BACKGROUND:The stepped-wedge cluster randomized trial (SW-CRT) is a pragmatic complex design that can be difficult to implement. We aimed to summarize the reported problems and responses to problems in studies recently published after the publication of the reporting guidelines for SW-CRTs. METHODS:We searched the literature for SW-CRTs published between 9 November 2018 and 23 February 2021 to identify reported SW-CRT-related problems (defined as relating to the components of the design, i.e. involving clusters and the staggered intervention implementation) and responses to problems. We carried out a thematic analysis to derive descriptive themes and overarching analytical themes. RESULTS:Among 84 included SW-CRTs, 62 (74%) reported 107 problems related to the SW-CRT design and 38 responses to 36 problems were reported by 24 trials. The "problems" formed six descriptive problem themes: "participant recruitment," "cluster issues" (e.g. cluster merger or dropout), "internal factors" (e.g. logistic or administrative issues), "external factors" (e.g. weather or religious events), "outcome measurement" (e.g. practicalities around measurement of repeated outcomes), and "intervention implementation" (e.g. delays or contamination). The "responses" formed six descriptive themes: "adding new clusters," "modifying the randomization," "reducing contamination," "changing outcomes," "intention-to-treat," and "modifying the analysis." CONCLUSION:SW-CRTs commonly run into problems. Two overarching and conflicting analytical problem themes emerged: the "struggle to adhere to the protocol," given the defining features of the SW-CRT design, when faced against "real-life pressures" created by internal and external factors. Further research is needed to explore whether responses to these problems have resource or integrity ramifications.

BACKGROUND AND OBJECTIVES:Multimorbidity, the coexistence of two or more chronic conditions, affects about 40% of all adults and over half of adults over 60 years. The complexity of multimorbidity (MM) often renders traditional trial designs inadequate, unable to account for the context of interventions, including the interplay of multiple health conditions in daily life. This gap reduces the generalizability and applicability of their results. METHODS:This commentary aims to review the current state of trials targeting or involving patients with MM. Highlighting current limitations and drawing on insights from an international dedicated workshop in Bielefeld, Germany, we identify an ongoing and pressing need for innovative, patient-centered approaches to their design and conduct. RESULTS:We propose a shift toward more holistic and integrative experimental approaches, including developing interventions tailored to the characteristics and needs of patients with MM, establishing relevant outcomes, and enhancing data collection and process evaluation. We specifically advocate for adaptive trial designs, prespecified subgroup analyses, and the incorporation of patient-reported outcomes and experience measures such as burden of care to ensure that research is both comprehensive and reflective of the needs of patients living with MM, their caregivers, and of the clinicians participating in their care. Ethical considerations are discussed in our commentary as well, emphasizing the importance of patient safety, data protection, and informed consent. Finally, we call for the development of specific reporting guidance, such as a SPIRIT extension tailored to MM trials, to help researchers adapt standard protocols to the complex and heterogeneous reality of this population. CONCLUSION:This commentary aims to bridge the gap between research and practice, fostering the development of effective interventions that improve patient outcomes and enhance the quality of care for patients living with MM.

Multiple long-term conditions (MLTC) represent a growing global public health challenge, yet research is hindered by inconsistent outcomes across health-care settings and populations. Although several core outcome sets (COS) have been developed, important gaps remain in their coverage, inclusivity, and measurement validity. This overview of reviews summarised outcomes reported in systematic reviews of MLTC research to identify existing domains, describe how measurement instruments were addressed, and highlight areas requiring standardisation. We conducted a prospectively registered overview of reviews (PROSPERO CRD420251005152), following PRISMA, PRIOR, and SWiM guidelines. Eligible reviews included adults or children with MLTC—defined as the coexistence of two or more chronic conditions—and reported on outcome measures or COS relevant to this population. Five databases (MEDLINE, CINAHL, Scopus, Cochrane Library, COMET (Core Outcome Measures in Effectiveness Trials)) were searched from inception to April 2025. Two reviewers independently screened, extracted data, and appraised quality using the Joanna Briggs Institute checklist. A narrative synthesis mapped outcomes by domain (clinical, patient-reported, service/system, engagement/experience), care setting, and population subgroup. From 6331 records, 10 reviews met inclusion criteria, encompassing 709 primary studies. Four developed COS, and six mapped outcomes without proposing COS. Quality of life and health-care utilisation were most consistently reported; treatment burden, patient engagement, and child outcomes were infrequently assessed. Existing COS advanced standardisation but remained limited in stakeholder diversity, geographic scope, and specification of measurement instruments, with only one including low- and middle-income countries. Greater inclusivity, validation, and global applicability are needed to operationalise agreed domains and improve comparability across MLTC research.

Background Structured medication reviews (SMRs) were introduced in 2020 to address polypharmacy in patients most at risk of medicines-related harm. Aim To evaluate the impact of SMRs on prescribing in primary care. Design and setting Retrospective observational cohort study of electronic health records from patients aged ≥65 years, prescribed ≥1 medications, and fulfilling the specific eligibility criteria for an SMR, registered at practices contributing data to the Oxford Clinical Informatics Digital Hub, between 1 April 2020 and 30 September 2022. Method The association between SMRs and prescription changes was examined by matching individuals who received an SMR to individuals who did not receive an SMR, according to age, sex, and primary care practice, using cumulative density sampling. Analyses were undertaken using adjusted logistic regression. Results Of 635 698 eligible patients, 82 285 (12.9%, 95% confidence interval [CI] = 12.9 to 13.0) received ≥1 SMR during the study observation period. In those prescribed potentially inappropriate drug combinations prior to an SMR, between 12.5% and 40.0% were corrected up to 3 months later. In matched analyses, SMRs were most strongly associated with an increase in new prescriptions of angiotensin-converting enzyme inhibitors (adjusted odds ratio [aOR] 1.56, 95% CI = 1.35 to 1.81), statins (aOR 1.78, 95% CI = 1.57 to 2.02), and antidepressants (aOR 1.45, 95% CI = 1.28 to 1.63). SMRs were also most strongly associated with stopping these drug classes in those previously prescribed treatment. Conclusion SMRs were associated with starting new medications and stopping existing prescriptions compared with usual care. Further work is needed to understand if these changes improved patient outcomes.

Background Pregnant and breastfeeding women and people are often excluded from non-obstetric clinical trials. Exclusion sometimes provides immediate protection. It also causes subsequent population-level harms. The importance of inclusion is widely recognised. However, the rates of inclusion and participation are uncertain, as are the contexts in which pregnant and breastfeeding women and people might choose to take part, and factors which influence inclusion and participation. This rapid scoping review identifies and maps the evidence to fill these gaps. Methods We included research using any study design, published in English between January 2006 and July 2025, where the participants included women and people with experience of pregnancy or breastfeeding, or health care professionals or researchers working with them. We searched MEDLINE, Embase, CINAHL, Google Scholar and Overton, selected websites and references. The most recent search was done on 3 July 2025. We embedded a Study Within A Review. Results We included 54 studies, most focused on the prevention or treatment of infectious diseases. Thirteen studies assessed the proportion of trials which included pregnant women and people; this ranged from 0-8%. Three studies assessed the proportion of trials in which breastfeeding women are included; from 0.5-14%. Data on participation are sparse. 7-90% of participants in five studies considered themselves likely to participate in a non-obstetric clinical trial during pregnancy. Based on six studies we identified and developed four main themes relating to opinions and feelings about inclusion and participation; risk, evidence, culture and trust. We identified and developed six themes grouping factors that affect inclusion and participation from 25 included studies; need for research, fair inclusion, risk, early inclusion, financial concerns, and practical issues. Conclusions Addressing factors that influence inclusion in clinical trials is essential to support pregnant and breastfeeding women and people’s access to evidence-based healthcare and to improve maternal and infant health outcomes. Registration https://osf.io/4am6b/

BACKGROUND:Structured medication reviews (SMRs) were introduced into primary care in England in 2020 for patients living with multiple long-term conditions (MLTC), polypharmacy, increased frailty, in care homes, or at risk of medicines-related harm. SMRs aim to optimise the therapeutic potential of medication and reduce medicine-related harms through holistic reviews. AIM:To explore the day-to-day work being undertaken with, and by, clinical pharmacists to implement, embed, and integrate SMRs into practice, and consider how to optimise SMRs. DESIGN AND SETTING:Qualitative one-to-one interviews with clinical pharmacists undertaking SMRs and SMR service leaders/managers (SMR leads) in England between February 2023 and November 2024. METHOD:Participants were recruited as part of a wider evaluation of the roll-out of SMRs in England. Interview topic guides and qualitative data analysis were informed by normalisation process theory. RESULTS:Eighteen clinical pharmacists and five SMR leads participated. Participants reported often having to explain the purpose of SMRs and clinical pharmacists' roles to patients, partly owing to patients not being informed about SMRs. Participants valued SMRs and expressed that trust-building and tailored consultations were important for optimising medications. Integration of SMRs into routine practice varied because of high workload, inconsistent leadership support, inadequate administrative/pharmacist technician resource, and lack of training. However, participants described SMRs as valuable for identifying and addressing unmet needs and supporting holistic, person-centred care across MLTC pathways. CONCLUSION:The findings demonstrate the need for improved information on SMRs for patients and primary care teams, adequate and appropriate resource allocation, and enhanced support for consultation skills training to optimise medicines use.

Background:The observational SYMPLIFY study reported the accuracy of a multi-cancer early detection (MCED) test in a referred symptomatic population. We explore how the MCED test may contribute to a faster or more efficient diagnosis if acted upon. Methods:We reviewed all cancers diagnosed in SYMPLIFY (ISRCTN10226380) using data collected at study sites plus two years of cancer registry data. All cancer diagnoses were classified based on the congruence between the participant's symptoms, diagnostic referral pathway, MCED test cancer signal origin (CSO) prediction, cancer site, and time to diagnosis. Findings:There were 533 cancers diagnosed among 5461 (9.8%) evaluable participants in SYMPLIFY during the 2-year follow-up period. Among the 79 participants with an apparent false positive test result in the original SYMPLIFY study, 28 (35%) were diagnosed with cancer based on cancer registry data, increasing the MCED PPV to 84.2% (80.1-87.6). In aggregate, only one of the 28 additional patients had a cancer diagnosed that was incongruent with a predicted MCED CSO. Among the 5014 patients with an apparent true negative MCED test result, 113 (2%) received a subsequent cancer diagnosis. In 101 (19%) of the 533 cancers diagnosed, the MCED test result might have contributed to a more efficient diagnosis had it been used to inform the clinical work-up. Conversely, 49 (9%) cancers might have taken longer to diagnose if the MCED test result alone had been used in the diagnostic process, directing investigations based upon an incorrect CSO prediction. Interpretation:These exploratory findings demonstrate a substantially higher rate of cancer diagnoses in symptomatic participants originally classified with a false positive MCED test result than those originally classified as true negative. We show how MCED tests have the potential to assist clinical decision making, which may in turn lead to a timelier cancer diagnosis for one fifth of cancers diagnosed. Funding:GRAIL Bio UK, Ltd. NIHR.

BACKGROUND:Accurate preoperative malignancy risk assessment in intraductal papillary mucinous neoplasm (IPMN) is essential to balance timely intervention for high-grade dysplasia or invasive cancer (HGD/IC) against avoiding unnecessary or premature surgery in low-grade IPMN. This study aimed to externally validate the 2023 International Association of Pancreatology (IAP)/Kyoto guidelines and develop a combined prediction model incorporating routinely collected clinical data and laboratory parameters. METHODS:We conducted a retrospective cohort study of 194 patients who underwent resection for IPMN between 2012 and 2024. We evaluated the predictive performance of the current IAP/Kyoto criteria ("Kyoto model"), developed a clinical model using routinely available laboratory and clinical variables, and integrated both into a combined model. Model performance was assessed using discrimination and calibration metrics, with internal validation via bootstrapping and five-fold cross-validation. RESULTS:The Kyoto model demonstrated modest discrimination (AUC 0.62). The clinical model, incorporating neutrophil-to-lymphocyte ratio (NLR), smoking history, blood glucose, CA19-9, and alkaline phosphatase, achieved an optimism-corrected AUC of 0.76. Compared to the Kyoto model, the combined model (AUC 0.77) significantly improved discrimination and calibration (p < 0.001). At a predicted probability threshold of >0.75, the combined model achieved a 90% specificity and 91% positive predictive value for HGD/IC, identifying a high-risk subgroup suitable for surgical intervention. CONCLUSIONS:Integrating routinely collected clinical and laboratory parameters with guideline-based imaging features shows promise to enhance preoperative identification of high-risk IPMN in patients already being considered for surgical resection. The combined model offers a practical, high-specificity tool to support surgical decision-making in this selected population, though its performance metrics should not be extrapolated to unselected surveillance cohorts. External validation is required before broader clinical implementation.

OBJECTIVES:Improving mental health services through value-based investment is high priority in healthcare systems globally. However, there is lack of comprehensive and robust evidence on the value for money of these services that incorporates several value elements and public preferences. This study aims to demonstrate the application of multicriteria decision analysis (MCDA) in the assessment of 2 early intervention in psychosis (EIP) services in England. METHODS:An MCDA-based evaluation using patient records was conducted to evaluate the value-for-money of 2 EIP services in South-East England: Oxfordshire (EIP-Oxf) and Buckinghamshire (EIP-Bucks). The assessment considered 5 value elements: years of life, quality of life (time to relapse), patient experience (disengagement rates), health inequality (time-to-relapse disparity), and average annual cost. Performance on each value element was estimated using generalized linear models and propensity score matching on electronic health records of 1127 patients. Total MCDA scores integrated standardized predicted means with relative weights that were derived in a previous study. Robustness was assessed using probabilistic sensitivity analysis and service affordability was illustrated in conditional multiattribute acceptability curves. RESULTS:EIP-Oxf outperformed EIP-Bucks in overall scores (0.563 vs 0.552) and offered higher value per pound spend according to cost-per-value ratios (£10 438 per unit of value vs £12 655). Results were driven by lower annual cost per patient and health inequality in EIP-Oxf. CONCLUSIONS:MCDA can facilitate value-for-money assessments of mental health services, addressing gaps in comprehensive rationing frameworks. This approach provides a systematic, evidence-driven method for local decision making, with potential for broader healthcare applications.

Artificial intelligence (AI) and digital health technologies are increasingly used in the medical field. Despite promises of leading the future of personalized medicine and better clinical outcomes, implementation of AI faces barriers for deployment at scale. We introduce a novel implementation framework that can facilitate digital health designers, developers, patient groups, policymakers, and other stakeholders, to co-create and solve issues throughout the life cycle of designing, developing, deploying, monitoring, and maintaining algorithmic models. This framework targets health systems that integrate multiple machine learning (ML) models with various modalities. This design thinking approach promotes clinical utility beyond model prediction, combining privacy preservation with clinical parameters to establish a reward function for reinforcement learning, ranking competing models. This allows leveraging explainable AI (xAI) methods for clinical interpretability. Governance mechanisms and orchestration platforms can be integrated to monitor and manage models. The proposed framework guides users toward human-centered AI design and developing AI-enhanced health system solutions.

Background:Blood tests used to identify patients at increased risk of undiagnosed cancer are commonly used in isolation, primarily by monitoring whether results fall outside the normal range. Some prediction models incorporate changes over repeated blood tests (or trends) to improve individualized cancer risk identification, as relevant trends may be confined within the normal range. Objective:Our aim was to critically appraise existing diagnostic prediction models incorporating blood test trends for the risk of cancer. Methods:MEDLINE and EMBASE were searched until April 3, 2025 for diagnostic prediction model studies using blood test trends for cancer risk. Screening was performed by 4 reviewers. Data extraction for each article was performed by 2 reviewers independently. To critically appraise models, we narratively synthesized studies, including model building and validation strategies, model reporting, and the added value of blood test trends. We also reviewed the performance measures of each model, including discrimination and calibration. We performed a random-effects meta-analysis of the c-statistic for a trends-based prediction model if there were at least 3 studies validating the model. The risk of bias was assessed using the PROBAST (prediction model risk of bias assessment tool). Results:We included 16 articles, with a total of 7 models developed and 14 external validation studies. In the 7 models derived, full blood count (FBC) trends were most commonly used (86%, n=7 models). Cancers modeled were colorectal (43%, n=3), gastro-intestinal (29%, n=2), nonsmall cell lung (14%, n=1), and pancreatic (14%, n=1). In total, 2 models used statistical logistic regression, 2 used joint modeling, and 1 each used XGBoost, decision trees, and random forests. The number of blood test trends included in the models ranged from 1 to 26. A total of 2 of 4 models were reported with the full set of coefficients needed to predict risk, with the remaining excluding at least one coefficient from their article or were not publicly accessible. The c-statistic ranged 0.69-0.87 among validation studies. The ColonFlag model using trends in the FBC was commonly externally validated, with a pooled c-statistic=0.81 (95% CI 0.77-0.85; n=4 studies) for 6-month colorectal cancer risk. Models were often inadequately tested, with only one external validation study assessing model calibration. All 16 studies scored a low risk of bias regarding predictor and outcome details. All but one study scored a high risk of bias in the analysis domain, with most studies often removing patients with missing data from analysis or not adjusting the derived model for overfitting. Conclusions:Our review highlights that blood test trends may inform further investigation for cancer. However, models were not available for most cancer sites, were rarely externally validated, and rarely assessed calibration when they were externally validated.

OBJECTIVES:This study explored how Structured Medication Reviews (SMRs) are being undertaken and the challenges to their successful implementation and sustainability. DESIGN:A cross-sectional mixed methods online survey. SETTING:Primary care in England. PARTICIPANTS:120 clinical pharmacists with experience in conducting SMRs in primary care. RESULTS:Survey responses were received from clinical pharmacists working in 15 different regions. The majority were independent prescribers (62%, n=74), and most were employed by Primary Care Networks (65%, n=78), delivering SMRs for one or more general practices. 61% (n=73) had completed, or were currently enrolled in, the approved training pathway. Patient selection was largely driven by the primary care contract specification: care home residents, patients with polypharmacy, patients on medicines commonly associated with medication errors, patients with severe frailty and/or patients using potentially addictive pain management medication. Only 26% (n=36) of respondents reported providing patients with information in advance. The majority of SMRs were undertaken remotely by telephone and were 21-30 min in length. Much variation was reported in approaches to conducting SMRs, with SMRs in care homes being deemed the most challenging due to additional complexities involved. Challenges included not having sufficient time to prepare adequately, address complex polypharmacy and complete follow-up work generated by SMRs, issues relating to organisational support, competing national priorities and lack of 'buy-in' from some patients and General Practitioners. CONCLUSIONS:These results offer insights into the role being played by the clinical pharmacy workforce in a new country-wide initiative to improve the quality and safety of care for patients taking multiple medicines. Better patient preparation and trust, alongside continuing professional development, more support and oversight for clinical pharmacists conducting SMRs, could lead to more efficient medication reviews. However, a formal evaluation of the potential of SMRs to optimise safe medicines use for patients in England is now warranted.

OBJECTIVES:Evidence-based support from healthcare professionals improves smoking cessation outcomes, yet intervention rates among UK general practitioners (GPs) remain suboptimal. This exploratory study explored whether framing messages around moral responsibility influences clinicians' intentions to offer smoking cessation support and explored their attitudes towards smoking. DESIGN:A between-subjects online experiment was conducted in May 2023 with 300 UK-based GPs and medical students. METHODS:Participants were randomised to one of three message conditions: professional obligation, shared responsibility, or neutral control. They rated their desire, duty, and intention to offer cessation support across clinical scenarios and completed attitude measures. RESULTS:Compared with control, professional obligation framing was associated with higher intention scores (β = .20, 95% CI [.01, .39]); shared responsibility showed no effect. Subgroup analyses suggested stronger effects among medical students. Contextual factors were influential: higher scores were observed for cardiovascular disease (β = .80) and bipolar disorder (β = .21), while time pressure and patient disinterest reduced intention (β = -.15 and -.14). Attitudes were mixed: 70% viewed smoking as a lifestyle choice, while 88% agreed addiction is a disease. CONCLUSIONS:Professional obligation framing was associated with clinicians' intentions to offer cessation support, particularly among early-career clinicians. Attitudinal inconsistencies highlight a disconnect between clinicians' perceptions and public health guidance. Responsibility-based messaging may be promising for education and training. Given single-item outcomes and the exploratory design, findings should be interpreted cautiously and future work should examine measurement properties more rigorously.

BACKGROUND:Prognostic tools for febrile illnesses are urgently required in resource-constrained community contexts. Circulating immune and endothelial activation markers stratify risk in common childhood infections. We aimed to assess their use in children with febrile illness presenting from rural communities across Asia. METHODS:Spot Sepsis was a prospective cohort study across seven hospitals in Bangladesh, Cambodia, Indonesia, Laos, and Viet Nam that serve as a first point of contact with the formal health-care system for rural populations. Children were eligible if aged 1-59 months and presenting with a community-acquired acute febrile illness that had lasted no more than 14 days. Clinical parameters were recorded and biomarker concentrations measured at presentation. The primary outcome measure was severe febrile illness (death or receipt of organ support) within 2 days of enrolment. Weighted area under the receiver operating characteristic curves (AUC) were used to compare prognostic accuracy of endothelial activation markers (ANG-1, ANG-2, and soluble FLT-1), immune activation markers (CHI3L1, CRP, IP-10, IL-1ra, IL-6, IL-8, IL-10, PCT, soluble TNF-R1, soluble TREM1 [sTREM1], and soluble uPAR), WHO danger signs, the Liverpool quick Sequential Organ Failure Assessment (LqSOFA) score, and the systemic inflammatory response syndrome (SIRS) score. Prognostic accuracy of combining WHO danger signs and the best performing biomarker was analysed in a weighted logistic regression model. Weighted measures of classification were used to compare prognostic accuracies of WHO danger signs and the best performing biomarker and to determine the number of children needed to test (NNT) to identify one additional child who would progress to severe febrile illness. The study was prospectively registered on ClinicalTrials.gov, NCT04285021. FINDINGS:3423 participants were recruited between March 5, 2020, and Nov 4, 2022, 18 (0·5%) of whom were lost to follow-up. 133 (3·9%) of 3405 participants developed severe febrile illness (22 deaths, 111 received organ support; weighted prevalence 0·34% [95% CI 0·28-0·41]). sTREM1 showed the highest prognostic accuracy to identify patients who would progress to severe febrile illness (AUC 0·86 [95% CI 0·82-0·90]), outperforming WHO danger signs (0·75 [0·71-0·80]; p<0·0001), LqSOFA (0·74 [0·69-0·78]; p<0·0001), and SIRS (0·63 [0·58-0·68]; p<0·0001). Combining WHO danger signs with sTREM1 (0·88 [95% CI 0·85-0·91]) did not improve accuracy in identifying progression to severe febrile illness over sTREM1 alone (p=0·24). Sensitivity for identifying progression to severe febrile illness was greater for sTREM1 (0·80 [95% CI 0·73-0·85]) than for WHO danger signs (0·72 [0·66-0·79]; NNT=3000), whereas specificities were comparable (0·81 [0·78-0·83] for sTREM1 vs 0·79 [0·76-0·82] for WHO danger signs). Discrimination of immune and endothelial activation markers was best for children who progressed to meet the outcome more than 48 h after enrolment (sTREM1: AUC 0·94 [95% CI 0·89-0·98]). INTERPRETATION:sTREM1 showed the best prognostic accuracy to discriminate children who would progress to severe febrile illness. In resource-constrained community settings, an sTREM1-based triage strategy might enhance early recognition of risk of poor outcomes in children presenting with febrile illness. FUNDING:Médecins Sans Frontières, Spain, and Wellcome. TRANSLATIONS:For the Arabic and French translations of the abstract see Supplementary Materials section.

BackgroundNHS England issued commissioning guidance on 18 low-priority treatments which should not be routinely prescribed in primary care. We aimed to monitor the impact of an educational intervention delivered to regional prescribing advisors by senior pharmacists from NHS England on the primary care spend on low-priority items.MethodsAn opportunistic randomised, controlled parallel-group trial. Participants (clinical commissioning groups, CCGs) were randomised to intervention or control in a 1:1 ratio. The intervention group were invited to participate. The intervention was a one-off educational session. Our primary outcomes concerned the total prescribing of low-priority items in primary care. Secondary outcomes concerned the prescribing of specific low-priority items. We also measured the impact on information-seeking behaviour.Results40 CCGs were randomised, 20 allocated to intervention, with 11 receiving the intervention. There was no significant impact on any prescribing outcomes. There was some possible evidence of increased engagement with data, in the form of CCG email alert sign-ups (p = 0.077). No harms were detected.ConclusionsA one-off intervention delivered to CCGs by NHS England did not significantly influence low-priority prescribing. This trial demonstrates how routine interventions planned to improve uptake or adherence to healthcare guidance can be delivered as low-cost randomised trials and how to robustly assess their effectiveness.Trial registrationISRCTN31218900, October 01 2018.

BACKGROUND:Nearly 900,000 people in the UK live with dementia (1), yet transitions between cognitive states and death remain poorly understood. This study explores the influence of sex, ethnicity, and socioeconomic status on transitions across no cognitive impairment (NCI), mild cognitive impairment (MCI), dementia, and death. METHOD:We analysed electronic health records from the UK Clinical Practice Research Datalink (2000-2022), including 668,554 adults diagnosed with dementia or MCI. Participants were followed from the 10 years before their first recorded dementia or MCI diagnosis, tracking transitions to MCI until death or moved out of the records. Data on sex, ethnicity, and socioeconomic status (indexed by multiple deprivation) were collected. Transition hazard ratios (HRs) and time probabilities in both directions were estimated using a multistate Markov model in R. RESULT:Among 668,554 individuals, 423,715 (63.4%) had MCI, 633,505 (94.2%) had dementia, and 317,415 (47.4%) died. Nearly 62% were women, and the average age at dementia diagnosis was 81 years (standard deviation 9 years). The average duration a person stayed in NCI, MCI, and dementia state were 2.7 years, 5 months, and 8 months, respectively. Death rates were lower from NCI than from MCI or dementia. Women showed reduced risks of transitioning from MCI to dementia (HR 0.91, 95% CI 0.89-0.94), MCI to NCI (HR 0.85, 95% CI 0.83-0.87), and dementia to death (HR 0.95, 95% CI 0.94-0.96) compared to men. Non-white populations had higher risks of transitioning from NCI to MCI (HR 1.06, 95% CI 1.03-1.09) and MCI to dementia (HR 1.13, 95% CI 1.06-1.21) but lower risks for dementia to death and MCI to NCI (reserve transition) compared to white populations. Higher socioeconomic status correlated with increased transitions from MCI to dementia and MCI to NCI. Transition probabilities from MCI to dementia or dementia to death rose over time while reverse transitions declined. The likelihood of moving from NCI to MCI or MCI to dementia peaked at 5 years. CONCLUSION:Sex, ethnicity, and socioeconomic status influence cognitive trajectories in the UK. The substantial probabilities of reverse transitions, such as dementia to MCI and MCI to NCI, highlight areas for further exploration.

BACKGROUND:Smoking significantly increases the risk of cardiovascular diseases (CVD), yet quitting smoking after diagnosis of CVD can mitigate further negative impacts. However, encouraging smoking cessation remains a challenge for General Practitioners (GPs) with concerns regarding mental health. Since 2004, the UK's Quality and Outcomes Framework (QOF) incentivises GP smoking cessation support. Despite this, a significant proportion of individuals diagnosed with CVD continue to smoke after diagnosis. This study aims to investigate the frequencies and types of smoking cessation interventions offered to people with CVD (defined as coronary heart disease (CHD) and stroke), with and without mental illness, and assess their association with successful cessation. METHODS:This retrospective cohort study examined adults diagnosed with CHD or stroke using the QResearch general practice records database (1996-2019). We evaluated the frequency and types of smoking cessation interventions documented in patients' records, including education, brief interventions, pharmacological support, referrals, and counselling. Logistic regression assessed the relationship between recorded interventions and smoking abstinence rates within the one-year post-index event, considering QOF incentives and mental illness presence. RESULTS:While smoking cessation education was common in general practice settings, prescriptions for nicotine replacement therapy or other evidence-based interventions were comparatively low. CHD and stroke populations showed a significant association between any intervention and smoking cessation within one year (CHD: OR 1.41, 95% CI 1.36-1.45; stroke: OR 1.49, 95% CI 1.43-1.55). Education consistently correlated with higher cessation likelihoods, while other interventions were linked to lower rates. Individuals with common and serious mental illness were less likely to quit, irrespective of intervention. QOF implementation led to increased documentation of advice but not intensive support or treatment, with pre-QOF interventions associated with significantly increased abstinence likelihoods (CHD: OR 5.09, 95% CI 4.84-5.35; stroke: OR 4.44, 95% CI 4.07-4.86). CONCLUSIONS:Financial incentives for GP smoking cessation support outlined in QOF may not suffice to enhance methods that are more efficacious or improve cessation rates, especially among people with mental illness. Practical strategies that provide tangible support and treatment are needed for CVD patients, including those with mental illness, to facilitate successful cessation.

Nearly 900,000 people in the UK live with dementia (1), yet transitions between cognitive states and death remain poorly understood. This study explores the influence of sex, ethnicity, and socioeconomic status on transitions across no cognitive impairment (NCI), mild cognitive impairment (MCI), dementia, and death. We analysed electronic health records from the UK Clinical Practice Research Datalink (2000–2022), including 668,554 adults diagnosed with dementia or MCI. Participants were followed from the 10 years before their first recorded dementia or MCI diagnosis, tracking transitions to MCI until death or moved out of the records. Data on sex, ethnicity, and socioeconomic status (indexed by multiple deprivation) were collected. Transition hazard ratios (HRs) and time probabilities in both directions were estimated using a multistate Markov model in R. Among 668,554 individuals, 423,715 (63.4%) had MCI, 633,505 (94.2%) had dementia, and 317,415 (47.4%) died. Nearly 62% were women, and the average age at dementia diagnosis was 81 years (standard deviation 9 years). The average duration a person stayed in NCI, MCI, and dementia state were 2.7 years, 5 months, and 8 months, respectively. Death rates were lower from NCI than from MCI or dementia. Women showed reduced risks of transitioning from MCI to dementia (HR 0.91, 95% CI 0.89–0.94), MCI to NCI (HR 0.85, 95% CI 0.83–0.87), and dementia to death (HR 0.95, 95% CI 0.94–0.96) compared to men. Non-white populations had higher risks of transitioning from NCI to MCI (HR 1.06, 95% CI 1.03–1.09) and MCI to dementia (HR 1.13, 95% CI 1.06–1.21) but lower risks for dementia to death and MCI to NCI (reserve transition) compared to white populations. Higher socioeconomic status correlated with increased transitions from MCI to dementia and MCI to NCI. Transition probabilities from MCI to dementia or dementia to death rose over time while reverse transitions declined. The likelihood of moving from NCI to MCI or MCI to dementia peaked at 5 years. Sex, ethnicity, and socioeconomic status influence cognitive trajectories in the UK. The substantial probabilities of reverse transitions, such as dementia to MCI and MCI to NCI, highlight areas for further exploration.

BACKGROUND:Financial incentives (money, vouchers, or self-deposits) can be used to positively reinforce smoking cessation. They may be used as one-off rewards, or in various schedules to reward steps towards sustained smoking abstinence (known as contingency management). They have been used in workplaces, clinics, hospitals, and community settings, and to target particular populations. This is a review update. The previous version was published in 2019. OBJECTIVES:Primary To assess the long-term effects of incentives and contingency management programmes for smoking cessation in mixed and pregnant populations. Secondary To assess the long-term effects of incentives and contingency management programmes for smoking cessation in mixed populations, considering whether incentives were offered at the final follow-up point. To assess the difference in outcomes for pregnant populations, considering whether rewards were contingent on abstinence or guaranteed. SEARCH METHODS:For this update, we searched CENTRAL, MEDLINE, Embase, PsycINFO, and two trials registers on 2 November 2023, and the Cochrane Tobacco Addiction Group Specialised Register on March 2023, together with reference checking, citation searching, and contact with study authors to identify additional studies. SELECTION CRITERIA:We considered only randomised controlled trials (RCTs), allocating individuals, workplaces, groups within workplaces, or communities to smoking cessation incentive schemes or control conditions. We included studies in a mixed-population setting (e.g. community-, work-, clinic- or institution-based), studies with specific populations (e.g. those with diagnosed mental health conditions), and studies in pregnant people who smoke. DATA COLLECTION AND ANALYSIS:We used standard Cochrane methods. The primary outcome measure in the mixed-population studies was abstinence from smoking at longest follow-up (at least six months from the start of the intervention). In the trials of pregnant people, we used abstinence from smoking measured at the longest follow-up, and at least to the end of the pregnancy. Where available, we pooled outcome data using a Mantel-Haenszel random-effects model, with results reported as risk ratios (RRs) and 95% confidence intervals (CIs), using adjusted estimates for cluster-randomised trials. We analysed studies carried out in mixed populations separately from those carried out in pregnant populations. MAIN RESULTS:Forty-eight mixed-population studies met our inclusion criteria, recruiting more than 21,924 participants; 15 of these are new to this version of the review. Studies were set in varying locations, including community settings, clinics or health centres, workplaces, and outpatient drug clinics. We judged eight studies to be at low risk of bias, and 16 to be at high risk of bias, with the remaining 24 studies at unclear risk. Thirty-three of the trials were run in the USA, two in Thailand, one in the Philippines, one in Hong Kong, and one in South Africa. The rest were European. Incentives offered included cash payments, self-deposits, or vouchers for goods and groceries, offered directly or collected and redeemable online. The pooled RR for quitting with incentives at longest follow-up (six months or more) compared with controls was 1.52 (95% CI 1.33 to 1.74; I2 = 23%; 39 studies, 18,303 participants; high-certainty evidence). Results were not sensitive to the exclusion of seven studies that offered an incentive for cessation at long-term follow-up (result excluding those studies: RR 1.46, 95% CI 1.23 to 1.73; I2 = 26%; 32 studies, 15,082 participants), suggesting the impact of incentives continues for at least some time after incentives cease (at least six months). For this update, we included an adjusted analysis incorporating three cluster-RCTs. The pooled odds ratio was 1.57 (95% CI 1.37 to 1.79; I2 = 30%; 43 studies, 23,960 participants; high-certainty evidence). Although not always clearly reported, the total financial amount of incentives varied considerably between trials, from zero (self-deposits), to a range of between 45 US dollars (USD) and USD 1185. There was no clear difference in effect between trials offering low or high total value of incentives, nor those encouraging redeemable self-deposits. We ran an updated exploratory meta-regression and found no significant association between the outcome and the total value of the financial incentive (P = 0.963). Any such indirect comparison is particularly crude in this context, due to differences in the cultural significance of financial amounts (e.g. USD 50 might have different significance in different contexts). We included 14 studies of 4314 pregnant people (11 conducted in the USA, one in France, and two in the UK). We judged four studies to be at low risk of bias, three at high risk of bias, and eight at unclear risk. When pooled, the 13 trials with usable data delivered a risk ratio at longest follow-up (up to 48 weeks postpartum) of 2.13 (95% CI 1.58 to 2.86; I2 = 31%; 13 studies, 3942 participants; high-certainty evidence), in favour of incentives. AUTHORS' CONCLUSIONS:Overall, our conclusion from this latest review update remains that there is high-certainty evidence that incentives improve smoking cessation rates at long-term follow-up in mixed population studies. The evidence demonstrates that the effectiveness of incentives is sustained even when the last follow-up occurs after the withdrawal of incentives. There is also now high-certainty evidence that incentive schemes conducted amongst pregnant people who smoke improve smoking cessation rates, both at the end of pregnancy and postpartum. This represents a change from the previous update in which we rated this evidence as moderate certainty. Current and future research might more precisely explore differences between trials offering low or high cash incentives and self-incentives (deposits), within a variety of smoking populations, focusing on low- and middle-income countries where the burden of tobacco use remains high.