Recent developments in frailty identification, management, risk factors and prevention: A narrative review of leading journals in geriatrics and gerontology.

Frailty is an age-related clinical condition characterised by an increased susceptibility to stressors and an elevated risk of adverse outcomes such as mortality. In the light of global population ageing, the prevalence of frailty is expected to soar in coming decades. This narrative review provides critical insights into recent developments and emerging practices in frailty research regarding identification, management, risk factors, and prevention. We searched journals in the top two quartiles of geriatrics and gerontology (from Clarivate Journal Citation Reports) for articles published between 01 January 2018 and 20 December 2022. Several recent developments were identified, including new biomarkers and biomarker panels for frailty screening and diagnosis, using artificial intelligence to identify frailty, and investigating the altered response to medications by older adults with frailty. Other areas with novel developments included exercise (including technology-based exercise), multidimensional interventions, person-centred and integrated care, assistive technologies, analysis of frailty transitions, risk-factors, clinical guidelines, COVID-19, and potential future treatments. This review identified a strong need for the implementation and evaluation of cost-effective, community-based interventions to manage and prevent frailty. Our findings highlight the need to better identify and support older adults with frailty and involve those with frailty in shared decision-making regarding their care.

Evolving Hybrid Partial Genetic Algorithm Classification Model for Cost-effective Frailty Screening: Investigative Study.

BACKGROUND: A commonly used method for measuring frailty is the accumulation of deficits expressed as a frailty index (FI). FIs can be readily adapted to many databases, as the parameters to use are not prescribed but rather reflect a subset of extracted features (variables). Unfortunately, the structure of many databases does not permit the direct extraction of a suitable subset, requiring additional effort to determine and verify the value of features for each record and thus significantly increasing cost. OBJECTIVE: Our objective is to describe how an artificial intelligence (AI) optimization technique called partial genetic algorithms can be used to refine the subset of features used to calculate an FI and favor features that have the least cost of acquisition. METHODS: This is a secondary analysis of a residential care database compiled from 10 facilities in Queensland, Australia. The database is comprised of routinely collected administrative data and unstructured patient notes for 592 residents aged 75 years and over. The primary study derived an electronic frailty index (eFI) calculated from 36 suitable features. We then structurally modified a genetic algorithm to find an optimal predictor of the calculated eFI (0.21 threshold) from 2 sets of features. Partial genetic algorithms were used to optimize 4 underlying classification models: logistic regression, decision trees, random forest, and support vector machines. RESULTS: Among the underlying models, logistic regression was found to produce the best models in almost all scenarios and feature set sizes. The best models were built using all the low-cost features and as few as 10 high-cost features, and they performed well enough (sensitivity 89%, specificity 87%) to be considered candidates for a low-cost frailty screening test. CONCLUSIONS: In this study, a systematic approach for selecting an optimal set of features with a low cost of acquisition and performance comparable to the eFI for detecting frailty was demonstrated on an aged care database. Partial genetic algorithms have proven useful in offering a trade-off between cost and accuracy to systematically identify frailty.

Management of frailty: opportunities, challenges, and future directions.

Frailty is a complex age-related clinical condition characterised by a decline in physiological capacity across several organ systems, with a resultant increased susceptibility to stressors. Because of the heterogeneity of frailty in clinical presentation, it is important to have effective strategies for the delivery of care that range across the continuum of frailty severity. In clinical practice, we should do what works, starting with frailty screening, case identification, and management of frailty. This process is unarguably difficult given the absence of an adequate evidence base for individual and health-system interventions to manage frailty. We advocate change towards individually tailored interventions that preserve an individual's independence, physical function, and cognition. This change can be addressed by promoting the recognition of frailty, furthering advancements in evidence-based treatment options, and identifying cost-effective care delivery strategies.

Application of an electronic Frailty Index in Australian primary care: data quality and feasibility assessment.

BACKGROUND: The primary care setting is the ideal location for identifying the condition of frailty in older adults. AIMS: The aim of this pragmatic study was twofold: (1) to identify data items to extract the data required for an electronic Frailty Index (eFI) from electronic health records (EHRs); and (2) test the ability of an eFI to accurately and feasibly identify frailty in older adults. METHODS: In a rural South Australian primary care clinic, we derived an eFI from routinely collected EHRs using methodology described by Clegg et al. We assessed feasibility and accuracy of the eFI, including complexities in data extraction. The reference standard for comparison was Fried's frailty phenotype. RESULTS: The mean (SD) age of participants was 80.2 (4.8) years, with 36 (60.0%) female (n = 60). Frailty prevalence was 21.7% by Fried's frailty phenotype, and 35.0% by eFI (scores > 0.21). When deriving the eFI, 85% of EHRs were perceived as easy or neutral difficulty to extract the required data from. Complexities in data extraction were present in EHRs of patients with multiple health problems and/or where the majority of data items were located other than on the patient's summary problem list. DISCUSSION: This study demonstrated that it is entirely feasible to extract an eFI from routinely collected Australian primary care data. We have outlined a process for extracting an eFI from EHRs without needing to modify existing infrastructure. Results from this study can inform the development of automated eFIs, including which data items to best access data from.

Socioeconomic inequalities in frailty among older adults in six low- and middle-income countries: Results from the WHO Study on global AGEing and adult health (SAGE).

OBJECTIVES: The aim of this study was to investigate socioeconomic inequalities in frailty among older adults in six low- and middle-income countries (LMICs), and to examine to what extent chronic diseases account for these inequalities. STUDY DESIGN: Data were used from the Study on global AGEing and adult health (SAGE) wave 1 (2007-2010). Nationally representative samples of adults aged 50+ years from China, Ghana, India, Mexico, the Russian Federation and South Africa were analyzed (n = 31,174). MAIN OUTCOME MEASURES: Educational level and wealth were used as socioeconomic indicators. Frailty was assessed with modified criteria for the frailty phenotype. Self-reported disease diagnoses were used. A relative index of inequality (RII) was calculated to compare socioeconomic inequalities in frailty between countries. RESULTS: People in lower socioeconomic positions had higher prevalence rates of frailty. The largest inequalities in frailty were found in Mexico (RII 3.7, 95% CI 2.1-6.4), and the smallest inequalities in Ghana (RII 1.1, 95% CI 0.7-1.8). Mediation analyses revealed that the chronic diseases considered in this study do not explain the higher prevalence of frailty seen in lower socioeconomic groups. CONCLUSIONS: Substantial socioeconomic inequalities in frailty were observed in LMICs, but additional research is needed to find explanations for these. Given that the population of older adults in many LMICs is expanding at a greater rate than in many high-income countries, our results indicate an urgent public health need to address frailty in these countries.

Identification of older adults with frailty in the Emergency Department using a frailty index: results from a multinational study.

Objective: frailty is a central concept in geriatric medicine, yet its utility in the Emergency Department (ED) is not well understood nor well utilised. Our objectives were to develop an ED frailty index (FI-ED), using the Rockwood cumulative deficits model and to evaluate its association with adverse outcomes. Method: this was a large multinational prospective cohort study using data from the interRAI Multinational Emergency Department Study. The FI-ED was developed from the Canadian cohort and validated in the multinational cohort. All patients aged ≥75 years presenting to an ED were included. The FI-ED was created using 24 variables included in the interRAI ED-Contact Assessment tool. Results: there were 2,153 participants in the Canadian cohort and 1,750 in the multinational cohort. The distribution of the FI-ED was similar to previous frailty indices. The mean FI-ED was 0.26 (Canadian cohort) and 0.32 (multinational cohort) and the 99th percentile was 0.71 and 0.81, respectively. In the Canadian cohort, a 0.1 unit increase in the FI-ED was significantly associated with admission (odds ratio (OR) = 1.43 [95% CI: 1.34-1.52]); death at 28 days (OR = 1.55 [1.38-1.73]); prolonged hospital stay (OR = 1.37 [1.22-1.54]); discharge to long-term care (OR = 1.30 [1.16-1.47]); and need for Comprehensive geriatric Assessment (OR = 1.51 [1.41-1.60]). The multinational cohort showed similar associations. Conclusion: the FI-ED conformed to characteristics previously reported. A FI, developed and validated from a brief geriatric assessment tool could be used to identify ED patients at higher risk of adverse events.

Frailty and usage of health care systems: Results from the South Australian Monitoring and Surveillance System (SAMSS).

OBJECTIVES: Little is known about frailty and its impact on health-care systems. Using large-scale population health surveillance data, this study determined the prevalence of frailty, its associated factors, and the impact it places on health care services. STUDY DESIGN: A cross-sectional snapshot of the 2013-2015 South Australian Monitoring and Surveillance System (SAMSS) database was used, focusing on individuals aged ≥65years. Frailty was assessed by the Frailty Index (FI), and classified as robust (scores≤0.1), pre-frail (>0.1 to ≤0.25), and frail (>0.25). RESULTS: 7207 people (53.7% female) were included; mean (SD) age was 74.8 (7.17) years. The mean (SD) FI score was 0.23 (0.11), with a 99% upper limit of 0.53. Over a third (36.3% (95% CI 34.8-37.9)) were classified as frail and over half (53.6% (95% CI 52.0-55.1)) as pre-frail. Frailty was less common in rural areas, and was associated with age, lower education level, and higher socioeconomic disadvantage. After adjustment for confounders, multivariable analyses showed a gradient effect by frailty classification with regard to both hospital- and non-hospital-based services. Frail older adults were more likely to present to hospital Emergency Departments (EDs) than their pre-frail or robust counterparts, yet visited the GP at the same rate as older adults with pre-frailty. CONCLUSION: Frail older adults were higher users of health care services, with the exception of GPs. Knowledge of the health service usage patterns of frail older adults can be used to direct public health policy and plan future GP provision.

Screening for malnutrition in hospitalised older people: Comparison of the Mini Nutritional Assessment with its short-form versions.

OBJECTIVE: To determine how well the Mini Nutritional Assessment (MNA) Short Form (MNA-SF) performed as a nutritional screening tool when calf circumference replaced body mass index (BMI) as the included anthropometric measurement. METHODS: A total of 100 patients ≥70 years were recruited from a Geriatric Evaluation and Management Unit. RESULTS: Mean age of patients was 85.2 (6.1) years. By the full MNA, 40% of patients were malnourished. The MNA correlated highly with both of its short-form versions (r = 0.87 and r = 0.90 for the BMI and calf circumference versions, respectively). Both MNA-SF versions also showed high accuracy in identifying malnutrition (auROC values >0.89). CONCLUSIONS: The MNA-SF is a rapid and accurate way to screen for malnutrition in hospitalised older adults. Substitution of BMI measurement with the time-efficient calf circumference measurement maintained MNA-SF accuracy. It is recommended that calf circumference measurement be used for nutritional screening by MNA-SF in a hospital setting.

Frailty prevalence and associated factors in the Mexican health and aging study: A comparison of the frailty index and the phenotype.

BACKGROUND: Frailty is a relatively new phenomenon described mainly in the older population. There are a number of different tools that aim at categorizing an older adult as frail. Two of the main tools for this purpose are the Fried's frailty phenotype (FFP) and the frailty index (FI). The aim of this report is to determine the prevalence of frailty and associated factors using both FFP and the FI. METHODS: Secondary analysis of 1108 individuals aged 60 or older is participating in the third (2012) wave from the Mexican Health and Aging Study (MHAS). The FFP and the FI were constructed and a set of variables from different domains were used to explore associations. Domains included were: socio-demographic, health-related, and psychological factors. Regarding prevalence, concordance was tested with a kappa statistic. To test significant associations when classifying with each of the tools, multiple logistic regression models were fitted. RESULTS: Mean (SD) age was 69.8 (7.6) years, and 54.6% (n=606) were women. The prevalence of frailty with FFP was 24.9% (n=276) while with FI 27.5% (n=305). Kappa statistics for concordance between tools was 0.34 (p<0.001). Age, years in school, number of past days in bed due to health problems, number of times that consulted a physician last year for health problems, having smoked in the past, and life satisfaction were associated with frailty when using any of the tools. CONCLUSIONS: There is a persistent heterogeneity on how frailty is measured that should be addressed in future research.

Translating a health service intervention into a rural setting: lessons learned.

BACKGROUND: Limited research exists on the process of applying knowledge translation (KT) methodology to a rural-based population health intervention. METHODS: This study reports on the implementation and translational stages of a previously described Co-creating KT (Co-KT) framework in the rural town of Port Lincoln, South Australia (population: 14,000). The Co-KT framework involves five steps: (i) collecting local data; (ii) building stakeholder relationships; (iii) designing an evidence-based intervention incorporating local knowledge; (iv) implementation and evaluation of the intervention; and (v) translating the research into policy and practice. Barriers and enablers to the overall Co-KT implementation process were identified. Our intervention focused on musculoskeletal (MSK) conditions. RESULTS: Although the Co-KT framework was valuable in engaging with the community, translating the final intervention into daily clinical practice was prevented by a lack of an accessible policy or financial framework to anchor the appropriate intervention, a lack of continued engagement with stakeholders, access problems to general practitioners (GPs) and Allied Health Professionals; and the paucity of referrals from GPs to Allied Health Professionals. Consequently, while many aspects of the intervention were successful, including the improvement of both function and pain in study participants, the full implementation of the Co-KT framework was not possible. DISCUSSION: This study implemented and evaluated a Co-KT framework for a population with MSK conditions, linking locally generated health care system knowledge with academic input. Further policy, health system changes, and on-the-ground support are needed to overcome the identified implementation challenges in order to create sustainable and effective system change.

Do psychosocial resources modify the effects of frailty on functional decline and mortality?

OBJECTIVE: Little is known about factors that may prevent or delay adverse health outcomes in frail older adults. Previous studies have demonstrated beneficial effects of psychosocial resources on health outcomes in older adults. The aim of this study was to investigate whether psychosocial resources modify the effects of frailty on functional decline and mortality. METHODS: The study sample consisted of 1665 men and women aged 58 and over from two waves of the Longitudinal Aging Study Amsterdam (LASA), a population based study. Frailty and psychosocial resources were assessed at T1 (2005/2006). Frailty was assessed using the criteria of Fried's phenotype. Psychosocial resources included sense of mastery, self-efficacy, instrumental support and emotional support. Functional decline and mortality were assessed at T2 (2008/2009). RESULTS: Results of logistic regression analyses demonstrated that frail older adults had higher odds of both functional decline (OR=2.63, 95% CI=1.61-4.27) and 3-year mortality (OR=3.17, 95% CI=1.95-5.15). After adjustment for covariates, higher levels of mastery and self-efficacy were associated with decreased odds of functional decline, but not mortality. No statistically significant interaction effects between frailty and psychosocial resources were found for either functional decline or mortality. CONCLUSION: This study found no evidence that psychosocial resources buffer against functional decline and mortality in frail older adults.