Approaching person-centered clinical practice: A cluster analysis of older inpatients utilizing the measurements of intrinsic capacity

Factors associated with intrinsic capacity impairment in hospitalized older adults: a latent class analysis

BACKGROUND

Intrinsic capacity (IC) is proposed by the World Health Organization (WHO) to promote healthy aging. Although some studies have examined the factors influencing IC, few studies have comprehensively confirmed lifestyle factors on IC, especially IC impairment patterns. The present study aimed to identify the patterns of IC impairment and explore the lifestyle and other factors associated with different patterns of IC impairment.

METHODS

This cross-sectional study was conducted in a Chinese geriatric hospital. IC was evaluated in five domains according to the recommendations of WHO: cognition, locomotion, vitality, sensory and psychological domains. The sociodemographic and health-related characteristics of participants were assessed.The health promoting lifestyle was evaluated using the Health-Promoting Lifestyle Profile-II scale, including nutrition, health responsibility, interpersonal relationships, physical activity, spiritual growth and stress management. We applied latent class analysis to identify IC impairment patterns and compared basic activities of daily living, instrumental activities of daily living, frailty, quality of life and falls among different IC impairment patterns. Multinomial logistic regression analysis was conducted to identify factors influencing the IC impairment patterns.

RESULTS

Among 237 participants included, the latent class analysis identified three patterns of IC impairment: 44.7% high IC (Class 1), 31.2% intermediate IC mainly locomotor impairment (Class 2) and 24.1% low IC mainly cognitive impairment (Class 3). Older adults in class 1 had the best function ability and quality of life, while class 3 had the highest levels of disability and frailty, the poorest quality of life and a higher prevalence of falls. Compared with class 1, older adults with advanced age (OR = 22.046, 95%CI:1.735-280.149), osteoporosis (OR = 3.377, 95%CI:1.161-9.825), and lower scores in physical activity (OR = 0.842, 95%CI:0.749-0.945), stress management (OR = 0.762, 95%CI:0.585-0.993) and social support (OR = 0.897, 95%CI:0.833-0.965) were more likely to belong to the class 2. Simultaneously, compared with class 1, older adults with advanced age (OR = 104.435, 95%CI:6.038-1806.410), stroke (OR = 3.877, 95%CI:1.172-12.823) and lower scores in physical activity (OR = 0.784, 95%CI:0.667-0.922) and social support (OR = 0.909, 95%CI:0.828-0.998) were more likely to be class 3. In addition, compared with class 2, older adults with a lower score in nutrition (OR = 0.764, 95%CI:0.615-0.950) were more likely to belong to the class 3.

CONCLUSIONS

This study provides evidence that there are heterogeneous IC impairment patterns in older adults and identifies various associated factors in each pattern, including age, stroke, osteoporosis, social support and lifestyle behaviors such as nutrition, physical activity and stress management. It informs stakeholders on which modifiable factors should be targeted through public health policy or early intervention to promote IC and healthy aging in older adults.

The assessment and detection rate of intrinsic capacity deficits among older adults: a systematic review and meta-analysis

BACKGROUND

Assessing and monitoring intrinsic capacity (IC) is an effective strategy to promote healthy ageing by intervening early in high-risk populations. This review systematically analyzed the global detection rates of IC deficits and explored variations across diverse populations and data collection methods.

METHODS

This study was preregistered with PROSPERO, CRD42023477315. In this systematic review and meta-analysis, we systematically searched ten databases from January 2015 to October 2023, for peer-reviewed, observational studies or baseline survey of trials that assessed IC deficits among older adults aged 50 and above globally following the condition, context and population approach. The main outcome was intrinsic capacity deficits which could be assessed by any tools. Meta-analyses were performed by a random-effect model to pool the detection rates across studies and subgroup analyses were conducted by populations and data collection methods.

RESULTS

Fifty-six studies conducted in 13 countries were included in the review and 44 studies with detection rates of IC were included in the meta-analysis. The pooled detection rate of IC deficits was 72.0% (65.2%-78.8%) and deficits were most detected in sensory (49.3%), followed by locomotion (40.0%), cognition (33.1%), psychology (21.9%), and vitality (20.1%). Variations in detection rates of IC deficits were observed across studies, with higher rates observed in low- and middle-income countries (74.0%) and hyper-aged societies (85.0%). Study population and measurement tools also explained the high heterogeneity across studies.

CONCLUSION

IC deficits are common among older adults, while heterogeneity exists across populations and by measurement. Early monitoring with standardized tools and early intervention on specific subdomains of IC deficits are greatly needed for effective strategies to promote healthy ageing.

Factors associated with the intrinsic capacity in older adults: A scoping review

INTRODUCTION

In 2015, the term 'intrinsic capacity' (IC) was proposed by the World Health Organisation to promote healthy aging. However, the factors associated with IC are still discrepant and uncertain.

AIM

We aim to synthesise the factors connected with IC.

METHODS

This scoping review followed the five-stage framework of Arksey and O'Malley and was reported using PRISMA-ScR guidelines.

RESULTS

In all, 29 articles were included. IC of older adults is associated with demographic characteristics, socioeconomic factors, disease conditions, behavioural factors, and biomarkers. Age, sex, marital status, occupation status, education, income/wealth, chronic diseases, hypertension, diabetes, disability, smoking status, alcohol consumption, and physical activity were emerged as important factors related to the IC of older adults.

CONCLUSIONS

This review shows that IC is related to multiple factors. Understanding these factors can provide the healthcare personnel with the theoretical basis for intervening and managing IC in older adults.

RELEVANCE TO CLINICAL PRACTICE

The influencing factors identified in the review help to guide older adults to maintain their own intrinsic capacity, thereby promoting their health and well-being. The modifiable factors also provide evidence for healthcare personnel to develop targeted intervention strategies to delay IC decline.

NO PATIENT OR PUBLIC CONTRIBUTION

As this is a scoping review, no patient or public contributions are required.

Intrinsic capacity trajectories and socioeconomic inequalities in health: the contributions of wealth, education, gender, and ethnicity

BACKGROUND

Life-long health inequalities exert enduring impacts and are governed by social determinants crucial for achieving healthy aging. A fundamental aspect of healthy aging, intrinsic capacity, is the primary focus of this study. Our objective is to evaluate the social inequalities connected with the trajectories of intrinsic capacity, shedding light on the impacts of socioeconomic position, gender, and ethnicity.

METHODS

Our dynamic cohort study was rooted in three waves (2009, 2014, 2017) of the World Health Organization's Study on Global AGEing and Adult Health in Mexico. We incorporated a nationally representative sample comprising 2722 older Mexican adults aged 50 years and over. Baseline measurements of socioeconomic position, gender, and ethnicity acted as the exposure variables. We evaluated intrinsic capacity across five domains: cognition, psychological, sensory, vitality, and locomotion. The Relative Index of Inequality and Slope Index of Inequality were used to quantify socioeconomic disparities.

RESULTS

We discerned three distinct intrinsic capacity trajectories: steep decline, moderate decline, and slight increase. Significant disparities based on wealth, educational level, gender, and ethnicity were observed. Older adults with higher wealth and education typically exhibited a trajectory of moderate decrease or slight increase in intrinsic capacity. In stark contrast, women and indigenous individuals were more likely to experience a steeply declining trajectory.

CONCLUSIONS

These findings underscore the pressing need to address social determinants, minimize gender and ethnic discrimination to ensure equal access to resources and opportunities across the lifespan. It is imperative for policies and interventions to prioritize these social determinants in order to promote healthy aging and alleviate health disparities. This approach will ensure that specific demographic groups receive customized support to sustain their intrinsic capacity during their elder years.

A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future

The increasing access to health data worldwide is driving a resurgence in machine learning research, including data-hungry deep learning algorithms. More computationally efficient algorithms now offer unique opportunities to enhance diagnosis, risk stratification, and individualised approaches to patient management. Such opportunities are particularly relevant for the management of older patients, a group that is characterised by complex multimorbidity patterns and significant interindividual variability in homeostatic capacity, organ function, and response to treatment. Clinical tools that utilise machine learning algorithms to determine the optimal choice of treatment are slowly gaining the necessary approval from governing bodies and being implemented into healthcare, with significant implications for virtually all medical disciplines during the next phase of digital medicine. Beyond obtaining regulatory approval, a crucial element in implementing these tools is the trust and support of the people that use them. In this context, an increased understanding by clinicians of artificial intelligence and machine learning algorithms provides an appreciation of the possible benefits, risks, and uncertainties, and improves the chances for successful adoption. This review provides a broad taxonomy of machine learning algorithms, followed by a more detailed description of each algorithm class, their purpose and capabilities, and examples of their applications, particularly in geriatric medicine. Additional focus is given on the clinical implications and challenges involved in relying on devices with reduced interpretability and the progress made in counteracting the latter via the development of explainable machine learning.

Associations of intrinsic capacity, fall risk and frailty in old inpatients

Introduction

This study explored the associations of intrinsic capacity (IC), fall risk, and frailty in geriatric inpatients.

Methods

A total of 703 hospitalized patients aged 75 years or older were recruited for this retrospective observational study from Zhejiang Hospital using a comprehensive geriatric assessment. The IC composite score was constructed from the scores of the Chinese version of the Mini-Mental State Examination, Short Physical Performance Battery, Short Form Mini Nutritional Assessment, 15-item Geriatric Depression Scale, and self-reported hearing and vision impairment. Adverse outcomes were recorded as the fall risk and frailty using the Morse Fall Scale and the Clinical Frailty Scale. Spearman's correlation coefficient analyses and multivariate logistic regression models were used to explore the associations between IC, high fall risk, and frailty.

Results

Declined IC composite scores were associated with increased risks of falls [odds ratio (OR) = 0.64, 95% confidence interval (CI): 0.57-0.72] and frailty (OR = 0.45, 95%CI: 0.37-0.54) among older hospitalized patients after adjusting for the related potential confounders. In addition, decreased cognitive, vitality, locomotion, and psychological scores were associated with increased adverse health conditions, with ORs ranging from 0.26 to 0.70. Vision impairment was observed to increase the risk of frailty (OR = 0.42, 95%CI: 0.23-0.76) after adjusting for the related potential confounders.

Discussion

This study indicated that declined IC was associated with fall risk and frailty in older inpatients. Further prospective studies are needed to explore the longitudinal associations between baseline IC and subsequent risk of falls and frailty.

Detection rate of decreased intrinsic capacity of older adults: a systematic review and meta-analysis

OBJECTIVES

To systematically assess the prevalence of decreased intrinsic capacity in older adults, stratified by relevant factors such as country, sex, sample source, and region.

METHODS

We conducted a comprehensive search of PubMed, Web of Science, EMBASE, The Cochrane Library, PsychINFO, CINAHL, China Knowledge Resource Integrated Database, Wanfang Database, Weipu Database, and Chinese Biomedical Database to collect studies published on the decline of intrinsic capacity in older adults before February 24, 2023. The results of the study were analyzed using the Stata 15.0 software package, using a random-effects model to estimate the pooled detection rate of decreased intrinsic capacity in older adults. The Joanna Briggs Institute Critical Appraisal Tool was used to assess the quality of all included studies.

RESULTS

A total of 16 studies (67,881 older adults in 4 countries) were included. The results showed that the pooled detection rate of decreased intrinsic capacity in older adults was 76.1% (95% CI: 68.0%-84.2%). The 16 studies had obvious heterogeneity, and further subgroup analysis showed that the detection rate of decreased intrinsic capacity in older adults was higher in developed countries, females, and hospitals. Thirteen studies found that the pooled detection rate was 73.7% (95%: CI 64.5%-82.8%) for decreased intrinsic capacity in Chinese older adults, with higher rates in mainland China and Hong Kong than in Taiwan.

CONCLUSIONS

Our study suggests that intrinsic capacity declines more rapidly in older adults. Understanding the degree of decline in the intrinsic capacity of older adults will help to provide an important basis for the formulation and development of care policies for older adults.

TRIAL REGISTRATION NUMBER

PROSPERO (CRD42023402680).

The icope Intrinsic Capacity Screening Tool: Measurement Structure and Predictive Validity of Dependence and Hospitalization

OBJECTIVES

To evaluate the measurement structure of the ICOPE screening tool (IST) of intrinsic capacity and to find out whether the IST as a global measure adds explanatory power over and above its domains in isolation to predict the occurrence of adverse health outcomes such as dependence and hospitalization in community-dwelling older people.

DESIGN

Secondary analysis of a cohort study, the Toledo Study of Healthy Ageing.

SETTING

Province of Toledo, Spain.

PARTICIPANTS

Community-dwelling older people.

MEASUREMENTS

Items equal or similar to those of the IST were introduced as a reflective-formative construct in a Structural Equation Model to evaluate its measurement structure and its association with dependence for basic and instrumental activities and hospitalization over a three-year period.

RESULTS

A total of 1032 individuals were analyzed. Mean age was 73.5 years (sd 5.4). The least preserved indicators were ability to recall three words (18%) and to perform chair stands (54%). Vision and hearing items did not form a single sensory domain, so six domains were considered. Several cognition items did not show sufficiently strong and univocal associations with the domain. After pruning the ill-behaved items, the measurement model fit was excellent (Satorra-Bentler scaled chi-square: 10.3, degrees of freedom: 11, p=0.501; CFI: 1.000; RMSEA: 0.000, 90% CI: 0.000-0.031, p value RMSEA<=0.05: 1; SRMR: 0.055). In the structural model, the cognition domain items were not associated as expected with age (p values 0.158 and 0.293), education (p values 0.190 and 0.432) and dependence (p values 0.654 and 0.813). The IST included as a composite in a model with the individual domains showed no statistically significant associations with any of the outcomes (dependence for basic activities: 0.162, p=0.167; instrumental: -0.052, p=0.546; hospitalization: 0.145, p=0.167), while only the mobility domain did so for dependence (basic: -0.266, p=0.005; instrumental: -0.138, p=0.019). The model fit of the last version was good (Satorra-Bentler scaled chi-square: 52.1, degrees of freedom: 52, p=0.469; CFI: 1.000; TLI: 1.000; RMSEA: 0.01, 90% CI: 0.000-0.02, p value RMSEA<=0.05: 1; SRMR: 0.071). The IST operationalized as the sum of non-impaired domains was not associated after covariate adjustment (dependence for basic activities: -0.065, p=0.356; instrumental: -0.08, p=0.05; hospitalization: -0.003, p=0.949) either.

CONCLUSION

The cognitive domain of the IST, and probably other of its items, may need a reformulation. A global measure of intrinsic capacity such as the IST does not add explanatory power to the individual domains that constitute it. So far, our results confirm the importance of checking the findings of the IST with a second confirmatory step, as described in the WHO's ICOPE strategy.

Association between Intrinsic Capacity and Sarcopenia in Hospitalized Older Patients

OBJECTIVES

This study aimed to clarify the association between intrinsic capacity (IC) and sarcopenia in hospitalized older patients.

DESIGN

A cross-sectional study.

SETTING

Hospital-based.

PARTICIPANTS

This study included 381 inpatients aged ≥ 60 years (225 men and 156 women).

MEASUREMENTS

IC was evaluated in five domains defined by the World Health Organization: cognition (Mini-Mental State Examination), locomotion (Short Physical Performance Battery test), vitality (Short-Form Mini Nutritional Assessment), sensory (self-reported hearing and vision) and psychological (5-item Geriatric Depression Scale) capacities. IC composite score (0-5) was calculated based on five domains, with lower scores representing greater IC. Sarcopenia was defined in accordance with the criteria recommended by the Asian Working Group for Sarcopenia (AWGS) 2019. Multiple linear and logistic regressions were performed to explore the associations between IC composite score and IC domains with sarcopenia and its defining components.

RESULTS

The mean age of 381 patients included was 81.95±8.42 years. Of them, 128 (33.6%) patients had sarcopenia. The median IC composite score was 1 (1, 2). Cognition, locomotion, vitality, sensory and psychological capacities were impaired in 22.6%, 63.5%, 18.9%, 27.3% and 11.3% of patients. Multiple linear regression analyses showed that favorable IC domain scores in cognition, locomotion and vitality were associated with a stronger handgrip strength. A higher vitality score was associated with a greater appendicular skeletal muscle mass index (ASMI), and a higher locomotion score was associated with a greater gait speed. The multiple logistic regression analysis showed that only vitality impairment was associated with sarcopenia. A higher IC composite score was associated with higher risks of sarcopenia, as well as low ASMI, handgrip strength and gait speed.

CONCLUSION

This study indicated that a more serious impairment of IC was associated with a greater risk of sarcopenia. Vitality was the domain most strongly associated with sarcopenia. IC may be employed to detect and manage sarcopenia.