Multiple Long-term Conditions Research Articles

Barriers and facilitators of self-management of diabetes amongst people experiencing socioeconomic deprivation: A systematic review and qualitative synthesis.

The number of people living with diabetes is rising worldwide and a higher prevalence of diabetes has been linked to those experiencing socioeconomic deprivation. Self-management strategies are vital and known to reduce the risks of long-term complications amongst people living with diabetes. Lack of knowledge about self-care activity required to manage diabetes is a key barrier to successful self-management. Self-management interventions can be less effective in socioeconomically deprived populations which can increase the risk of exacerbating health inequalities. The purpose of this review is to identify and synthesise qualitative evidence on the barriers and facilitators of self-management of diabetes amongst people who are socioeconomically disadvantaged. MEDLINE, EMBASE, AMED, PsycINFO and CINAHL Plus were searched for qualitative studies concerning self-management of multiple long-term conditions amongst socioeconomically disadvantaged populations. Relevant papers which focused on diabetes were identified. Data were coded and thematically synthesised using NVivo. From the search results, 79 qualitative studies were identified after full-text screening and 26 studies were included in the final thematic analysis. Two overarching analytical themes were identified alongside a set of subthemes: (1) Socioeconomic barriers to diabetes self-management; healthcare costs, financial costs of healthy eating, cultural influences, living in areas of deprivation, competing priorities and time constraints, health literacy, (2) facilitators of diabetes self-management; lifestyle and having goals, support from healthcare providers, informal support. Self-management of diabetes is challenging for people experiencing socioeconomic deprivation due to barriers associated with living in areas of deprivation and financial barriers surrounding healthcare, medication and healthy food. Support from healthcare providers can facilitate self-management, and it is important that people with diabetes have access to interventions that are designed to be inclusive from a cultural perspective as well as affordable. A patient advisory group contributed to the research questions and interpretation of the qualitative findings by reflecting on the themes developed.

#2832 Lean tissue mass is associated with mortality across different stages of chronic kidney disease: a systematic review and meta-analysis

Abstract Background and Aims Loss of lean tissue mass (LLTM) commonly occurs in multiple long-term conditions (LTC), including chronic kidney disease (CKD), and is thought to be associated with adverse outcomes including mortality, frailty surrogates and poor quality of life. It remains unclear whether LLTM is directly associated with mortality in CKD after adjusting for the severity of CKD or the degree of multimorbidity, and whether such associations remain in other LTC with similar levels of multimorbidity, such as heart failure (HF). Method A systematic review was conducted in adult CKD [kidney transplant (KT), CKDG3-5 or dialysis treated kidney failure (D-KF)] and HF patients who had whole body bioimpedance defined lean tissue mass (BI-LTM). The primary outcome was mortality, with secondary outcomes including hospitalisation and health related quality of life (HRQoL). The review was registered with PROSPERO (CRD42021240688) and was conducted according to PRISMA guidelines. Electronic database searches of MEDLINE, EMBASE, AMED, CINAHL, PsychInfo, Web of Science, CENTRAL, ICTRP and ISRCTN were searched from inception until June 2023. Data extraction and risk of bias assessments, using the Quality in Prognosis Studies (QUIPS) tool, was performed by two independent reviewers. Random effects meta-analysis was conducted using STATA SE16.2 using restricted maximum likelihood (REML) estimation. Results From 10,024 citations, 126 studies were identified (100 D-KF, 12 CKDG3-5, 2 KT, 3 mixed CKD and 9 HF) reporting outcomes on 143,053 D-KF, 15,164 CKDG3-5, 346 KTR and 3716 HF patients respectively. There were 1,227 deaths (over 2-5 years) in the HF studies and 16,471 deaths (over 1-20 years) in the CKD studies. The weighted mean eGFRCreat was 54 and 42 ml/min/1.73 m2 in the KT and CKDG3-5 studies, with only 3 HF studies reporting any measure of renal function (all using categorical cut offs). In 87 studies survival analyses of all-cause mortality (ACM) showed that BI-LTM was associated with mortality in 67%, 100%, 85% and 74% of the HF, KT, CKDG3-5 and D-KF studies respectively after adjusting for age, sex, diabetic status, comorbidity score, CRP / IL-6, albumin and bioimpedance defined fluid measures in 93%, 77%, 64%, 17%, 32%, 59% and 24% of analyses. Meta-analysis within D-KF studies reporting MVA revealed a 1-degree decrease in phase angle (pooled HR 1.82, 95% CI 1.50-2.20: Fig. 1A) and lean tissue index <10th percentile (pooled HR 1.48, 95% CI 1.31-1.66: Fig. 1B) was associated with ACM. Leave one out meta-analysis and sensitivity analyses removing studies at high-risk of statistical analysis and study confounding bias confirmed these pooled estimates were robust. Of the studies reporting secondary outcomes including hospitalisation and HRQoL (including the Short Form-36 and Kidney Disease Quality of Life Instrument), 67% showed associations with BI-LTM. Conclusion LLTM is associated with mortality across all stages of CKD and in heart failure. Furthermore, LLTM is associated with adverse outcomes such as hospitalisation and poor quality of life. This study confirms that LLTM potentially has an important role in the explanatory pathway for adverse outcomes in patients with LTCs, including CKD. Using BI-LTM may provide a way to identify early LLTM and target interventions to reduce the risk of adverse outcomes in these multimorbid cohorts.

#560 The representation of multimorbidity and frailty in the development and validation of kidney failure risk prediction models – a systematic review

Abstract Background and Aims Prognostic models that identify individuals with chronic kidney disease (CKD) at highest risk of developing kidney failure help clinicians to make decisions and deliver precision medicine. People with CKD are very likely to have multiple long-term health conditions (multimorbidity) and often experience frailty. These factors impact progression of kidney disease and influence the risk of other outcomes such as death. It is unclear to what extent prognostic models, that estimate the risk of kidney failure, consider the impact of multimorbidity and frailty and whether these models are valid in such sub-populations. This systematic review (CRD42022347295) describes and evaluates the representation of multimorbidity and frailty within cohorts used to develop and/or validate prognostic models assessing the risk of kidney failure in individuals with CKD. The review aims to determine if multimorbidity or frailty has been considered in relation to prediction of kidney failure and if reliable prognostic models exist for use in this population. Method We included studies that described the derivation, validation or update of a kidney failure prognostic model (outcome assessed at ≥2 years) for use in adults with CKD and reported at least one measure of either discrimination or calibration. The primary outcome for the review was the representation of multimorbidity or frailty in these models. An electronic search for published peer-reviewed articles involved MEDLINE, CINAHL Plus and the Cochrane Library – CENTRAL and was supplemented with manual review of references from previous systematic reviews and clinical guidelines. Results A total of 97 studies, reporting 121 different kidney failure prognostic models were identified. A total of 2 925 413 participants and 149 380 kidney failure events were included across all studies. Included participants had a mean age of 58.9 years (SD 9.6), 44.4% were female, with a mean eGFR of 47.5 ml/min/1.73 m2 (SD 10.7). Only two studies reported multimorbidity, measured by Elixhauser Comorbidity Index and Charlson Co-morbidity Index (CCI), and a single study reported a self-reported proxy frailty measure. The rates of specific co-morbidities were reported in a greater proportion of studies: 67.0% (n = 65) studies reported baseline data on diabetes, 54.6% (n = 53) reported hypertension, and 39.2% (n = 38) reported cardiovascular disease. No studies included frailty in model development and only one study considered multimorbidity as a predictor variable (via CCI). No studies assessed model performance in populations with multimorbidity. A single study assessed clinical utility of a model and referral algorithms considering frailty and the risk of kidney failure and death. Conclusion There is a paucity of kidney failure risk prediction models that consider the impact of multimorbidity and/or frailty in adults with CKD, resulting in a lack of clear evidence-based practice and guidance for multimorbid or frail individuals. These knowledge gaps should be explored to help clinicians know whether these models can be used for patients who experience multimorbidity and/or frailty.

#559 Validation of the Kidney Failure Risk Equation (KFRE) in individuals with chronic kidney disease and multimorbidity

Abstract Background and Aims Increasing numbers of individuals with chronic kidney disease (CKD) experience multiple long-term conditions (multimorbidity). Clinical guidance recommends the use of validated risk prediction equations, such as the kidney failure risk equation (KFRE), to guide referral to specialist kidney care services. However, multimorbidity may impact the accuracy of creatinine-based eGFR and bias the prognostic utility of KFRE. Equations with alternative filtration markers, such as Cystatin C eGFR (eGFRcys) or the combined creatinine and Cystatin C eGFR (eGFRcrcys), may improve KFRE's risk stratification and discrimination of future kidney failure risks. This study aimed to validate the four-variable KFRE in individuals with CKD, with and without multimorbidity in a research-based cohort (UK Biobank) and a population-based cohort (Stockholm Creatinine Measurements project (SCREAM)). The study also assessed the performance of KFRE when using eGFRcr, eGFRcys and eGFRcrcys. Method Individuals from both cohorts were included if they had CKD, defined as eGFR<60 mL/min/1.73 m2 by any of the three eGFR equations (eGFRcr, eGFRcys and eGFRcrcys), and had available proteinuria measurement at time of testing or within the previous 12 months. Multimorbidity was defined as the presence of two or more long-term conditions in addition to CKD and was grouped into multimorbidity clusters based on previous research. The outcome was kidney failure, defined as the need for long-term dialysis or kidney transplantation. KFRE performance at 2- and 5-years was assessed using the area under the receiver operating characteristic curve and c-index for discrimination and calibration curves for calibration. Results We included 24 489 individuals from UK Biobank and 42 902 individuals from SCREAM (mean age 62.8 (SD 5.6) and 70.1 (SD14.1), 54% and 66% female, respectively). In UK biobank, 14 998 individuals had multimorbidity, of which 5 375 had cardiometabolic multimorbidity. In SCREAM, 30 147 had multimorbidity and 17 854 cardiometabolic multimorbidity. Overall, there were 252 and 312 kidney failure events and 1 108 and 1 471 death events in UK Biobank and 918 and 1 098 kidney failure events and 8 785 and 10 152 death events in SCREAM within 2- and 5-years respectively. Model performance was consistent across both cohorts. Discrimination power of KFRE was good in individuals with and without multimorbidity and across the 2-year and 5-year models (Table 1). Calibration plots revealed over-estimation of risk at 2-years in both cohorts and under-estimation of risk at 5-years in patients with multimorbidity in UK Biobank. There was no improvement in model performance when using eGFRcys or eGFRcrcys compared to eGFRCr. There was a higher cumulative incidence of both kidney failure and death in the multimorbidity group, with a prominent increase in risk of death over time compared to the no multimorbidity group. This was most evident in the SCREAM cohort (Fig. 1). Conclusion KFRE adequately predicts kidney failure in individuals with multimorbidity and either creatinine or cystatin C can be used. Given the high rates of mortality amongst people with multimorbidity, exploration of models that account for the competing risk of death is warranted.

A Grounded Theory of Interdisciplinary Communication and Collaboration in the Outpatient Setting of the Hospital for Patients with Multiple Long-Term Conditions.

Interdisciplinary communication and collaboration are crucial in the care of people with multiple long-term conditions (MLTCs) yet are often experienced as insufficient. Through the lens of complexity science, this study aims to explain how healthcare professionals (HCPs) adapt to emerging situations in the care of patients with MLTC by examining interdisciplinary communication and collaboration in the outpatient hospital setting. We used the constant comparative method to analyze transcribed data from seven focus groups with twenty-one HCPs to generate a constructivist grounded theory of 'interdisciplinary communication and collaboration in the outpatient setting of the hospital for patients with multiple long-term conditions'. Our theory elucidates the various pathways of communication and collaboration. Why, when, and how team members choose to collaborate influences if and to what degree tailored care is achieved. There is great variability and unpredictability to this process due to internalized rules, such as beliefs on the appropriateness to deviate from guidelines, and the presence of an interprofessional identity. We identified organizational structures that influence the dynamics of the care team such as the availability of time and financial compensation for collaboration. As we strive for tailored care for patients with MLTC, our theory provides promising avenues for future endeavors.

Comparing natural language processing representations of coded disease sequences for prediction in electronic health records.

Natural language processing (NLP) algorithms are increasingly being applied to obtain unsupervised representations of electronic health record (EHR) data, but their comparative performance at predicting clinical endpoints remains unclear. Our objective was to compare the performance of unsupervised representations of sequences of disease codes generated by bag-of-words versus sequence-based NLP algorithms at predicting clinically relevant outcomes. This cohort study used primary care EHRs from 6286233 people with Multiple Long-Term Conditions in England. For each patient, an unsupervised vector representation of their time-ordered sequences of diseases was generated using 2 input strategies (212 disease categories versus 9462 diagnostic codes) and different NLP algorithms (Latent Dirichlet Allocation, doc2vec, and 2 transformer models designed for EHRs). We also developed a transformer architecture, named EHR-BERT, incorporating sociodemographic information. We compared the performance of each of these representations (without fine-tuning) as inputs into a logistic classifier to predict 1-year mortality, healthcare use, and new disease diagnosis. Patient representations generated by sequence-based algorithms performed consistently better than bag-of-words methods in predicting clinical endpoints, with the highest performance for EHR-BERT across all tasks, although the absolute improvement was small. Representations generated using disease categories perform similarly to those using diagnostic codes as inputs, suggesting models can equally manage smaller or larger vocabularies for prediction of these outcomes. Patient representations produced by sequence-based NLP algorithms from sequences of disease codes demonstrate improved predictive content for patient outcomes compared with representations generated by co-occurrence-based algorithms. This suggests transformer models may be useful for generating multi-purpose representations, even without fine-tuning.

The economic burden of multimorbidity: Protocol for a systematic review.

Multimorbidity, also known as multiple long-term conditions, leads to higher healthcare utilisation, including hospitalisation, readmission, and polypharmacy, as well as a financial burden to families, society, and nations. Despite some progress, the economic burden of multimorbidity remains poorly understood. This paper outlines a protocol for a systematic review that aims to identify and synthesise comprehensive evidence on the economic burden of multimorbidity, considering various definitions and measurements of multimorbidity, including their implications for future cost-of-illness analyses. The review will include studies involving people of all ages with multimorbidity without any restriction on location and setting. Cost-of-illness studies or studies that examined economic burden including model-based studies will be included, and economic evaluation studies will be excluded. Databases including Scopus (that includes PubMed/MEDLINE), Web of Science, CINAHL Plus, PsycINFO, NHS EED (including the HTA database), and the Cost-Effectiveness Analysis Registry, will be searched until March 2024. The risk of bias within included studies will be independently assessed by two authors using appropriate checklists. A narrative synthesis of the main characteristics and results, by definitions and measurements of multimorbidity, will be conducted. The total economic burden of multimorbidity will be reported as mean annual costs per patient and disaggregated based on counts of diseases, disease clusters, and weighted indices. The results of this review will provide valuable insights for researchers into the key cost components and areas that require further investigation in order to improve the rigour of future studies on the economic burden of multimorbidity. Additionally, these findings will broaden our understanding of the economic impact of multimorbidity, inform us about the costs of inaction, and guide decision-making regarding resource allocation and cost-effective interventions. The systematic review's results will be submitted to a peer-reviewed journal, presented at conferences, and shared via an online webinar for discussion.

Multiple Long-Term Conditions and Disability are Independently Associated with Higher Risk of Fall Among Community Adults: a Cross-Sectional Study

Multiple Long-Term Conditions and Disability are Independently Associated with Higher Risk of Fall Among Community Adults: a Cross-Sectional Study

Guidance for a deprescribing approach that can be implemented in care homes: STOPPING study findings and lessons

Abstract Introduction Care home residents often have multiple long-term conditions and experience polypharmacy. Deprescribing is the reduction or stopping of prescription medicines that may no longer be providing benefit. Deprescribing is generally safe but it is unknown how to make it work well in practice, like care homes. Current tools and approaches often overlook the specific contextual factors and various stakeholder views within care homes. Aim To inform the development of a deprescribing approach that can be implemented in care homes. Methods The findings from two qualitative work packages of the STOPPING project[1,2] were synthesised to develop a better deprescribing practice approach within care homes, considering different views and environments, and recommendations for designing a deprescribing approach for care homes. In total, 42 interviews were conducted with 36 participants (residents and their family members/friends, care home staff, and healthcare professionals) from 15 different care homes. A framework analysis approach, informed by the Consolidated Framework for Implementation Research (CFIR), was used to analyse data from both work packages. Similar and divergent determinants spanning all CFIR domains were aggregated. Then how and why key these factors operated were considered from generating relationships using conceptual mapping. Researchers and a family carer representative met regularly to discuss discrepancies and refine the themes. Results Key considerations for a deprescribing approach for care homes are: engaging multiple individuals and organisations; recognising their various roles, responsibilities, expertise, and beliefs; information access and sharing; and active monitoring of the impact of deprescribing. The guidance is presented as a cycle to illustrate deprescribing as a process, which then works through four implementation aspects: (1) Plan and coordinate, (2) Communicate and collaborate, (3) Access and share information, and (4) Monitor and evaluate. They are a guide rather than a rigid set of steps, as some activities overlap and feed into each other, and demonstrate how deprescribing for residents should be ongoing and iterative. Proposed actions to encourage deprescribing in care homes are provided for each implementation aspect and presented as questions for consideration. For example, in Plan and coordinate, one of the questions is ‘Are the goals of care with respect to medicine optimisation and deprescribing for residents established?’. The key factor influencing this guidance is the quality of local working relationships between care homes and primary care, which was more crucial than the type of care home organisation management structure. Conclusion Communication and collaboration between care homes and healthcare professionals (such as GPs, nurses, and pharmacists) are essential to ensure deprescribing is done well. A strength of the work is the use of a comprehensive, well-recognised implementation science framework; however, a limitation is that most participants were care home staff, so the findings reflect their perspectives and experiences. Further work is needed to develop tools and approaches that address how this can be achieved within current structures and limited resources of health and social care. The guidance, developed from the STOPPING project findings, suggests several courses of action for how to improve future deprescribing in care homes.

Reporting and representation of underserved groups in intervention studies for patients with multiple long-term conditions: a systematic review

Objectives Globally, there is a growing number of people who are living with multiple long-term conditions (MLTCs). Due to complex management needs, it is imperative that research consists of participants who may benefit most from interventions. It is well documented that ethnic minority groups and lower socioeconomic status (SES) groups are at an increased risk of developing MLTCs. Therefore, the aim of this systematic review was to determine the level of reporting and representation of underserved groups (ethnic minority and low SES) in intervention studies addressing MLTCs. Design Systematic review. Four databases including Cochrane Library, MEDLINE, CINAHL and Scopus were searched for intervention studies from North America or Europe published between January 1990 and July 2023. Setting Hospital and community-based interventions. We included interventional studies focusing on improving MLTC-related outcomes. Participants Patients with MLTCs. Main outcome measures Total number of studies reporting on ethnicity and SES. Number and proportion of studies reporting by ethnic/SES group. Results Thirteen studies met the inclusion criteria. Only 4 of 13 studies (31%) recorded and reported ethnicity information. Of these four studies that reported on ethnicity, three studies consisted of primarily White participants. Ethnic minority groups were underrepresented, but one study included a majority of African American participants. Moreover, 12 of 13 studies (92%) reported on SES with income and educational level being the primary measures used. SES representation of higher deprivation groups was varied due to limited data. Conclusions For ethnicity, there was a lack of reporting, and ethnic minority groups were underrepresented in intervention studies. For SES, there was a high level of reporting but the proportion of study samples from across the spectrum of SES varied due to the variety of SES measures used. Findings highlight a need to improve the reporting and representation of ethnic minority groups and provide more detailed information for SES through using consistent measures (e.g. education, income and employment) to accurately determine the distribution of SES groups in intervention studies of people with MLTCs.

Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (PERFORM): protocol for a randomised feasibility trial

IntroductionPersonalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (PERFORM) is a research programme that seeks to develop and evaluate a comprehensive exercise-based rehabilitation intervention designed for people with multimorbidity, the...

Reviews for multimorbidity risk in people with inflammatory conditions: a qualitative study.

People with inflammatory rheumatological conditions (IRCs) are at high risk of developing other conditions including cardiovascular disease and mood disorders. To explore perspectives of people with IRCs and healthcare practitioners (HCPs) on the content and delivery of a review consultation aimed at identification and management of multiple long-term conditions. Semi-structured interviews and focus groups with people with IRCs and HCPs. People with IRCs participated in individual semi-structured interviews by telephone or online platform. HCPs (including primary and secondary care clinicians) participated in online focus groups. Data were transcribed verbatim and analysed using inductive thematic analysis. 15 people with IRCs were interviewed; three focus groups with HCPs were conducted. Two main themes were identified: reflecting on the value of review consultations and what would a new review look like. Overall, people with IRCs and HCPs reflected that access to reviews is inequitable, leading to duplication of reviews and fragmentation in care. People with IRCs, at times, had difficulty conceptualising reviews, especially when discussing their future risk of conditions. People suggested that preparation before the healthcare review could align patient and HCP agendas as part of a flexible and person-centred discussion. Any review introduced for people with IRCs must move beyond a "tick-box" exercise. To gain maximum value from a review, preparation from both patient and HCP may be required alongside a person-centred approach whilst ensuring they are targeted at people most likely to benefit.

A qualitative exploration of the barriers and facilitators to self-managing multiple long-term conditions amongst people experiencing socioeconomic deprivation.

Globally, it is estimated that one in three adults live with two or more long-term conditions (multiple long-term conditions, MLTCs), that require self-management. People who experience socioeconomic deprivation face significant health inequalities due to a range of interrelated characteristics that lead to a lack of resources and opportunities. Previous research with underserved populations indicate low levels of trust towards primary care providers and potential barriers for developing patient-healthcare professional relationships. The purpose of this paper is to explore the barriers and facilitators to self-managing MLTCs, amongst people who experience socioeconomic deprivation. Semistructured one-to-one interviews with adults (n = 28) living in London and Sheffield, United Kingdom with MLTCs who are experiencing socioeconomic deprivation. Participants were recruited through general practices, community channels and social media. Data were analysed in NVivo using reflexive thematic analysis methods. Four analytical themes were developed: (1) challenges in accessing healthcare services, financial assistance, and cultural awareness; (2) empowerment and disempowerment through technology, including digital exclusion, and use of technology; (3) impact and causes of exclusion on self-management, including social isolation, area-based and economic exclusion, and health-related stigma and (4) adapting self-management strategies, including cost-effective, and culturally/lifestyle appropriate strategies. Future health interventions and services need to be developed with consideration of the combined complexities of managing MLTCs while experiencing socioeconomic deprivation. Increased awareness in practitioners and commissioners of the complexities surrounding the lives of people experiencing socioeconomic deprivation, and the need for targeted strategies to promote self-management of MLTCs are of great importa. A patient advisory group contributed to all stages of the study, including providing important feedback on study documents (topic guides and recruitment materials), as well as providing critical insights surrounding the interpretation of interview data.

Improving care for patients with multiple long-term conditions admitted to hospital: challenges and potential solutions.

Increasing numbers of people live with multiple long-term conditions. These people are more likely to be admitted to hospital, experience adverse outcomes and receive poorer quality care than those with a single condition. Hospitals remain organised around a model of single-organ, disease-specific care which is not equipped to meet the needs of people living with multiple long-term conditions. This article considers these challenges and explores potential solutions. These include different service models to provide holistic, multidisciplinary inpatient and outpatient care across specialty boundaries, training a workforce to deliver high-quality hospital care for people living with multiple long-term conditions, and developing technological, financial and cultural enablers of change. Considerably more research is required to fully appreciate the shared risk factors, underlying mechanisms, patterns and consequences of multiple long-term conditions. This is essential to design and deliver better structures and processes of hospital care for people living with multiple long-term conditions.

The status of drug evaluation in older adults in the United Kingdom: Bridging the representation gap.

Older adults are persistently underrepresented in clinical drug trials worldwide, despite increasing multiple long-term conditions and significant prescribing in this demographic. We discuss systemic challenges such as the exclusion of people with comorbid conditions and the lack of assessment for comorbidities as modifiers of treatment effects and highlight the rising trend of polypharmacy, especially among the oldest age groups, which is linked to a significant percentage of unplanned hospitalizations and medication errors. The consequences of these trends prompted the United Kingdom National Overprescribing review, culminating in a set of recommendations for drug development tailored to older adults. Building on this, two critical reports released in April 2023 by the International Longevity Centre (ILC) and the Nuffield Council on Bioethics (NCOB) are discussed. These reports emphasize the importance of diversity and inclusion in clinical trials, advocating for ethical frameworks and methodologies that cater to the complex needs of older adults. The development of inclusive criteria, innovative statistical methodologies, and the integration of patient-reported outcomes are needed to address the persistent barriers to older adult participation in research, suggesting that pragmatic trials, exemplified by the UK's RECOVERY trial during the COVID-19 pandemic, could pave the way for more inclusive research practices.

Identifying future high healthcare utilization in patients with multimorbidity – development and internal validation of machine learning prediction models using electronic health record data

PurposeTo develop and internally validate prediction models with machine learning for future potentially preventable healthcare utilization in patients with multiple long term conditions (MLTC). This study is the first step in investigating whether prediction models can help identify patients with MLTC that are most in need of integrated care.MethodsA retrospective cohort study was performed with electronic health record data from adults with MLTC from an academic medical center in the Netherlands. Based on demographic and healthcare utilization characteristics in 2017, we predicted ≥ 12 outpatient visits, ≥ 1 emergency department (ED) visits, and ≥ 1 acute hospitalizations in 2018. Four machine learning models (elastic net regression, extreme gradient boosting (XGB), logistic regression, and random forest) were developed, optimized, and evaluated in a hold-out dataset for each outcome.ResultsA total of 14,486 patients with MLTC were included. Based on the area under the curve (AUC) and calibration curves, the XGB model was selected as final model for all three outcomes. The AUC was 0.82 for ≥ 12 outpatient visits, 0.76 for ≥ 1 ED visits and 0.73 for ≥ 1 acute hospitalizations. Despite adequate AUC and calibration, precision-recall curves showed suboptimal performance.ConclusionsThe final selected models per outcome can identify patients with future potentially preventable high healthcare utilization. However, identifying high-risk patients with MLTC and substantiating if they are most in need of integrated care remains challenging. Further research is warranted investigating whether patients with high healthcare utilization are indeed the most in need of integrated care and whether quantitively identified patients match the identification based on clinicians’ experience and judgment.

Assigning disease clusters to people: A cohort study of the implications for understanding health outcomes in people with multiple long-term conditions.

Identifying clusters of co-occurring diseases may help characterise distinct phenotypes of Multiple Long-Term Conditions (MLTC). Understanding the associations of disease clusters with health-related outcomes requires a strategy to assign clusters to people, but it is unclear how the performance of strategies compare. First, to compare the performance of methods of assigning disease clusters to people at explaining mortality, emergency department attendances and hospital admissions over one year. Second, to identify the extent of variation in the associations with each outcome between and within clusters. We conducted a cohort study of primary care electronic health records in England, including adults with MLTC. Seven strategies were tested to assign patients to fifteen disease clusters representing 212 LTCs, identified from our previous work. We tested the performance of each strategy at explaining associations with the three outcomes over 1 year using logistic regression and compared to a strategy using the individual LTCs. 6,286,233 patients with MLTC were included. Of the seven strategies tested, a strategy assigning the count of conditions within each cluster performed best at explaining all three outcomes but was inferior to using information on the individual LTCs. There was a larger range of effect sizes for the individual LTCs within the same cluster than there was between the clusters. Strategies of assigning clusters of co-occurring diseases to people were less effective at explaining health-related outcomes than a person's individual diseases. Furthermore, clusters did not represent consistent relationships of the LTCs within them, which might limit their application in clinical research.

Behavioural activation to mitigate the psychological impacts of COVID-19 restrictions on older people in England and Wales (BASIL+): a pragmatic randomised controlled trial

Older adults were more likely to be socially isolated during the COVID-19 pandemic, with increased risk of depression and loneliness. We aimed to investigate whether a behavioural activation intervention delivered via telephone could mitigate depression and loneliness in at-risk older people during the COVID-19 pandemic. BASIL+ (Behavioural Activation in Social Isolation) was a pragmatic randomised controlled trial conducted among patients recruited from general practices in England and Wales, and was designed to assess the effectiveness of behavioural activation in mitigating depression and loneliness among older people during the COVID-19 pandemic. Eligible participants were aged 65 years and older, socially isolated, with a score of 5 or higher on the Patient Health Questionnaire-9 (PHQ-9), and had multiple long-term conditions. Participants were allocated in a 1:1 ratio to the intervention (behavioural activation) or control groups by use of simple randomisation without stratification. Behavioural activation was delivered by telephone; participants were offered up to eight weekly sessions with trained BASIL+ Support Workers. Behavioural activation was adapted to maintain social connections and encourage socially reinforcing activities. Participants in the control group received usual care with existing COVID-19 wellbeing resources. The primary clinical outcome was self-reported depression severity, assessed by the PHQ-9, at 3 months. Outcomes were assessed masked to allocation and analysis was by treatment allocation. This trial is registered with the ISRCTN registry (ISRCTN63034289). Between Feb 8, 2021, and Feb 28, 2022, 449 eligible participants were identified and 435 from 26 general practices were recruited and randomly assigned (1:1) to the behavioural activation intervention (n=218) or to the control group (usual care with signposting; n=217). The mean age of participants was 75·7 years (SD 6·7); 270 (62·1%) of 435 participants were female, and 418 (96·1%) were White. Participants in the intervention group attended an average of 5·2 (SD 2·9) of eight remote behavioural activation sessions. The adjusted mean difference in PHQ-9 scores between the control and intervention groups at 3 months was -1·65 (95% CI -2·54 to -0·75, p=0·0003). No adverse events were reported that were attributable to the behavioural activation intervention. Behavioural activation is an effective and potentially scalable intervention that can reduce symptoms of depression and emotional loneliness in at-risk groups in the short term. The findings of this trial add to the range of strategies to improve the mental health of older adults with multiple long-term conditions. These results can be helpful to policy makers beyond the pandemic in reducing the global burden of depression and addressing the health impacts of loneliness, particularly in at-risk groups. UK National Institute for Health and Care Research.

A silver bullet for ageing medicine?: clinical relevance of T-cell checkpoint receptors in normal human ageing.

Immunosenescence describes dysregulation of the immune system with ageing manifested in both the innate and adaptive immunity, including changes in T-cell checkpoint signaling. Through complex and nuanced process, T-cells lose excitatory signaling pathways and upregulate their inhibitory signaling, leading to ineffective immune responses that contribute to the formation of the ageing phenotype. Here we expand on the expression, function, and clinical potential of targeting the T-cell checkpoint signaling in age and highlight interventions offering the most benefits to older adults' health. Notably, modifications in vaccination such as with mTOR inhibitors show immediate clinical relevance and good tolerability. Other proposed treatments, including therapies with monoclonal antibodies fail to show clinical efficacy or tolerability needed for implementation at present. Although T-cell co-signaling fits a valuable niche for translational scientists to manage immunosenescence, future study would benefit from the inclusion of older adults with multiple long-term conditions and polypharmacy, ensuring better applicability to actual patients seen in clinical settings.

The implications of competing risks and direct treatment disutility in cardiovascular disease and osteoporotic fracture: risk prediction and cost effectiveness analysis.

Clinical guidelines commonly recommend preventative treatments for people above a risk threshold. Therefore, decision-makers must have faith in risk prediction tools and model-based cost-effectiveness analyses for people at different levels of risk. Two problems that arise are inadequate handling of competing risks of death and failing to account for direct treatment disutility (i.e. the hassle of taking treatments). We explored these issues using two case studies: primary prevention of cardiovascular disease using statins and osteoporotic fracture using bisphosphonates. Externally validate three risk prediction tools [QRISK®3, QRISK®-Lifetime, QFracture-2012 (ClinRisk Ltd, Leeds, UK)]; derive and internally validate new risk prediction tools for cardiovascular disease [competing mortality risk model with Charlson Comorbidity Index (CRISK-CCI)] and fracture (CFracture), accounting for competing-cause death; quantify direct treatment disutility for statins and bisphosphonates; and examine the effect of competing risks and direct treatment disutility on the cost-effectiveness of preventative treatments. Discrimination and calibration of risk prediction models (Clinical Practice Research Datalink participants: aged 25-84 years for cardiovascular disease and aged 30-99 years for fractures); direct treatment disutility was elicited in online stated-preference surveys (people with/people without experience of statins/bisphosphonates); costs and quality-adjusted life-years were determined from decision-analytic modelling (updated models used in National Institute for Health and Care Excellence decision-making). CRISK-CCI has excellent discrimination, similar to that of QRISK3 (Harrell's c = 0.864 vs. 0.865, respectively, for women; and 0.819 vs. 0.834, respectively, for men). CRISK-CCI has systematically better calibration, although both models overpredict in high-risk subgroups. People recommended for treatment (10-year risk of ≥ 10%) are younger when using QRISK-Lifetime than when using QRISK3, and have fewer observed events in a 10-year follow-up (4.0% vs. 11.9%, respectively, for women; and 4.3% vs. 10.8%, respectively, for men). QFracture-2012 underpredicts fractures, owing to under-ascertainment of events in its derivation. However, there is major overprediction among people aged 85-99 years and/or with multiple long-term conditions. CFracture is better calibrated, although it also overpredicts among older people. In a time trade-off exercise (n = 879), statins exhibited direct treatment disutility of 0.034; for bisphosphonates, it was greater, at 0.067. Inconvenience also influenced preferences in best-worst scaling (n = 631). Updated cost-effectiveness analysis generates more quality-adjusted life-years among people with below-average cardiovascular risk and fewer among people with above-average risk. If people experience disutility when taking statins, the cardiovascular risk threshold at which benefits outweigh harms rises with age (≥ 8% 10-year risk at 40 years of age; ≥ 38% 10-year risk at 80 years of age). Assuming that everyone experiences population-average direct treatment disutility with oral bisphosphonates, treatment is net harmful at all levels of risk. Treating data as missing at random is a strong assumption in risk prediction model derivation. Disentangling the effect of statins from secular trends in cardiovascular disease in the previous two decades is challenging. Validating lifetime risk prediction is impossible without using very historical data. Respondents to our stated-preference survey may not be representative of the population. There is no consensus on which direct treatment disutilities should be used for cost-effectiveness analyses. Not all the inputs to the cost-effectiveness models could be updated. Ignoring competing mortality in risk prediction overestimates the risk of cardiovascular events and fracture, especially among older people and those with multimorbidity. Adjustment for competing risk does not meaningfully alter cost-effectiveness of these preventative interventions, but direct treatment disutility is measurable and has the potential to alter the balance of benefits and harms. We argue that this is best addressed in individual-level shared decision-making. This study is registered as PROSPERO CRD42021249959. This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/12/22) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.