Atrial fibrillation (AF) is the most common arrhythmia in older adults and often coexists with other chronic conditions, exacerbating physical and cognitive decline and contributing to frailty. The interplay between frailty and comorbidity in AF remains underexplored, particularly regarding quality of life (QoL), health management, and outcome prioritization. Within the AFFIRMO project, this study investigated the experiences of older adults with AF and at least one chronic condition via an online survey. Frailty was assessed using the FRAIL questionnaire, and participants were grouped by frailty status and number of comorbidities. Health-related quality of life (HRQoL) was measured using the EQ-5D-3L and Visual Analogue Scale (VAS). Challenges in health management and prioritized outcomes were also explored. We included 659 participants (median age 72 years, 52.8% female). Those with pre-frailty or frailty and ≥ 3 comorbidities reported the poorest HRQoL. Comorbidity, particularly combined with frailty, was associated with health management difficulties, including healthcare visits, polypharmacy, and mobility limitations. Across all groups, maintaining independence and improving QoL were prioritized outcomes. Pain relief was especially important for those with higher comorbidities. In older adults with AF, comorbidity and frailty significantly affect QoL and health burden. Tailored, patient-centred care strategies and routine assessment of frailty and comorbidity are essential to improve care coordination and outcomes.
Identify subgroups of oncology patients with distinct joint chemotherapy-induced nausea (CIN) AND morning fatigue profiles and distinct joint CIN AND evening fatigue profiles, as well as modifiable and non-modifiable risk factors. Oncology patients receiving chemotherapy completed self-report questionnaires that provided information on demographic and clinical characteristics, as well as on CIN and morning and evening fatigue. The three symptoms were assessed six times over two cycles of chemotherapy. Joint latent class profile analyses (LCPA) were performed to identify subgroups of patients with distinct joint symptom profiles. Parametric and non-parametric tests were used to evaluate for differences in modifiable and non-modifiable risk factors among the profiles. Five and four subgroups were identified with distinct joint CIN and morning fatigue and distinct joint CIN and evening fatigue profiles, respectively. Risk factors associated with membership in the worse profiles included younger age, lower annual household income, high comorbidity burden, lower functional status, self-reported diagnosis of depression, and higher levels of neuropsychological and gastrointestinal symptoms. Across both LCPAs, 60% of the sample reported CIN with occurrence rates that ranged from approximately 30% to 90%. In addition, wide variations were found in both morning and evening fatigue severity scores depending on the distinct profile. These initial findings suggest that CIN co-occurs with both morning and evening fatigue. The co-occurrence of CIN and fatigue may be related to shared biological mechanisms that warrant evaluation in future studies.
Preterm birth (PTB) is a leading global cause of neonatal morbidity and mortality. While individual maternal chronic conditions are established risk factors, the role of maternal multimorbidity remains underexplored. This study aimed to examine the association between maternal multimorbidity and PTB, and to identify chronic conditions associated with the occurrence and severity of PTB. A retrospective matched case-control study was conducted at Archbishop Makarios III Hospital in Nicosia, Cyprus. The sample included 978 singleton live births, consisting of 489 preterm cases (<37 weeks) matched 1:1 with 489 term controls (≥37 weeks) by maternal age and country of origin. Data were extracted from patient's medical records. Multimorbidity was defined as the presence of two or more chronic conditions. Conditional logistic regression assessed associations with PTB, and binary logistic regression examined predictors of extreme/very PTB (<32 weeks) versus moderate/late PTB (32 to <37 weeks). Maternal multimorbidity was associated with increased odds of PTB (aOR = 1.80; 95% CI: 1.16-2.79; p=0.009). Hypertension (aOR=4.26; 95% CI: 1.84-9.86), kidney disease (aOR=3.67; 95% CI: 1.01-13.30), thrombophilia (aOR=3.53; 95% CI: 1.14-10.88), thyroid disorders (aOR = 1.77; 95% CI: 1.05-2.98), and allergies (aOR=1.82; 95% CI: 1.12-2.99) were independently associated with PTB. Diabetes was inversely associated with extreme PTB (aOR=0.19; 95% CI: 0.10-0.92). Maternal multimorbidity and several chronic conditions are significant and independent predictors of PTB. These findings underscore the importance of comprehensive antenatal screening and integrated care for women with multiple health conditions. Tailored risk assessment strategies may help reduce the burden of PTB, particularly in populations with rising rates of chronic disease.
The syndemic burden of cardiovascular disease (CVD), chronic kidney disease (CKD), and type 2 diabetes mellitus (T2DM) represents a growing global health challenge, yet standardized tools for quantifying integrated disease burden remain lacking. We developed and preliminarily evaluated a novel Cardio-Kidney-Metabolic (CKM) Index to assess multimorbidity trends and to explore its potential to inform evidence-based policy interventions. Using Global Burden of Disease Study 2021 data spanning 204 countries and territories from 1990 to 2021, we extracted age-standardized disability-adjusted life years (DALYs) for CVD, CKD, and T2DM. The CKM Index was constructed through logarithmic transformation (log[x + 1]), min-max normalization, and weighted integration based on global burden proportions and clinical significance (CVD = 0.5, CKD = 0.2, T2DM = 0.3) to generate a standardized 0-100 scale. We analyzed temporal trends using estimated annual percentage change (EAPC), performed joinpoint regression to identify trajectory inflection points, and conducted forecasting through 2030 using ARIMA and Bayesian ridge regression models. Sensitivity analyses evaluated index robustness across alternative weighting schemes, and clustering analysis identified distinct country trajectory patterns across socio-demographic index (SDI) regions. Global CKM-related DALYs increased dramatically by 60% from 343 million person-years in 1990 to 548 million in 2021 (EAPC + 1.51%). T2DM demonstrated the most explosive growth (EAPC + 3.57%), followed by CKD (+ 2.46%) and CVD (+ 1.18%). The CKM Index revealed marked global health inequalities, with high-SDI countries exhibiting the highest burden (70.7 in 2021) despite advanced healthcare systems, while middle-SDI regions showed concerning acceleration (reaching 77.1). Low-SDI regions demonstrated lower absolute burden (22.7) but concerning stagnation since 2005. China's CKM Index rose substantially from 27.7 in 1990 to 67.6 in 2021, with joinpoint analysis revealing acceleration phases in 1998 and 2006, reflecting rapid epidemiological transition during economic development. Age-stratified analysis revealed 35% of total burden concentrated in individuals aged 60-74 years, with consistent male predominance. Pairwise comorbidity analysis showed CVD + T2DM combinations increasing fastest globally (EAPC + 1.45%), while CKD + T2DM burden nearly tripled. Forecasting models projected continued escalation through 2030, with middle-SDI regions reaching 86.6-87.5 and China plateauing at 66.7-77.5, though COVID-19 highlighted forecasting limitations under structural disruptions. The CKM Index provides a promising methodological prototype for quantifying multimorbidity burden and reveals alarming global escalation trends with pronounced health inequalities. The syndemic nature of CKM diseases demands paradigmatic shifts from specialty-siloed to integrated chronic disease management. Countries achieving burden reductions within similar development contexts demonstrate the potential for coordinated policy interventions. Urgent global action is required to address the growing CKM crisis through enhanced surveillance, integrated care delivery, and targeted interventions addressing social determinants of health.
Multimorbidity, having two or more chronic conditions, is a growing public health concern associated with substantial health and societal burdens. However, evidence on its impact on health-related quality of life (HRQoL) among U.S. adults remains limited. This study fills a major research gap by examining the association between multimorbidity and HRQoL among U.S. adults, a population often overlooked in prior research and provides evidence to inform policies aligned with national and global health goals for reducing the chronic disease burden. A cross-sectional study was conducted among adults aged 18 to 64 years. Data from the Medical Expenditure Panel Survey was used in this study for years 2019 to 2021. The primary study outcome was the HRQoL; it was evaluated using the 12-item Veterans RAND 12. Descriptive analysis was used to describe the characteristics of the study sample. The adjusted relationship between Multimorbidity and HRQoL was assessed using the multivariable linear regression after other factors were adjusted in the regression analysis. The study sample consists of 30,827 adults. Multimorbidity was prevalent among 23.4% of adults. It was higher among women, unemployed, poor, and physically inactive adults. Adults with multimorbidity had a lower mean HRQoL score than those without multimorbidity (Physical health = 46.06 vs. 53.29, Mental health = 47.62 vs. 52.37). Results from the adjusted linear regression model found that adults with multimorbidity have a significantly lower HRQoL in both the physical domain (β = -2.658, p-value<0.0001), and the mental domain (β = -3.119, p-value<0.0001). Multimorbidity has a substantial negative impact on both physical and mental aspects of HRQoL in U.S. adults. These findings highlight the need for targeted public health strategies and clinical interventions, such as promoting integrated chronic disease management to address the burden of multimorbidity. Future research should explore specific condition clusters most strongly associated with reduced HRQoL to better inform policy and care models.
Atrial fibrillation (AF) often coexists with multiple chronic conditions, worsening health-related quality of life (HRQoL) and increasing the burden on patients and caregivers. While multimorbidity is known to worsen clinical outcomes, the role of distinct comorbidity patterns in shaping patients' experience remains unclear. This cross-sectional study assessed whether the number and patterns of comorbidities differentially affect HRQoL, care needs, and priorities of AF patients and caregivers. An online survey on living with AF and multimorbidity was disseminated between May 2022 and January 2023 in the UK, Italy, Spain, Romania, and Denmark. The analysis included 633 AF patients (46.9% females, median age 73 years) and 198 caregivers (26.8% females, median age 57 years). Exposure variables were the number and patterns (derived through latent class analysis) of comorbidities. Outcomes included HRQoL (measured with the EQ-5D-3L), perceived management problems and health priorities assessed through a structured questionnaire developed ad hoc for the survey. Three patterns emerged: unspecific (65.5%), diabetes-kidney-liver (18.2%), and complex (16.4%). More comorbidities and belonging to the complex pattern were associated with worse HRQoL, mainly due to limited mobility, dependency, and pain. Main issues were managing multiple diseases, medi ions, and appointments. The diabetes-kidney-liver group prioritized improving quality of life (OR=3.08, 95%CI:1.68-6.00) and living longer (OR=1.67, 95%CI:1.05-2.64), while pain relief was a distinct priority in the complex pattern (OR=2.32, 95%CI:1.38-3.86). Both number and combinations of AF comorbidities shape patients' and caregivers' experiences. Considering comorbidity profiles can help define targeted care plans and caregiver support initiatives.
This cross-sectional study aims to explore the independent and combined effects of physical frailty and sleep quality on cognitive function in low-income older adults in the urban-rural fringe of China, and to examine whether daily activities (ADL) play a mediating role between frailty and cognitive function. A combination of convenience sampling and stratified sampling was used to recruit 198 people over 55 and above from a community in the urban-rural fringe of Keerqin District, Tongliao City, Inner Mongolia. Cognitive function was assessed using the Montreal Cognitive Assessment Beijing version (MoCA BJ), frailty was assessed using the FRAIL scale, sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI), depressive symptoms were assessed using the 15-item version of the Geriatric Depression Scale (GDS-15), and daily functioning was assessed using the ADL scale. Covariates included age, sex, years of education, smoking status, alcohol consumption, and number of chronic diseases. The statistical methods include hierarchical multiple linear regression and Bootstrap mediation analysis (resampling 2,000 times). 48.5% of participants in the sample had cognitive impairment (MoCA<18 points), and 65.2% reported poor sleep quality (PSQI ≥ 5 points). One-way ANOVA showed significant differences in MoCA scores among the three groups of frailty grades (F = 7.26, p < 0.001, η 2 = 0.069), with the frailty group scoring significantly lower than the robust group (Bonferroni adjusted p = 0.001). Hierarchical regression analysis (Model 4, R2 = 0.254) showed that the PSQI total score (B = -0.78, p = 0.016) and ADL score (B = 0.85, p = 0.010) were independent predictors of MoCA, while the health and lifestyle covariates (smoking, alcohol, chronic disease count) were non-significant. Bootstrap mediation analysis showed that ADL function exhibited a significant mediation effect in the frailty-cognition association (indirect effect = -0.42, 95% CI [-0.80, -0.14]), accounting for 45.4% of the total effect; however, after controlling for lifestyle and comorbidity covariates, this mediation effect was not statistically significant (indirect effect = -0.19, 95% CI [-0.40, 0.03], p = 0.092). The sleep-depression-cognition pathway did not reach statistical significance. Frailty and sleep quality (especially sleep latency) are independently correlated with cognitive function. Daily functional impairment shows a significant mediation trend in the frailty-cognition association, and this effect only reaches marginal significance after controlling for chronic disease burden and lifestyle factors. This suggests that comprehensive interventions addressing multimorbidity may be more fundamental than simple daily functional rehabilitation. Therefore, on the basis of systematic management of multiple chronic diseases, combining interventions aimed at improving sleep difficulties and maintaining physical functional independence can provide practical entry points for promoting cognitive health in this vulnerable group.
The global rise in the ageing population has increased the burden of chronic oral diseases among older adults, particularly in regions with limited geriatric-focused healthcare resources. Age-related physiological decline, multimorbidity, and polypharmacy collectively heightened susceptibility to dental caries, periodontal disease, tooth loss, xerostomia, and prosthetic complications. Despite this growing concern, evidence on how comorbidities influence oral health and quality of life among geriatric individuals remained fragmented. This systematic review aimed to determine the prevalence of oral diseases among geriatric adults and to assess oral health-related quality of life (OHRQoL), while examining the impact of comorbidities, multimorbidity, and polypharmacy. The review was conducted according to PRISMA 2020 guidelines and was prospectively registered in PROSPERO [CRD420251232457]. A comprehensive search of PubMed, Scopus, Web of Science, Cochrane Library, and Google Scholar was performed for studies published from January 2000 up to date. Observational studies involving adults aged ≥60 years that reported oral health indicators and OHRQoL using validated instruments (GOHAI, OHIP) were included. Data extraction and quality appraisal were carried out independently by two reviewers using the Joanna Briggs Institute (JBI) checklist. Due to heterogeneity across populations and assessment tools, a narrative synthesis was employed. Five studies met the eligibility criteria, representing institutionalized Italian elders, tribal elders in Kerala and Tamil Nadu, dental outpatients in Delhi, and community-dwelling older adults in Iran. Across all settings, high levels of dental caries, periodontal destruction, tooth loss, and inadequate prosthetic rehabilitation were observed. OHRQoL was consistently reduced, with the poorest scores among individuals with multimorbidity and functional impairment. Comorbidities and polypharmacy showed strong associations with compromised oral health and diminished OHRQoL. Oral diseases remained a major public-health concern among geriatric adults. The strong influence of comorbidities, multimorbidity, and polypharmacy on oral health underscored the need for integrating oral healthcare into routine geriatric services. Targeted preventive strategies, improved accessibility, and interdisciplinary care approaches are essential to enhance functional well-being and quality of life in ageing populations.
Multimorbidity is a growing global challenge, associated with premature death, impaired activities of daily living, reduced capacity for independent living, poor functional outcomes, and lower quality of life. However, there is limited evidence on multimorbidity and their determining factors among stroke survivors in the Ethiopian context. This study aimed to assess the prevalence of multimorbidity and its associated factors among stroke survivors in public hospitals of Amhara Regional State Northwest Ethiopia. A multi-center, institution-based cross-sectional study was conducted from June 26 to August 30, 2024. Systematic random sampling was used to select 292 study participants. Data were collected using a structured, interviewer-administered questionnaire and chart review. Bivariable and multivariable logistic regression analyses were performed to identify factors associated with multimorbidity. Variables with a p-value < 0.05 in multivariable analysis were considered statistically significant. The prevalence of multimorbidity was 72.9%. Hypertension was the most frequently reported comorbidity. Significant factors associated with multimorbidity included age 50 and above (AOR: 2.48, 95% CI: 1.29, 4.74), having no formal education (AOR: 3.72, 95% CI: 1.49, 9.26), secondary education (AOR: 3.76, 95% CI: 1.46, 9.73), use of assistive technology (AOR: 2.60, 95% CI: 1.32, 5.09), duration of hospitalization (AOR:3.08,95%CI:1.37,6.95), and post-stroke disability (AOR: 4.47, 95% CI: 2.23,8.93). Multimorbidity is highly prevalent. Targeted interventions particular focus on aged population, educational status, assistive technology provision, and post-stroke disability are essential to improve health outcomes.
Patient and public involvement (PPI) in clinical trials for adults with multimorbidity (multiple long-term conditions) in primary care is essential to ensure research is person-centred. However, PPI is often underreported, limiting understanding of its application and impact. This protocol describes a systematic review examining the uptake, impact and reporting quality of PPI in clinical trials of interventions to improve mental health, clinical or quality-of-life outcomes for adults with multimorbidity in primary care. The review will be guided by the Cochrane Handbook and reported according to PRISMA-P guidelines. Eligible studies include completed and ongoing randomised and non-randomised controlled trials. Multimorbidity is defined as the co-existence of two or more long-term conditions. Electronic databases (MEDLINE, CINAHL, Embase, Cochrane) will be searched from 2019 to update Smith et al. (2021) without language restrictions. Trial registries and grey literature will identify protocols and supplementary data. Inclusion criteria - Population: adults with multimorbidity; Interventions: targeted at this population; Comparison: usual care; Outcomes: mental health, clinical or quality-of-life; Setting: primary or community care. Studies will be included irrespective of whether PPI was reported. Data extraction will capture PPI presence, characteristics, activities, training and acknowledgement. A narrative synthesis will describe reported PPI in clinical trials. Two PPI partners will contribute throughout the review. The protocol is registered with PROSPERO (CRD420251090082). This review will enhance understanding of PPI in trials aiming to improve outcomes for adults with multimorbidity in primary and community care, identify gaps in reporting, and inform future trials to support person-centred research.
Study purposes were to identify subgroups of patients with distinct co-occurring pain AND sleep disturbance profiles and evaluate for differences in demographic, clinical, pain, and sleep characteristics between the subgroups. Oncology outpatients receiving chemotherapy (n = 972) completed self-report questionnaires on various demographic and clinical characteristics. Pain and sleep disturbance were assessed six times over two cycles of chemotherapy, using the Brief Pain Inventory and the General Sleep Disturbance Scale, respectively. A joint latent profile analysis was performed using the six ratings of worst pain severity and sleep disturbance. Parametric and non-parametric tests were used to evaluate for differences in modifiable and non-modifiable risk factors between the profiles. Two subgroups of patients with distinct joint pain and sleep disturbance profiles were identified (i.e., Moderate Pain and Sleep Disturbance (Both Moderate, 53.4%) and Severe Pain and Sleep Disturbance (Both Severe, 46.6%)). Compared to the Both Moderate class, patients in Both Severe class were younger, female, had lower level of education, were unemployed, and had a lower annual income. In addition, they had a higher comorbidity burden and a lower functional status. The Both Severe class had problems with sleep initiation and maintenance. A significant proportion of patients receiving chemotherapy experience the co-occurrence of severe pain and sleep disturbance. Oncology clinicians need to work with primary care providers to optimize the management of these two symptoms.
In people with multimorbidity, traditional, disease-oriented approaches may overlook the impact of symptoms on daily functioning. To explore the assumption that symptoms and signs provide information on functional limitations beyond that of diseases in older adults, specifically those with multimorbidity. 4025 participants in the Longitudinal Aging Study Amsterdam (1995-2022). Analyses included six symptoms, five signs and eight diseases as exposures and a sum score of six functional limitations as the outcome. Partial Information Decomposition was used to partition the total variability in functional limitations into unique, redundant and synergistic information provided by the exposures in the total sample and in the multimorbidity subgroup. Random forest prediction models were run to examine the added predictive value of symptoms, signs and diseases. In the total sample, 59% had multimorbidity. Symptoms, signs and diseases together explained 13.3% of variability in functional limitations. None of the three domains contributed unique information. Synergy accounted for most of the explained variability (signs = 9.2%, symptoms = 34.3%, diseases = 34.3%). In the multimorbidity subgroup, symptoms, signs and diseases together explained 8.7% of variability in functional limitations. Symptoms uniquely contributed 35.5% of their information, while signs and diseases were redundant. Prediction models showed that symptoms provided substantial predictive value beyond diseases alone, with a 110% increase in predictive agreement when symptoms were added to diseases in the multimorbidity subgroup, compared to 58% in the total sample. In people with multimorbidity, symptoms and signs explain more variability in functional limitations than diseases alone, supporting the need for a symptom-oriented approach in clinical care and research.
People living with multimorbidity often experience unmet social care needs, which can negatively affect wellbeing and increase pressure on health and social care systems. Artificial intelligence (AI)-enabled tools may support more timely and tailored responses to these needs. Large language models (LLMs) are emerging as tools to support qualitative research, although research detailing their integration into qualitative analytic workflows remains limited. We conducted a secondary thematic analysis of 75 qualitative interview transcripts involving people with multimorbidity and their carers. The dataset was coded according to an analytic framework of exploratory, interpretive, and integrative layers of meaning. The dataset was analysed according to two parallel analytic streams: human reflexive thematic analysis, and qualitative analysis using Claude Sonnet 4. Model outputs were iteratively reviewed and compared against manual thematic analysis for convergence and divergence. Across the analytic workflow, twelve themes from the original human-led analysis were used as a reference framework for examining areas of alignment, extension, or divergence in LLM-generated interpretations. The LLM-assisted analysis highlighted shifts in analytic emphasis and candidate interpretive nuances, including emotive tone and latent cross-cutting concerns, while requiring human oversight to determine evidential grounding. We present a structured methodological illustration for integrating LLM-assisted outputs within qualitative analysis. Using convergence-divergence mapping, we examine how LLM-generated interpretations may function as an additional analytic lens that can support reflexivity, transparency, and analytic auditability in qualitative research applied within the context of multimorbidity.
Multiple long-term conditions co-occur in people with type 1 diabetes. We aim to investigate the association between comorbidities and physical function, fall risk and hospitalization cost. A cross-sectional study was conducted at the First Affiliated Hospital of Sun Yat-sen University. Adult patients with type 1 diabetes admitted between 2021 and 2025 were included. Prevalence of each morbidity was compared in people with different diabetes duration. ADL was assessed by the Barthel Index. Fall risk was evaluated by the Johns Hopkins Fall Risk Assessment Tool. Logistic regression models were used to analyze the association between multimorbidity and physical function and fall risk. Linear regression was used between eight variables and hospitalization costs. Variables associated with increasing risk of multimorbidity were identified using multivariate logistic regression model. The mean number of morbidities per patient was 3.6 ± 1.8, with 31.4% (n=118), 41.5% (n=156), and 27.1% (n=102) had 1-2, 3-4, and ≥5 morbidities. Cardiovascular, kidney, metabolic conditions were the most prevalent comorbidities. Cataract, anemia, cancer, autoimmune thyroid disorders, chronic obstructive pulmonary disease, and mental health disorders were also notable. Older age and longer diabetes duration were strongly associated with higher multimorbidity burden. Increased multimorbidity was associated with higher fall risk (odds ratio (OR): 1.23, 95% confidence interval (CI): 1.01-1.52) (P<0.05), greater dependence in Activities of daily living (OR: 1.58, 95% CI: 1.08-2.32) (P = 0.02) and elevated hospitalization costs (β: 66.12, 95% CI: 14.65-117.58) (P = 0.012). Our findings demonstrate that multimorbidity is highly prevalent among Chinese adults with T1D. A higher burden of multimorbidity is significantly associated with adverse functional outcomes, including increased fall risk and greater dependence in ADL, as well as higher hospitalization costs. These findings highlight the critical need to integrate assessments of functional status, fall risk, and multimorbidity into routine clinical care for adults with T1D.
Childhood socioeconomic disadvantage is linked to individual chronic diseases in adulthood, but its relationship with multimorbidity remains unclear. Understanding this is crucial for informing prevention strategies and the economic case for investment. This review and meta-analysis evaluated the association between childhood disadvantage and adult multimorbidity. Following pre-registration (PROSPERO: CRD42024588657), we searched MEDLINE, SocIndex, ASSIA, and ProQuest Public Health to March 2025 for studies assessing childhood socioeconomic circumstances (SECs) and adult multimorbidity (≥2 chronic conditions). Risk of bias was assessed using ROBINS-E and evidence certainty using GRADE. Random-effects meta-analysis and synthesis without meta-analysis (SWiM) were conducted. Subgroup analyses explored heterogeneity by region, design, and exposure type. From 5,617 records, 10 studies met inclusion criteria. Most were cross-sectional, using retrospective reports of exposure and self-reported outcomes. Exposures included perceived childhood economic adversity (n=6), parental education (n=4), parental occupation (n=1), and composite measures (n=3). Meta-analyses found no clear associations for perceived adversity (OR 1.08, 95% CI 0.87-1.23; I2 = 94.4%) or parental education (father's (Odds ratio (OR) 0.95, 95% CI 0.66-1.37; I2 = 66.8%); mother's (OR 1.07, 95% CI 0.70-1.61; I2 = 36.9%)). Relative Index of Inequality estimates generally indicated higher mortality risk with greater childhood disadvantage, though effect sizes varied widely and some studies suggested the reverse.. All studies were high/very high risk of bias with very low certainty. Evidence for an association between childhood socioeconomic disadvantage and adult multimorbidity is limited and uncertain. Findings suggest possible harmful effects but remain constrained by methodological weaknesses and heterogeneity. High-quality longitudinal studies with standardised multimorbidity definitions are needed.
Incomplete and inconsistent reporting amongst research studies in people with Multiple Long-Term Conditions (MLTC) hinders the comprehensive evaluation, synthesis, and interpretation of study findings for application by clinicians, researchers, patients and policymakers. This limitation leads to heterogeneous findings, duplication of work and restricts the practical application of research outcomes in clinical settings, public health strategies, and policymaking. Given the high prevalence and complexity of MLTC, there is a pressing need for standardised guidelines to promote clarity, consistency, and comprehensiveness in study reporting. Such guidelines can enhance transparency and reproducibility, thereby increasing the impact of research on healthcare decisions and policy development. We followed a four-stage process of guidelines development: a review of MLTC reporting practices; a workshop with diverse stakeholders to identify and refine items for inclusion; a prioritisation consensus exercise to agree on key items; and pilot-testing to refine interpretation and usability of the guidelines. This work has produced the first set of reporting guidelines addressing the need for standardised reporting in MLTC research. Application of these guidelines has the potential to improve research clarity and reproducibility, enabling better comparisons across studies and shared learning. Improved reporting standards will also facilitate the translation of research findings into effective healthcare strategies and policies, contributing to better health outcomes for MLTC patients. These initial guidelines offer a structured approach to improving the reporting quality of MLTC research. Future evaluations will assess its impact on research transparency and real-world application.
Previous reports of transcatheter aortic valve implantation (TAVI) in adults ≥90 years emphasise procedural success and survival. Whether nonagenarians experience clinically meaningful, sustained improvements in patient-reported outcomes, and how frailty and multimorbidity may modify these benefits, remains uncertain. We performed an exploratory single-centre retrospective cohort study of consecutive nonagenarians undergoing TAVI (January 2019 - 31 October 2024). EuroQol 5-Dimensions 3-Level (EQ-5D-3L) (including Visual Analogue Scale, VAS) and the Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) Summary Score were collected at baseline, 30 days and 12 months. Responders were defined using a ≥10-point minimally important difference. Deterioration was any negative pre- to 12-month change. Frailty was stratified into three prespecified Clinical Frailty Scale (CFS) categories: 1-3 (fit to managing well), 4-5 (vulnerable to mildly frail), and 6-9 (moderately to severely frail/terminally ill). Of 26 nonagenarians, 19 met inclusion criteria. Most were mildly-moderately frail (CFS 3-5: n=18; CFS 6: n=1). Median 30-day changes were +25 (IQR 10-38) for EQ-5D VAS (exact sign test p=0.001) and +39 (30-50) for KCCQ-12 (p<0.001), with gains largely sustained at 12-months (EQ-5D VAS p=0.096; KCCQ-12 p<0.001). At 12-months, 13/18 (72%) were EQ-5D VAS responders and 17/18 (94%) KCCQ-12 responders. Responder proportions were highest in less frail strata, noting CFS 6-9 contained a single patient. EQ-5D-3L problem burden improved across all domains, especially Mobility (p=0.002) and Usual activities (p=0.012). Twelve-month survival was 94% (18/19). In this single-centre nonagenarian cohort, we observed 30-day improvements in symptoms and function following TAVI that were maintained to 12 months. Observed changes appeared smaller with greater frailty and multimorbidity, and higher comorbidity burden coincided with a higher probability of deterioration. Findings should be interpreted as exploratory and hypothesis-generating.
Veterans using Department of Veterans Affairs (VA) healthcare have a high burden of pre-pregnancy chronic disease that likely contributes to the observed high rate of pregnancy-related morbidity. Many common diseases frequently co-occur; understanding patterns of multimorbidity may inform the design and delivery of pre-pregnancy interventions to lower pregnancy morbidity risk. The current study sought to identify patterns of co-occurrence of pre-pregnancy chronic disease among Veterans. We conducted a retrospective cohort study using VA administrative data. Our population included Veterans ages 18-45 with ⩾1 pregnancy outcome (ectopic, spontaneous abortion, stillbirth, and/or live birth) during fiscal years 2010-2019. Presence of common chronic diseases with implications for pregnancy was detected using encounter International Classification of Diseases, 9th and 10th Revision (ICD-9 and ICD-10) codes in the 2 years prior to pregnancy. Patients were grouped based on latent class models of diagnosis patterns; two to seven latent groups were examined for model fit and clinical interpretability. We identified 56,853 pregnancies from 41,034 Veterans. More than half of pregnancies were complicated by an array of pre-pregnancy medical and mental health conditions that may negatively impact pregnancy health and contribute to adverse pregnancy outcomes. The most frequently occurring conditions included chronic pain (51.2% of pregnancies), depression (31.4%), anxiety (25.9%), and post-traumatic stress disorder (22.8%). A five-group model demonstrated the best balance between model fit and clinical interpretability. Groups included: "Pain and Mental Health" (28%), with high prevalence of chronic pain, depression, and anxiety; "Pain and Metabolic" (17%), high prevalence of chronic pain, obesity, and migraines; "Substance Use and Mental Health" (7%), high prevalence of alcohol use disorder, depression, and post-traumatic stress disorder; "Low Diagnosis" (43%), lower than average prevalence of diagnoses; and "High Complexity" (5%), high prevalence of conditions across multiple physiologic systems. We identified five distinct, clinically meaningful groups of Veterans based on co-occurring pre-pregnancy diseases. Tailoring interventions to these groups may address Veterans' complex pre-pregnancy health risks effectively and efficiently.
The Multimorbidity Questionnaire (MMQ1) is a patient-reported outcome measure assessing quality of life (QoL) in people with multimorbidity. An English-language version was recently validated for use in the United Kingdom. This study examines: (1) Whether MMQ1 detects expected variations in QoL according to individual characteristics; (2) How MMQ1 compares with EQ-5D-5L in detecting such variations, and in discriminating between different levels of QoL. A postal survey was distributed to 2753 patients with multimorbidity. Relationships between MMQ1 and EQ-5D-5L with six independent variables (long-term condition count, mental-physical multimorbidity, deprivation, self-rated QoL, age and sex) were examined using linear regression analyses. Discriminative ability was assessed using Receiver Operating Characteristic curves and sample size calculations with respect to consecutive classes of self-rated QoL. 597 responses were received (22%). Respondents had a mean age of 69.5 years and 48% were men. Higher long-term condition count, the presence of mental-physical multimorbidity and increasing deprivation were associated with poorer QoL on both measures. In addition, three MMQ1 domains demonstrated age-related variations in QoL that were not detected using EQ-5D-5L. MMQ1 exhibited superior discriminative ability to EQ-5D-5L, especially in distinguishing between individuals with 'Poor' vs 'Very Poor' self-rated QoL, where EQ-5D-5L was particularly weak. MMQ1 detected expected variations in QoL according to individual characteristics, supporting known-groups validity. It was superior to EQ-5D-5L in its ability to detect age-related variations in QoL and to discriminate between different levels of self-rated QoL. MMQ1 has the potential to improve the measurement of QoL in people with multimorbidity.
Multimorbidity significantly affects prognosis in patients after transvenous lead extraction (TLE). The CHA2DS2-VASc and CHA2DS2-VA scores, widely used for stroke risk stratification in atrial fibrillation, include clinical factors that are also associated with long-term mortality. To evaluate the usefulness of the CHA2DS2-VASc and CHA2DS2-VA scores in predicting short- and long-term mortality in patients following non-laser TLE. This retrospective study included 3822 patients who underwent non-laser TLE between March 2006 and April 2023 at high-volume centres. The median follow-up was 1848 days (Q1-Q3: 815-3146 days). Patients were stratified into two groups according to CHA2DS2-VASc score (<3 vs. ≥3). 30-day, 1-year, and 3-year, and overall follow-up mortality were assessed. Cox proportional hazards models were used to identify independent predictors of death during short and long follow-up. Patients with CHA2DS2-VASc ≥3 had significantly higher mortality at 30 days 1 year, 3 years, and during overall follow-up compared with those scoring <3. A cut-off ≥3 showed 80.6% sensitivity and 62.3% specificity for predicting 3-year mortality. Mortality increased progressively with higher CHA2DS2-VASc scores (Spearman's r = 0.983, p<0.001). The multivariate Cox regression demonstrated that number of points on CHA2DS2-VASc and CHA2DS2-VA scores were independent predictors long-term mortality, alongside Charlson comorbidity index, atrial fibrillation, infective TLE indications, and renal dysfunction. Each 1-point increase in the CHA2DS2VA score was associated with an 11.7% increase in the risk of death. In sex-specific analysis, the risk increased by 33.0% per point in females (HR 1.330; p<0.001) and by 20.6% in males (HR 1.206; p<0.001). CHA2DS2-VASc and CHA2DS2-VA score may be a useful tool for predicting the risk of death during long-term observation of patients after TLE. Incorporation of this score into clinical decision-making may improve risk stratification and support individualized management of patients undergoing TLE.