Multimorbidity Index Research Articles

Functional Impairments, Phenotypic Frailty and Sector-Specific Incremental Healthcare Costs in Older Adults.

This study quantifies incremental healthcare expenditures of functional impairments and phenotypic frailty in specific healthcare sectors. Pooled 2023 analysis of 4 prospective cohort studies linked with Medicare claims including 4318 women and 3847 men attending an index examination (2002-2011). Annualized inpatient, skilled nursing facility (SNF), home healthcare (HHC) and outpatient costs (2023 dollars) ascertained for 36 months following index examination. Functional impairments (difficulty performing 4 activities of daily living) and frailty phenotype (operationalized using 5 components) derived from cohort data. Weighted multimorbidity index including demographics derived from claims. Mean age at index examination was 79.2 years. After accounting for multimorbidity and each other, average annualized incremental costs of 3-4 functional impairments versus no impairment in women (men) was $2838 ($5516) in inpatient, $1572 ($1446) in SNF and $1349 ($1060) in HHC sectors; average incremental costs of phenotypic frailty versus robust in women (men) was $4100 (not significant for men) in inpatient, $1579 ($1254) in SNF and $645 ($526) in HHC sectors. Incremental inpatient costs were primarily due to a higher hospitalization risk, while incremental SNF and HHC costs were related to both increased risks of utilization and higher costs among individuals with utilization. Neither geriatric domain was associated with outpatient costs. In this study of community-dwelling beneficiaries, functional impairments were independently associated with higher subsequent expenditures in inpatient, SNF and HHC sectors among both sexes. Phenotypic frailty was independently associated with higher subsequent inpatient costs in women, and higher SNF and HHC costs in both sexes.

Capturing the care of complex community-based health center patients: A comparison of multimorbidity indices and clinical classification software.

To compare morbidity burden captured from multimorbidity indices and aggregated measures of clinically meaningful categories captured in primary care community-based health center (CBHC) patients. Electronic health records of patients seen in 2019 in OCHIN's national network of CBHCs serving patients in rural and underserved communities. Age-stratified analyses comparing the most common conditions captured by the Charlson, Elixhauser, and Multimorbidity Weighted (MWI) indices, and Classification Software Refined (CCSR) and Chronic Condition Indicator (CCI) algorithms. Active ICD-10 conditions on patients' problem list in 2019. Approximately 35%-56% of patients with at least one condition are not captured by the Charlson, Elixhauser, and MWI indices. When stratified by age, this range broadens to 9%-90% with higher percentages in younger patients. The CCSR and CCI reflect a broader range of acute and chronic conditions prevalent among CBHC patients. Three commonly used indices to capture morbidity burden reflect conditions most prevalent among older adults, but do not capture those on problem lists for younger CBHC patients. An index with an expanded range of care conditions is needed to understand the complex care provided to primary care populations across the lifespan.

Muscle Mitochondrial Bioenergetic Capacities Are Associated With Multimorbidity Burden in Older Adults: The Study of Muscle, Mobility and Aging.

The geroscience hypothesis posits that aging biological processes contribute to many age-related deficits, including the accumulation of multiple chronic diseases. Though only one facet of mitochondrial function, declines in muscle mitochondrial bioenergetic capacities may contribute to this increased susceptibility to multimorbidity. The Study of Muscle, Mobility and Aging (SOMMA) assessed ex vivo muscle mitochondrial energetics in 764 older adults (mean age = 76.4, 56.5% women, and 85.9% non-Hispanic White) by high-resolution respirometry of permeabilized muscle fibers. We estimated the proportional odds ratio (POR [95% CI]) for the likelihood of greater multimorbidity (4 levels: 0 conditions, N = 332; 1 condition, N = 299; 2 conditions, N = 98; or 3+ conditions, N = 35) from an index of 11 conditions, per SD decrement in muscle mitochondrial energetic parameters. Distribution of conditions allowed for testing the associations of maximal muscle energetics with some individual conditions. Lower oxidative phosphorylation supported by fatty acids and/or complex I- and II-linked carbohydrates (eg, Max OXPHOSCI+CII) was associated with a greater multimorbidity index score (POR = 1.32 [1.13, 1.54]) and separately with diabetes mellitus (OR = 1.62 [1.26, 2.09]), depressive symptoms (OR = 1.45 [1.04, 2.00]) and possibly chronic kidney disease (OR = 1.57 [0.98, 2.52]) but not significantly with other conditions (eg, cardiac arrhythmia, chronic obstructive pulmonary disease). Lower muscle mitochondrial bioenergetic capacities were associated with a worse composite multimorbidity index score. Our results suggest that decrements in muscle mitochondrial energetics may contribute to a greater global burden of disease and are more strongly related to some conditions than others.

The Scope of Multimorbidity in Family Medicine: Identifying Age Patterns Across the Lifespan.

Multimorbidity rates are both increasing in prevalence across age ranges, and also increasing in diagnostic importance within and outside the family medicine clinic. Here we aim to describe the course of multimorbidity across the lifespan. This was a retrospective cohort study across 211,953 patients from a large northeastern health care system. Past medical histories were collected in the form of ICD-10 diagnostic codes. Rates of multimorbidity were calculated from comorbid diagnoses defined from the ICD10 codes identified in the past medical histories. We identify 4 main age groups of diagnosis and multimorbidity. Ages 0 to 10 contain diagnoses which are infectious or respiratory, whereas ages 10 to 40 are related to mental health. From ages 40 to 70 there is an emergence of alcohol use disorders and cardiometabolic disorders. And ages 70 to 90 are predominantly long-term sequelae of the most common cardiometabolic disorders. The mortality of the whole population over the study period was 5.7%, whereas the multimorbidity with the highest mortality across the study period was Circulatory Disorders-Circulatory Disorders at 23.1%. The results from this study provide a comparison for the presence of multimorbidity within age cohorts longitudinally across the population. These patterns of comorbidity can assist in the allocation to practice resources that will best support the common conditions that patients need assistance with, especially as the patients transition between pediatric, adult, and geriatric care. Future work examining and comparing multimorbidity indices is warranted.

How valid is a prescription-based multimorbidity index (Rx-risk) in predicting mortality in the Outcomes and Multimorbidity In Type 2 diabetes (OMIT) study? A nation-wide registry-based cohort study from Norway

ObjectiveThe prescription-based Rx-risk index has previously been developed to measure multimorbidity. We aimed to adapt and evaluate the validity of the Rx-risk index in prediction of mortality among persons with...

Peculiarities of pharmacotherapy of patients with rheumatoid arthritis associated with interstitial lung disease

Objective: a comparative study of the peculiarities of pharmacotherapy of rheumatoid arthritis (RA) in presence and in absence of interstitial lung disease (ILD).Material and methods. The study included 1034 patients with active RA who met the 2010 ACR/EULAR criteria. Patients were divided into two groups: with ILD according to high-resolution computed tomography of the lungs (n=82) and without ILD or other types of chronic obstructive pulmonary diseases, including bronchial asthma (52 patients excluded; n=900). Based on medical documentation, archived medical records and medical history, a “drug card” was created for all stages of pharmacotherapy of patients with active RA. The Cumulative Illness Index Score (CIRS) was used to assess the profile and severity of comorbidities.Results and discussion. The main indicators of RA activity in the patients of the two groups were comparable, but a greater number of comorbidities (p˂0.0001) and a higher value of the CIRS multimorbidity index (p˂0.0001) were found in the group with ILD. The presence of ILD had no influence on the frequency of prescription, the total duration of use and the maximum dose of glucocorticoids (GC) (p˂0.05). The average dose of GC was statistically significantly higher in the group with ILD (p=0.008). These patients were taking disease-modifying antirheumatic drugs (DMARDs): methotrexate (p=0.04), leflunomide (p=0.02) and sulfasalazine (p=0.03), less frequently, but they took hydroxychloroquine significantly more frequently (p=0.02) with a comparable total duration of use of each medication. RA patients with ILD and without ILD received biologic DMARDs (bDMARDs) and targeted synthetic DMARDs (tsDMARDs) in 62.2 and 59.6% of cases, respectively (p˂0.05). At the same time, patients without ILD had experience of taking a greater number of different bDMARDs/tsDMARDs (p=0.03). In the group with ILD, patients more frequently received anti-B-cell therapy (p˂0.0001) and significantly less frequently drugs of other classes: tumour necrosis factor α inhibitors (p˂0.0001) and interleukin 6 inhibitors (p=0.01), T-cell costimulation blocker (p=0.04) and Janus kinase inhibitors (p=0.001). Patients with ILD were statistically significantly older at the start of bDMARD/tsDMARD therapy (p˂0.0001), and the period from the onset of RA to the start of bDMARD/tsDMARD therapy was comparable in both groups (p˂0.05).Conclusion. The observed peculiarities of pharmacotherapy in the group with ILD (frequency of use, choice and dose of GC, DMARDs, biologics and tsDMARDs) are probably related to the presence of ILD on the one hand and to the characteristics of concomitant pathology and older age on the other, as the activity of RA was comparable in our patients with and without ILD.

1709 Comparative performance of six multimorbidity indices to discriminate intrinsic capacity impairments among older adults

Abstract Introduction Optimal intrinsic capacity (IC) is crucial for preserving the functional abilities of older adults. The presence of multimorbidity is closely associated with IC impairments. Various multimorbidity indices have been developed for diverse health outcomes. This study aimed to compare the performance of six commonly used multimorbidity indices to discriminate IC impairments among community-dwelling older adults. Method We used data from a multidimensional geriatric assessment program including 627 community-dwelling older adults in five cities of Hunan, China. Six multimorbidity indices were extracted from the data, including disease counts, Functional Comorbidity Index (FCI), the Deyo Charlson comorbidity index, two indices (total score and comorbidity index) derived from the Cumulative Illness Rating Scale-Geriatric (CIRS-G), and medication counts. The IC was measured with five individual domains, i.e., locomotion, vitality, sensory, cognition, and psychological capacity. Individuals were regarded as having IC impairments if they had impairments in one or more domains. Associations between multimorbidity indices and IC impairments were examined using logistic regression analyses. The discriminative ability of multimorbidity indices for IC impairments was compared using the c-statistics. Results A total of 374 (59.6%) participants had IC impairments. All multimorbidity indices were significantly associated with IC impairments after adjusting for confounding factors. All indices showed acceptable discriminative power (c-statistic ranged from 0.711 to 0.759) for IC impairments. The comorbidity index derived from CIRS-G resulted in the highest c-statistic, followed by the total score of CIRS-G and FCI. Conclusions Our study results suggest that multimorbidity indices differed in their ability to discriminate IC impairments. The comorbidity index derived from CIRS-G performed better than other multimorbidity indices included in this study. The comorbidity index has the potential as a simple proxy measure of indicating the need for interventions to optimise IC for older adults in community settings.

MULTIMORBIDITY PREDICTS REMAINING LIFESPAN IN NONHUMAN PRIMATE MODEL OF ACCELERATED AGING

Abstract Multimorbidity is common among older adults and linked to shorter lifespans, but it is unclear how naturally-occurring multimorbidity impacts lifespan in non-human primate models of aging. We developed a clinical multimorbidity index based on standardized veterinary diagnoses in 288 rhesus macaques (Macaca mulatta) from the Wake Forest Radiation Late Effects Cohort, animals that survived an early-life insult from whole-body radiation and controls (73 female, 237 irradiated, ages 2-24). Our index is based on diagnosis of arthritis, low bone density, cataracts, diabetes, gastrointestinal disorders, heart disease, hepatic dysfunction, hypertension, kidney disease, lung fibrosis, skin disorders, tumors, and overweight/underweight. All diseases were seen in both control and irradiated animals and there was a broad distribution of multimorbidity trajectories across the lifespan both in number and combinations of diseases. On average, the first diagnosis occurred at age 9.0 (equal to 35% of median lifespan) and the second at age 10.7. However, 20% of animals that lived to age 12 were without any diagnoses while others had as many as 9 comorbidities, highlighting broad variability in multimorbidity with aging. Cox proportional-hazard ratios (HR) show significant negative associations (p < 0.05) between survival and multimorbidity. Ages 3-6 years, each additional morbidity doubles likelihood of death (HR > 2) with HR falling from 1.9 to 1.4 from ages 6-15. Based on receiver operating characteristic (ROC) curves, multimorbidity predicts 2-year mortality with AUC > 0.65 from ages 7-14. Our findings suggest multimorbidity is prevalent and predicts lifespan in NHP survivors of radiation. Research was funded by NIHU01AI150578.

Socioeconomic, Health Services, and Multimorbidity Disparities in Chinese Older Adults

IntroductionAs one of the world's most populous countries, China persistently confronts a significant multimorbidity burden. This study aimed to elucidate the multimorbidity burden experienced by Chinese older adults, explore its interplay with socioeconomic disparity, and investigate potential correlations between these provincial disparities and health services availability. MethodsThe fourth wave of China's national Urban and Rural Elderly Population study, conducted in 2015, was used to construct a multimorbidity index (MHI) and elucidate the geographical differences in the multimorbidity burden. Incorporating macro-level indicators about socioeconomic and health services availability, quantile regression and spearman correlation analyses were employed to investigate the relationship between multimorbidity and socioeconomic disparities, and examine the potential linkages between these provincial disparities and health services availability. Analyses were performed in 2023. ResultsFinal analysis included a total of 213,857 older adults. At the provincial level, significant geographic disparities in multimorbidity burden were identified. After adjusting for individual social determinants of health, an independent association was found between the human development index (HDI) and a higher MHI [coefficient = -0.22; 95% CI: (-0.24, -0.19)]. Furthermore, a significant positive correlation emerged between HDI and both population and geographic densities of health services availability. Notably, geographic density displayed greater inequality (Gini coefficients of 0.45 to 0.48) compared to population density (Gini coefficients of 0.03 to 0.10). ConclusionsThis study demonstrates that multimorbidity burden in China is linked to provincial socioeconomic disparities, and inequality in health services availability may account for this, which would advocate for a need to reduce disparities in health services availability.

Any infection among patients with hip fracture: Predictive ability of Charlson, Elixhauser, Rx-Risk, and Nordic comorbidity indices

BackgroundIn studies on infection after hip fracture surgery, a common and serious complication, it remains unknown which comorbidity index is best for case-mix confounder adjustment. We evaluated the predictive ability of Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index (ECI), Rx-Risk Index (Rx-Risk), and Nordic Multimorbidity Index (NMI) for any infection up to 1 year from discharge after hip fracture surgery. MethodsUsing Danish medical registries, we included 92,600 patients (mean age 83 years) surgically treated for hip fracture between 2004 and 2018. Comorbidity-index scores were calculated using prevalence of diagnosis codes, prescription codes, or both. Lookback periods of 1, 5, and 10 years were applied. Logistic regression was used to calculate c-index to assess discrimination of comorbidity indices individually and in combination with a base model of age and sex. Outcome was any infection (not only surgical site infection) in-hospital and 1 year after discharge. ResultsAt 10-year lookback period, the c-index for individual comorbidity indices for in-hospital infections varied from 0.53 to 0.56, similar to base model alone (0.56). The predictive ability of comorbidity indices in combination with base model varied from 0.56 to 0.57. Within 1 year after discharge, NMI in combination with base model had best predictive ability for infection (c-index = 0.62), followed by CCI and ECI (c-index = 0.60) and Rx-Risk (c-index = 0.58). Discrimination was similar for all lookback periods. ConclusionsComorbidity indices have low predictive ability for any infection up to 1 year after hip fracture surgery, similar to that of age and sex alone. For case-mix adjustment, evaluated comorbidity indices are of equal value.

Comparing a new multimorbidity index with other multimorbidity measures for predicting disability trajectories

BackgroundThe optimal multimorbidity measures for predicting disability trajectories are not universally agreed upon. We developed a multimorbidity index among middle-aged and older community-dwelling Chinese adults and compare its predictive ability of disability trajectories with other multimorbidity measures. MethodsThis study included 17,649 participants aged ≥50 years from the China Health and Retirement Longitudinal Survey 2011–2018. Two disability trajectory groups were estimated using the total disability score differences calculated between each follow-up visit and baseline. A weighted index was constructed using logistic regression models for disability trajectories based on the training set (70 %). The index and the condition count were used, along with the pattern identified by the latent class analysis to measure multimorbidity at baseline. Logistic regression models were used in the training set to examine associations between each multimorbidity measure and disability trajectories. C-statistics, integrated discrimination improvements, and net reclassification indices were applied to compare the performance of different multimorbidity measures in predicting disability trajectories in the testing set (30 %). ResultsIn the newly developed multimorbidity index, the weights of the chronic conditions varied from 1.04 to 2.55. The multimorbidity index had a higher predictive performance than the condition count. The condition count performed better than the multimorbidity pattern in predicting disability trajectories. LimitationSelf-reported chronic conditions. ConclusionsThe multimorbidity index may be considered an ideal measurement in predicting disability trajectories among middle-aged and older community-dwelling Chinese adults. The condition count is also suggested due to its simplicity and superior predictive performance.

Prevalence of multiple long‐term conditions with psoriasis in England: A cohort study using the Clinical Practice Research Datalink

AbstractBackgroundPeople with psoriasis live with other long‐term conditions (co‐morbidities) that affect their use of healthcare, but the scale of this is not well characterised.ObjectivesEstimate the concurrent prevalence of co‐morbidities known to affect the use of healthcare in people living with psoriasis in England.MethodsA retrospective cohort study using linked data from the UK's Clinical Practice Research Datalink with Hospital Episode Statistics, Office for National Statistics mortality records, and Index of Multiple Deprivation 2010. A cohort of adults (≥18 years) with psoriasis was matched with a comparator cohort of individuals based on age, sex and registered general practice between April 2007 and December 2017. A predefined list of 21 co‐morbidities was selected from a published measure: the Cambridge Multimorbidity Index (CMI). Descriptive analysis describes prevalence with statistical tests (t tests; two‐sample proportions test) of difference for selected variables.ResultsThe study cohort comprised 372,949 individuals (54,817 psoriasis; and 318,132 matched‐comparator). The calculated CMI general score was statistically higher at 0.54 (standard deviation: 0.9) for psoriasis compared with 0.39 (standard deviation: 0.75) for the matched comparator (t test; p < 0.001). A higher percentage (53.2%) of individuals within the psoriasis cohort had at least one co‐morbidity compared with 45.4% of individuals in the matched‐comparator cohort. The prevalence of 20 individual co‐morbidities was statistically significantly (two‐sample proportions test; p < 0.001) higher than in the matched‐comparator cohort.ConclusionsIndividuals living with psoriasis are more likely to live with multiple long‐term conditions that have developed at an earlier age compared with those without psoriasis. Knowing the characteristics for a higher prevalence of co‐morbidities in people living with psoriasis provides clinicians with the motivation to consider more holistic approaches to improve management and treatment, noting the importance of mental health alongside physical health, and enabling a conversation about the importance of making lifestyle changes.

Workshop (Knowledge Generation) ID 2001657

Background Multi-morbidity is common in persons with spinal cord injury (SCI). Network Analysis is a tool used to visualize and estimate complex relationships among variables. Three network models: Gaussian Graphical Model, Ising model, and Mixed Graphical Model were applied to the 2011-2012 Canadian SCI Community Survey dataset, which included individuals with traumatic and non-traumatic SCI. Data utilized included demographic and injury data as we well as 30 secondary health conditions (comorbidities and secondary complication) that are included in the Multi-Morbidity Index (MMI-30). Five health outcomes were included: healthcare utilization (HCU), health status (i.e. Short Form-12 physical and mental component summary (SF-12 PCS & MCS) score), life satisfaction, and quality of life. Using Network Analysis, we reduced the number of items in the Multi-Morbidity Index (MMI-30) by 5 items (MMI-25) and the psychometric properties were comparable. This interactive workshop will include presentations from a clinician, researcher and person with lived experience (PLEX). Objective The goals of this workshop are to: Conclusion This workshop will demonstrate the benefit of using Network Analysis, a type of Machine Learning, in SCI research. Specifically, the example of how Network Analysis identified key associations among 30 secondary health conditions and five health outcomes which resulted in the MMI-25 will be discussed as well as future opportunities for using Network Analysis and other Machine Learning methodologies in SCI research.

The digitized chronic disease management model: scalable strategies for implementing standardized healthcare and big data analytics in Shanghai.

Chronic disease management (CDM) falls under production relations, and digital technology belongs to the realm of productivity. Production relations must adapt to the development of productivity. Simultaneously, the prevalence and burden of chronic diseases are becoming increasingly severe, leveraging digital technology to innovate chronic disease management model is essential. The model was built to cover experts in a number of fields, including administrative officials, public health experts, information technology staff, clinical experts, general practitioners, nurses, metrologists. Integration of multiple big data platforms such as General Practitioner Contract Platform, Integrated Community Multimorbidity Management System and Municipal and District-Level Health Information Comprehensive Platform. This study fully analyzes the organizational structure, participants, service objects, facilities and equipment, digital technology, operation process, etc., required for new model in the era of big data. Based on information technology, we build Integrated Community Multimorbidity Care Model (ICMCM). This model is based on big data, is driven by "technology + mechanism," and uses digital technology as a tool to achieve the integration of services, technology integration, and data integration, thereby providing patients with comprehensive people-centered services. In order to promote the implementation of the ICMCM, Shanghai has established an integrated chronic disease management information system, clarified the role of each module and institution, and achieved horizontal and vertical integration of data and services. Moreover, we adopt standardized service processes and accurate blood pressure and blood glucose measurement equipment to provide services for patients and upload data in real time. On the basis of Integrated Community Multimorbidity Care Model, a platform and index system have been established, and the platform's multidimensional cross-evaluation and indicators are used for management and visual display. The Integrated Community Multimorbidity Care Model guides chronic disease management in other countries and regions. We have utilized models to achieve a combination of services and management that provide a grip on chronic disease management.

Multimorbidity in persons with non-traumatic spinal cord injury and its impact on healthcare utilization and health outcomes.

Cross-sectional surveyin Canada. To explore multimorbidity (the coexistence of two/more health conditions) in persons with non-traumatic spinal cord injury (NTSCI) and evaluate its impact on healthcare utilization (HCU) and health outcomes. Community-dwelling persons. Data from the Spinal Cord Injury Community Survey (SCICS) was used. A multimorbidity index (MMI) consisting of 30 secondary health conditions (SHCs), the 7-item HCU questionnaire, the Short Form-12 (SF-12), Life Satisfaction-11 first question, and single-item Quality of Life (QoL) measure were administered. Additionally, participants were grouped as "felt needed healthcare was received" (Group 1, n = 322) or "felt needed healthcare was not received" (Group 2, n = 89) using the HCU question. Associations among these variables were assessed using multivariable analysis. 408 of 412 (99%) participants with NTSCI reported multimorbidity. Constipation, spasticity, and fatigue were the most prevalent self-reported SHCs. Group 1 had a higher MMI score compared to Group 2 (p < 0.001). A higher MMI score correlated with the feeling of not receiving needed care (OR1.4, 95% CI 1.08-1.21), lower SF-12 (physical/mental component summary scores), being unsatisfied with life, and lower QoL (all p < 0.001). Additionally, Group 1 had more females (p < 0.001), non-Caucasians (p = 0.034), and lower personal annual income (p = 0.025). Persons with NTSCI have multimorbidity, and the MMI score was associated with increased HCU and worse health outcomes. This work emphasizes the critical need for improved healthcare and monitoring. Future work determining specific thresholds for the MMI could be helpful for triage screening to identify persons at higher risk of poor outcomes.

Association Between the Healthy Lifestyle Index and Risk of Multimorbidity in the Women's Health Initiative.

Multimorbidity, defined as the presence of 2 or more chronic health conditions, is increasingly common among older adults. The combination of lifestyle characteristics such as diet quality, smoking status, alcohol intake, physical activity (PA), sleep duration, and body fat as assessed by body mass index (BMI) or waist circumference, and risk of multimorbidity are not well understood. We investigated the association between the healthy lifestyle index (HLI), generated by combining indicators of diet quality, smoking, alcohol, PA, sleep amount, and BMI, and risk of multimorbidity, a composite outcome that included cardiovascular disease (CVD), diabetes, cancer, and fracture. We studied 62 037 postmenopausal women aged 50-79 years at enrollment in the Women's Health Initiative, with no reported history of CVD, diabetes, cancer, or fracture at baseline. Lifestyle characteristics measured at baseline were categorized and a score (0-4) was assigned to each category. The combined HLI (0-24) was grouped into quintiles, with higher quintiles indicating a healthier lifestyle. Multivariable adjusted estimates of hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the risk of developing multimorbidity were obtained using Cox proportional hazard models. Over an average follow-up period of 16.3 years, 5 656 women developed multimorbidity. There was an inverse association between the HLI levels and risk of multimorbidity (compared to the HLI_1st quintile: HR_2nd quintile = 0.81 95% CI 0.74-0.83, HR_3rd quintile = 0.77 95% CI 0.71-0.83, HR_4th quintile = 0.70 95% CI 0.64-0.76, and HR_5th quintile = 0.60 95% CI 0.54-0.66; p trend < .001). Similar associations were observed after stratification by age or BMI categories. Among postmenopausal women, higher levels of the HLI were associated with a reduced risk of developing multimorbidity.

Long-term use of glucocorticoids in patients with active rheumatoid arthritis: therapeutic "freeze frame"

In Russia, as well as throughout the world, the use of glucocorticoids (GC) in the treatment of rheumatoid arthritis (RA) is widespread, often going beyond the recommendations for both duration and dose regimen, which makes it relevant to study the long-term consequences of such a "wrong" (EULAR, 2022) use of GC in RA therapy. Of 1143 patients with active RA (ACR/EULAR 2010), two groups were formed: A (n=782) RA patients with more than 6 months of experience with systemic GC; group B (n=245) - no experience of taking GC. The cumulative disease index (CIRS) was used to assess the comorbidity profile. Patients in group A were older (p<0.0001), with a longer duration of RA (p=0.0004) and more often with IV radiological stage (p=0.02). With comparable (DAS28) RA activity, the D2T variant of RA was more often detected in them (p=0.036). RA therapy in group A was characterized by a large number of used disease-modifying anti-rheumatic drugs (p=0.0003), more frequent development of methotrexate-induced hepatitis (p=0.03). In group A, the time interval between the onset of RA and the initiation of biological therapy was longer (p=0.0001) and directly correlated with the duration of GC therapy (Rs=0.38) with a comparable qualitative structure of the used b/tsDMARDs. In the same group, tuberculosis, hypertension, chronic kidney disease, cataract and osteoporosis (p<0.05) and its complications were diagnosed significantly more often with a comparable frequency of cardiovascular disease, diabetes, and gastrointestinal lesions. In group A, a higher CIRS multimorbidity index was detected, and the CIRS severity index was lower than in group B (p<0.05). Long-term use of GC did not lead to a decrease in disease activity, inhibition of radiographic progression, delayed the timely administration of b/tsDMARDS and was accompanied by an increase in the multimorbid load.

Correlation of frailty assessment metrics in one-year follow-up of aged care residents: a sub-study of a randomised controlled trial

IntroductionFrailty is increasingly recognised as a dynamic syndrome, with multiple causes, dimensions and consequences. There is little understanding of how those frailty assessment metrics interact over time. The aim of this study was to describe the longitudinal correlation between five frailty metrics, namely multimorbidity, muscular strength, mood alterations, cognitive capacity, and functional capacity in a cohort study of aged care (nursing home) residents.Methods248 aged care residents with Frailty Index at baseline of < 0.4 and no dementia were followed for 12 months. A multimorbidity score and an activity of daily living limitation score were created using individual items of the Frailty Index. Muscular strength was measured by grip strength. Cognitive capacity was measured using the Montreal Cognitive Assessment (MoCA) test. Mood alterations were measured using the anxiety/depression screening question from EQ-5D. We analysed the inter-individual correlation at baseline, association between baseline and future change, and within-individual correlation at baseline, 6 and 12 months.ResultsPopulation analysis shows that metrics were not associated at baseline. All of the studied metrics at baseline were associated with change in 12 months, with the exception of anxiety/depression scores. Pairwise within-individual correlation was strong between MoCA and grip strength (0.13, p = 0.02) and activity of daily living (− 0.48, p < 0.001), and between activities of daily living and multimorbidity index (0.28, p < 0.001). No within-individual correlation was found between anxiety depression score and other metrics.ConclusionThe results suggest an interdependence between comorbidities, physical capacity, cognition and activities of daily living in aged care residents. Comprehensive measurement of frailty-related metrics may provide improved understanding of frailty progression at later life stages.

Predicting 6-month mortality of patients from their medical history: Comparison of multimorbidity index to Deyo-Charlson index.

While every disease could affect a patient's prognosis, published studies continue to use indices that include a selective list of diseases to predict prognosis, which may limit its accuracy. This paper compares 6-month mortality predicted by a multimorbidity index (MMI) that relies on all diagnoses to the Deyo version of the Charlson index (DCI), a popular index that utilizes a selective set of diagnoses. In this retrospective cohort study, we used data from the Veterans Administration Diabetes Risk national cohort that included 6,082,018 diabetes-free veterans receiving primary care from January 1, 2008 to December 31, 2016. For the MMI, 7805 diagnoses were assigned into 19 body systems, using the likelihood that the disease will increase risk of mortality. The DCI used 17 categories of diseases, classified by clinicians as severe diseases. In predicting 6-month mortality, the cross-validated area under the receiver operating curve for the MMI was 0.828 (95% confidence interval of 0.826-0.829) and for the DCI was 0.749 (95% confidence interval of 0.748-0.750). Using all available diagnoses (MMI) led to a large improvement in accuracy of predicting prognosis of patients than using a selected list of diagnosis (DCI).

Physical Activity versus Selected Health Behaviors, Subjective Physical and Psychological Health and Multimorbidity in a Large Cohort of Polish Seniors during the COVID-19 Pandemic (Results of the National Test for Poles’ Health )

National Test for Poles' Health is an online study conducted on a large group of Polish Internet users. For the purpose of this study, 64,732 subjects (48.8% female) over 65 years old were included. Subjects provided answers on the level of physical activity (PA) they engage in, prevalence of non-communicable diseases (obesity, hypertension, diabetes, heart diseases, chronic obstructive pulmonary disease (COPD), depression, cancer) and subjective physical and psychological health. Additionally, their Body Mass Index (BMI) and prevalence of multimorbidity was assessed. We found that older people who engage in at least 2 h of physical activity/week had significantly lower prevalence of hypertension, obesity and heart diseases than those who engaged in 1-1.5 h/week or less than 1 h/week. Multimorbidity was present in 33.2% of subjects from the most active group and 52.6% of the least active ones. Subjective physical and psychological health was rated as "very good" by 26.6% and 41.2%, respectively, by subjects from the most active group. Only 9.1% of the least active subjects rated their physical health as "very good" and only 27.4% rated their psychological health as such. Regular physical activity may be a helpful tool in combating the reduced well-being of older people affected by the isolation caused by the COVID-19 pandemic. Unfortunately, over 65% of respondents claimed to engage in less than 1 h of PA a week or less.