Multimorbidity patterns of chronic conditions and geriatric syndromes in older patients from the MoPIM multicentre cohort study

Trajectories of chronic multimorbidity patterns in older patients: MTOP study

BACKGROUND

Multimorbidity is associated with negative results and poses difficulties in clinical management. New methodological approaches are emerging based on the hypothesis that chronic conditions are non-randomly associated forming multimorbidity patterns. However, there are few longitudinal studies of these patterns, which could allow for better preventive strategies and healthcare planning. The objective of the MTOP (Multimorbidity Trajectories in Older Patients) study is to identify patterns of chronic multimorbidity in a cohort of older patients and their progression and trajectories in the previous 10 years.

METHODS

A retrospective, observational study with a cohort of 3988 patients aged > 65 was conducted, including suspected and confirmed COVID-19 patients in the reference area of Parc Taulí University Hospital. Real-world data on socio-demographic and diagnostic variables were retrieved. Multimorbidity patterns of chronic conditions were identified with fuzzy c-means cluster analysis. Trajectories of each patient were established along three time points (baseline, 5 years before, 10 years before). Descriptive statistics were performed together with a stratification by sex and age group.

RESULTS

3988 patients aged over 65 were included (58.9% females). Patients with ≥ 2 chronic conditions changed from 73.6 to 98.3% in the 10-year range of the study. Six clusters of chronic multimorbidity were identified 10 years before baseline, whereas five clusters were identified at both 5 years before and at baseline. Three clusters were consistently identified in all time points (Metabolic and vascular disease, Musculoskeletal and chronic pain syndrome, Unspecific); three clusters were only present at the earliest time point (Male-predominant diseases, Minor conditions and sensory impairment, Lipid metabolism disorders) and two clusters emerged 5 years before baseline and remained (Heart diseases and Neurocognitive). Sex and age stratification showed different distribution in cluster prevalence and trajectories.

CONCLUSIONS

In a cohort of older patients, we were able to identify multimorbidity patterns of chronic conditions and describe their individual trajectories in the previous 10 years. Our results suggest that taking these trajectories into consideration might improve decisions in clinical management and healthcare planning.

TRIAL REGISTRATION NUMBER

NCT05717309.

Multimorbidity, consisting of a combination of chronic diseases and geriatric syndromes, predicts the risk of difficulty in discharge home in older patients admitted to acute care hospital

AIM

To determine whether multimorbidity, consisting of chronic diseases and geriatric syndromes, is associated with home discharge difficulties in older patients.

METHODS

A total of 522 older adults (mean age: 85 ± 7 years) who were admitted to an acute care hospital were enrolled. Multimorbidity was assessed by calculating the number of 16 chronic conditions (CCs): 8 chronic diseases (cardiac diseases, diabetes mellitus, chronic kidney disease, respiratory diseases, gastrointestinal diseases, anemia, dementia, and Parkinson disease) and 8 geriatric syndromes (depression, constipation, chronic pain, polypharmacy, dysphagia, underweight, hypoalbuminemia, and functional limitations). The patients were divided into four groups based on the number of CCs. The outcome was difficulty in discharging home (transfer to other facilities or in-hospital death). Multivariate logistic regression analysis was performed to assess independent associations between four CC groups and failure to discharge home after adjusting for age, sex, living alone, and Barthel index and odds ratio (OR) and 95% confidence interval (CI) were calculated.

RESULTS

Of the 522 patients, 18.8% were transferred to other facilities or died. The proportion of poor outcome in those with 0-2, 3-4, 5-6, and ≥7 CCs was 4.4%, 14.8%, 25.5%, and 37.5%, respectively. Logistic regression analysis after adjusting for covariates revealed that multimorbidity increased the risk of difficulty in discharging home (OR, 2.9 [95% CI, 1.1-8.0] for 3-4 CCs; OR, 4.9 [95% CI, 1.8-13.5] for 5-6 CCs; OR, 8.7 [95% CI, 3.1-24.6] for ≥7 CCs).

CONCLUSION

Multimorbidity, consisting of chronic diseases and geriatric syndromes, predicted difficulty in discharge home in older patients. Geriatr Gerontol Int 2024; 24: 300-305.

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.

A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods

OBJECTIVES

Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.

STUDY DESIGN AND SETTING

We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.

RESULTS

Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.

CONCLUSION

The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.

Cohort Profile: Better Health in Late Life

Purpose

Humans are living longer and may develop multiple chronic diseases in later life. The Better Health in Late Life cohort study aims to improve our understanding of the risks and outcomes of multimorbidity in the Danish population.

Methods

A randomly-selected sample of Danish residents who were 50-65 years of age received a questionnaire and an invitation to participate in this study. Respondents completed an online survey between October 2021 and January 2022 which addressed topics that included self-assessed health, mental health, sleep, specific medical conditions, use of painkillers, diet, alcohol consumption, smoking, physical activity, and body composition. This information was linked to the Danish health and social registries (some established in 1943 and onwards) that maintain data on filled prescriptions, hospital records, socioeconomic status, and health care utilization.

Results

Responses were received from 115,431 of the 301,244 residents invited to participate (38%). We excluded respondents who answered none of the questions as well as those who provided no information on sex or indicated an age other than 50-65 years. Of the 114,283 eligible respondents, 54.8% were female, 30.3% were overweight, and 16.7% were obese. Most participants reported a weekly alcohol consumption of less than seven units and 13.3% were current smokers; 5.2% had a history of hospitalization for solid cancer, and 3.0%, 2.3%, 2.0%, and 0.9% reported chronic pulmonary disease, diabetes, stroke, and myocardial infarction, respectively. The most frequently filled prescriptions were for medications used to treat the nervous system and cardiovascular diseases (38.1% and 37.4%, respectively).

Epidemiology, mortality, and health service use of local-level multimorbidity patterns in South Spain

Multimorbidity -understood as the occurrence of chronic diseases together- represents a major challenge for healthcare systems due to its impact on disability, quality of life, increased use of services and mortality. However, despite the global need to address this health problem, evidence is still needed to advance our understanding of its clinical and social implications. Our study aims to characterise multimorbidity patterns in a dataset of 1,375,068 patients residing in southern Spain. Combining LCA techniques and geographic information, together with service use, mortality, and socioeconomic data, 25 chronicity profiles were identified and subsequently characterised by sex and age. The present study has led us to several findings that take a step forward in this field of knowledge. Specifically, we contribute to the identification of an extensive range of at-risk groups. Moreover, our study reveals that the complexity of multimorbidity patterns escalates at a faster rate and is associated with a poorer prognosis in local areas characterised by lower socioeconomic status. These results emphasize the persistence of social inequalities in multimorbidity, highlighting the need for targeted interventions to mitigate the impact on patients' quality of life, healthcare utilisation, and mortality rates.

Multimorbidity patterns in COVID-19 patients and their relationship with infection severity: MRisk-COVID study

BACKGROUND

Several chronic conditions have been identified as risk factors for severe COVID-19 infection, yet the implications of multimorbidity need to be explored. The objective of this study was to establish multimorbidity clusters from a cohort of COVID-19 patients and assess their relationship with infection severity/mortality.

METHODS

The MRisk-COVID Big Data study included 14 286 COVID-19 patients of the first wave in a Spanish region. The cohort was stratified by age and sex. Multimorbid individuals were subjected to a fuzzy c-means cluster analysis in order to identify multimorbidity clusters within each stratum. Bivariate analyses were performed to assess the relationship between severity/mortality and age, sex, and multimorbidity clusters.

RESULTS

Severe infection was reported in 9.5% (95% CI: 9.0-9.9) of the patients, and death occurred in 3.9% (95% CI: 3.6-4.2). We identified multimorbidity clusters related to severity/mortality in most age groups from 21 to 65 years. In males, the cluster with highest percentage of severity/mortality was Heart-liver-gastrointestinal (81-90 years, 34.1% severity, 29.5% mortality). In females, the clusters with the highest percentage of severity/mortality were Diabetes-cardiovascular (81-95 years, 22.5% severity) and Psychogeriatric (81-95 years, 16.0% mortality).

CONCLUSION

This study characterized several multimorbidity clusters in COVID-19 patients based on sex and age, some of which were found to be associated with higher rates of infection severity/mortality, particularly in younger individuals. Further research is encouraged to ascertain the role of specific multimorbidity patterns on infection prognosis and identify the most vulnerable morbidity profiles in the community.

TRIAL REGISTRATION

NCT04981249. Registered 4 August 2021 (retrospectively registered).

[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.

Association between sleep problems and multimorbidity patterns in older adults

BACKGROUND

Sleep problems are frequent in older adults and are associated with chronic diseases. However, the association with multimorbidity patterns is still unknown. Considering the negative impacts that multimorbidity patterns can have on older adults' life, knowledge of this association can help in the screening and early identification of older adults with sleep problems. The objective was to verify the association between sleep problems and multimorbidity patterns in older Brazilian adults.

METHODS

This was a cross-sectional study conducted with data from 22,728 community-dwelling older adults from the 2019 National Health Survey. The exposure variable was self-reported sleep problems (yes/no). The study outcomes were: multimorbidity patterns, analyzed by self-report of the coexistence of two or more chronic diseases with similar clinical characteristics: (1) cardiopulmonary; (2) vascular-metabolic; (3) musculoskeletal; (4) coexisting patterns.

RESULTS

Older adults with sleep problems had 1.34 (95%CI: 1.21; 1.48), 1.62 (95%CI: 1.15; 2.28), 1.64 (95%CI: 1.39; 1.93), and 1.88 (95%CI: 1.52; 2.33) greater odds of presenting vascular-metabolic, cardiopulmonary, musculoskeletal, and coexisting patterns, respectively.

CONCLUSIONS

These results suggest that public health programs aimed at preventing sleep problems in older adults are essential to reduce possible adverse health outcomes, including multimorbidity patterns and their negative consequences for older adults' health.

Social determinants of multimorbidity patterns: A systematic review

Social determinants of multimorbidity are poorly understood in clinical practice. This review aims to characterize the different multimorbidity patterns described in the literature while identifying the social and behavioral determinants that may affect their emergence and subsequent evolution. We searched PubMed, Embase, Scopus, Web of Science, Ovid MEDLINE, CINAHL Complete, PsycINFO and Google Scholar. In total, 97 studies were chosen from the 48,044 identified. Cardiometabolic, musculoskeletal, mental, and respiratory patterns were the most prevalent. Cardiometabolic multimorbidity profiles were common among men with low socioeconomic status, while musculoskeletal, mental and complex patterns were found to be more prevalent among women. Alcohol consumption and smoking increased the risk of multimorbidity, especially in men. While the association of multimorbidity with lower socioeconomic status is evident, patterns of mild multimorbidity, mental and respiratory related to middle and high socioeconomic status are also observed. The findings of the present review point to the need for further studies addressing the impact of multimorbidity and its social determinants in population groups where this problem remains invisible (e.g., women, children, adolescents and young adults, ethnic groups, disabled population, older people living alone and/or with few social relations), as well as further work with more heterogeneous samples (i.e., not only focusing on older people) and using more robust methodologies for better classification and subsequent understanding of multimorbidity patterns. Besides, more studies focusing on the social determinants of multimorbidity and its inequalities are urgently needed in low- and middle-income countries, where this problem is currently understudied.

Sex Differences in Multimorbidity, Inappropriate Medication and Adverse Outcomes of Inpatient Care: MoPIM Cohort Study

There is no published evidence on the possible differences in multimorbidity, inappropriate prescribing, and adverse outcomes of care, simultaneously, from a sex perspective in older patients. We aimed to identify those possible differences in patients hospitalized because of a chronic disease exacerbation. A multicenter, prospective cohort study of 740 older hospitalized patients (≥65 years) was designed, registering sociodemographic variables, frailty, Barthel index, chronic conditions (CCs), geriatric syndromes (GSs), polypharmacy, potentially inappropriate prescribing (PIP) according to STOPP/START criteria, and adverse drug reactions (ADRs). Outcomes were length of stay (LOS), discharge to nursing home, in-hospital mortality, cause of mortality, and existence of any ADR and its worst consequence. Bivariate analyses between sex and all variables were performed, and a network graph was created for each sex using CC and GS. A total of 740 patients were included (53.2% females, 53.5% ≥85 years old). Women presented higher prevalence of frailty, and more were living in a nursing home or alone, and had a higher percentage of PIP related to anxiolytics or pain management drugs. Moreover, they presented significant pairwise associations between CC, such as asthma, vertigo, thyroid diseases, osteoarticular diseases, and sleep disorders, and with GS, such as chronic pain, constipation, and anxiety/depression. No significant differences in immediate adverse outcomes of care were observed between men and women in the exacerbation episode.

Osteoporosis and sarcopenia are associated with each other and reduced IGF1 levels are a risk for both diseases in the very old elderly

It is mandatory to manage musculoskeletal disorders in the elderly to prevent their becoming bed-ridden or requiring long-term care. However, the prevalence of musculoskeletal disorders such as osteoporosis and sarcopenia in otherwise healthy people over 85 years old is not completely known. Here we enrolled 1026 healthy subjects between 85 and 89 years old and evaluated them for the presence of osteoporosis, sarcopenia and fragility fracture(s), and how those conditions were related. We also evaluated biomarkers such as serum levels of insulin-like growth factor 1 (IGF1) and vitamin D status. The prevalence of osteoporosis, sarcopenia or fragility fracture(s) in these subjects was 22.4, 10.2 or 15.0 %, respectively. Serum IGF1 and 25(OH)D were significantly and negatively correlated with osteoporosis or sarcopenia. Osteoporosis and either sarcopenia or fragility fracture(s) were significantly related and shown to be risk factors for each other, even after adjustment for gender and BMI, while sarcopenia and fragility fracture(s) were not associated. Our data may provide a health platform for the very elderly and suggest strategies to prevent musculoskeletal disorders in this population.

Comprehensive Multimorbidity Patterns in Older Patients Are Associated with Quality Indicators of Medication-MoPIM Cohort Study

Multimorbidity is increasing and poses a challenge to the clinical management of patients with multiple conditions and drug prescriptions. The objectives of this work are to evaluate if multimorbidity patterns are associated with quality indicators of medication: potentially inappropriate prescribing (PIP) or adverse drug reactions (ADRs). A multicentre prospective cohort study was conducted including 740 older (≥65 years) patients hospitalised due to chronic pathology exacerbation. Sociodemographic, clinical and medication related variables (polypharmacy, PIP according to STOPP/START criteria, ADRs) were collected. Bivariate analyses were performed comparing previously identified multimorbidity clusters (osteoarticular, psychogeriatric, minor chronic disease, cardiorespiratory) to presence, number or specific types of PIP or ADRs. Significant associations were found in all clusters. The osteoarticular cluster presented the highest prevalence of PIP (94.9%) and ADRs (48.2%), mostly related to anxiolytics and antihypertensives, followed by the minor chronic disease cluster, associated with ADRs caused by antihypertensives and insulin. The psychogeriatric cluster presented PIP and ADRs of neuroleptics and the cardiorespiratory cluster indicators were better overall. In conclusion, the associations that were found reinforce the existence of multimorbidity patterns and support specific medication review actions according to each patient profile. Thus, determining the relationship between multimorbidity profiles and quality indicators of medication could help optimise healthcare processes. Trial registration number: NCT02830425.

Are multimorbidity patterns associated with fear of falling in community-dwelling older adults?

Background

Multimorbidity is defined as the co-occurrence of multiple chronic or acute diseases and medical conditions in the same individual and can be grouped into different patterns based on the type of disease. These patterns are associated with poorer quality of life and premature death. It is believed that these patterns entail functional limitations, which may contribute to the fear of falling; however, this association remains unknown. Identifying this possible association is fundamental for developing individual and collective care approaches aimed at preventing the different patterns of chronic diseases in older adults in order to decrease the fear of falling. The objective of this study was to investigate the association between multimorbidity patterns and fear of falling in older adults.

Methods

This was a cross-sectional study including 308 older adults. The exposure variables were the presence of three multimorbidity patterns (cardiopulmonary, musculoskeletal, and vascular-metabolic) and pattern association assessed by self-report of two or more similar coexisting chronic diseases. The outcome was fear of falling assessed by the Brazilian version of Falls Efficacy Scale-International (cut-off point ≥ 23 points). Multivariable logistic regression was used to analyze the association between variables.

Results

Older adults with cardiopulmonary, musculoskeletal, vascular-metabolic patterns and pattern association had 3.49 (95%CI 1.13; 10.78), 2.03 (95%CI 1.13; 3.64), 2.14 (95%CI 1.20; 3.82), and 4.84 (95%CI 2.19; 10.68), respectively, greater chances of presenting fear of falling when compared to older adults without the patterns.

Conclusions

The presence of multimorbidity patterns is associated with higher chances of reporting fear of falling. It is emphasized that the introduction of public health programs aimed at preventing multimorbidity patterns is essential to reduce possible adverse health outcomes, including fear of falling and its negative consequences for older adult health.

Factors associated to potentially inappropriate prescribing in older patients according to STOPP/START criteria: MoPIM multicentre cohort study

OBJECTIVES

The objectives of the present analyses are to estimate the frequency of potentially inappropriate prescribing (PIP) at admission according to STOPP/START criteria version 2 in older patients hospitalised due to chronic disease exacerbation as well as to identify risk factors associated to the most frequent active principles as potentially inappropriate medications (PIMs).

METHODS

A multicentre, prospective cohort study including older patients (≥65) hospitalized due to chronic disease exacerbation at the internal medicine or geriatric services of 5 hospitals in Spain between September 2016 and December 2018 was conducted. Demographic and clinical data was collected, and a medication review process using STOPP/START criteria version 2 was performed, considering both PIMs and potential prescribing omissions (PPOs). Primary outcome was defined as the presence of any most frequent principles as PIMs, and secondary outcomes were the frequency of any PIM and PPO. Descriptive and bivariate analyses were conducted on all outcomes and multilevel logistic regression analysis, stratified by participating centre, was performed on the primary outcome.

RESULTS

A total of 740 patients were included (mean age 84.1, 53.2% females), 93.8% of them presenting polypharmacy, with a median of 10 chronic prescriptions. Among all, 603 (81.5%) patients presented at least one PIP, 542 (73.2%) any PIM and 263 (35.5%) any PPO. Drugs prescribed without an evidence-based clinical indication were the most frequent PIM (33.8% of patients); vitamin D supplement in older people who are housebound or experiencing falls or with osteopenia was the most frequent PPO (10.3%). The most frequent active principles as PIMs were proton pump inhibitors (PPIs) and benzodiazepines (BZDs), present in 345 (46.6%) patients. This outcome was found significantly associated with age, polypharmacy and essential tremor in an explanatory model with 71% AUC.

CONCLUSIONS

PIMs at admission are highly prevalent in these patients, especially those involving PPIs or BZDs, which affected almost half of the patients. Therefore, these drugs may be considered as the starting point for medication review and deprescription.

TRIAL REGISTRATION NUMBER

NCT02830425.