chiesi and BI; participation on a Data Safety Monitoring Board or Advisory Board as Chair on the Act on COPD Programme for AZ in Scotland; and a leadership or fiduciary role as Chair for the Lothian Respiratory Managed Clinical Network. N.D. Bakerly declares they have received nonrestrictive educational grants from Chiesi, AZ and Teva for attending conferences; honoraria from Teva, AZ and GSK; support for attending meetings and/or travel from Chiesi and AZ; participation on a Data Safety Monitoring Board or Advisory Board for Teva; and receipt of equipment from Global Access Diagnostics (previously Mologic Inc). A. Shikotra declares that their institute was awarded joint funding from UKRI and the NIHR (MR/V027859/1 and COV0319) to complete this work. R. Aul declares lecture fees and support for attending a meeting from Boehringer Ingelheim. C. Echevarria declares a grant from GSK. J.R. Hurst declares funding from AstraZeneca; consulting fees from AstraZeneca and GSK; payment for lectures and presentations from AstraZeneca, Boehringer Ingelheim, Chiesi, Sanofi and Takeda; support for attending meetings and/or travel from AstraZeneca; participation on a Data Safety Monitoring Board or Advisory Board for AstraZeneca; and receipt of equipment from Nonin. M. Jones declares funding from the MRC to complete this work; funding from the MRC, British Lung Foundation and Boehringer Ingelheim; consulting fees from Skyhawk Therapeutics; and a leadership or fiduciary role in the AAIR Charity Scientific Committee. P. Pfeffer declares funding from NIHR. S. Rowland-Jones declares that their institute received funding from UKRI to complete this work; and their institute received funding from NIHR Sheffield Biomedical Research centre, Bill and Melinda Gates Foundation, UKRI (MRC) and EDCTP. D. Parekh declares funding from NIHR and MRC; and a leadership or fiduciary role for the Faculty of Intensive Care Medicine Board. A.A.R. Thompson declares that their institute was awarded a fellowship from the British Heart Foundation, and grant funding from Heart Research UK and the National Institute for Health and Care Research; payment for lectures and presentations from Janssen-Cilag Ltd; and support for attending meetings from Janssen-Cilag Ltd. M.J. Davies declares grant funding from Novo Nordisk, Sanofi-Aventis, Lilly, Boehringer Ingelheim, AstraZeneca and Janssen; consulting fees from Eli Lilly, Boehringer Ingelheim, Novo Nordisk and Sanofi; payment for speaking for Boehringer Ingelheim, Lilly, Novo Nordisk, Sanofi, AstraZeneca, Amgen, Napp Pharmaceuticals and Novartis; and is an advisory board member for Boehringer Ingelheim, Lilly, Novo Nordisk, Sanofi, Lexicon, Pfizer, Medtronic and ShouTi Pharma Inc., and Zealand Pharma. A. De Soyza declares that their institute was awarded grant funding from AstraZeneca, Bayer, GSK, Chiesi, Novartis and Pfizer, outside the submitted manuscript; consulting fees from AstraZeneca, Bayer, GSK, Chiesi, Novartis, Pfizer, Insmed and Gilead; payment for lectures and presentations from AstraZeneca, Bayer, GSK, Chiesi, Novartis, Pfizer, Insmed, Gilead and 30T; participation on a Data Safety Monitoring Board or Advisory Board for Bayer; and receipt of drugs from GSK outside the submitted manuscript. S. Heller declares consulting fees from NovoNordisk; and participation on a Data Safety Monitoring Board or Advisory Board for Eli Lilly with payments made to their institution. J. Jacob declares funding from Gilead, Microsoft Research and GlaxoSmithKline; consulting fees from Boehringer Ingelheim, Roche, GlaxoSmithKline and NHSX; payment for lectures and presentations received from Boehringer Ingelheim, Roche, GlaxoSmithKline and Takeda; support for attending meetings and/or travel from Boehringer Ingelheim; patents planned, issued or pending (UK patent application number 2113765.8 and UK patent application number GB2211487.0); and participation on a Data Safety Monitoring Board or Advisory Board for Boehringer Ingelheim and Roche. R.G. Jenkins declares that their institute received funding from AstraZeneca, Biogen, Galecto, GlaxoSmithKline, Nordic Biosciences, RedX and Pliant; consulting fees from AstraZeneca, Brainomix, Bristol Myers Squibb, Chiesi, Cohbar, Daewoong, GlaxoSmithKline, Veracyte, Resolution Therapeutics and Pliant; payment for lectures and presentations received from Boehringer Ingelheim, Chiesi, Roche, PatientMPower and AstraZeneca; payment for expert testimony from Pinsent Masons LLP; participation on a Data Safety Monitoring Board or Advisory Board for Boehringer Ingelheim, Galapagos and Vicore; and a leadership or fiduciary role for NuMedii and is president for Action for Pulmonary Fibrosis. W.D-C. Man declares that their institute received funding from National Institute for Health Research and NHS Accelerated Access Collaborative; and is Honorary President of the Association for Respiratory Technology and Physiology, and an associate editor of ERJ Open Research. G.P. McCann declares funding from NIHR (RP-2017-ST2-007) to complete this work; funding from the British Heart Foundation, Wellcome Trust and NIHR; and research support from Resonance Health, Circle CVi and Perspectum. S. Neubauer declares grant funding from Oxford NIHR Biomedical Research centre. P.J.M. Openshaw declares funding from UKRI-MRC/DHSC NIHR and UKRI-BEIS. M.J. Rowland declares support for attending meetings and/or travel from Novartis Pharmaceuticals; stock or stock options from Novartis Pharmaceuticals and Roche Pharmaceuticals; and is employed full time as a Senior Clinical Development Medical Director at Novartis Pharmaceuticals. J. Porter declares funding from Breathing Matters and UCL/H BRC (NIHR), and consulting fees from The Limbic. L.G. Heaney declares that their institute received funding from GSK, AstraZeneca and Roche/Genentech; payment for lectures received from AstraZeneca, Novartis, Roche/Genentech, Sanofi, Circassia, GlaxoSmithKline, Chiesi and Teva; support to travel to meetings from AstraZeneca and GSK; participation on a Data Safety Monitoring Board or Advisory Board for Novartis, Roche/Genentech, GSK, Teva and Celltrion; and funding from the NIHR (RfPB grant PB-PG-0317-20032). J.T. Scott declares funding from UKRI. M.G. Semple declares grant funding from National Institute of Health Research UK, Medical Research Council UK and Health Protection Research Unit in Emerging and Zoonotic Infections, and University of Liverpool to complete this work; participation on a Data Safety Monitoring Board or Advisory Board for Pfizer; leadership or fiduciary roles as Chair of Infectious Disease Scientific Advisory Board Integrum Scientific LLC and Director of MedEx Solutions Ltd; stock or stock options as minority owner of Integrum Scientific LLC and majority owner of MedEx Solutions Ltd; receipt of equipment, materials, drugs, medical writing, gifts or other services from Chiesi Farmaceutici SpA; and is a nonremunerated independent member of HMG UK Scientific Advisory Group for Emergencies (SAGE), COVID-19 Response (March 2020 to March 2022) and a nonremunerated independent member of HMG UK New Emerging Respiratory Virus Threats Advisory Group (NERVTAG) (2014 to July 2023). S.J. Singh declares grants or contracts from NIHR (programme grant (NIHR 202020), Wellcome Doctoral Training Programme, HTA Project Grant (NIHR 131015), NIHR DHSC/UKRI COVID-19 Rapid Response Initiative, NIHR Global Research Group (NIHR 17/63/20)), Actegy Limited and NIHR Senior Investigator; payment for presentations for GSK, Ministry of Justice, CIPLA, Sherbourne Gibbs; participation on NICE Expert Adviser Panel (long COVID), Wales Long COVID Advisory Board and NHS-E Long Covid Your Covid Recovery working group; and leadership or fiduciary roles as ATS Pulmonary Rehabilitation Assembly Chair, Clinical Lead RCP Pulmonary Rehabilitation Accreditation Scheme and Clinical Lead NACAP Audit for Pulmonary Rehabilitation. M. Toshner declares grant funding from the NIHR Cambridge BRC and NIHR HTA to complete this work; consulting fees from Janssen; support for attending meetings and/or travel from GSK and Janssen; and participation on a Data Safety Monitoring Board or Advisory Board for ComCov and FluCov. A. Horsley declares that their institute was awarded funding from UK Research and Innovation (MR/V027859/1), the National Institute of Health Research (NIHR) (COV0319) and NIHR Manchester BRC; and is Chair for the NIHR Translational Research Collaboration. M. Marks declares that their institute received joint funding from UKRI and NIHR to complete this work. K. Poinasamy declares funding from UKRI and NIHR to complete this work. A. Briggs declares consulting fees from Roche, Merck, Sanofi and GSK. J.K. Quint declares that their institute received funding from the Industrial Strategy Challenge Fund, the Medical Research Council, Health Data Research, GSK, BI, Asthma+Lung UK and AZ; and consulting fees from GlaxoSmithKline, Evidera, Chiesi, AstraZeneca and Insmed. J.D. Chalmers declares funding from AstraZeneca, Boehringer Ingelheim, Grifols, Gilead Sciences, Insmed, Genentech and GlaxoSmithKline; consulting fees from AstraZeneca, Boehringer Ingelheim, Grifols, Gilead Sciences, Insmed, Genentech, Glaxosmithkline, Antabio, Zambon and Trudell; and leadership or fiduciary roles as Chief Editor of the European Respiratory Journal and associate editor of ERJ Open Research, Chair of the British Thoracic Society Science and Research Committee, and Trustee of the British Thoracic Society. L.V. Wain declares funding from UK Research and Innovation (MR/V027859/1), GSK/Asthma+Lung UK (Professorship (C17-1)) and National Institute of Health Research (COV0319) to complete this work; funding from Orion Pharma, GSK, Genentech, AstraZeneca, Nordic Bioscience and Sysmex (OGT); consulting fees Galapagos, Boehringer Ingelheim and GSK; support for attending meetings and/or travel Genentech; participation on Advisory Board for Galapagos; leadership or fiduciary roles as an associate editor for the European Respiratory Journal, and Medical Research Council Board member and Deputy Chair. C.E. Brightling declares that their institute received grant funding from MRC/NIHR and NIHR to complete this work; their institute received grant funding from GSK, AZ, Sanofi, Regeneron, Roche, Genentech, BI, Novartis, Chiesi, 4Dpharma and Mologic; and consulting fees from GSK, AZ, Sanofi, Regeneron, Roche, Genentech, BI, Novartis, Chiesi, 4Dpharma, Mologic and Areteia. R.A. Evans declares funding from UKRI/MRC/NIHR to complete this work; funding from Wolfson Foundation and Genentech/Roche; consulting fees from AstraZeneca/Evidera; speaking fees from Boehringer and Moderna; support for attending meetings from Chiesi; and leadership or fiduciary roles as ERS Group 01.02 Pulmonary Rehabilitation and Chronic Care Secretary, and ATS Pulmonary Rehabilitation Assembly Chair. All other authors declare no conflicts of interest., (Copyright ©The authors 2024.)

Background and Aims: Although extreme cardiac adaptions mirroring phenotypes of cardiomyopathy have been observed in endurance athletes, adaptions to high levels of physical activity within the wider population are under-explored. Therefore, in this study, associations between device-measured physical activity and clinically relevant cardiac magnetic resonance volumetric indices were investigated., Methods: Individuals without known cardiovascular disease or hypertension were included from the UK Biobank. Cardiac magnetic resonance data were collected between 2015 and 2019, and measures of end-diastolic chamber volume, left ventricular (LV) wall thickness, and LV ejection fraction were extracted. Moderate-to-vigorous-intensity physical activity (MVPA), vigorous-intensity physical activity (VPA), and total physical activity were assessed via wrist-worn accelerometers., Results: A total of 5977 women (median age and MVPA: 62 years and 46.8 min/day, respectively) and 4134 men (64 years and 49.8 min/day, respectively) were included. Each additional 10 min/day of MVPA was associated with a 0.70 [95% confidence interval (CI): 0.62, 0.79] mL/m2 higher indexed LV end-diastolic volume (LVEDVi) in women and a 1.08 (95% CI: 0.95, 1.20) mL/m2 higher LVEDVi in men. However, even within the top decile of MVPA, LVEDVi values remained within the normal ranges [79.1 (95% CI: 78.3, 80.0) mL/m2 in women and 91.4 (95% CI: 90.1, 92.7) mL/m2 in men]. Associations with MVPA were also observed for the right ventricle and the left/right atria, with an inverse association observed for LV ejection fraction. Associations of MVPA with maximum or average LV wall thickness were not clinically meaningful. Results for total physical activity and VPA mirrored those for MVPA., Conclusions: High levels of device-measured physical activity were associated with cardiac remodelling within normal ranges., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Obesity is a chronic disease associated with serious complications and increased mortality. Weight loss (WL) through lifestyle changes results in modest WL long-term possibly due to compensatory biological adaptations (increased appetite and reduced energy expenditure) promoting weight gain. Bariatric surgery was until recently the only intervention that consistently resulted in ≥ 15% WL and maintenance. Our better understanding of the endocrine regulation of appetite has led to the development of new medications over the last decade for the treatment of obesity with main target the reduction of appetite. The efficacy of semaglutide 2.4 mg/week-the latest glucagon-like peptide-1 (GLP-1) receptor analogue-on WL for people with obesity suggests that we are entering a new era in obesity pharmacotherapy where ≥15% WL is feasible. Moreover, the WL achieved with the dual agonist tirzepatide (GLP-1/glucose-dependent insulinotropic polypeptide) for people with type 2 diabetes and most recently also obesity, indicate that combining the GLP-1 with other gut hormones may lead to additional WL compared with GLP-1 receptor analogues alone and in the future, multi-agonist molecules may offer the potential to bridge further the efficacy gap between bariatric surgery and the currently available pharmacotherapies., Competing Interests: Conflict of interest: D.P. has acted as speaker for Novo Nordisk and has received grants from Novo Nordisk, Novo Nordisk UK Research Foundation, Academy of Medical Sciences/Diabetes UK, and Health Education East Midlands. C.W.l.R. reports grants from the Irish Research Council, Science Foundation Ireland, Anabio, and the Health Research Board. He serves on the advisory boards of Novo Nordisk, Herbalife, GI Dynamics, Eli Lilly, Johnson & Johnson, Sanofi Aventis, AstraZeneca, Janssen, Bristol-Myers Squibb, Glia, and Boehringer Ingelheim. C.W.l.R. is a member of the Irish Society for Nutrition and Metabolism outside the area of work commented on here. He is the chief medical officer and director of the Medical Device Division of Keyron since January 2011. Both of these are unremunerated positions. C.W.l.R. was a previous investor in Keyron, which develops endoscopically implantable medical devices intended to mimic the surgical procedures of sleeve gastrectomy and gastric bypass. The product has only been tested in rodents and none of Keyron’s products are currently licensed. They do not have any contracts with other companies to put their products into clinical practice. No patients have been included in any of Keyron’s studies and they are not listed on the stock market. C.W.l.R. was gifted stock holdings in September 2021 and divested all stock holdings in Keyron in September 2021. He continues to provide scientific advice to Keyron for no remuneration. J.J.H. is a member of advisory boards for Novo Nordisk and has acted as a speaker for Novo Nordisk and Lilly. M.J.D. has acted as consultant, advisory board member and speaker for Boehringer Ingelheim, Lilly, Novo Nordisk and Sanofi, an advisory board member and speaker for AstraZeneca, an advisory board member for Janssen, Lexicon, Pfizer, and ShouTi Pharma Inc., a speaker for Napp Pharmaceuticals, Novartis, and Takeda Pharmaceuticals International Inc. and has received grants in support of investigator and investigator initiated trials from Novo Nordisk, Sanofi-Aventis, Lilly, Boehringer Ingelheim, Astrazeneca, and Janssen., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)