Multimorbidity

Introduction

As people are living for longer with multiple long-term health conditions (MLTCs), there are also more people dying with and from MLTCs.  Dying with/from MLTCs can be unpredictable, lead to uncertainty for patients, caregivers and healthcare professionals, and hinder timely conversations around future care planning.

There is no universally accepted definition informing the identification of individuals with MLTCs who may be approaching the end of life (advanced multimorbidity). This scoping review synthesised how advanced multimorbidity is defined in research, policy and practice.

Methods

Using the Arksey and O’Malley framework and relevant updates, scoping review methodology was used to search multiple databases and Grey Literature, summarised via the PRISMA-ScR. Two reviewers selected final study texts, which underwent content analysis. Stakeholder consultations with clinicians, academics and public participants ensured context and relevance of findings.

Results

From 10,316 unique publications, 38 final texts were included. Most (33/38) were published in the last decade. Many were quantitative (18/38) though a variety of other study types were included. Participants were mainly elderly - mean age 78.5years. Only 4/38 studies integrated patient and public involvement.

Forty-four different definitions of advanced multimorbidity were identified across the 38 studies, with only 2 definitions used across multiple studies. Definitions varied in the type and number of conditions included. Twenty-six definitions incorporated multiple variables to define advanced multimorbidity, while the remaining 18 used a single variable. Variables were conceptualised as discrete (functional assessments, age, healthcare utilisation etc) or holistic (self-assessment, clinician assessment, assessment tools). Stakeholders preferred definitions that were user-friendly and clinically driven.

Conclusions

The lack of consensus around an advanced multimorbidity definition creates unwarranted heterogeneity and barriers to advancing research in this field. This review highlights the need for a standardised approach that is context-appropriate and meaningful to practice and care, to facilitate proactive realistic conversations and decision-making.

Background: Multimorbidity patterns is associated with future mortality among older adutls. However, the addictive effect of disability for distinct multimorbidity patters is unclear. Our aim was to identify the multimorbidity patterns of Taiwanese people aged over 50 years and to explore their association between multimorbidity patterns with/without disability and future mortality.

Methods: This longitudinal cohort study used data from the Taiwan Longitudinal Study on Aging. The data were obtained from wave 3, and the multimorbidity patterns in 1996, 1999, 2003, 2007, and 2011 were analyzed separately by latent class analysis (LCA). The association between each disease group with/without disability and mortality was examined using logistic regression.

Results: 5124 older adults with average age of 66.7 years old were included. Four disease patterns were identified in 1996, namely, the cardiometabolic (21.6%), arthritis-cataract (11.6%), relatively healthy (61.2%), and multimorbidity (5.6%) groups. After adjusting all the confounders, the cardiometabolic group with disability showed the highest risk for mortality (odds ratio: 2.83, 95% CI: 1.70-4.70), followed by Multimorbidity group with disability (odds ratio: 2.33, 95% CI: 1.17-4.64) and relatively health group with disability (odds ratio: 1.79, 95% CI: 1.22-2.62) and cardiometabolic group without disability (odds ratio: 1.21, 95% CI: 1.01-1.45).

Conclusion: This longitudinal study reveals disability plays an important role on mortality among older adults with distinct multimorbidity patterns. Older adults with a cardiometabolic multimorbidity pattern with disability had a dismal outcome. Thus, healthcare professionals should put more emphasis on the prevention and identification of cardiometabolic multimorbidity, with routine checkup of their functional limitation.

Subjective cognitive decline (SCD) is defined by cognitive complaints expressed by the individual, without evidence of cognitive impairment on objective neuropsychological tests. Studies have analyzed SCD among patients with specific groups of diseases. An increased understanding of the association between disease patterns and subjective cognitive decline is essential to develop targeted interventions for these groups. Using data from the baseline of the Brazilian Longitudinal Study of Aging (ELSI-Brazil), this cross-sectional study included 2,508 participants. Subjective Cognitive Decline (SCD) was assessed using the Subjective Cognitive Decline Initiative Working Group's criteria. Multimorbidity (MM) was defined as the presence of two or more of 14 self-reported health conditions. Clusters of MM were identified based on the most prevalent dyads and triads of diseases within the sample. Robust Poisson regression models were used to estimate adjusted prevalence ratios (PR) for the association between MM clusters and SCD, accounting for potential confounders. The following dyads of chronic conditions were associated with higher prevalence of SCD: ophthalmological problems/osteoporosis (RR: 1.497 p=0.042), heart problems/stroke (RR: 2.33, p<.001), and hypertension />asthma (RR: 3.309, p=0.013). No triads had positive association with SCD, although the triads of ophthalmological problem/hypertension/osteoporosis (RR: 0.367, p<.001) and hypertension />cardiac problems/dyslipidemia (RR: 0.545, p=0.012) were negatively associated with the prevalence of SCD. Our study demonstrated an association between SCD and MM clusters, which is important for developing and managing care for individuals with cognitive decline and/or those multimorbidity patterns. The results could also provide a foundation for future research exploring the causality between these variables.

Introduction: People living with multiple long-term conditions (MLTC) are more likely to experience hospital admission, which is often associated with unintended consequences. Preventing or providing alternatives to admission by predicting adverse admission-related outcomes is important. This study aims to provide an overview of the association between MLTCs and adverse outcomes following hospital admission through a systematic review of systematic reviews.

Method: We searched Medline, Embase, CINAHL, Web of Science and PsycINFO for systematic reviews assessing risk factors/predictors of functional decline (FD), nursing home admission (NHA), or changes in quality of life among adults (≥18 years) experiencing unscheduled acute hospital admission. Eligible reviews had to assess MLTC (LTC counts, indices, or individual LTCs), either alone or with other predictors. Titles/abstracts and full texts were screened in duplicate and candidate predictors were extracted.

Results: 14 systematic reviews assessed predictors of FD (n=8) or NHA (n=6). Reviews focused on studies of general inpatients/mixed presentations (n=8: 6 FD, 2 NHA); hip fracture (n=2: 1 FD, 1 NHA); stroke (n=2: 1 FD, 1 NHA) and cognitive impairment (n=1, NHA) or delirium (n=1, NHA). Assessment of MLTC was heterogenous: comorbidity indices (n=4), counts of LTC (n=2), specific LTC (n=8), and ‘comorbidity’ without further qualification (n=3). Higher comorbidity indices, higher counts, and a range of specific comorbidities (most notably dementia) were associated with FD and NHA. Reviews assessing MLTC alongside other predictors highlighted a broad range of sociodemographic, functional, social, and admission-related factors that were associated with FD and NHA. In general, reviews did not assess the relative importance of MLTC alongside other predictors.

Conclusion: While MLTC may predict unwanted outcomes following admission their qualification is often inconsistent and their relative importance as predictors, alongside broader factors such as social complexity, is rarely assessed in existing systematic reviews.

Objective

Ageing is associated with reduced vaccine efficacy due to immunosenescence. Severe COVID-19 outcomes are associated with comorbidities prevalent in older people. We report results from the INFORM study on severe COVID-19 outcomes in vaccinated older individuals with varying numbers of comorbidities.

Methods

A retrospective observational cohort study was conducted in England using a 25% random sample from NHS databases. COVID-19-related outcomes (hospitalisations and mortality) in fully vaccinated (≥3 doses) older individuals from 1 Jan to 31 Dec 2022 are reported.

Results

Of a reference population of 7,180,205 fully vaccinated individuals ≥12 years, 2,232,140 were ≥65 years. The proportion of older people with ≥1 COVID-19 hospitalisation increased with age (≥65, 0.6%; ≥70, 0.7%; ≥75, 0.9%; ≥80, 1.2%) compared to overall population (OP, 0.2%). Incidence rates (IR) (95% CI) per 100 person years also increased with age for hospitalisation (≥65, 0.58 [0.57-0.59]; ≥70, 0.71 [0.69-0.73]; ≥75, 0.90 [0.88-0.92]; ≥80, 1.20 [1.18-1.22] versus OP, 0.22 [0.21-0.23]) and death (≥65, 0.16 [0.15-0.17]; ≥70, 0.20 [0.18-0.22]; ≥75, 0.28 [0.26-0.30]; ≥80, 0.42 [0.39-0.45] versus OP, 0.05 [0.04-0.06]).

In those ≥65, 1,375,470 were not immunocompromised (IC) but had ≥1 high-risk comorbidity (no-IC/+Com), 586,155 had neither IC or comorbidity (noIC/noCom). An increased number of comorbidities was associated with increased hospitalisation and death IRs. In those ≥65 noIC/+Com, IRs (95% CI) were 0.63 (0.61-0.65), 0.88 (0.86-0.90) and 1.25 (1.22-1.28) for hospitalisation vs 0.20 (0.17-0.23) in noIC/noCom; and 0.16 (0.14-0.18), 0.23 (0.21-0.25) and 0.32 (0.29-0.09) vs 0.06 (0.03-0.09) for noIC/noCom for death where individuals had ≥1, ≥2 and ≥3 noIC/+Com, respectively.

Conclusions

Despite vaccination, older people are at increased risk for severe COVID-19 outcomes, with higher risk associated with more comorbidities. Even older patients with no-IC conditions have increased risk, especially those with other high-risk comorbidities. Additional interventions may be required to protect older people against severe COVID-19 outcomes.

Introduction: A growing body of evidence suggests that metabolic syndrome is associated with endocrine disorders, including thyroid dysfunction. Thyroid dysfunction in patients with metabolic syndrome may further increase the risk of cardiovascular disease, thus increasing mortality. This study was conducted to assess thyroid function in patients with metabolic syndrome and to assess its relationship to components of metabolic syndrome.

Methods: A cross-sectional study was carried out among 170 geriatric patients. Anthropometric measurements (height, weight, waist circumference) and blood pressure were taken. Fasting blood samples were analyzed for glucose, triglycerides, high-density lipoprotein (HDL) cholesterol, and thyroid hormones (triiodothyronine, thyroxine, and thyroid-stimulating hormone).

Results: Thyroid dysfunction was observed in 31.9% (n = 54) of patients with metabolic syndrome. Subclinical hypothyroidism (26.6%) was the main thyroid dysfunction followed by overt hypothyroidism (3.5%) and subclinical hyperthyroidism (1.7%). Thyroid dysfunction was much more common in women (39.7%, n=29) than in men (26%, n=25), but not statistically significant (p=0.068). The relative risk of having thyroid dysfunction in women was 1.525 (CI: 0.983-2.368) compared to men. Significant differences (p = 0.001) were observed in waist circumference between patients with and without thyroid dysfunction and HDL cholesterol that had a significant negative correlation with thyroid-stimulating hormone.

Conclusion: Thyroid dysfunction, particularly subclinical hypothyroidism, is common among patients with metabolic syndrome and is associated with some components of metabolic syndrome (waist circumference and HDL cholesterol).