Prevalence and associations of frailty in residents of Australian aged care facilities: findings from a retrospective cohort study

Prevalence of frailty in Indonesia: a systematic review and meta-analysis

BACKGROUND

Frailty increases the risks of hospitalization, injury, fall, psychological disorders, and death in older adults. Accurate estimation of the prevalence of frailty is crucial for promoting health in these individuals. Therefore, this study was conducted to estimate the prevalence of frailty and prefrailty in older adults residing in Indonesia.

METHODS

In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, six electronic databases were searched (without any language restriction) for relevant articles from inception to February 2023. Studies on the prevalence of frailty and prefrailty in older adults (age ≥ 60 years) residing in Indonesia were included in the analysis. A random-effects model was selected a priori because of the expected high degree of heterogeneity in the study, followed by sensitivity analysis, subgroup analysis, and meta-regression. The protocol of this review study was registered in the PROSPERO database (CRD42022381132).

RESULTS

A total of 79 studies were identified, of which 20 were finally included in the analysis. The pooled prevalence of frailty and prefrailty in older adults in Indonesia was 26.8% and 55.5%, respectively. The pooled prevalence of frailty and prefrailty was 37.9% and 44.8% in nursing homes, 26.3% and 61.4% in hospitals, and 21.1% and 59.6% in community settings, respectively. Furthermore, the pooled prevalence of frailty and prefrailty was 21.6% and 64.3%, 18.7% and 62%, and 27.8% and 59.8% in studies using the Frailty Index-40, FRAIL, and Fried Frailty Phenotype questionnaires, respectively. However, the parameters did not vary significantly across measurement tools or study settings. Publication bias was not detected while the year of data collection influenced the heterogeneity between the studies.

CONCLUSIONS

To the best of our knowledge, this study is the first meta-analysis to report the prevalence of frailty and prefrailty in older adults residing in Indonesia. The gradual increase in the number of older adults with frailty or prefrailty in Indonesia is concerning. Therefore, the government, private sectors, health-care professionals, and the community must jointly design effective strategies and policies to address this problem.

Machine learning approaches for frailty detection, prediction and classification in elderly people: A systematic review

BACKGROUND

Frailty in older people is a syndrome related to aging that is becoming increasingly common and problematic as the average age of the world population increases. Detecting frailty in its early stages or, even better, predicting its appearance can greatly benefit health in later years of life and save the healthcare system from high costs. Machine Learning models fit the need to develop a tool for supporting medical decision-making in detecting or predicting frailty.

METHODS

In this review, we followed the PRISMA methodology to conduct a systematic search of the most relevant Machine Learning models that have been developed so far in the context of frailty. We selected 41 publications and compared them according to their purpose, the type of dataset used, the target variables, and the results they obtained, highlighting their shortcomings and strengths.

RESULTS

The variety of frailty definitions allows many problems to fall into this field, and it is often challenging to compare results due to the differences in target variables. The data types can be divided into gait data, usually collected with sensors, and medical records, often in the context of aging studies. The most common algorithms are well-known models available from every Machine Learning library. Only one study developed a new framework for frailty classification, and only two considered Explainability.

CONCLUSIONS

This review highlights some gaps in the field of Machine Learning applied to the assessment and prediction of frailty, such as the need for a universal quantitative definition. It emphasizes the need for close collaboration between medical professionals and data scientists to unlock the potential of data collected in hospital and clinical settings. As a suggestion for future work, the area of Explainability, which is crucial for models in medicine and health care, was considered in very few studies.

Exercise to Prevent and Manage Frailty and Fragility Fractures

PURPOSE OF REVIEW

This review identifies exercise-based recommendations to prevent and manage frailty and fragility fractures from current clinical practice guidelines. We also critically assess recently published literature in relation to exercise interventions to mitigate frailty and fragility fractures.

RECENT FINDINGS

Most guidelines presented similar recommendations that included the prescription of individually tailored, multicomponent exercise programs, discouragement of prolonged sitting and inactivity, and combining exercise with optimal nutrition. To target frailty, guidelines recommend supervised progressive resistance training (PRT). For osteoporosis and fragility fractures, exercise should include weight-bearing impact activities and PRT to target bone mineral density (BMD) at the hip and spine, and also incorporate balance and mobility training, posture exercises, and functional exercise relevant to activities of daily living to reduce falls risk. Walking as a singular intervention has limited benefits for frailty and fragility fracture prevention and management. Current evidence-based clinical practice guidelines for frailty, osteoporosis, and fracture prevention recommend a multifaceted and targeted approach to optimise muscle mass, strength, power, and functional mobility as well as BMD.

Dysphagia and its association with other health-related risk factors in institutionalized older people: A systematic review

BACKGROUND

Dysphagia is considered a geriatric syndrome that is characterized by inability to or difficulty in safely and effectively forming or moving the food bolus toward the esophagus. This pathology is very common and affects approximately 50% of institutionalized older people. Dysphagia is often accompanied by high nutritional, functional, social, and emotional risks. This relationship implies a higher rate of morbidity, disability, dependence, and mortality in this population. This review is aimed at studying the relationship between dysphagia and different health-related risk factors in institutionalized older people.

METHOD

We conducted a systematic review. The bibliographic search was performed in the Web of Science, Medline, and Scopus databases. Data extraction and methodological quality were evaluated by two independent researchers.

RESULTS

Twenty-nine studies met the inclusion and exclusion criteria. A clear relationship between the development and progression of dysphagia and a high nutritional, cognitive, functional, social, and emotional risk in institutionalized older adults was found.

CONCLUSIONS

There is an important relationship between these health conditions that shows the need for research and new approaches to considerations such as their prevention and treatment as well as the design of protocols and procedures that will help reduce the percentage of morbidity, disability, dependence, and mortality in older people.

Systematic review and meta-analysis of prevalence, trajectories, and clinical outcomes for frailty in COPD

This systematic review synthesised measurement and prevalence of frailty in COPD and associations between frailty and adverse health outcomes. We searched Medline, Embase and Web of Science (1 January 2001-8 September 2021) for observational studies in adults with COPD assessing frailty prevalence, trajectories, or association with health-related outcomes. We performed narrative synthesis and random-effects meta-analyses. We found 53 eligible studies using 11 different frailty measures. Most common were frailty phenotype (n = 32), frailty index (n = 5) and Kihon checklist (n = 4). Prevalence estimates varied by frailty definitions, setting, and age (2.6-80.9%). Frailty was associated with mortality (5/7 studies), COPD exacerbation (7/11), hospitalisation (3/4), airflow obstruction (11/14), dyspnoea (15/16), COPD severity (10/12), poorer quality of life (3/4) and disability (1/1). In conclusion, frailty is a common among people with COPD and associated with increased risk of adverse outcomes. Proactive identification of frailty may aid risk stratification and identify candidates for targeted intervention.

Sex Differences in Frailty Factors and Their Capacity to Identify Frailty in Older Adults Living in Long-Term Nursing Homes

Frailty is a phenomenon that precedes adverse health events in older people. However, there is currently no consensus for how to best measure frailty. Several studies report that women have a higher prevalence of frailty than men, but there is a gap in studies of the high rates of frailty in older people living in long-term nursing homes (LTNHs) stratified by sex. Therefore, we analyzed health parameters related to frailty and measured their capacity to identify frailty stratified by sex in older people living in LTNHs. According to the Fried Frailty Phenotype (FFP), anxiety increased the risk of frailty in women, while for men functionality protected against the risk of frailty. Regarding the Tilburg Frailty Indicator (TFI), functionality had a protective effect in men, while for women worse dynamic balance indicated a higher risk of frailty. The analyzed parameters had a similar capacity for detecting frailty measured by the TFI in both sexes, while the parameters differed in frailty measured by the FFP. Our study suggests that assessment of frailty in older adults should incorporate a broad definition of frailty that includes not only physical parameters but also psycho-affective aspects as measured by instruments such as the TFI.

Development and validation of retrospective electronic frailty index using operational data of aged care homes

Background

Although elderly population is generally frail, it is important to closely monitor their health deterioration to improve the care and support in residential aged care homes (RACs). Currently, the best identification approach is through time-consuming regular geriatric assessments. This study aimed to develop and validate a retrospective electronic frailty index (reFI) to track the health status of people staying at RACs using the daily routine operational data records.

Methods

We have access to patient records from the Royal Freemasons Benevolent Institution RACs (Australia) over the age of 65, spanning 2010 to 2021. The reFI was developed using the cumulative deficit frailty model whose value was calculated as the ratio of number of present frailty deficits to the total possible frailty indicators (32). Frailty categories were defined using population quartiles. 1, 3 and 5-year mortality were used for validation. Survival analysis was performed using Kaplan-Meier estimate. Hazard ratios (HRs) were estimated using Cox regression analyses and the association was assessed using receiver operating characteristic (ROC) curves.

Results

Two thousand five hundred eighty-eight residents were assessed, with an average length of stay of 1.2 ± 2.2 years. The RAC cohort was generally frail with an average reFI of 0.21 ± 0.11. According to the Kaplan-Meier estimate, survival varied significantly across different frailty categories (p < 0.01). The estimated hazard ratios (HRs) were 1.12 (95% CI 1.09–1.15), 1.11 (95% CI 1.07–1.14), and 1.1 (95% CI 1.04–1.17) at 1, 3 and 5 years. The ROC analysis of the reFI for mortality outcome showed an area under the curve (AUC) of ≥0.60 for 1, 3 and 5-year mortality.

Conclusion

A novel reFI was developed using the routine data recorded at RACs. reFI can identify changes in the frailty index over time for elderly people, that could potentially help in creating personalised care plans for addressing their health deterioration.

Using electronic admission data to monitor temporal trends in local medication use: Experience from an Australian tertiary teaching hospital

Background and aims: Medication usage varies according to prescribing behavior, professional recommendations, and the introduction of new drugs. Local surveillance of medication usage may be useful for understanding and comparing prescribing practices by healthcare providers, particularly in countries such as Australia that are in the process of enhancing nationwide data linkage programs. We sought to investigate the utility of electronic hospital admission data to investigate local trends in medication use, to determine similarities and differences with other Australian studies, and to identify areas for targeted interventions.

Methods: We performed a retrospective longitudinal analysis using combined data from a hospital admissions administrative dataset from a large tertiary teaching hospital in Adelaide, South Australia and a hospital administrative database documenting medication usage matched for the same set of patients. All adult admissions over a 12-year period, between 1 January 2007 and 31st December 2018, were included in the study population. Medications were categorized into 21 pre-defined drug classes of interest according to the ATC code list 2021.

Results: Of the 692,522 total admissions, 300,498 (43.4%) had at least one recorded medication. The overall mean number of medications for patients that were medicated increased steadily from a mean (SD) of 5.93 (4.04) in 2007 to 7.21 (4.98) in 2018. Results varied considerably between age groups, with the older groups increasing more rapidly. Increased medication usage was partly due to increased case-complexity with the mean (SD) Charlson comorbidity index increasing from 0.97 (1.66) in 2007-to-2012 to 1.17 (1.72) in 2013-to-2018 for medicated patients. Of the 21 medication classes, 15 increased (p < 0.005), including antithrombotic agents; OR = 1.18 [1.16–1.21], proton pump inhibitors; OR = 1.14 [1.12–1.17], statins; OR = 1.12; [1.09–1.14], and renin-angiotensin system agents; OR = 1.06 [1.04–1.08], whilst 3 decreased (p < 0.005) including anti-inflammatory drugs (OR = 0.55; 99.5% CI = 0.53–0.58), cardiac glycosides (OR = 0.81; 99.5% CI = 0.78–0.86) and opioids (OR = 0.82; 99.5% CI = 0.79–0.83). The mean number of medications for all admissions increased between 2007 and 2011 and then declined until 2018 for each age group, except for the 18-to-35-year-olds.

Conclusion: Increased medication use occurred in most age groups between 2007 and 2011 before declining slightly even after accounting for increased comorbidity burden. The use of electronic hospital admission data can assist with monitoring local medication trends and the effects of initiatives to enhance the quality use of medicines in Australia.

Association between Dysphagia and Frailty in Older Adults: A Systematic Review and Meta-Analysis

Background: Increasing bodies of epidemiological evidence indicate potential associations between dysphagia and the risk of frailty in older adults. We hypothesized that older adults with symptoms of dysphagia might have a higher prevalence of frailty or prefrailty than those without dysphagia. Methods: We systematically searched the PubMed, Embase, and Cochrane Library databases for relevant studies published through 20 April 2022. Cross-sectional and longitudinal studies that examined the associations between dysphagia and the existence of frailty or prefrailty in community-dwelling, facility-dwelling, or hospitalized adults aged 50 years or older were synthesized. The Newcastle–Ottawa Scale was used to evaluate study quality. Results: The meta-analysis comprised 12 cohorts, including 5,503,543 non-frailty participants and 735,303 cases of frailty or prefrailty. Random-effect meta-analysis demonstrated a significant association between dysphagia and the risk of frailty and prefrailty (OR, 3.24; 95% CI, 2.51–4.20). In addition, we observed consistent results across the subgroups and heterogeneity assessments. Conclusions: We propose including dysphagia assessment as a critical factor in the cumulative deficit model for identifying frailty in older adults. Understanding dysphagia and the potential role of nutritional supplements in older adults may lead to improved strategies for preventing, delaying, or mitigating frailty.

How frail is frail? A systematic scoping review and synthesis of high impact studies

AIMS

While the frailty index (FI) is a continuous variable, an FI score of 0.25 has construct and predictive validity to categorise community-dwelling older adults as frail or non-frail. Our study aimed to explore which FI categories (FI scores and labels) were being used in high impact studies of adults across different care settings and why these categories were being chosen by study authors.

METHODS

For this systematic scoping review, Medline, Cochrane and EMBASE databases were searched for studies that measured and categorised an FI. Of 1314 articles screened, 303 met the eligibility criteria (community: N = 205; residential aged care: N = 24; acute care: N = 74). For each setting, the 10 studies with the highest field-weighted citation impact (FWCI) were identified and data, including FI scores and labels and justification provided, were extracted and analysed.

RESULTS

FI scores used to distinguish frail and non-frail participants varied from 0.12 to 0.45 with 0.21 and 0.25 used most frequently. Additional categories such as mildly, moderately and severely frail were defined inconsistently. The rationale for selecting particular FI scores and labels were reported in most studies, but were not always relevant.

CONCLUSIONS

High impact studies vary in the way they categorise the FI and while there is some evidence in the community-dweller literature, FI categories have not been well validated in acute and residential aged care. For the time being, in those settings, the FI should be reported as a continuous variable wherever possible. It is important to continue working towards defining frailty categories as variability in FI categorisation impacts the ability to synthesise results and to translate findings into clinical practice.

The Frailty In Residential Sector over Time (FIRST) study: methods and baseline cohort description

BACKGROUND

The Frailty In Residential Sector over Time (FIRST) Study is a 3-year prospective cohort study investigating the health of residents living in residential aged care services (RACS) in South Australia. The study aims to examine the change in frailty status and associated health outcomes.

METHODS

This interim report presents data from March 2019-October 2020. The study setting is 12 RACS from one organisation across metropolitan and rural South Australia involving 1243 residents. All permanent (i.e. respite or transition care program excluded) residents living in the RACS for at least 8 weeks were invited to participate. Residents who were deemed to be medically unstable (e.g. experiencing delirium), have less than 3 months to live, or not fluent in English were excluded. Data collected included frailty status, medical diagnoses, medicines, pain, nutrition, sarcopenia, falls, dementia, anxiety and depression, sleep quality, quality of life, satisfaction with care, activities of daily living, and life space use at baseline and 12-months. Data Linkage will occur over the 3 years from baseline.

RESULTS

A total of 561 permanent residents (mean age 87.69 ± 7.25) were included. The majority of residents were female (n = 411, 73.3%) with 95.3% (n = 527) being classified as either frail (n = 377, 68.2%) or most-frail (n = 150, 27.1%) according to the Frailty Index (FI). Most residents were severely impaired in their basic activities of daily living (n = 554, 98.8%), and were at-risk of malnutrition (n = 305, 55.0%) and at-risk of sarcopenia (n = 492, 89.5%). Most residents did not experience pain (n = 475, 85.4%), had normal daytime sleepiness (n = 385, 69.7%), and low anxiety and depression scores (n = 327, 58.9%).

CONCLUSION

This study provides valuable information on the health and frailty levels of residents living in RACS in South Australia. The results will assist in developing interventions that can help to improve the health and wellbeing of residents in aged care services.

TRIAL REGISTRATION

Prospectively registered with the Australian New Zealand Clinical Trials Registry ( ACTRN12619000500156 ).

The application of artificial intelligence (AI) techniques to identify frailty within a residential aged care administrative data set

INTRODUCTION

Research has shown that frailty, a geriatric syndrome associated with an increased risk of negative outcomes for older people, is highly prevalent among residents of residential aged care facilities (also called long term care facilities or nursing homes). However, progress on effective identification of frailty within residential care remains at an early stage, necessitating the development of new methods for accurate and efficient screening.

OBJECTIVES

We aimed to determine the effectiveness of artificial intelligence (AI) algorithms in accurately identifying frailty among residents aged 75 years and over in comparison with a calculated electronic Frailty Index (eFI) based on a routinely-collected residential aged care administrative data set drawn from 10 residential care facilities located in Queensland, Australia. A secondary objective included the identification of best-performing candidate algorithms.

METHODS

We designed a frailty prediction system based on the eFI identification of frailty, allocating 84.5 % and 15.5 % of the data to training and test data sets respectively. We compared the performance of 18 specific scenarios to predict frailty against eFI based on unique combinations of three ML algorithms (support vector machines [SVM], decision trees [DT] and K-nearest neighbours [KNN]) and six cases (6, 10, 11, 14, 39 and 70 input variables). We calculated accuracy, percentage positive and negative agreement, sensitivity, specificity, Cohen's kappa and Prevalence- and Bias- Adjusted Kappa (PABAK), table frequencies and positive and negative predictive values.

RESULTS

Of 592 eligible resident records, 500 were allocated to the training set and 92 to the test set. Three scenarios (10, 11 and 70 input variables), all based on SVM algorithm, returned overall accuracy above 75 %.

CONCLUSIONS

There is some potential for AI techniques to contribute towards better frailty identification within residential care. However, potential benefits will need to be weighed against administrative burden, data quality concerns and presence of potential bias.