British Journal of General Practice

BACKGROUND Safe and effective antidepressant deprescribing strategies are needed in general practice where most antidepressant prescribing occurs. METHODS We conducted a pragmatic, cluster-randomised controlled trial in general practice to test invitation to general practitioner (GP) review combined with resources to inform shared decision-making and guide hyperbolic tapering for stopping antidepressants compared to usual care. Adults taking antidepressants for longer than 12 months were recruited from 26 Australian GP practices between March 2023 and November 2024, irrespective of their intention to stop or depression or anxiety symptom scores. The primary outcome was cessation at 12 months. Secondary outcomes included cessation at 6 months, and >75% dose reduction and depression, anxiety and withdrawal symptom scores at 6 and 12 months. RESULTS Overall, 483 patients were randomised. Mean age was 50 years; 73% were women; mean duration of antidepressant use was 14.1 years. Cessation at 12 months was observed in 32 of 215 (14.9%) intervention and 16 of 187 (8.6%) usual care patients (odds ratio (OR) = 1.95 [95%CI, 1.00 to 3.81]; p=0.050). Cessation at 6 months was observed in 11.7% intervention vs 4.8% usual care (OR = 2.68; 95%CI, 1.18 to 6.05), and >75% dose reduction at 12 months in 19.6% intervention vs 9.9% usual care (OR = 2.28; 95%CI, 1.20 to 4.31). Symptom scores were similar between groups. No adverse events were attributable to the intervention. CONCLUSIONS In general practice, invitation to GP antidepressant review combined with information and guidance on hyperbolic tapering can support cessation or dose reduction without causing adverse effects or relapse. Absolute cessation rates were modest but still meaningful given the high prevalence of long term antidepressant use. TRIAL REGISTRATION ANZCT registry identifier, ACTRN12622001379707p.

Background Effective communication during consultations is facilitated by clinical empathy and realistic optimism, and can enhance patient satisfaction with care, alleviate symptoms, and improve quality of life. However, primary care systems are under significant strain and changing rapidly, which may affect practitioners' ability to communicate empathically and convey realistic optimism, with implications for the patient-practitioner relationship and patient outcomes. Understanding patients' perspectives of healthcare communication in the current clinical context is therefore important. We aimed to explore patients' experiences and perceptions of communication in UK primary care consultations, focussing on the communication of clinical empathy and realistic optimism. Methods A qualitative interview study was conducted as part of a multi-centre cluster-randomised trial of EMPathicO, a brief e-learning package for Primary Care Practitioners (PCPs) on communicating clinical empathy and realistic optimism. Participants were not aware whether their general practice had access to EMPathicO or not. Interviews were conducted within 7-14 days of participants' consultations, explored their views and experiences of clinical empathy and realistic optimism, and were transcribed verbatim. Interviews were analysed using Ritchie and Spencer's Framework Method. Results We conducted semi-structured audio-recorded qualitative telephone interviews with 71 participants from 29 primary care practices taking part in the EMPathicO trial. Following comprehensive mapping of data to the framework derived following initial analysis, four themes were agreed. Overall, most participants described positive empathic consultations with their PCPs, however, participants' experiences were shaped by wider systemic and contextual factors. They described a stretched and inefficient primary care system impacting empathy and optimism; the impact of PCP 'preparedness' as a marker for empathy; how consultation modality (i.e. in-person or telephone) shaped perceptions of empathy, and how PCPs sharing next steps in participants' treatment and management could foster realistic optimism. Conclusions While clinical empathy and realistic optimism may be experienced by patients during consultations with practitioners, the wider contextual challenges of accessing and navigating primary care systems can threaten overall perceptions of feeling cared for. Future primary care policy and workforce training must consider these system pressures to preserve effective communication in consultations and positive patient-practitioner encounters.

Background: Maternal postpartum checks with a general practitioner (GP) are recognised as an essential service in England and vital for recovery after pregnancy and reducing risk of long-term morbidity. Despite this, its reported fewer than of women have a record of the examination in the recommended 6-8 weeks, with observed disparities in uptake nationally. The impact of the COVID-19 pandemic disrupted delivery of these checks nationally, but there is limited data on the impact of the pandemic and its recovery for regional populations representing diversity and areas of dense poverty and ethnic minority populations. This study utilised region level data to assess the impact of COVID-19 on postnatal care. Methods: Anonymised electronic health records with clinical coded birth events for females, aged 16-49 years, were analysed for patients registered with a GP using the Greater Manchester Care Record (GMCR) between January 2018 and August 2023. Unique delivery episodes were defined and monthly rates calculated separately for women with a postnatal-related code within 4-, 6-, 8-, or 12-weeks or 1 year follow-up. Rates were also generated by key maternal demographics to assess any differences in postpartum care. Interrupted time series, modelling the onset of the pandemic estimated the IRR of 0.49 (95% CI 0.40-0.58). To assess the impact of maternal characteristics on the odds of non-attendance at examination, a logistic regression adjusting for various maternal characteristics was fitted. Results: There were 114,874 unique delivery episodes, relating to 85,076 women in the 12-week follow up cohort; 72,595 episodes to 55,784 women in 8-weeks and 28,846 episodes to 24,018 women in 6-weeks. The rate of postpartum checks was greater the longer the follow-up period. For checks within 8 weeks the first lockdown reduced from ~325 per 1000 delivery episodes in 2019 to 225 per 1000 by April 2020 (30.8%), which remained low, before returning to pre-pandemic rates by rates by October 2022. Rates remained lower overall for Black, or Asian women compared to White. Conclusion: The COVID-19 pandemic reduced postnatal follow-up in primary care across Greater Manchester, with rates frequently falling outside the recommended 6-8 week window. Significant disparities exist in the provision and uptake of these services. Improved integration of data across care sites, combined with enhanced risk management, could increase equity in access and support the timely delivery of care for those at greatest risk of postnatal complications and longer-term health issues.

Mobile clinical-support applications can facilitate access to evidence-based information at the point of care, but evidence on their usability and perceived usefulness among newly graduated physicians working in health facilities with limited capacity is scarce. We assessed physicians experiences with BMJ Best Practice using a convergent mixed-methods study. All 81 eligible physicians assigned to rural facilities were invited; 32 enrolled and received application access and training. After three months, participants completed an online survey, and 23 reported using the application. Ten physicians reporting the highest consultation frequency were purposively selected for semi-structured interviews. Survey findings showed a predominantly favorable perception of usability: for most items, 70%-90% of participants agreed or strongly agreed with the statements assessed. Among users, 14 of 23 (60.9%) used the mobile application and 9 (39.1%) used the web version. Interviews indicated that participants valued rapid searches, organized and evidence-based information, and support for diagnostic reasoning, referral decisions, learning, and clinical confidence. Barriers included limited connectivity, difficulties searching in Spanish, automatic updates, challenges locating or using some calculators, and treatment information that was sometimes insufficiently specific. Most importantly, participants could not always implement recommendations because suggested medicines, diagnostic tests, or other resources were unavailable in their facilities. Mobile clinical-support applications may complement decision-making and learning among early-career physicians in rural primary care. However, their practical value depends not only on usability and evidence quality, but also on adaptation to users language, workflow, connectivity, and local service capacity.

Background The number of novel cancer therapies approved for use in England by the National Institute for Health and Care Excellence is increasing. Monitoring the adoption of new therapies is important to assess equity of access and evaluate real-world prescribing practices. OpenPrescribing Hospitals has recently been launched to facilitate analysis of open secondary care medicines data in England. Using this platform, we set out to describe the use of cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors, including the frequency of dose reductions, within National Health Service (NHS) hospitals in England between January 2019 and December 2024. Methods The monthly proportion of each CDK4/6 inhibitor relative to total CDK4/6 inhibitor use was calculated at hospital level. Regional variation was assessed across Cancer Alliances by comparing the proportions of each CDK4/6 inhibitor used within each alliance in 2021 and 2024. Use of lower strength palbociclib and abemaciclib was used as a proxy for dose reductions. Findings There was more than a 3-fold increase in the use of CDK4/6 inhibitors between 2019 and 2024. In 2019, 78.6%, 11.9% and 9.5% of CDK4/6 inhibitors used were palbociclib, abemaciclib and ribociclib, compared with 40.2%, 41.2% and 18.6% in 2024. There was variation in the relative percentage change in use of each agent by Cancer Alliance. Use of lower strengths was common for both palbociclib (60%) and abemaciclib (63%). Interpretation Changes in usage appeared responsive to publication of key evidence and regulatory milestones. There was a higher apparent frequency of dose reductions than reported in clinical trials. OpenPrescribing Hospitals is an accessible, publicly available tool for understanding uptake and use of medicines in NHS hospitals in England.

Study Objective Little is known about where in hospital care for multiple long-term conditions (MLTC) is delivered. We aimed to describe pathways of care (ward transfers) and outcomes for people admitted to hospital for unscheduled care by MLTC status and other key sociodemographic characteristics. Design and setting Analysis of routinely-collected electronic health records from a large acute UK hospital. Participants Adult unscheduled care admissions from 1st July 2018 to 30th June 2019. The presence of two or more of 59 long-term conditions was ascertained using ICD-10 codes from previous hospital discharges. Main outcome measures Markov state transition probabilities were derived for ward moves and compared for MLTC vs no MLTC, age, sex, ethnicity and neighbourhood deprivation. Outcomes (length of stay, death, readmission, move from definitive ward) and time spent in emergency and assessment departments were compared between subgroups. Results A total of 33,252 adults, mean age 56.0 (SD 21.9) years were analysed; 14,834 (42.4%) had MLTC. People with MLTC were more likely to die in hospital (4.2 vs 1.9%, p<0.001), transfer to internal medicine wards or older peoples medicine wards, were less likely to transfer to surgical wards, had longer median length of stay (1.83 vs 0.69 days, p<0.001), stayed longer in acute medical units (15.5 vs 9.6 hours, p<0.001), and were more likely to move from their definitive ward (18.2 vs 16.4%, p=0.002). Conclusion Unscheduled hospital care pathways are complex and differ for people with MLTC, who have worse outcomes and may be less likely to receive optimal care.

Objectives To assess the concurrent and lagged associations between quality of primary care and planned and unplanned secondary care use for patients with multimorbidity, examining the modifying role of frailty. Design A retrospective cohort study Setting This population-level analysis included 468,172 patients with multimorbidity in England from the Discover research platform (April 2022-March 2024). Participants Patients with multimorbidity Main outcome measures We used principal component analysis to combine a set of quality indicators (QIs) and assessed the impacts of QIs on both planned and unplanned care. Results Generally, patients with higher QI attainment also had higher likelihood of planned (outpatient visits) and unplanned care (emergency admissions and ED visits) utilisation. There was a lower lagged odds of elective hospital admissions in the following 12 months among those with higher attainment of multimorbidity-specific QIs (OR=0.94, 95%CI 0.93-0.95). In the complex multimorbidity cohort ([&ge;]3 conditions), multimorbidity-specific QIs were longitudinally associated with lower odds of elective admissions (OR=0.94, 95%CI 0.92-0.95) and outpatient visits (OR=0.96, 95%CI 0.95-0.98), while generic QIs were related to lower odds of outpatient non-attendance (OR=0.95, 95%CI 0.91-0.99). In non-frail patients with multimorbidity, multimorbidity-specific QIs were longitudinally associated with reduced odds of outpatient visits (OR=0.98, 95%CI 0.97-0.99), elective admissions (OR=0.92, 95%CI 0.90-0.94) and prolonged elective hospital stay (IRR=0.94, 95%CI 0.89-0.99). Conclusions Attainment of generic and multimorbidity QIs was generally associated with slightly increased planned and unplanned care. However, patients for whom we identified higher attainment of multimorbidity-specific QIs had lower odds of elective admissions and outpatient visits, especially for those with complex multimorbidity. Our research suggests that the quality of primary care may influence patients' use of secondary care, with the potential to improve care for people with multimorbidity and warrant further investigation into management strategies.

Background: Public and clinical attention to postural orthostatic tachycardia syndrome (POTS) has increased, particularly since the COVID-19 pandemic. We quantified changes in United Kingdom Google search interest and examined whether searches increasingly used diagnostic and self-assessment language. Methods: We extracted monthly Google Trends relative search volume (RSV; 0-100) for the Health-category search term 'Pots syndrome' in the United Kingdom from January 2004 through July 2026. Five extraction attempts were made; two returned complete, identical monthly series and were retained. Prespecified eras were summarised and an exploratory interrupted time-series model at March 2020 used ordinary least squares with Newey-West heteroskedasticity and autocorrelation consistent standard errors (12 lags). Comparator searches included conventional orthostatic diagnoses, POTS diagnostic terms, associated conditions and YouTube searches. Results: The primary series comprised 271 complete months. Mean RSV increased from 18.6 during 2015-2019 to 64.8 during 2022-2023 (3.49-fold) and remained 50.6 during January 2024-July 2026 (2.73-fold above baseline). Search interest peaked in October 2022 (RSV 100); July 2026 RSV was 57. The interrupted time-series model estimated an immediate March 2020 level increase of 21.8 points (95% CI 2.8-40.7; p=0.024), while the slope change was not statistically supported (0.069 points/month, 95% CI 0.299 to 0.438; p=0.713). Searches for 'POTS symptoms', 'POTS test' and 'POTS heart rate' increased more steeply than the general term, although low baseline volumes made fold changes unstable. Conclusions: UK Google search interest in POTS rose before 2020, increased sharply after the pandemic began, and remained substantially above its prepandemic baseline. The results demonstrate a sustained change in public attention, not disease incidence or social-media causation. The growth of symptom- and testing-oriented searches is compatible with increased diagnostic self-investigation and warrants linkage to referral, diagnosis and social-media exposure data.

Background: Consumer use of AI chatbots for health advice is rising, yet triage safety relative to established services remains unclear. Australia's Healthdirect, a government-backed symptom checker with 2.4 million uses in FY2024-25, remains unevaluated against frontier large language models (LLMs), and whether premium subscriptions improve triage safety remains unexplored. This study compared the triage accuracy and safety of Healthdirect against six LLM configurations across ChatGPT, Claude, and Gemini, assessed whether paid subscriptions improve triage safety, and characterised each system's error patterns. Methods: Forty-five clinical vignettes from the Semigran et al. benchmark spanning emergency, non-emergent, and self-care categories (15 each) were evaluated across seven systems. Healthdirect was tested following a seven-rule interaction protocol. LLMs were evaluated using first-person patient-language prompts under free-tier and paid-tier conditions. Outcomes were triage accuracy, emergency sensitivity, under-triage, and critical misses, analysed using Cochran's Q, Bonferroni-corrected McNemar tests, Cohen's kappa, and Wilson intervals. Findings: Triage accuracy differed significantly (Cochran's Q = 36.79, p < 0.001). Healthdirect achieved 48.9% accuracy (95% CI 35.0% to 63.0%; kappa = 0.233) versus 73.3% to 86.7% for LLMs (kappa = 0.600 to 0.800). Healthdirect operated under conservative interactive defaults while LLMs received complete information in a single prompt, which may have disadvantaged Healthdirect. Emergency sensitivity was 46.7% versus 80.0% to 86.7% for LLMs. Healthdirect produced two critical misses; no LLM produced any across 270 evaluations (95% CI 0% to 1.4%). When LLMs undertriaged, they recommended GP care rather than self-care. No tier differences were significant (all p > 0.05), and most systems over-triaged self-care cases. Interpretation: Frontier LLMs demonstrated higher triage accuracy and safer error profiles than Healthdirect. All LLMs avoided critical misses; Healthdirect did not. Premium subscriptions did not significantly improve triage safety. These findings support clinical governance decisions about whether LLMs warrant formal evaluation alongside government-backed symptom checkers.

Pharmacogenomics (PGx) can improve safety and effectiveness of commonly dispensed medicines, but its value at the population level depends on how often clinically actionable PGx phenotypes co-occur with the medicines they affect. We assessed this co-occurrence in a cross-sectional analysis of Our Future Health (OFH), a new UK national biobank, by applying Pharmacogenomics Clinical Annotation Tool (PharmCAT v3.1.1) to imputed genotypes from 738,531 participants across 17 pharmacogenes with established PGx prescribing guidelines. Every participant had at least one actionable PGx phenotype, with a mean of 6.1 (SD 1.3). The number of actionable PGx phenotypes was similar across genetically inferred ancestry groups, although the pharmacogenes contributing to that count differed between groups. Using linked primary care dispensing records, 36.8% (95% CI 36.7-36.9) had been dispensed at least one medicine between April 2018 and June 2025 matched to a gene for which they carried an actionable PGx phenotype. Co-occurrence rose with age, ranging from 43.7% to 58.9% across ancestry groups among those aged [&ge;]70 years. Participants carried an actionable PGx phenotype for a mean of 13.8 (SD 6.5) of the 33 medicines dispensed in English primary care with PGx prescribing guidance, of which a mean of 0.6 (SD 1.0) had been dispensed. Co-occurrence was concentrated in a few widely dispensed classes, principally proton-pump inhibitors and antidepressants acting through CYP2C19 and statins through SLCO1B1. These findings highlight opportunities to optimise treatment for a large proportion of patients receiving routine medications and identify where pre-emptive PGx testing could have the greatest clinical benefit.

Background Patient-reported satisfaction is a core tracer of health-system responsiveness in Universal Health Coverage (UHC) monitoring, yet its determinants in rural Sierra Leone are poorly characterised. We quantified overall and domain-specific satisfaction and identified modifiable predictors across three rural border districts. Methods We conducted a cross-sectional, population-based household survey in October 2024 in Kailahun, Kambia and Pujehun districts, using a two-stage cluster design (chiefdoms sampled with probability proportional to size; households sampled at random). A validated 29-item instrument measured overall satisfaction and eight patient-experience domains on five-point Likert scales. The primary outcome was the five-level single-item overall satisfaction rating. We fitted a multivariable proportional-odds ordinal logistic regression, with 95% confidence intervals (CIs) obtained by a cluster bootstrap resampling the 20 chiefdom clusters. Robustness was assessed with binary and composite-outcome sensitivity models. Results Of 750 respondents, 679 (90.5%) had used a formal health facility in the previous 12 months and formed the analytic sample (510 [75.1%] female; mean age 28.2 years [SD 13.8]). The instrument showed high internal consistency (Cronbach = 0.87 for the five core domains). Overall, 375/679 (55.2%) were satisfied or very satisfied, ranging from 185/244 (75.8%) in Kambia to 110/224 (49.1%) in Kailahun and 80/211 (37.9%) in Pujehun ({chi}{superscript 2} = 70.8; p<0.001). In the adjusted model, staff attitude was the strongest predictor of higher satisfaction (adjusted odds ratio [AOR] 2.74, 95% CI 2.03-3.70; p<0.001 per one-point increase), followed by waiting-time satisfaction (AOR 1.89, 1.39-2.46) and medicine availability (AOR 1.43, 1.16-2.10). Travel-time category, facility type and sex were not independently associated. Large district disparities persisted after adjustment: relative to Kambia, the AOR for higher satisfaction was 0.27 (0.15-0.50) in Kailahun and 0.33 (0.20-0.66) in Pujehun. Adjusted probabilities of high satisfaction were 0.72, 0.48 and 0.43, respectively. Conclusions Respectful provider behaviour, shorter waits and reliable medicine supply, all amenable to district-level management, were the dominant and actionable drivers of patient satisfaction, whereas geographic distance was not. Persistent between-district gaps call for tailored quality-improvement in Kailahun and Pujehun. Institutionalising routine patient-experience measurement would strengthen accountability for people-centred care and support equitable progress towards UHC.

Introduction: Continuous glucose monitoring (CGM) offers an advancement over traditional self-monitoring of blood glucose (SMBG) for people living with type 1 diabetes (T1D). However, evidence on the acceptability and feasibility of different CGM use cases in African populations remains limited. Methods: This was a pragmatic three-arm, randomised controlled trial on CGM conducted among people living with T1D in three public healthcare clinics in South Africa. Participants were assigned to Arm 1 (continuous CGM), Arm 2 (periodic CGM), or Arm 3 (SMBG). Diabetes education was provided at all study visits. Feasibility was assessed by adherence to CGM use and through the Glucose Monitoring Satisfaction Survey (GMSS). Diabetes distress was measured by the Diabetes Distress Scale (DDS), health-related quality of life (HRQoL) by the EQ-5D scales, and acceptability using the Theoretical Framework of Acceptability (TFA). Surveys were collected on paper and transferred to OpenClinica. Analyses were performed in R. The trial was registered in the Clinical Trials Registry (NCT05944718) on July 13, 2023. Results: A total of 83 participants were included in Arm 1, 85 in Arm 2, and 80 in Arm 3. CGM mean active time was 55% in Arm 1 versus 69% in Arm 2. The proportion of participants meeting the [&ge;]70% active time threshold was higher in Arm 2 (52%) than in Arm 1 (34%). Diabetes' distress declined across arms during the intervention period, with no significant difference between arms; distress increased slightly six months post-intervention but remained below baseline. At 6 months, glucose monitoring satisfaction was significantly higher in both CGM arms than in the SMBG arm, and satisfaction increased over time in CGM arms. Health-related quality of life remained stable across arms during the intervention period with no significant difference between arms. High acceptability was observed in both CGM arms, with higher ratings in the periodic arm. Conclusions: CGM was acceptable to people living with type 1 diabetes and feasible to use in public-sector clinics in South Africa, with high acceptability under continuous and periodic use. Health-related quality of life remained stable across arms, and diabetes-related distress declined, during the intervention period, across arms. Glucose monitoring satisfaction rose significantly in both CGM arms compared to SMBG. Periodic CGM might be a promising and potentially more scalable option than continuous use for public-sector care.

Background: Observational research reports positive associations between type 2 diabetes mellitus (T2DM) and obesity-related cancers (ORCs), but causality remains unclear due to confounding (namely the shared risk factor of obesity, commonly approximated as body mass index, BMI), immortal time bias, and detection-time bias. Here, we aimed to use causal inference methods to minimise the above problems and estimate causal associations between new-onset T2DM and incident cancer. Methods: We performed a cohort study within UK Biobank, comparing new-onset T2DM with unexposed individuals matched 1 to 3 on BMI, age, and sex using a sequential longitudinal approach. The primary outcomes were total incident cancer, divided into ORCs and non-obesity-related cancers (NORCs). The secondary outcomes were site-specific cancers. We developed Cox models to estimate time-split hazard ratios (tsHRs) and 95% confidence intervals (CIs) stratified by sex. Findings: 23,771 participants with new-onset T2DM were matched with 71,170 unexposed participants. During a median follow-up of 5 years, there were 7694 (T2DM: 2432; unexposed: 5262) incident cancers. In men, there was evidence for an effect of T2DM on obesity-related cancer (tsHR 1.39, 95% CI 1.21-1.59), particularly on hepatocellular carcinoma (tsHR 3.97, 95% CI 2.38-6.65), pancreatic (tsHR 1.77, 95% CI 1.15-2.72) and kidney (tsHR 1.62, 95% CI 1.13-2.32) cancers. In women, there was evidence for an effect on obesity-related cancers (tsHR 1.33, 95% CI 1.16-1.52). Importantly, there were no associations with post-menopausal breast and endometrial cancers, two cancer types consistently associated with elevated BMI. There was no effect of new-onset T2DM on incidence of NORCs. There was evidence of detection-time bias, particularly in men. Interpretation: This is the first large-scale study to demonstrate evidence of a BMI-independent associations between new-onset T2DM and incident cancer. In men, this was primarily driven by hepatocellular carcinoma, pancreatic cancer, and kidney cancer. In women, the underlying cancers driving this relationship were less clearly defined. Funding: This study was funded by Cancer Research UK and administered through the Manchester Cancer Research Centre MB-PhD scheme (SEBCATP-2023/100010).

Importance: Evidence on GLP-1/GIP therapies is largely derived from trials enrolling selected populations or medical records that miss utilization outside healthcare channels. No nationally representative cohort has characterized real-world uptake, indications, and access. Objective: To characterize GLP-1/GIP prevalence, indication, clinical profile, and access. Design: Prospective cohort study with three GLP-1/GIP surveillance waves (March 2024, December 2024, October 2025). Setting: The Understanding America Study, an address-based, nationally representative panel of approximately 15,000 US adults aged 18+ years initiated in 2014. Participants: UAS participants responding to at least one surveillance wave (n=9150). Exposures: GLP-1/GIP use status (never vs any use, comprising current and former use), self-reported primary indication (diabetes, weight loss, or other), and access pathway (traditional vs non-traditional). Main Outcomes and Measures: Survey-weighted prevalence of GLP-1/GIP use, overall and by indication and access pathway; sociodemographic, cardiometabolic, treatment, and access characteristics; and smartwatch-derived resting heart rate, heart rate variability, maximum activity heart rate, step count, and sleep duration and variability. Results: Among n=9150 adults (1274 with any use; 60.9% female; median age 53 years), weighted prevalence increased 46%, from 8.2% (March 2024) to 12.0% (October 2025) representing 32 million. Weight-loss indications grew, reaching nearly half of use (4.1% to 5.6%); diabetes-indicated use was stable (5.3% to 5.4%). Users carried high cardiometabolic burden (obesity, 68.2%; diabetes, 53.6%) but diverged by indication: diabetes-indicated users were older (median, 59 vs 49 years), whereas weight-loss-indicated users were more often female (69.9% vs 51.3%) and healthier. One in three users (~9 million) had non-traditional access, especially in weight-loss-indicated users, of whom 33% had no conventional prescription; 41% used compounding, online, or foreign pharmacies; and, 43% lacked coverage. Non-traditional users were five times as likely to report an unlisted, likely compounded formulation (19.8% vs 4.1%). All p<0.05. Conclusions and Relevance: Real-world GLP-1/GIP use has grown rapidly and diversified substantially in indication, access, and population profile. One in 3 users obtained treatment through nontraditional channels largely invisible to claims data, raising long-term safety, efficacy, and coverage questions. GLIMMER provides a public, nationally representative longitudinal evidence base for future payer and provider decisions.

Introduction: Shared medical appointments (SMAs) are medical visits where multiple individuals are seen together in a group setting. For patients with inherited cardiovascular disease, where multiple family members often require ongoing cardiac care and screening, family SMAs may be particularly valuable as a tool to facilitate family communication and comprehension of their condition. This research aimed to identify patient perspectives on the potential benefits and challenges of family SMAs in comparison to an existing individual clinic model. Methods: Qualitative semi-structured interviews were conducted with adult family representatives. Each family had at least one family member seen at the adult and pediatric inherited cardiovascular disease clinics. Interview recordings were transcribed verbatim and inductively coded using a content analysis approach. Results: Sixteen families were interviewed in this study. The mean age of the family representative interviewed was 43.4 years ({+/-} 9.3 SD), and they were followed at Stanford Health Care for a mean of 7.3 years ({+/-} 4.2 SD). 81.2% (13/16) of families said they would find family SMAs beneficial. For interested families who consented to recorded interviews (n=12), benefits and challenges fell into two major categories: care quality and access and logistics. Interested families thought family SMAs would provide an added care quality benefit by increasing understanding among adults, children, and providers (83.3%, 10/12). Six of twelve participants interested in having family SMA visits felt there would be logistical/access-based benefits to this new model (50%, 6/12). Families also identified possible challenges with this model, such as less individualized care, potential privacy concerns, and concerns regarding the smoothness of the clinic process in coordinating a family SMA. Conclusion: The majority of families believed a family SMA model would provide added benefit to families with inherited cardiovascular disease, but requires thoughtful implementation and should be tailored to families? unique needs.

Introduction Diabetes distress describes the psychological and emotional burden of living with diabetes and is associated with reduced self-management and adverse diabetes outcomes. Clinical guidelines recommend routine assessment and management of diabetes distress, but this is not always implemented. Therefore, there is a need to develop approaches to deliver emotional health support in routine clinical care more effectively. We describe here the protocol for a study to I) assess the feasibility of implementation of the D-stress Pathway, comprising Enhanced Usual Care (EUC) and an online, group-based, psychological diabetes distress reduction intervention called REDUCE, ii) evaluate the feasibility of the study protocol iii) detect an effect signal of diabetes distress score and Interstitial Glucose Time in Range and iv) refine initial programme theories of how both interventions (EUC and REDUCE) work, for whom, and under what circumstances. Methods This feasibility study includes a multicentre trial within a cohort design (TWICs) where sites have a staggered exposure to the interventions alongside a realist process evaluation. Four UK NHS diabetes services will recruit 80 adults with type 1 diabetes ([&ge;]1 year) using continuous glucose monitoring (CGM) ([&ge;]3 months). All participants will receive EUC and provide monthly data over 7 months on diabetes distress (measured by the Type 1 Diabetes Distress Assessment System (T1DDAS) and interstitial glucose measured by using continuous glucose monitoring. Participants with elevated diabetes distress, will be offered the six-week, group-based, online REDUCE intervention plus EUC, compared to EUC alone. Up to twenty participants with type 1 diabetes, ten family members/friends, sixteen healthcare professionals delivering EUC and five REDUCE facilitators will be interviewed to explore their experience of receiving training and delivering the D-stress Pathway. Up to 20 EUC consultations and REDUCE sessions will be observed. Analysis Feasibility will be assessed against pre-specified progression criteria and analysed descriptively using summary statistics. Primary outcomes include baseline level of diabetes distress, recruitment rate, intervention uptake, and data completeness, which will be analysed descriptively. Qualitative data will be analysed using framework analysis guided by realist programme theories developed for this study. Ethics Ethics approval has been granted by NHS Research Ethics Committee (REC) (Bromley REC: 25/LO/0469) and Health Research Authority obtained. All participants will provide informed consent. Trial registration no: Registered at ClinicalTrials.gov number NCT07193446 on 26/11/2025. Protocol and statistical analysis plan: The trial protocol and statistical analysis plan can be accessed at ClinicalTrials.gov.

Background Ambient AI documentation tools, known as scribes, are entering routine clinical practice at scale, but the evidence comparing the notes they produce against clinician-written notes is dominated by single-site, single-language studies that rely on human review to find errors, a method known to miss most documentation errors. Methods We conducted a paired simulation across five countries and languages (Cambridge/English, Barcelona/Spanish, Milan/Italian, Paris/French, Cologne/German; 385 paired consultations, 770 notes). From each actor-performed consultation, an AI scribe (Heidi) and a junior-to-middle-grade clinician independently produced a note. Notes were scored on the PDQI-9 by evaluators blinded to authorship. Documentation errors were identified by two methods of deliberately different sensitivity - clinician adjudication, and a calibrated automated reviewer externally validated against a blinded ten-clinician panel - then graded for clinical risk by a three-model panel. The co-primary outcomes were PDQI-9 total and Critical+High error burden, the latter reported under both detection arms. The analysis plan was registered before any pooling across sites. Results AI notes scored higher than clinician notes on the PDQI-9 (40.6 vs 35.6; difference +5.08, 95% CI 4.6-5.6; Cohen dz=0.55), consistently across all five sites (dz 0.41-0.75), and were less dispersed (5.7% of AI vs 27.8% of clinician notes fell below the study pre-specified low-score threshold (<32)). On the principal safety outcome - the paired probability that a note carried [&ge;]Critical+High error - clinician notes were affected more often under both detection arms: 61.0% versus 24.4% by the calibrated reviewer (relative risk 2.50, 95% CI 2.09-3.00) and 21.8% versus 6.2% by clinician adjudication (relative risk 3.50, 95% CI 2.32-5.27). The difference was largest for omissions. Unaided clinician review identified roughly 12% of the errors the calibrated reviewer retained, and a smaller fraction in AI notes than in clinician notes. Conclusions In this simulation, AI-generated notes scored higher on documentation quality, varied less, and carried fewer clinically significant errors than notes written on the same consultations by junior-to-middle-grade clinicians. The magnitude of the safety difference depends on the sensitivity of error detection, so we report both detection regimes and bound rather than point-estimate the absolute error rate. Extension to live practice, consultant-authored documentation, and notes as filed after clinician editing remains to be established.

Objectives: To examine the conformance to type 2 diabetes NICE guidelines across cardiovascular risk strata; and to quantify geographical variation in treatment pathways following the COVID-19 pandemic, encompassing guideline changes. Design: We carried out a retrospective observational study using linked electronic health records across England. Process mining, a data driven method that can reconstruct clinical treatment pathways, was applied to map 12-month treatment trajectories after treatment initiation. Conformance with NICE NG28 (2022) was quantified using a structural similarity index. Further, behavioural and entropy-based similarity (capturing treatment variability and complexity) measures were used to assess sequencing and heterogeneity of treatment. Setting: Primary and secondary care in England datasets within the National Health Service England Secure Data Environment (NHSE SDE), analysed first at national level and then across 42 Integrated Care Boards (ICBs) which are the devolved health care geographical delivery regions in England. Participants: 822,650 individuals with newly diagnosed T2DM between 1-February-2022 and 1-November-2025, stratified into low cardiovascular risk (LR-C; QRISK3<10), high risk (HR-C; QRISK3>=10 or receiving statins/blood pressure lowering treatment), and established cardiovascular disease (eCVD-C). Participants were followed for 12 months after first dispensed glucose lowering therapy. Main outcome measure: First line therapy, treatment intensification and switching within 12 months; change in glycated haemoglobin (HbA1c); quantified conformance to NICE recommended pathways; and regional variation in broader similarity measures. Results: Metformin monotherapy was the dominant initiation strategy in LR-C and HR-C cohorts (92.4% and 90.2%, respectively), whereas eCVD-C showed lower uptake of metformin (68.9%) and higher uptake of SGLT2 inhibitors (26.3%). Intensification from metformin to combination therapy was infrequent across all cohorts (<1%), although HR-C demonstrated the highest treatment transitions and switching behaviour. Dispensed SGLT2 inhibitor use was nearly threefold higher in eCVD-C (26.7%) than in LR-C (9.0%) or HR-C (10.7%). Overall, conformance to NICE-recommended pathways remained modest nationally, particularly in LR-C and HR-C. Across 42 ICBs, substantial regional heterogeneity in treatment pathways and guideline conformance was observed, with conformance ranging from 0.29 to 1.00 in LR-C pathways, 0.40 to 1.00 in HR-C pathways, and 0.54 to 0.92 in eCVD pathways. Conclusion: National T2DM treatment pathways for post-pandemic showed higher alignment to NICE guidelines in eCVD-C compared to the other risk groups, with ongoing gaps and large regional variations in other risk groups. Process mining offers a scalable approach to monitor implementation of guideline recommended care that could support learning health systems. Using T2DM during and post COVID-19 pandemic as a case study, this work demonstrates how these methods can assess the use of existing and innovative therapies, identify gaps and guide future adoption to ensure recommended treatments reach the right patient groups.

Background: Systematic reviews of clinical prediction models increasingly include studies using artificial intelligence (AI) and machine learning (ML) methods alongside traditional multivariable regression approaches. A previously published Excel tool enabled standardised data extraction using the CHARMS checklist and risk of bias assessment using PROBAST. The recent publication of the PROBAST+AI framework, which distinguishes the assessment of model development quality from the assessment of model evaluation risk of bias and assesses applicability in both parts, necessitates an updated digital instrument applicable across prediction modelling methods. Methods: We updated an open-access Excel tool to incorporate the full PROBAST+AI framework. The updated template incorporates structural separation between assessment of model development quality and model evaluation risk of bias, with applicability assessed in both parts. It also incorporates updated signalling questions, including those addressing methodological issues particularly relevant to AI/ML, and automates the generation of summary tables and graphical displays. Results: The updated tool (CHARMS & PROBAST+AI Template) contains 11 worksheets and supports data extraction and appraisal for up to 30 prediction models. Dedicated, linked worksheets enable separate assessment of model development and model evaluation, with Domain 4 distinguishing among Apparent, Internal, and External evaluation settings. Key updates include dedicated assessments for predictor pre-processing, class imbalance handling and recalibration, data leakage prevention, and replication of the full model development pipeline within resampling procedures. Automated sheets dynamically format tables and summary charts covering PROBAST+AI parts. Conclusions: The CHARMS & PROBAST+AI Excel template provides a standardised, user-friendly, and rigorous digital framework for systematic reviewers appraising traditional statistical and AI-driven clinical prediction models.

Background Statins and ezetimibe are the preferred lipid-lowering therapies (LLTs) for children with heterozygous familial hypercholesterolaemia (HeFH). Proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i) are newer add-on therapies for individuals not achieving low-density lipoprotein-cholesterol (LDL-C) targets. We evaluated the efficacy and safety of PCSK9i in children aged <18 years with HeFH. Methods Systematic review and pairwise meta-analyses of randomised-controlled trials (RCTs) of evolocumab, alirocumab and inclisiran. Comprehensive bibliographic searches were conducted in February 2026. Risk of bias was assessed with Cochrane RoB 2. Results Of 2798 unique records screened, three RCTs were included (n=451, mean age 13 years, follow-up 24 to 47 weeks). Each trial evaluated either evolocumab, alirocumab or inclisiran against placebo as add-on to baseline LLT. Participants had elevated LDL-C (>3.4 mmol/L [130 mg/dL]) despite stable LLT. Overall risk of bias was low. PCSK9i reduced LDL-C by an average of 35.44% (95% CI -41.74 to -29.14, I2=50.8%) and by 1.63 mmol/L [62.93 mg/dL] (95% CI -1.86 to -1.39, I2=18.6%) compared with placebo. There was no evidence of differences between PCSK9i and placebo in tolerability, growth and maturation, and overall incidence of adverse events. Conclusions PCSK9i add-on therapy leads to substantial reductions in LDL-C in paediatric patients with HeFH failing to achieve LDL-C targets with standard LLT. While the findings of this review support the use of PCSK9i in a subset of children and young people with HeFH, limited trial numbers and short follow-up periods underscore the need for future high-quality studies evaluating long-term safety, effectiveness and cost-effectiveness.