Comorbidity versus multimorbidity: Why it matters

Association between sleep disturbances and challenging behavior in children and adolescents with Angelman syndrome

Angelman Syndrome (AS) is a neurodevelopmental disorder with severe symptoms and associated comorbidities. It is caused by the inactivity or lack of the UBE3a gene. Symptoms of the syndrome include intellectual disability and developmental delay. The current study investigated sleep disturbances (SD) in children and adolescents with AS, associations between SD and possible predictors of SD. Variables examined included age, gender, newborn and infancy history, challenging behavior, type of therapy received, genetic type of AS, and seizures. The sample included data from 109 participants with a mean age of 8.21, accessed via the Global Angelman Syndrome Registry. Chi-square tests were carried out to assess the associations between the variables and a logistical regression was carried out to assess the possible predictors of SD. Associations were found between SD and certain repetitive behaviors: slapping walls, focal hand movements, and agitation at new situations. From these associations, a regression formed a predictive model for sleep disturbances. The findings of this research demonstrated the importance of investigating the relationship between sleep disturbances and challenging behavior in children and adolescents with AS and the need for further research in this area.

Exploring the Impact of Medical Complexity on Nursing Complexity of Care in Paediatric Patients: A Retrospective Observational Study

AIMS

To explore the impact of medical complexity, defined by the number of chronic conditions, on the complexity of care, as described by the frequency of nursing diagnoses (NDs) and nursing actions (NAs), in paediatric patients.

DESIGN

Retrospective observational study.

METHODS

This study was conducted in an Italian university hospital and involved the analysis of electronic health records for neonatal and paediatric patients who were consecutively admitted from January to December 2022. The sample was classified into three categories-non-chronic, single chronic and multimorbid patients-according to their clinical profiles. NDs recorded within the first 24 h from patient hospital admission and NAs performed throughout the hospital stay were counted for each group.

RESULTS

Distinct variations in the prevalence and patterns of NDs and NAs were observed across different levels of medical complexity. A significant moderate positive correlation between the number of NDs and NAs was found. However, the frequency of NDs did not directly correlate with the number of chronic conditions. Conversely, a weak but significant negative correlation was identified between the quantity of NAs and the number of chronic conditions. While the frequency of NDs showed a stable but decreasing trend as the number of chronic conditions increased, a higher number of chronic conditions were associated with a lower quantity of NAs.

CONCLUSIONS

We discovered a notable variation in the complexity of care across varying levels of medical complexity in paediatric patients. Our findings suggest that the complexity of care does not necessarily correspond to the degree of medical complexity. The observed negative relationship between the number of chronic conditions and the quantity of NAs underscores the need for further research to explore this unexpected finding and its implications for clinical practice.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Without the adoption of standardised nursing terminologies, such as nursing diagnoses (NDs) and nursing actions (NAs), assessing the complexity of care in paediatric settings can be challenging. Integrating clinical nursing information systems that incorporate standardised NDs and NAs into electronic health records is crucial for accurately documenting and analysing the complexity of care and its relationship with medical complexity.

IMPACT

In paediatric patients, the frequency of nursing diagnoses (NDs) at hospital admission is significantly associated with the quantity of nursing actions (NAs) delivered during hospitalisation. However, there is no correlation between the frequency of NDs and medical complexity, as defined by the number of chronic disorders. Specifically, the frequency of NDs decreases with increasing medical complexity, while the quantity of NAs is negatively associated with the number of chronic disorders. This indicates that the complexity of care cannot be inferred solely from medical complexity, and additional factors need to be explored. These findings enhance understanding of how complexity of care relates to medical complexity in paediatric patients. Insights into the prevalence and patterns of NDs and NAs can benefit nurses, managers, researchers and policymakers by informing clinical and organisational decision-making to ensure high-quality care.

REPORTING METHOD

The study adhered to the RECORD Statement.

PATIENT OR PUBLIC CONTRIBUTION

Patients, service users, caregivers or public members were not directly involved in the design, conduct, analysis and interpretation of data or in writing this paper. Patients contributed only to data collection.

Pulmonary vascular disease in chronic lung diseases: cause or comorbidity?

PURPOSE OF REVIEW

To provide timely and relevant insights into the complex relationship between pulmonary vascular disease (PVD) and chronic lung disease (CLD), focusing on the causative and consequential dynamics between these conditions.

RECENT FINDINGS

There are shared pathogenic mechanisms between pulmonary arterial hypertension (PAH) and group 3 pulmonary hypertension, including altered expression of mediators and growth factors implicated in both conditions. Factors such as hypoxia, hypoxemia, and hypercapnia also contribute to pulmonary vascular remodelling and endothelial dysfunction. However, the role of hypoxia as the sole driver of pulmonary hypertension in CLD is being reconsidered, particularly in chronic obstructive pulmonary disease (COPD), with evidence suggesting a potential role for cigarette smoke products in initiating pulmonary vascular impairment. On the other hand, interstitial lung disease (ILD) encompasses a group of heterogeneous lung disorders characterized by inflammation and fibrosis of the interstitium, leading to impaired gas exchange and progressive respiratory decline, which could also play a role as a cause of pulmonary hypertension.

SUMMARY

Understanding the intricate interplay between the pulmonary vascular compartment and the parenchymal and airway compartments in respiratory disease is crucial for developing effective diagnostic and therapeutic strategies for patients with PVD and CLD, with implications for both clinical practice and research.

Molecular Morbidity Score-Can MicroRNAs Assess the Burden of Disease?

Multimorbidity refers to the presence of two or more chronic diseases and is associated with adverse outcomes for patients. Factors such as an ageing population have contributed to a rise in prevalence of multimorbidity globally; however, multimorbidity is often neglected in clinical guidelines. This is largely because patients with multimorbidity are systematically excluded from clinical trials. Accordingly, there is an urgent need to develop novel biomarkers and methods of prognostication for this cohort of patients. The hallmarks of ageing are now thought to potentiate the pathogenesis of multimorbidity. MicroRNAs are small, regulatory, noncoding RNAs which have been implicated in the pathogenesis and prognostication of numerous chronic diseases; there is a substantial body of evidence now implicating microRNA dysregulation with the different hallmarks of ageing in the aetiology of chronic diseases. This article proposes using the hallmarks of ageing as a framework to develop a panel of microRNAs to assess the prognostic burden of multimorbidity. This putative molecular morbidity score would have many potential applications, including assessing the efficacy of clinical interventions, informing clinical decision making and facilitating wider inclusion of patients with multimorbidity in clinical trials.

Living with multimorbidity: A qualitative exploration of shared experiences of patients, family caregivers, and healthcare professionals in managing symptoms in the United States

AIMS

To elicit experiences of patients, family caregivers, and healthcare professionals in intermediate care units (IMCUs) in an academic medical centre in Baltimore, MD related to the challenges and intricacies of multimorbidity management to inform development of a multimorbidity symptom management toolkit.

DESIGN

Experience-based co-design.

METHODS

Between July and October 2021, patients aged 55 years and older with multimorbidity admitted to IMCUs at an academic medical centre in Baltimore, Maryland, USA were recruited and interviewed in person. Interdisciplinary healthcare professionals working in the IMCU were interviewed virtually. Participants were asked questions about their role in recognizing and treating symptoms, factors affecting the quality of life, symptom burden and trajectory over time, and strategies that have and have not worked for managing symptoms. An inductive thematic analysis approach was used for analysis.

RESULTS

Twenty-three interviews were conducted: 9 patients, 2 family caregivers, and 12 healthcare professionals. Patients' mean age was 67.5 (±6.5) years, over half (n = 5) were Black or Hispanic, and the average number of comorbidities was 3.67. Five major themes that affect symptom management emerged: (1) the patient-provider relationship; (2) open and honest communication; (3) accessibility of resources during hospitalization and at discharge; (4) caregiver support, training, and education; and (5) care coordination and follow-up care.

CONCLUSION

Patients, caregivers, and healthcare professionals often have similar goals but different priorities for multimorbidity management. It is imperative to identify shared priorities and target holistic interventions that consider patient and caregiver experiences to improve outcomes.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE AND IMPACT

This paper addresses the paucity of research related to the shared experience of disease trajectory and symptom management for people living with multimorbidity. We found that patients, caregivers, and healthcare professionals often have similar goals but different care and communication priorities. Understanding differing priorities will help better design interventions to support symptom management so people with multimorbidity can have the best possible quality of life.

REPORTING METHOD

We have adhered to the Consolidated Criteria for Reporting Qualitative Studies (COREQ) guidelines in our reporting.

PATIENT OR PUBLIC CONTRIBUTION

This study has been designed and implemented with patient and public involvement throughout the process, including community advisory board engagement in the project proposal phase and interview guide development, and member checking in the data collection and analysis phases. The method we chose, experience-based co-design, emphasizes the importance of engaging members of a community to act as experts in their own life challenges. In the coming phases of the study, the public will be involved in developing and testing a new intervention, informed by these qualitative interviews and co-design events, to support symptom management for people with multimorbidity.

Application of Machine Learning in Multimorbidity Research: Protocol for a Scoping Review

BACKGROUND

Multimorbidity, defined as the coexistence of multiple chronic conditions, poses significant challenges to health care systems on a global scale. It is associated with increased mortality, reduced quality of life, and increased health care costs. The burden of multimorbidity is expected to worsen if no effective intervention is taken. Machine learning has the potential to assist in addressing these challenges since it offers advanced analysis and decision-making capabilities, such as disease prediction, treatment development, and clinical strategies.

OBJECTIVE

This paper represents the protocol of a scoping review that aims to identify and explore the current literature concerning the use of machine learning for patients with multimorbidity. More precisely, the objective is to recognize various machine learning models, the patient groups involved, features considered, types of input data, the maturity of the machine learning algorithms, and the outcomes from these machine learning models.

METHODS

The scoping review will be based on the guidelines of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). Five databases (PubMed, Embase, IEEE, Web of Science, and Scopus) are chosen to conduct a literature search. Two reviewers will independently screen the titles, abstracts, and full texts of identified studies based on predefined eligibility criteria. Covidence (Veritas Health Innovation Ltd) will be used as a tool for managing and screening papers. Only studies that examine more than 1 chronic disease or individuals with a single chronic condition at risk of developing another will be included in the scoping review. Data from the included studies will be collected using Microsoft Excel (Microsoft Corp). The focus of the data extraction will be on bibliographical information, objectives, study populations, types of input data, types of algorithm, performance, maturity of the algorithms, and outcome.

RESULTS

The screening process will be presented in a PRISMA-ScR flow diagram. The findings of the scoping review will be conveyed through a narrative synthesis. Additionally, data extracted from the studies will be presented in more comprehensive formats, such as charts or tables. The results will be presented in a forthcoming scoping review, which will be published in a peer-reviewed journal.

CONCLUSIONS

To our knowledge, this may be the first scoping review to investigate the use of machine learning in multimorbidity research. The goal of the scoping review is to summarize the field of literature on machine learning in patients with multiple chronic conditions, highlight different approaches, and potentially discover research gaps. The results will offer insights for future research within this field, contributing to developments that can enhance patient outcomes.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/53761.

What is the burden of multimorbidity and the factors associated with its occurrence in elderly Brazilians?

OBJECTIVE

To estimate the prevalence of multimorbidity in elderly people and its association with sociodemographic characteristics, lifestyle, and anthropometry.

METHODS

This was a cross-sectional study using data from the National Health Survey, 2019. A total of 22,728 elderly individuals from all 27 Brazilian states were randomly selected. Poisson regression models with robust variance were employed, and a significance level of 5% was adopted.

RESULTS

The prevalence of multimorbidity was 51.6% (95% CI: 50.4-52.7), with the highest estimates observed in the South and Southeast. Multimorbidity was associated with being female (aPR = 1.33; 95% CI: 1.27-1.39), being 80 years old or older (aPR = 1.12; 95% CI: 1.05-1.19), having low education (aPR = 1.16; 95% CI: 1.07-1.25), past cigarette use (aPR = 1.16; 95% CI: 1.11-1.21), insufficient physical activity (aPR = 1.13; 95% CI: 1.06-1.21), and screen use for 3 hours or more per day (aPR = 1.13; 95% CI: 1.08-1.18).

CONCLUSION

Multimorbidity affects more than half of the elderly population in Brazil and is associated with social, demographic, and behavioral factors.

Pattern of multimorbidity in middle-aged and older-aged people with mild intellectual disability in Australia

BACKGROUND

Non-communicable diseases (NCDs), also known as chronic diseases, now constitute a major proportion of ill-health across most adult and older populations including in people with intellectual disability. The current paper is a comparative analysis of prevalence of NCDs across mid-aged and older-aged people with mild intellectual disability.

METHOD

Comparative data comes from two cross-sectional surveys using similar methodology and timeframes. The analysis sample comprises mid-aged group (30-50 years, N = 291) and older-aged group (≥60 years, N = 391).

RESULTS

People with mild intellectual disability start developing NCDs in early to mid-adulthood and increases with age. The mean number of NCDs in mid-aged group was 0.86 (SD, 0.84) compared to 3.82 in older group (SD, 2.67).

CONCLUSION

There needs to be early identification and management of NCDs using relevant health promotion and preventative measures at optimal intervention points. The training of healthcare professionals needs improvement.

Identification of gene networks jointly associated with depressive symptoms and cardiovascular health metrics using whole blood transcriptome in the Young Finns Study

Background

Studies have shown that cardiovascular health (CVH) is related to depression. We aimed to identify gene networks jointly associated with depressive symptoms and cardiovascular health metrics using the whole blood transcriptome.

Materials and methods

We analyzed human blood transcriptomic data to identify gene co-expression networks, termed gene modules, shared by Beck's depression inventory (BDI-II) scores and cardiovascular health (CVH) metrics as markers of depression and cardiovascular health, respectively. The BDI-II scores were derived from Beck's Depression Inventory, a 21-item self-report inventory that measures the characteristics and symptoms of depression. CVH metrics were defined according to the American Heart Association criteria using seven indices: smoking, diet, physical activity, body mass index (BMI), blood pressure, total cholesterol, and fasting glucose. Joint association of the modules, identified with weighted co-expression analysis, as well as the member genes of the modules with the markers of depression and CVH were tested with multivariate analysis of variance (MANOVA).

Results

We identified a gene module with 256 genes that were significantly correlated with both the BDI-II score and CVH metrics. Based on the MANOVA test results adjusted for age and sex, the module was associated with both depression and CVH markers. The three most significant member genes in the module were YOD1, RBX1, and LEPR. Genes in the module were enriched with biological pathways involved in brain diseases such as Alzheimer's, Parkinson's, and Huntington's.

Conclusions

The identified gene module and its members can provide new joint biomarkers for depression and CVH.

Multimorbidity in middle-aged women and COVID-19: binary data clustering for unsupervised binning of rare multimorbidity features and predictive modeling

BACKGROUND

Multimorbidity is typically associated with deficient health-related quality of life in mid-life, and the likelihood of developing multimorbidity in women is elevated. We address the issue of data sparsity in non-prevalent features by clustering the binary data of various rare medical conditions in a cohort of middle-aged women. This study aims to enhance understanding of how multimorbidity affects COVID-19 severity by clustering rare medical conditions and combining them with prevalent features for predictive modeling. The insights gained can guide the development of targeted interventions and improved management strategies for individuals with multiple health conditions.

METHODS

The study focuses on a cohort of 4477 female patients, (aged 45-60) in Piedmont, Italy, and utilizes their multimorbidity data prior to the COVID-19 pandemic from their medical history from 2015 to 2019. The COVID-19 severity is determined by the hospitalization status of the patients from February to May 2020. Each patient profile in the dataset is depicted as a binary vector, where each feature denotes the presence or absence of a specific multimorbidity condition. By clustering the sparse medical data, newly engineered features are generated as a bin of features, and they are combined with the prevalent features for COVID-19 severity predictive modeling.

RESULTS

From sparse data consisting of 174 input features, we have created a low-dimensional feature matrix of 17 features. Machine Learning algorithms are applied to the reduced sparsity-free data to predict the Covid-19 hospital admission outcome. The performance obtained for the corresponding models are as follows: Logistic Regression (accuracy 0.72, AUC 0.77, F1-score 0.69), Linear Discriminant Analysis (accuracy 0.7, AUC 0.77, F1-score 0.67), and Ada Boost (accuracy 0.7, AUC 0.77, F1-score 0.68).

CONCLUSION

Mapping higher-dimensional data to a low-dimensional space can result in information loss, but reducing sparsity can be beneficial for Machine Learning modeling due to improved predictive ability. In this study, we addressed the issue of data sparsity in electronic health records and created a model that incorporates both prevalent and rare medical conditions, leading to more accurate and effective predictive modeling. The identification of complex associations between multimorbidity and the severity of COVID-19 highlights potential areas of focus for future research, including long COVID and intervention efforts.

Modifiable risk factors that may be addressed in routine care to prevent progression to and extension of multimorbidity in people with COPD: a systematic literature review

Chronic obstructive pulmonary disease (COPD) is a multisystem disease, and many patients have multiple conditions. We explored multimorbidity patterns that might inform intervention planning to reduce health-care costs while preserving quality of life for patients. Literature searches up to February 2022 revealed 4419 clinical observational and comparative studies of risk factors for multimorbidity in people with COPD, pulmonary emphysema, or chronic bronchitis at baseline. Of these, 29 met the inclusion criteria for this review. Eight studies were cluster and network analyses, five were regression analyses, and 17 (in 16 papers) were other studies of specific conditions, physical activity and treatment. People with COPD more frequently had multimorbidity and had up to ten times the number of disorders of those without COPD. Disease combinations prominently featured cardiovascular and metabolic diseases, asthma, musculoskeletal and psychiatric disorders. An important risk factor for multimorbidity was low socioeconomic status. One study showed that many patients were receiving multiple drugs and had increased risk of adverse events, and that 10% of medications prescribed were inappropriate. Many patients with COPD have mainly preventable or modifiable multimorbidity. A proactive multidisciplinary approach to prevention and management could reduce the burden of care.

Learning prevalent patterns of co-morbidities in multichronic patients using population-based healthcare data

The prevalence of longstanding chronic diseases has increased worldwide, along with the average age of the population. As a result, an increasing number of people is affected by two or more chronic conditions simultaneously, and healthcare systems are facing the challenge of treating multimorbid patients effectively. Current therapeutic strategies are suited to manage each chronic condition separately, without considering the whole clinical condition of the patient. This approach may lead to suboptimal clinical outcomes and system inefficiencies (e.g. redundant diagnostic tests and inadequate drug prescriptions). We develop a novel methodology based on the joint implementation of data reduction and clustering algorithms to identify patterns of chronic diseases that are likely to co-occur in multichronic patients. We analyse data from a large adult population of multichronic patients living in Tuscany (Italy) in 2019 which was stratified by sex and age classes. Results demonstrate that (i) cardio-metabolic, endocrine, and neuro-degenerative diseases represent a stable pattern of multimorbidity, and (ii) disease prevalence and clustering vary across ages and between women and men. Identifying the most common multichronic profiles can help tailor medical protocols to patients' needs and reduce costs. Furthermore, analysing temporal patterns of disease can refine risk predictions for evolutive chronic conditions.

Experiences of hospital care for people with multiple long-term conditions: a scoping review of qualitative research

BACKGROUND

Multiple long-term conditions-the co-existence of two or more chronic health conditions in an individual-present an increasing challenge to populations and healthcare systems worldwide. This challenge is keenly felt in hospital settings where care is oriented around specialist provision for single conditions. The aim of this scoping review was to identify and summarise published qualitative research on the experiences of hospital care for people living with multiple long-term conditions, their informal caregivers and healthcare professionals.

METHODS

We undertook a scoping review, following established guidelines, of primary qualitative research on experiences of hospital care for people living with multiple long-term conditions published in peer-reviewed journals between Jan 2010 and June 2022. We conducted systematic electronic searches of MEDLINE, CINAHL, PsycInfo, Proquest Social Science Premium, Web of Science, Scopus and Embase, supplemented by citation tracking. Studies were selected for inclusion by two reviewers using an independent screening process. Data extraction included study populations, study design, findings and author conclusions. We took a narrative approach to reporting the findings.

RESULTS

Of 8002 titles and abstracts screened, 54 papers reporting findings from 41 studies conducted in 14 countries were identified as eligible for inclusion. The perspectives of people living with multiple long-term conditions (21 studies), informal caregivers (n = 13) and healthcare professionals (n = 27) were represented, with 15 studies reporting experiences of more than one group. Findings included poor service integration and lack of person-centred care, limited confidence of healthcare professionals to treat conditions outside of their specialty, and time pressures leading to hurried care transitions. Few studies explored inequities in experiences of hospital care.

CONCLUSIONS

Qualitative research evidence on the experiences of hospital care for multiple long-term conditions illuminates a tension between the desire to provide and receive person-centred care and time pressures inherent within a target-driven system focussed on increasing specialisation, reduced inpatient provision and accelerated journeys through the care system. A move towards more integrated models of care may enable the needs of people living with multiple long-term conditions to be better met. Future research should address how social circumstances shape experiences of care.

Emotional distress and multimorbidity patterns in Chinese Han patients with osteoporosis: a network analysis

With the aging of the population, the prevalence of osteoporosis and multimorbidity is increasing. Patients with osteoporosis often experience varying levels of emotional distress, including anxiety and depression. However, few studies have explored the patterns of multiple conditions and their impact on patients' emotional distress. Here, we conducted a network analysis to explore the patterns of multimorbidities and their impact on emotional distress in 13,359 Chinese Han patients with osteoporosis. The results showed that multimorbidity was prevalent in Chinese patients with osteoporosis and increased with age, and was more frequent in males than in females, with the most common pattern of multimorbidity being osteoporosis and essential (primary) hypertension. Finally, we found that patients' emotional distress increased with the number of multimorbidities, especially in female patients, and identified eight multimorbidities with high correlation to patients' emotional distress.

Childhood and adolescence physical activity and multimorbidity later in life: A systematic review

Background

No systematic summary exists on childhood physical activity and later-life multimorbidity risks. We primarily investigated the association of physical activity in childhood and adolescence and the development of multimorbidity in adulthood. Secondarily, we examined whether physical activity level differ in children and adolescents with and without multimorbidity and whether there is a cross-sectional association between physical activity and multimorbidity.

Methods

Following Cochrane Handbook guidelines and adhering to PRISMA recommendations, we included cross-sectional, case-control and longitudinal studies that investigated the association between physical activity in children and adolescents and development of multimorbidity. Results were summarized narratively and we assessed the certainty of the evidence using the GRADE approach. The protocol was registered in PROSPERO, CRD42023407063.

Results

Of 9064 studies identified, 11 were included in 13 papers. Longitudinals studies suggested that being physically active in childhood and adolescence was associated with a lower risk of multimorbidity in adulthood. Three out of five studies reported lower physical activity level in children and adolescents with multimorbidity compared to those without, and two did not find a between-group difference. Cross-sectional evidence on the association between multimorbidity and lower physical activity was uncertain. Overall, the evidence certainty for all outcomes was considered low due to the indirectness and inconsistency in findings.

Conclusions

Childhood and adolescence physical activity appeared to be linked with a reduced risk of later-life multimorbidity but the certainty of the evidence is low. These results support the promotion of physical activity during childhood and adolescence.

The prevalence and correlates of comorbidities among patients with cancer attending a tertiary care cancer center in South India: An analytical cross-sectional study

Background

Comorbidities in patients with cancer can affect treatment, and should, therefore, be prioritized and managed.

Objectives

Our primary aim was to assess the prevalence of comorbidities among patients with cancer. The secondary objective was to identify the association of comorbidities with various sociodemographic and clinical variables.

Materials and Methods

This was a cross-sectional study conducted between December 2019 and March 2020 among patients with cancer, seeking treatment at Malabar Cancer Center, in Kannur District of northern Kerala in South India. Semi-structured interviews were conducted, and comorbidities were assessed using the Charlson Comorbidity Index. The anthropometric measurements were recorded using a standardized instrument and protocol.

Results

We enrolled 242 patients in this study. There were 148 (61.2%) female patients; 106 (43.8%) were aged between 41 and 50 years. Cancers of the head-and-neck and breast accounted for the majority of cases (23.1% each, n = 56), followed by the digestive system (18.6%, n = 45) and female reproductive system (11.2%, n = 27). The most common primary cancers in the head-and-neck, digestive, and female reproductive systems were oral, colorectal, and cervical, respectively. The prevalence of comorbidities among patients with cancer was 70.2% (n = 170). Common comorbidities were hypertension (n = 82 ; 33.9%), arthritis (n = 57; 23.6%), and diabetes (n = 53; 21.6%). After controlling for potential confounders, the factors noted to be independently associated with the presence of comorbidities were advanced age, family history of comorbidity, normal weight or underweight, and cancer treatment for more than 6 months' duration.

Conclusions

The high prevalence of comorbidities among patients with cancer suggests the need for an integrated system of care and management as the comorbidities affect the overall management of cancer treatment and care.

The Role of a Smart Health Ecosystem in Transforming the Management of Chronic Health Conditions

The effective management of chronic conditions requires an approach that promotes a shift in care from the clinic to the home, improves the efficiency of health care systems, and benefits all users irrespective of their needs and preferences. Digital health can provide a solution to this challenge, and in this paper, we provide our vision for a smart health ecosystem. A smart health ecosystem leverages the interoperability of digital health technologies and advancements in big data and artificial intelligence for data collection and analysis and the provision of support. We envisage that this approach will allow a comprehensive picture of health, personalization, and tailoring of behavioral and clinical support; drive theoretical advancements; and empower people to manage their own health with support from health care professionals. We illustrate the concept with 2 use cases and discuss topics for further consideration and research, concluding with a message to encourage people with chronic conditions, their caregivers, health care professionals, policy and decision makers, and technology experts to join their efforts and work toward adopting a smart health ecosystem.

Dementia and comorbidities in primary care: a scoping review

BACKGROUND

People with dementia (PwD) are known to have more chronic conditions compared to those without dementia, which can impact the clinical presentation of dementia, complicate clinical management and reduce overall quality of life. While primary care providers (PCPs) are integral to dementia care, it is currently unclear how PCPs adapt dementia care practices to account for comorbidities. This scoping review maps recent literature that describes the role for PCPs in the prevention, detection/diagnosis and management of dementia in the context of comorbidities, identifies critical knowledge gaps and proposes potential avenues for future research.

METHODS

We searched for peer-reviewed literature published between 2017-2022 in MEDLINE, Cochrane Library, and Scopus using key terms related to dementia, primary care, and comorbidity. The literature was screened for relevance by title-abstract screening and subsequent full-text screening. The prioritized papers were categorized as either 'Risk Assessment and Prevention', 'Screening, Detection, and Diagnosis' or 'Management' and were further labelled as either 'Tools and Technologies', 'Recommendations for Clinical Practice' or 'Programs and Initiatives'.

RESULTS

We identified 1,058 unique records in our search and respectively excluded 800 and 230 publications during title-abstract and full-text screening. Twenty-eight articles were included in our review, where ~ 50% describe the development and testing of tools and technologies that use pre-existing conditions to assess dementia risk. Only one publication provides official dementia screening guidelines for PCPs in people with pre-existing conditions. About 30% of the articles discuss managing the care of PwD, where most were anchored around models of multidisciplinary care and mitigating potentially inappropriate prescribing.

CONCLUSION

To our knowledge, this is the first scoping review that examines the role for PCPs in the prevention, detection/diagnosis and management of dementia in the context of comorbidities. Given our findings, we recommend that future studies: 1) further validate tools for risk assessment, timely detection and diagnosis that incorporate other health conditions; 2) provide additional guidance into how comorbidities could impact dementia care (including prescribing medication) in primary care settings; 3) incorporate comorbidities into primary care quality indicators for dementia; and 4) explore how to best incorporate dementia and comorbidities into models/frameworks of holistic, person-centred care.

Current definitions of advanced multimorbidity: a protocol for a scoping review

INTRODUCTION

People living with and dying from multimorbidity are increasing in number, and ensuring quality care for this population is one of the major challenges facing healthcare providers. People with multimorbidity often have a high burden of palliative and end-of-life care needs, though they do not always access specialist palliative care services. A key reason for this is that they are often not identified as being in the last stages of their life by current healthcare providers and systems.This scoping review aims to identify and present the available evidence on how people with multimorbidity are currently included in research, policy and clinical practice.

METHODS AND ANALYSIS

Scoping review methodology, based on Arksey and O'Malley's framework, will be undertaken and presented using the Preferred Reporting Items for Systematic Review and Meta-Analyses extension for Scoping Reviews. Search terms have been generated using the key themes of 'multimorbidity', 'end of life' and 'palliative care'. Peer-reviewed research will be obtained through systematic searching of Medline, EMBASE, CINAHL, Scopus and PsycINFO. Grey literature will be searched in a systematic manner. Literature containing a definition for adults with multimorbidity in a terminal phase of their illness experience will be included. After screening studies for eligibility, included studies will be described in terms of setting and characteristics as well as using inductive content analysis to highlight the commonalities in definitions.

ETHICS AND DISSEMINATION

Ethical approval is not required for this scoping review. The findings of the scoping review will be used internally as part of SPB's PhD thesis at the University of St Andrews through the Multimorbidity Doctoral Training Programme for Health Professionals, which is supported by the Wellcome Trust (223499/Z/21/Z) and published in an open access, peer-reviewed journal for wider dissemination.

Race, everyday discrimination, and cognitive function in later life

Discrimination is pernicious in many ways, but there are inconsistent findings regarding whether it is harmful to cognitive function in later life. To address the inconsistency, we use two closely related concepts of everyday discrimination to predict cognitive trajectories in a diverse sample. Using data from the Health and Retirement Study (HRS), we examine whether the frequency of discrimination, measured at baseline with six questions, is related to poorer cognitive function and change in function over time (2008-2016). Age at baseline ranged from 53 to 100. Growth curve models of initial cognitive function and change in function were estimated. Everyday global discrimination was associated with poorer initial cognition and slower declines over time, and these relationships were not moderated by race and ethnicity. By contrast, the relationship between everyday racial discrimination and cognition was moderated by race: more frequent everyday racial discrimination was associated with better initial cognitive function among Black adults but not among Hispanic and White adults. Discrimination is a multifaceted concept, and specific types of discrimination manifest lower or higher cognitive function during later life for White, Black, and Hispanic adults.

The Multimorbidity Web in rheumatoid arthritis

Multimorbidity, the presence of multiple chronic conditions, is highly prevalent in people with RA. An essential characteristic of multimorbidity is the interrelatedness of the different conditions that may develop in a multimorbid person. Recent studies have begun to identify and describe the Multimorbidity Web by elucidating unique multimorbidity patterns in people with RA. The primary multimorbidity patterns in this web are cardiopulmonary, cardiometabolic, and mental health and chronic pain multimorbidity. Once caught in the Multimorbidity Web, the consequences can be devastating, with reduced quality of life, physical function, survival, and treatment responses observed in multimorbid RA persons. The development of effective management and preventive approaches for multimorbidity in people with RA is in its infancy. Determining how best to assess, intervene, and prevent multimorbidity in RA is crucial to optimize long-term outcomes in people with RA.

Medical profile of patients referred to an Australian postgraduate oral surgery clinic

BACKGROUND AND OBJECTIVES

Thorough knowledge of a patient's medical history and medications is necessary for providing safe oral surgery care, and may be considered a form of risk management. This study investigated the prevalence of medical conditions and medication types in patients referred to an Australian postgraduate oral surgery clinic over 2 years.

MATERIALS AND METHODS

A retrospective cross-sectional study of the clinical records of 233 randomized patients referred to the Griffith University (Queensland, Australia) postgraduate oral surgery clinic in 2018 and 2019 was performed. Medical conditions and medications were counted and categorized, and descriptive statistics were generated.

RESULTS

In all, 133 patients (57%) had at least one medical condition. 58% of them (77) had two or more categories of medical conditions, representing nearly a third (33.0%) of all sampled patients. The most prevalent category of medical conditions was psychiatric (25.3%), followed closely by cardiovascular (24.5%) diseases. Cardiovascular medications were the most prevalent, comprising 23.6% of all medications recorded, followed by psychotropics (18.3%).

CONCLUSION

Over half of patients referred to the postgraduate oral surgery clinic had at least one systemic medical condition. Nearly a third of patients referred had at least two distinct systemic medical conditions. With an ageing population and the accompanying rise in multimorbidity globally, dental school curricula must adapt to prepare students to meet these challenges in their careers.

[Influence of multimorbidity patterns on the activities in the day-to-day lives of the elderly: nine-year follow-up of the Fibra Study]

The scope of this article was to evaluate the influence of multimorbidity and associated effects on the activities in the day-to-day lives of community-dwelling elderly individuals. It involved a cohort study with data from the FIBRA Study, the baseline (2008-2009) and follow-up (2016-2017). The basic activities in daily living (ADL) were evaluated using Katz's index, and the chronic diseases were classified as: (1) multimorbidity and multimorbidity patterns; (2) cardiopulmonary; (3) vascular-metabolic; and (4) mental-musculoskeletal. The chi-square test and Poisson regression data were used for analysis. A total of 861 older adults with no functional dependency at baseline were analyzed. Elderly individuals with multimorbidity (RR = 1.58; 95%CI: 1.19-2.10) and classified according to cardiopulmonary (RR = 2.43; 95%CI: 1.77-3.33), vascular-metabolic (RR = 1.50; 95%CI: 1.19-1.89) and mental-musculoskeletal (RR = 1.30; 95%CI: 1.03-1.65) had a higher risk of presenting functional decline in ADL in the follow-up compared to those who didn't have the same disease patterns. Multimorbidity and its patterns increased the risk of functional disability in older adults over the nine-year period.

Translational longevity medicine: a Swiss perspective in an ageing country

Breakthroughs in medical research in the last century have led to a significant extension of the human lifespan, resulting in a shift towards an elderly population worldwide. Due to the ongoing progress of global development towards elevated standards of living, this study specifically examines Switzerland as a representative nation to explore the socioeconomic and healthcare ramifications associated with an ageing population, thereby highlighting the tangible impact experienced in this context. Beyond the exhaustion of pension funds and medical budgets, by reviewing the literature and analysing publicly available data, we observe a "Swiss Japanification". Old age is associated with late-life comorbidities and an increasing proportion of time spent in poor health. To address these problems, a paradigm shift in medical practice is needed to improve health rather than respond to existing diseases. Basic ageing research is gaining momentum to be translated into therapeutic interventions and provides machine learning tools driving longevity medicine. We propose that research focus on closing the translational gap between the molecular mechanisms of ageing and a more prevention-based medicine, which would help people age better and prevent late-life chronic diseases.

Prediction of disease comorbidity using explainable artificial intelligence and machine learning techniques: A systematic review

OBJECTIVE

Disease comorbidity is a major challenge in healthcare affecting the patient's quality of life and costs. AI-based prediction of comorbidities can overcome this issue by improving precision medicine and providing holistic care. The objective of this systematic literature review was to identify and summarise existing machine learning (ML) methods for comorbidity prediction and evaluate the interpretability and explainability of the models.

MATERIALS AND METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was used to identify articles in three databases: Ovid Medline, Web of Science and PubMed. The literature search covered a broad range of terms for the prediction of disease comorbidity and ML, including traditional predictive modelling.

RESULTS

Of 829 unique articles, 58 full-text papers were assessed for eligibility. A final set of 22 articles with 61 ML models was included in this review. Of the identified ML models, 33 models achieved relatively high accuracy (80-95%) and AUC (0.80-0.89). Overall, 72% of studies had high or unclear concerns regarding the risk of bias.

DISCUSSION

This systematic review is the first to examine the use of ML and explainable artificial intelligence (XAI) methods for comorbidity prediction. The chosen studies focused on a limited scope of comorbidities ranging from 1 to 34 (mean = 6), and no novel comorbidities were found due to limited phenotypic and genetic data. The lack of standard evaluation for XAI hinders fair comparisons.

CONCLUSION

A broad range of ML methods has been used to predict the comorbidities of various disorders. With further development of explainable ML capacity in the field of comorbidity prediction, there is a significant possibility of identifying unmet health needs by highlighting comorbidities in patient groups that were not previously recognised to be at risk for particular comorbidities.

Clinical practice guidelines for cardiovascular disease: how is depression addressed? Protocol for a systematic review

INTRODUCTION

Depression frequently affects patients with cardiovascular disease (CVD). When these conditions co-occur, outcomes such as quality of life and life expectancy worsen. In everyday practice, this specific and prevalent disease-disease interaction complicates patient management. Clinical practice guidelines (CPGs) aim to provide the best available advice for clinical decision-making to improve patient care. This study will aim to evaluate how CPGs specifically address depression in patients with CVD, and whether they provide any operational guidance for screening and management of depression in the primary care and outpatient setting.

METHODS AND ANALYSIS

We will conduct a systematic review of CPGs on CVD management published from 2012 to 2023. A broad literature search for guidelines will be performed through electronic medical databases, grey literature search tools, and websites of national and professional medical organisations.Based on the inclusion criteria, two independent reviewers will evaluate eligible guidelines for screening and management recommendations on depression in patients with CVD. Additional points to be evaluated will be any mention of drug-drug or drug-disease interactions, other aspects of specific relevance to treating physicians, as well as general information on mental health. We will assess the quality of CPGs with a recommendation regarding depression in CVD patients using the Appraisal of Guidelines for Research and Evaluation II.

ETHICS AND DISSEMINATION

As this systematic review is based on available published data, ethics approval and consent are not applicable. Our intent is that our results will be published in a peer-reviewed journal, presented at international scientific meetings, and distributed to healthcare providers.

PROSPERO REGISTRATION NUMBER

CRD42022384152.

Longitudinal models for the progression of disease portfolios in a nationwide chronic heart disease population

BACKGROUND AND AIM

With multimorbidity becoming increasingly prevalent in the ageing population, addressing the epidemiology and development of multimorbidity at a population level is needed. Individuals subject to chronic heart disease are widely multimorbid, and population-wide longitudinal studies on their chronic disease trajectories are few.

METHODS

Disease trajectory networks of expected disease portfolio development and chronic condition prevalences were used to map sex and socioeconomic multimorbidity patterns among chronic heart disease patients. Our data source was all Danish individuals aged 18 years and older at some point in 1995-2015, consisting of 6,048,700 individuals. We used algorithmic diagnoses to obtain chronic disease diagnoses and included individuals who received a heart disease diagnosis. We utilized a general Markov framework considering combinations of chronic diagnoses as multimorbidity states. We analyzed the time until a possible new diagnosis, termed the diagnosis postponement time, in addition to transitions to new diagnoses. We modelled the postponement times by exponential models and transition probabilities by logistic regression models.

FINDINGS

Among the cohort of 766,596 chronic heart disease diagnosed individuals, the prevalence of multimorbidity was 84.36% and 88.47% for males and females, respectively. We found sex-related differences within the chronic heart disease trajectories. Female trajectories were dominated by osteoporosis and male trajectories by cancer. We found sex important in developing most conditions, especially osteoporosis, chronic obstructive pulmonary disease and diabetes. A socioeconomic gradient was observed where diagnosis postponement time increases with educational attainment. Contrasts in disease portfolio development based on educational attainment were found for both sexes, with chronic obstructive pulmonary disease and diabetes more prevalent at lower education levels, compared to higher.

CONCLUSIONS

Disease trajectories of chronic heart disease diagnosed individuals are heavily complicated by multimorbidity. Therefore, it is essential to consider and study chronic heart disease, taking into account the individuals' entire disease portfolio.

Primary healthcare competencies needed in the management of person-centred integrated care for chronic illness and multimorbidity: Results of a scoping review

BACKGROUND

Chronic disease management is important in primary care. Disease management programmes focus primarily on the respective diseases. The occurrence of multimorbidity and social problems is addressed to a limited extent. Person-centred integrated care (PC-IC) is an alternative approach, putting the patient at the centre of care. This asks for additional competencies for healthcare professionals involved in the execution of PC-IC. In this scoping review we researched which competencies are necessary for healthcare professionals working in collaborative teams where the focus lies within the concept of PC-IC. We also explored how these competencies can be acquired.

METHODS

Six literature databases and grey literature were searched for guidelines and peer-reviewed articles on chronic illness and multimorbidity in primary care. A data synthesis was carried out resulting in an overview of the competencies that healthcare professionals need to deliver PC-IC.

RESULTS

Four guidelines and 21 studies were included and four core competencies could be derived through the synthesis: 1. interprofessional communication, 2, interprofessional collaborative teamwork, 3. leadership and 4. patient-centred communication. Included papers mostly lack a clear description of the competencies in terms of knowledge, skills and attitudes which are necessary for a PC-IC approach and on how these competencies can be acquired.

CONCLUSION

This review provides insight on competencies necessary to provide PC-IC within primary care. Research is needed in more depth on core concepts of these competencies which will then benefit educational programmes to ensure that healthcare professionals in primary care are better equipped to deliver PC-IC for patients with chronic illness and multimorbidity.

Prevalence of Comorbidity and Its Effects on Sickness-Absenteeism among Brazilian Legislative Civil Servants

Studies have shown there is an association of chronic diseases with working days lost, considering the impact of these pathologies on the levels of vulnerability of the individual's health, with an increased risk of work disability. This article is part of a more comprehensive investigation on the sickness absenteeism of civil servants of the legislative branch in Brazil, with the purpose of determining the comorbidity index (CI) of the individuals and its correlation with days of absence from work. Sickness absenteeism was counted from the data of 37,690 medical leaves, from 2016 to 2109, involving 4149 civil servants. The self-administered comorbidity questionnaire (SCQ) was used to estimate the CI, based on the diseases or chronic health problems declared by the participants. The average number of working days lost per servant per year was 8.73 days, totaling 144,902 days of absence. The majority of the servants (65.5%) declared at least one chronic health condition. A significant association between the CI scores and working days lost was observed (r = 0.254, p-value < 0.01), thus showing that the CI may be an important predictor of sickness absenteeism. Chronic diseases or health problems are a characteristic of the general population, often affecting working capacity.

Multimorbidity in People with Epilepsy

Multimorbidity is an emerging priority in healthcare due to associations with the ageing population, frailty, polypharmacy, health and social care demands. It affects 60-70% of adults and 80% of children with epilepsy. Neurodevelopmental conditions are commonly seen in children with epilepsy, while cancer, cardiovascular and neurodegenerative conditions often afflict older people with epilepsy. Mental health problems are common across the lifespan. Genetic, environmental, social and lifestyle factors contribute to multimorbidity and its consequences. Multimorbid people with epilepsy (PWE) are at higher risk of depression and suicide, premature death, suffer lower health-related quality of life, and require more hospital admissions and health care costs. The best management of multimorbid PWE requires a paradigm shift from the traditional single disease-single comorbidity approach and a refocus on a person-centred approach. Improvements in health care must be informed by assessing the burden of multimorbidity associated with epilepsy, delineating disease clusters, and measuring the effects on health outcomes.

Economic evaluations of interventional opportunities for the management of mental-physical multimorbidity: a systematic review

OBJECTIVES

Economic evaluations of interventions for people with mental-physical multimorbidity, including a depressive disorder, are sparse. This study examines whether such interventions in adults are cost-effective.

DESIGN

A systematic review.

DATA SOURCES

MEDLINE, CINAHL Plus, PsycINFO, Cochrane CENTRAL, Scopus, Web of Science and NHS EED databases were searched until 5 March 2022.

ELIGIBILITY CRITERIA

We included studies involving people aged ≥18 with two or more chronic conditions (one being a depressive disorder). Economic evaluation studies that compared costs and outcomes of interventions were included, and those that assessed only costs or effects were excluded.

DATA EXTRACTION AND SYNTHESIS

Two authors independently assessed risk of bias in included studies using recommended checklists. A narrative analysis of the characteristics and results by type of intervention and levels of healthcare provision was conducted.

RESULTS

A total of 19 studies, all undertaken in high-income countries, met inclusion criteria. Four intervention types were reported: collaborative care, self-management, telephone-based and antidepressant treatment. Most (14 of 19) interventions were implemented at the organisational level and were potentially cost-effective, particularly, the collaborative care for people with depressive disorder and diabetes, comorbid major depression and cancer and depression and multiple long-term conditions. Cost-effectiveness ranged from £206 per quality-adjusted life year (QALY) for collaborative care programmes for older adults with diabetes and depression at primary care clinics (USA) to £79 723 per QALY for combining collaborative care with improved opportunistic screening for adults with depressive disorder and diabetes (England). Conclusions on cost-effectiveness were constrained by methodological aspects of the included studies: choice of perspectives, time horizon and costing methods.

CONCLUSIONS

Economic evaluations of interventions to manage multimorbidity with a depressive disorder are non-existent in low-income and middle-income countries. The design and reporting of future economic evaluations must improve to provide robust conclusions.

PROSPERO REGISTRATION NUMBER

CRD42022302036.

Multimorbidity status and annual healthcare expenditures of rheumatoid arthritis patients: a Dutch hospital-centered versus population-based comparison

The prevalence of multimorbidity among rheumatoid arthritis (RA) patients is increasing and associated with worse outcomes. Therefore, management of multimorbid patients requires a multidisciplinary approach. However, healthcare systems consist of mono-disciplinary subsystems, which limits collaboration across subsystems. To study the importance of a multidisciplinary, integrated approach, associations between expenditures and multimorbidity are assessed in real-life data. Retrospective data on RA patients from a Dutch single-hospital are analyzed and compared to the Dutch RA population data. The Elixhauser index is used to measure the multimorbidity prevalence. Regression analyses were conducted to derive the relationship between multimorbidity, healthcare costs and self-reported quality of life (e.g. EQ-5D). When analyzing the impact of multimorbidity within RA patients in context of a single-hospital context, multimorbidity is only partially captured: 13% prevalence versus 24% of the Dutch population. Multimorbidity is associated with higher care expenditures. Depending on the type of multimorbidity, expenditures are €43-€5821 higher in a single-hospital and from €2259-€9648 in population data. Finally, medication use associated with chronic diseases and self-reported aspects of well-being are associated with similar increases in healthcare expenditures as multimorbidity based on hospital care. Within RA, a single-hospital approach underestimates the association between multimorbidity and healthcare expenditures as 43% of healthcare utilization and expenditures are missed. To overcome a single-provider perspective in healthcare and efficiently coordinate multimorbid patients, besides providing holistic care, professionals also need to use data providing comprehensive pictures of patients.

A mixed-methods systematic review of nurse-led interventions for people with multimorbidity

AIMS

To identify types of nurse-led interventions for multimorbidity and which outcomes are positively affected by them.

DESIGN

Mixed-methods systematic review following the Joanna Briggs Institute (JBI) methods for convergent-integrated reviews.

PROSPERO ID

CRD42020197956.

DATA SOURCES

Cochrane CENTRAL, CINAHL, Embase and MEDLINE were searched in October 2020. Grey literature sources included OpenGrey, the Journal of Multimorbidity and Comorbidity and reference mining.

REVIEW METHODS

English-language reports of nurse-led interventions for people with multimorbidity were included based on author consensus. Two reviewers performed independent quality appraisal using JBI tools. Data were extracted and synthesized using a pre-existing taxonomy of interventions and core outcome set.

RESULTS

Twenty studies were included, with a median summary quality score of 77.5%. Interventions were mostly case-management or transitional care interventions, with nurses in advanced practice, support to self-manage conditions, and an emphasis on continuity of care featuring frequently. Patient-centred outcomes such as quality of healthcare and health-related quality of life were mostly improved, with mixed effects on healthcare utilization, costs, mortality and other outcomes.

CONCLUSION

Interventions such as case management are agreeable to patients and transitional care interventions may have a small positive impact on healthcare utilization. Interventions include long-term patient management or short-term interventions targeted at high-risk junctures. These interventions feature nurses in advanced practice developing care plans in partnership with patients, to simplify and improve the quality of care both in the long and short-term.

IMPACT

This is the first mixed-methods review which includes all types of nurse-led interventions for multimorbidity and does not focus on specific comorbidities or elderly/frail populations. Using adapted consensus-developed frameworks for interventions and outcomes, we have identified the common features of interventions and their overall typology. We suggest these interventions are of value to patients and healthcare systems but require localization and granular evaluation of their components to maximize potential benefits.

Multimorbidity

Multimorbidity (two or more coexisting conditions in an individual) is a growing global challenge with substantial effects on individuals, carers and society. Multimorbidity occurs a decade earlier in socioeconomically deprived communities and is associated with premature death, poorer function and quality of life and increased health-care utilization. Mechanisms underlying the development of multimorbidity are complex, interrelated and multilevel, but are related to ageing and underlying biological mechanisms and broader determinants of health such as socioeconomic deprivation. Little is known about prevention of multimorbidity, but focusing on psychosocial and behavioural factors, particularly population level interventions and structural changes, is likely to be beneficial. Most clinical practice guidelines and health-care training and delivery focus on single diseases, leading to care that is sometimes inadequate and potentially harmful. Multimorbidity requires person-centred care, prioritizing what matters most to the individual and the individual's carers, ensuring care that is effectively coordinated and minimally disruptive, and aligns with the patient's values. Interventions are likely to be complex and multifaceted. Although an increasing number of studies have examined multimorbidity interventions, there is still limited evidence to support any approach. Greater investment in multimorbidity research and training along with reconfiguration of health care supporting the management of multimorbidity is urgently needed.

Improving multimorbidity measurement using individualized disease-specific quality of life impact assessments: predictive validity of a new comorbidity index

BACKGROUND

Interpretation of health-related quality of life (QOL) outcomes requires improved methods to control for the effects of multiple chronic conditions (MCC). This study systematically compared legacy and improved method effects of aggregating MCC on the accuracy of predictions of QOL outcomes.

METHODS

Online surveys administered generic physical (PCS) and mental (MCS) QOL outcome measures, the Charlson Comorbidity Index (CCI), an expanded chronic condition checklist (CCC), and individualized QOL Disease-specific Impact Scale (QDIS) ratings in a developmental sample (N = 5490) of US adults. Controlling for sociodemographic variables, regression models compared 12- and 35-condition checklists, mortality vs. population QOL-weighting, and population vs. individualized QOL weighting methods. Analyses were cross-validated in an independent sample (N = 1220) representing the adult general population. Models compared estimates of variance explained (adjusted R2) and model fit (AIC) for generic PCS and MCS across aggregation methods at baseline and nine-month follow-up.

RESULTS

In comparison with sociodemographic-only regression models (MCS R2 = 0.08, PCS = 0.09) and Charlson CCI models (MCS R2 = 0.12, PCS = 0.16), increased variance was accounted for using the 35-item CCC (MCS R2 = 0.22, PCS = 0.31), population MCS/PCS QOL weighting (R2 = 0.31-0.38, respectively) and individualized QDIS weighting (R2 = 0.33 & 0.42). Model R2 and fit were replicated upon cross-validation.

CONCLUSIONS

Physical and mental outcomes were more accurately predicted using an expanded MCC checklist, population QOL rather than mortality CCI weighting, and individualized rather than population QOL weighting for each reported condition. The 3-min combination of CCC and QDIS ratings (QDIS-MCC) warrant further testing for purposes of predicting and interpreting QOL outcomes affected by MCC.

Comparison of 6 Mortality Risk Scores for Prediction of 1-Year Mortality Risk in Older Adults With Multimorbidity

IMPORTANCE

The most appropriate therapy for older adults with multimorbidity may depend on life expectancy (ie, mortality risk), and several scores have been developed to predict 1-year mortality risk. However, often, these mortality risk scores have not been externally validated in large sample sizes, and a head-to-head comparison in a prospective contemporary cohort is lacking.

OBJECTIVE

To prospectively compare the performance of 6 scores in predicting the 1-year mortality risk in hospitalized older adults with multimorbidity.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study analyzed data of participants in the OPERAM (Optimising Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older People) trial, which was conducted between December 1, 2016, and October 31, 2018, in surgical and nonsurgical departments of 4 university-based hospitals in Louvain, Belgium; Utrecht, the Netherlands; Cork, Republic of Ireland; and Bern, Switzerland. Eligible participants in the OPERAM trial had multimorbidity (≥3 coexisting chronic diseases), were aged 70 years or older, had polypharmacy (≥5 long-term medications), and were admitted to a participating ward. Data were analyzed from April 1 to September 30, 2020.

MAIN OUTCOMES AND MEASURES

The outcome of interest was any-cause death occurring in the first year of inclusion in the OPERAM trial. Overall performance, discrimination, and calibration of the following 6 scores were assessed: Burden of Illness Score for Elderly Persons, CARING (Cancer, Admissions ≥2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, ≥2 Noncancer hospice guidelines) Criteria, Charlson Comorbidity Index, Gagné Index, Levine Index, and Walter Index. These scores were assessed using the following measures: Brier score (0 indicates perfect overall performance and 0.25 indicates a noninformative model); C-statistic and 95% CI; Hosmer-Lemeshow goodness-of-fit test and calibration plots; and sensitivity, specificity, and positive and negative predictive values.

RESULTS

The 1879 patients in the study had a median (IQR) age of 79 (74-84) years and 835 were women (44.4%). The median (IQR) number of chronic diseases was 11 (8-16). Within 1 year, 375 participants (20.0%) died. Brier scores ranged from 0.16 (Gagné Index) to 0.24 (Burden of Illness Score for Elderly Persons). C-statistic values ranged from 0.62 (95% CI, 0.59-0.65) for Charlson Comorbidity Index to 0.69 (95% CI, 0.66-0.72) for the Walter Index. Calibration was good for the Gagné Index and moderate for other mortality risk scores.

CONCLUSIONS AND RELEVANCE

Results of this prognostic study suggest that all 6 of the 1-year mortality risk scores examined had moderate prognostic performance, discriminatory power, and calibration in a large cohort of hospitalized older adults with multimorbidity. Overall, none of these mortality risk scores outperformed the others, and thus none could be recommended for use in daily clinical practice.

Models of care for improving health-related quality of life, mental health, or mortality in persons with multimorbidity: A systematic review of randomized controlled trials

Objectives

To categorize and examine the effectiveness regarding health-related quality of life (HRQoL), mental health, and mortality of care models for persons with multimorbidity in primary care, community care, and hospitals through a systematic review.

Methods

We searched PubMed, Embase, and Cochrane Central Register of Controlled Trials up to May 2020. One author screened titles and abstracts, and to validate, a second author screened 5% of the studies. Two authors independently extracted data and assessed risk of bias using the tool by the Cochrane Effective Practice and Organisation of Care group. Study inclusion criteria were (1) participants aged ≥ 18 years with multimorbidity; (2) referred to multimorbidity or two or more specific chronic conditions in the title or abstract; (3) randomized controlled design; and (4) HRQoL, mental health, or mortality as primary outcome measures. We used the Foundation Framework to categorize the models and the PRISMA-guideline for reporting.

Results

In this study, the first to report effectiveness of care models in patients with multimorbidity in hospital settings, we included 30 studies and 9,777 participants with multimorbidity. 12 studies were located in primary care, 9 in community care, and 9 in hospitals. HRQoL was reported as the primary outcome in 12 studies, mental health in 17 studies, and mortality in three studies-with significant improvements in 5, 14, and 2, respectively. The studies are presented according to settings.

Conclusions

Although 20 of the care models reported positive effects, the variations in populations, settings, model elements, and outcome measures made it difficult to conclude on which models and model elements were effective.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

Sociodemographic Differences in Multimorbidity: A Closer Look from Indonesian Family and Life Survey

The prevalence of multimorbidity, the coexistence of two or more chronic diseases, is expected to increase, including in Indonesia. This phenomenon is associated with increased life expectancy and incidence of non-communicable diseases. Therefore, this study assesses the burden of multimorbidity in Indonesia by sociodemographic factors. The researchers analyzed cross-sectional data from the latest wave of IFLS conducted in 2014, the IFLS wave 5. The researchers included individuals aged 15 and above with blood pressure measurements (n= 32.256) from 13,536 households. Meanwhile, the researchers excluded individuals with missing data on BMI (183 individuals) or who had biologically implausible or extreme values (n=6). The analyses were then conducted on 32,067 individuals. The analyses comprised the ten most common self-reported chronic diseases diagnosis in IFLS-5. The findings revealed that the prevalence of self-reported multimorbidity in Indonesia was relatively high, at 9.32% (n= 2.989), with the highest proportion of multimorbidity reported among the elderly. Approximately 2.76% of the respondents (n- 885) reported having three or more chronic diseases. The most common combinations were hypertension and digestive problem (2.15%, n= 689), followed by hypertension and arthritis (1.79%, n= 574), and hypertension and high cholesterol (1.68%, n= 539). When stratified by sociodemographic factors, the researchers found a higher proportion of multimorbidity among females (11.01%, n= 3,530) compared to males (7.41%, n= 2.376), elderly (21.54%, n= 3.530) compared to younger adults, and previous smokers (20.90%, n= 6.072). People who were obese and overweight also reported a higher prevalence of multimorbidity (13.73%, n= 4.403 and 9.3%, n= 2.998, respectively). In addition, those living in urban areas had a higher proportion of multimorbidity (10.33%, n= 3.313) compared to rural areas (7.2%, n= 2.527). In conclusion, this study uncovered a relatively high prevalence of multimorbidity. People living in urban areas were overweight/obese and those who had low SES had a higher proportion of multimorbidity. With the nature of self-reported data and previously reported underdiagnosis of chronic diseases, screening to examine multimorbidity is needed.

Conceptualising comorbidity and multimorbidity in dementia: A scoping review and syndemic framework

Background

Older people and people with dementia experience a high prevalence of multiple health conditions. The terms ‘comorbidity’ and ‘multimorbidity’ are often used interchangeably to describe this, however there are key conceptual differences between these terms and their definitions. This has led to issues in the validity and comparability of research findings, potentially inappropriate intervention development and differences in quality of health care.

Objective

To review how the terms ‘comorbidity’ and ‘multimorbidity’ are defined within peer-reviewed dementia research and propose an operational framework.

Design

A scoping review of definitions within dementia research was carried out. Searches took place across five databases: Academic Search Premier, CINAHL Complete, MEDLINE, PsycARTICLES and PsycINFO. PRISMA-ScR guidelines were followed.

Results

Content analysis revealed five key themes, showing significant overlap and inconsistencies from both within, and between, the comorbidity and multimorbidity definitions; 1. Number of conditions; 2. Type of health conditions; 3. The co-occurrence of conditions; 4. The inclusion of an index disease (or not); 5. Use of medical language. The analysis also revealed gaps in how the underlying concepts of the definitions relate to people with dementia living with multiple health conditions.

Conclusion

This scoping review found that current definitions of comorbidity and multimorbidity are heterogeneous, reductionist and disease-focussed. Recommendations are made on the design of research studies including transparency and consistency of any terms and definitions used. A syndemic framework could be a useful tool for researchers, clinicians and policy makers to consider a more holistic picture of a person with dementia’s health and wellbeing.

The association between educational level and multimorbidity among adults in Southeast Asia: A systematic review

BACKGROUND

In Southeast Asia, the prevalence of multimorbidity is gradually increasing. This paper aimed to investigate the association between educational level and multimorbidity among over 15-years old adults in Southeast Asia.

METHODS

We conducted a systematic review of published observational studies. Studies were selected according to eligibility criteria of addressing definition and prevalence of multimorbidity and associations between level of education and multimorbidity in Southeast Asia. The Newcastle-Ottawa Scale (NOS) was used to measure the quality and risk of bias. The methodology has been published in PROSPERO with registered number ID: CRD42021259311.

RESULTS

Eighteen studies were included in the data synthesis. The results are presented using narrative synthesis due to the heterogeneity of differences in exposures, outcomes, and methodology. The prevalence of multimorbidity ranged from 1.7% to 72.6% among over 18 years-old adults and from 1.5% to 51.5% among older people (≥ 60 years). There were three association patterns linking between multimorbidity and education in these studies: (1) higher education reducing odds of multimorbidity, (2) higher education increasing odds of multimorbidity and (3) education having no association with multimorbidity. The association between educational attainment and multimorbidity also varies widely across countries. In Singapore, three cross-sectional studies showed that education had no association with multimorbidity among adults. However, in Indonesia, four cross-sectional studies found higher educated persons to have higher odds of multimorbidity among over 40-years-old persons.

CONCLUSIONS

Published studies have shown inconsistent associations between education and multimorbidity because of different national contexts and the lack of relevant research in the region concerned. Enhancing objective data collection such as physical examinations would be necessary for studies of the connection between multimorbidity and education. It can be hypothesised that more empirical research would reveal that a sound educational system can help people prevent multimorbidity.

Nurses' perceptions and beliefs related to the care of adults living with multimorbidity: A systematic qualitative review

AIMS AND OBJECTIVES

To identify and synthesise the available qualitative evidence on nurses' perceptions and beliefs related to the care of adults living with multimorbidity.

BACKGROUND

The rising prevalence of adults living with multimorbidity has increased demand for health care and challenges nursing care. No review has been conducted to date of the studies of nurses' perceptions and beliefs related to the provision of care to guide policy makers, practitioners and further research to identify and deliver quality care for persons living with multimorbidity.

DESIGN

Systematic review of qualitative studies conducted in line with the PRISMA checklist.

METHODOLOGY

Eight electronic publication databases and sources of grey literature were searched to identify original qualitative studies of the experience of nurses caring for adults with multiple chronic conditions with no restrictions on the date of publication or study context. Study quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research. Data were extracted using the Joanna Briggs Institute standardised data extraction tool for qualitative research. Data synthesis was undertaken through meta-aggregation.

RESULTS

Eleven qualitative studies were included in the review. All studies met eight or more of the 10 assessment criteria of the JBI Critical Appraisal Checklist for Qualitative Research. Four synthesised findings were generated from the aggregated findings: (i) the challenge of providing nursing care; (ii) the need to deliver holistic and person-centred nursing care; (iii) the importance of developing a therapeutic nurse-patient relationship, and (iv) delivering nursing care as part of an interprofessional care team.

CONCLUSIONS

The complexity of multimorbidity and the predominant single-disease model of chronic care present challenges for the delivery of nursing care to adults living with multimorbidity.

RELEVANCE TO CLINICAL PRACTICE

The nursing care of persons with multimorbidity needs to incorporate holistic assessment and person-centred care principles as part of a collaborative and interprofessional team approach.

PROSPERO REGISTRATION

CRD42020186773.

Polypharmacy in polymorbid pregnancies and the risk of congenital malformations-A systematic review

With an increased prevalence of concurrent morbidities during pregnancy, polypharmacy has become increasingly common in pregnant women. The risks associated with polypharmacy may exceed those of individual medication because of drug-drug interactions. This systematic review aims to evaluate the risk of congenital malformations in polymorbid pregnancies exposed to first-trimester polypharmacy. PubMed, Embase and Scopus were searched to identify original human studies with first- trimester polypharmacy due to polymorbidity as the exposure and congenital malformations as the outcome. After screening of 4034 identified records, seven studies fulfilled the inclusion criteria. Four of the seven studies reported an increased risk of congenital malformations compared with unexposed or monotherapy, odds ratios ranging from 1.1 to >10.0. Particularly, short-term anti-infective treatment combined with other drugs and P-glycoprotein substrates were associated with increased malformation risks. In conclusion, knowledge is limited on risks associated with first-trimester polypharmacy due to polymorbidity with the underlying evidence of low quantity and quality. Therefore, an increased focus on pharmacovigilance to enable safe drug use in early pregnancy is needed. Large-scale register-based studies and better knowledge of placental biology are needed to support the clinical management of polymorbid pregnancies that require polypharmacy.

Multimorbidity measures from health administrative data using ICD system codes: A systematic review

BACKGROUND

We aimed to identify and characterize adult population-based multimorbidity measures using health administrative data and the International Classification of Diseases (ICD) codes for disease identification.

METHODS

We performed a narrative systematic review of studies using or describing development or validation of multimorbidity measures. We compared the number of diseases included in the measures, the process of data extraction (case definition) and the validation process. We assessed the methodological robustness using eight criteria, five based on general criteria for indicators (AIRE instrument) and three multimorbidity-specific criteria.

RESULTS

Twenty-two multimorbidity measures were identified. The number of diseases they included ranged from 5 to 84 (median = 20), with 19 measures including both physical and mental conditions. Diseases were identified using ICD codes extracted from inpatient and outpatient data (18/22) and sometimes including drug claims (10/22). The validation process relied mainly on the capacity of the measures to predict health outcome (5/22), or on the validation of each individual disease against a gold standard (8/22). Six multimorbidity measures met at least six of the eight robustness criteria assessed.

CONCLUSION

There is significant heterogeneity among the measures used to assess multimorbidity in administrative databases, and about a third are of low to moderate quality. A more consensual approach to the number of diseases or groups of diseases included in multimorbidity measures may improve comparison between regions, and potentially provide better control for multimorbidity-related confounding in studies.