Multimorbidity and functional status in institutionalized older adults

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

Background

Identifying clusters of co-occurring diseases may help characterise distinct phenotypes of Multiple Long-Term Conditions (MLTC). Understanding the associations of disease clusters with health-related outcomes requires a strategy to assign clusters to people, but it is unclear how the performance of strategies compare.

Aims

First, to compare the performance of methods of assigning disease clusters to people at explaining mortality, emergency department attendances and hospital admissions over one year. Second, to identify the extent of variation in the associations with each outcome between and within clusters.

Methods

We conducted a cohort study of primary care electronic health records in England, including adults with MLTC. Seven strategies were tested to assign patients to fifteen disease clusters representing 212 LTCs, identified from our previous work. We tested the performance of each strategy at explaining associations with the three outcomes over 1 year using logistic regression and compared to a strategy using the individual LTCs.

Results

6,286,233 patients with MLTC were included. Of the seven strategies tested, a strategy assigning the count of conditions within each cluster performed best at explaining all three outcomes but was inferior to using information on the individual LTCs. There was a larger range of effect sizes for the individual LTCs within the same cluster than there was between the clusters.

Conclusion

Strategies of assigning clusters of co-occurring diseases to people were less effective at explaining health-related outcomes than a person's individual diseases. Furthermore, clusters did not represent consistent relationships of the LTCs within them, which might limit their application in clinical research.

Multimorbidity Patterns and 5-Year Mortality in Institutionalized Older Adults

OBJECTIVES

The aim was to characterize multimorbidity patterns in a large sample of older individuals living in nursing homes (NHs) and to investigate their association with mortality, also considering the effect of functional status.

DESIGN

Observational and retrospective study.

SETTING AND PARTICIPANTS

We analyzed data on 4131 NH residents in Italy, aged 60 years and older, assessed through the interRAI long-term care facility instrument. Entry date was between 2014 and 2018, and participants were followed until 2019.

METHODS

Multimorbidity patterns were identified through principal component analysis; for the identified components, subjects were stratified in quintiles (Q) with respect to their loading values, with the higher quantiles indicating greater expression of the component's pattern. Their association [hazard ratio (HR) and 95% CI] with mortality was tested in Cox regression models. Analyses were stratified by disability status.

RESULTS

Four patterns of multimorbidity were identified: (1) heart diseases; (2) dementia and sensory impairments; (3) heart, respiratory, and psychiatric diseases; and (4) diabetes, musculoskeletal, and vascular diseases. For the heart diseases pattern [HR Q5 vs Q1 = 1.83 (1.53-2.20)] and the dementia and sensory impairments pattern [HR Q5 vs Q1 = 1.23 (1.06-1.42)], as the specific multimorbidity expression increases, the risk of mortality increases. On stratifying by disability status, the association between the multimorbidity patterns and mortality was not always present.

CONCLUSIONS AND IMPLICATIONS

Different multimorbidity patterns are differentially associated with mortality in older residents of NHs, confirming that multimorbidity's prognosis is strictly dependent on the underlying disease combinations. This knowledge may be useful to implement personalized preventive and therapeutic care pathways for institutionalized older adults, which respond to individuals' health needs.

Do replicable profiles of multimorbidity exist? Systematic review and synthesis

This systematic review aimed to synthesise multimorbidity profiling literature to identify replicable and clinically meaningful groupings of multimorbidity. We searched six electronic databases (Medline, EMBASE, PsycINFO, CINAHL, Scopus, and Web of Science) for articles reporting multimorbidity profiles. The identified profiles were synthesised with multidimensional scaling, stratified by type of statistical analysis used in the derivation of profiles. The 51 studies that met inclusion criteria reported results of 98 separate analyses of multimorbidity profiling, with a total of 407 multimorbidity profiles identified. The statistical techniques used to identify multimorbidity profiles were exploratory factor analysis, cluster analysis of diseases, cluster analysis of people, and latent class analysis. Reporting of methodological details of statistical methods was often incomplete. The discernible groupings of multimorbidity took the form of both discrete categories and continuous dimensions. Mental health conditions and cardio-metabolic conditions grouped along identifiable continua in the synthesised results of all four methods. Discrete groupings of chronic obstructive pulmonary disease with asthma, falls and fractures with sensory deficits and of Parkinson's disease and cognitive decline where partially replicable (identifiable in the results of more than one method), while clustering of musculoskeletal conditions and clustering of reproductive systems were each observed only in one statistical approach. The two most replicable multimorbidity profiles were mental health conditions and cardio-metabolic conditions. Further studies are needed to understand aetiology and evolution of these multimorbidity groupings. Guidelines for strengthening the reporting of multimorbidity profiling studies are proposed.

Who Is (Still) Looking After Mom and Dad? Few Improvements in Care Aides' Quality-of-Work Life

ABSTRACTUnregulated care aides provide most of the direct care to nursing home residents. We previously reported the first demographic profile of care aides in Western Canada through the Translating Research in Elder Care (TREC) longitudinal research program (2007-2022) in applied health services. Here we describe demographic, health, and work life characteristics of aides from 91 nursing homes in Western Canada. Demographics and work life varied significantly across health regions and facility owner-operator models. Our longitudinal cohort of aides from Alberta and Winnipeg had higher emotional exhaustion (a negative attribute), professional efficacy (a positive attribute), and experience of dementia-related responsive behaviours from residents. Overall, results indicate little improvement or worsening of care aide health and quality of work life. Coupled with limited provincial or national initiatives for workforce planning and training of these workers, this signals a long-term care system ill-prepared to care effectively for Canada's aging population.

Acetylcholinesterase Inhibitors: Beneficial Effects on Comorbidities in Patients With Alzheimer's Disease

Elderly patients with Alzheimer's disease (AD) and other dementias are at high risk of polypharmacy and excessive polypharmacy for common coexisting medical conditions. Polypharmacy increases the risk of drug-drug and drug-disease interactions in these patients who may not be able to communicate early symptoms of adverse drug events. Three acetylcholinesterase inhibitors (ACHEIs) have been approved for AD: donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne). They are also used off-label for other causes of dementia such as Lewy body and vascular dementia. We here report evidence from the literature that ACHEI treatment, prescribed for cognitive impairment, can reduce the load of medications in patients with AD by also addressing cardiovascular, gastrointestinal, and other comorbidities. Using one drug to address multiple symptoms can reduce costs and improve medication compliance.