The bidirectional relationship between chronic joint pain and frailty: data from the Investigating Musculoskeletal Health and Wellbeing cohort

Modifiable factors associated with frailty in older Australians in retirement living: A partial proportional odds model

OBJECTIVE

Frailty in older adults is a vulnerable state, often leading to a reduction in function and quality of life. This study sought to identify modifiable factors associated with frailty in Australian retirement village residents.

METHODS

A cross-sectional survey was undertaken with individuals 65 years or older living in 25 retirement villages to collect demographic, health and lifestyle information and screen for frailty (modified Reported Edmonton Frail Scale) and loneliness (UCLA 3-item Loneliness Scale). Partial proportional odds modelling was utilised to determine modifiable resident characteristics associated with frailty, accounting for age and gender.

RESULTS

Of 2240 residents, 1230 completed the survey (55% response rate) with 1081 eligible for analysis. Respondent frailty levels were as follows: Not Frail = 67% (n = 720), Prefrail = 14% (n = 157), Mildly Frail = 11% (n = 123), Moderately-Severely Frail = 7% (n = 81). For individuals 85-89 years old, age was significantly associated with increased odds of frailty (OR = 3.40; 95% CI: 1.62-7.09; p = .001). After adjusting for age and gender, the odds of higher frailty were greater for individuals experiencing (a) pain, which interfered with usual activities (interferes sometimes OR = 3.17; 95% CI: 2.42-4.15; p ≤ .001; interferes all of the time OR = 10.18; 95% CI: 5.42-19.14; p ≤ .001), or (b) feelings of loneliness (OR = 2.55; 95% CI: 1.80-3.62; p ≤ .001). For Not Frail or Prefrail persons, a recent fall incident was associated with enhanced odds of frailty (OR = 2.60; 95% CI: 1.69-3.98; p ≤ .001).

CONCLUSIONS

This cohort of older adults living in Australian retirement villages had greater odds of frailty if experiencing pain, loneliness or falls. Addressing these risk factors could reduce or delay progression to frailty and optimise positive ageing in this population.

Predictive model to identify multiple synergistic effects of geriatric syndromes on quality of life in older adults: a hospital-based pilot study

BACKGROUND

Quality of life (QOL) has been reported to be associated with sociodemographic characteristics and geriatric syndromes in older adults, but the impact of interactions among multiple geriatric syndromes on QOL remains unexplored. We aimed to apply a machine learning method to evaluate the effects of interactions among multiple geriatric syndromes on QOL in older adults.

METHODS

We recruited adults aged ≥ 65 years admitted to a tertiary medical center from June 2018 to September 2018. The main outcome was the three-level five-dimensional Euro-Quality of Life tool (EQ-5D-3 L) utility value. The random forest algorithm was used to identify and rank the strongest predictors of geriatric syndromes. The relation between predictors and outcomes was visualized with accumulated local effects plots and interaction effects. Model performance was evaluated by 5-fold cross-validation with metrics of R-square, the mean square error of estimation and the mean absolute error of estimation.

RESULTS

The study included 160 older adults with a mean age of 79 years. The top ten features that significantly influenced the utility prediction were activities of daily living (ADL), frailty, pain, the number of medications used, age, depression, the Charlson Comorbidity Index (CCI), body mass index (BMI), peptic ulcer, and emotional loneliness. The two-way interactions between ADL, frailty, and pain significantly interacted with other predictors.

CONCLUSION

ADL, frailty, and pain are important factors to be considered when assessing QOL in older adults. It is important for clinicians to consider them together in clinical decision-making.

Association of chronic pain with frailty and pre-frailty in older adults: A systematic review and meta-analysis

PURPOSE

Frailty has been demonstrated to correlate with chronic pain (CP). This study aimed to estimate the risk of frailty/pre-frailty and evaluate the potential bidirectional relationship between frailty/pre-frailty and CP.

METHODS

A systematic search was conducted across ten databases, covering literature from their inception through November 23, 2024. Two independent reviewers screened relevant studies, assessed study quality, and extracted data. All analyses were performed using R software, version 4.3.1.

RESULTS

A total of 25,904 participants aged ≥ 60 years were included in 33 studies. CP significantly increased the risk of frailty (OR = 1.91, 95 % CI: 1.47-2.47; I2 = 82 %, p < 0.01), whereas no significant association was found between frailty/pre-frailty and CP risk (OR = 1.52, 95 % CI: 0.66-3.50; I2 = 98 %, p < 0.01). Eleven studies were classified as high quality, and the remainder as moderate quality.

CONCLUSIONS

No evidence supports a bidirectional relationship between frailty/pre-frailty and CP. Nonetheless, addressing and managing CP in older adults may mitigate the risk of frailty and promote healthy aging.

Longitudinal association between frailty and pain in three prospective cohorts of older population

BACKGROUND AND OBJECTIVES

As the global population ages, frailty and pain have become two significant health issues that impact the quality of life in older adults. Previous studies have not thoroughly explored the relationship between them. This study aims to investigate the longitudinal association between frailty and pain using data from prospective cohorts in China (CHARLS), the United Kingdom (ELSA), and the United States (HRS).

METHODS

This study utilized data from three prospective cohort studies: the China Health and Retirement Longitudinal Study (CHARLS), the English Longitudinal Study of Ageing (ELSA), and the Health and Retirement Study (HRS). Frailty status was assessed using the Rockwood frailty index and categorized into robust, pre-frail, and frail. Pain was evaluated by self-reports. Pain degrees were categorized into mild, moderate and severe. Pain areas were grouped into four main areas: head and neck, trunk, limbs, oral. Generalized linear mixed-effects models were employed to analyze the longitudinal relationship between frailty and pain while adjusting for covariates, including gender, age, marital status, education level, sleep quality, smoking, drinking, hypertension, and diabetes.

RESULTS

According to the inclusion and exclusion criteria, 10,624 participants from CHARLS (47% female, mean age: 60.76 years), 4945 participants from ELSA (52.2% female, mean age: 70.05 years), and 11,439 participants from HRS (55.8% female, mean age: 69.28 years) were included in the subsequent analysis. Compared to robust individuals, those in pre-frail and frail states showed a significantly increased risk of experiencing pain. In all three cohorts, pre-frail individuals had a 3.82-fold increased likelihood of pain compared to robust individuals (OR = 3.82, 95%CI = 3.51-4.15, p-value < 0.001, CHARLS), 4.29-fold (OR = 4.29, 95%CI = 3.74-4.93, p-value < 0.001, ELSA), and 4.17-fold (OR = 4.17, 95%CI = 3.81-4.57 p-value < 0.001, HRS). Frail individuals had a 10.44-fold increased likelihood of pain (OR = 10.44, 95%CI = 9.05-12.04, p-value < 0.001, CHARLS), 10.14-fold (OR = 10.14, 95%CI = 8.05-12.76, p-value < 0.001, ELSA), and 13.27-fold (OR = 13.27, 95%CI = 11.71-15.03, p-value < 0.001, HRS).

CONCLUSION

This study demonstrates that frailty significantly impacts the risk of pain, the degree of pain, and the areas of pain. And this association is consistently observed across older populations in different countries. Future pain management strategies should incorporate frailty assessments to mitigate the adverse effects of pain on the health of older adults.

The effects of frailty on opioid consumption after total knee arthroplasty

PURPOSE

This study evaluated the effects of frailty on postoperative opioid consumption in elderly patients.

METHODS

Patients aged 65 and older scheduled for unilateral primary total knee arthroplasty under spinal anesthesia were included. A blinded anesthesiologist assessed patients using the FRAIL scale during the preoperative visit, classifying them into robust (Group I), pre-frail (Group II), and frail (Group III) categories. The main outcome measure was total opioid consumption over 24 h. Opioid consumption was recorded at 6 (T1), 12 (T2) and 24 (T3) hours postoperatively. Secondary outcomes included visual analog pain scores (VAS) at rest (VAS-R) and during 45° knee flexion (VAS-F), as well as postoperative nausea and vomiting.

RESULTS

Seventy-five patients were included in the study, with seventy-three completing it and two being excluded. Total opioid consumption was significantly higher in Groups II and III compared to Group I (p < 0.001 for both). There were no significant differences in VAS-R scores between groups at T0, T1, T2, and T3 (p = 0.659, p = 0.425, p = 0.994, and p = 0.689, respectively), and no significant differences in VAS-F scores at the same time points (p = 0.580, p = 0.739, p = 0.322, and p = 0.679, respectively).

CONCLUSION

Our study results indicate that frailty, easily assessed preoperatively in elderly surgical patients, is a significant predictor of postoperative opioid consumption.

Immunological Insights into the Causal Link Between Arthritis, Osteoarthritis, and Frailty: An Integrated Analytical Study

Background: Previous observational studies have observed associations between rheumatoid arthritis (RA), knee osteoarthritis (KOA), hip osteoarthritis (HOA), and frailty, but the causal relationships remain unestablished. Objective: This study aimed to evaluate the causal relationships between RA, KOA, HOA, KneeHipOA, and frailty using Mendelian randomization (MR) and bioinformatics analysis. Methods: We performed two-sample MR to test for causality between RA, KOA, HOA, KneeHipOA, and frailty. Subsequently, we combined our results in a meta-analysis and conducted multiple sensitivity analyses (MR-Egger, weighted median, constrained maximum likelihood and model averaging (cML-MA), and Bayesian weighted MR (BWMR)). We further explored the role of circulating immune cells and the effects of RA and OA-related gene expression on frailty. Results: Genetically determined RA, KOA, HOA, and KneeHipOA were correlated with a higher risk of frailty. The results of multivariate MR analyses were consistent with those of two-sample MR. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes analysis indicated that RA and OA-related genes were primarily enriched in various immune responses. Our findings suggested that increases in monocyte cell AC, eosinophil cell AC, and neutrophil cell AC were associated with a higher risk of frailty. Conclusion: This research provides evidence supporting the associations between RA, KOA, HOA, KneeHipOA, and frailty. It also highlights the significant role of circulating immune cells in the development of frailty, indicating the importance of frailty management from an immunological perspective.

The vicious cycle of frailty and pain: a two-sided causal relationship revealed

Background

The decline in physiological functions in the older people is frequently accompanied with pain and frailty, yet the causal connection between frailty and pain remains uncertain. In this study, we utilized a two-sample Mendelian randomization (MR) approach to investigate the potential causal association between frailty and pain.

Methods

Two-sample bidirectional MR was conducted using summary data from genome-wide association studies to examine the potential causal relationship between frailty (defined by the frailty index and frailty phenotype) and pain. Summary genome wide association statistics were extracted from populations of European ancestry. We also investigated the causal relationship between frailty and site-specific pain, including joint pain, limb pain, thoracic spine pain and low back pain. Causal effects were estimated using the inverse variance weighting method. Sensitivity analyses were performed to validate the robustness of the results.

Results

Genetic predisposition to frailty was associated with an increased risk of pain (frailty phenotype odds ratio [OR]: 1.73; P = 3.54 × 10-6, frailty index OR: 1.36; P = 2.43 × 10-4). Meanwhile, individuals with a genetic inclination toward pain had a higher risk of developing frailty. Regarding site-specific pain, genetic prediction of the frailty phenotype increased the occurrence risk of joint pain, limb pain and low back pain. Reverse MR analysis further showed that limb pain and low back pain were associated with an increased risk of frailty occurrence.

Conclusion

This study presented evidence supporting a bidirectional causal relationship between frailty and pain. We highlighted the significance of addressing pain to prevent frailty and recommend the inclusion of pain assessment in the evaluation system for frailty.

Preoperative frailty predicts postoperative pain after total knee arthroplasty in older patients: a prospective observational study

PURPOSE

Frailty is reportedly associated with postoperative adverse outcomes and may increase the risk of post-surgical pain. Our study aimed to explore whether frailty was an independent risk factor for pain after total knee arthroplasty (TKA) in older patients.

METHODS

Included in this prospective observational study were patients aged 65 or older who underwent primary TKA. Frailty of the patients was assessed before surgery using the comprehensive geriatric assessment-frailty index and pain was evaluated before and after surgery using the Numerical Rating Scale.

RESULTS

Of the 164 patients including 125 females with a mean age of 71.4 ± 4.6 years, 51 patients were identified as being frail. Patients with chronic post-surgical pain had a significantly higher frailty index than those without chronic post-surgical pain, which was the same in patients with acute post-surgical pain. After adjusting for other confounding factors, frailty was shown to be an independent risk factor for both acute (OR: 13.23, 95% CI 3.73-46.93, P < 0.001) and chronic post-surgical pain (OR: 4.24, 95% CI 1.29-14.00, P = 0.02). The area under the receiver operating characteristic curve for frailty predicting chronic post-surgical pain was 0.73 (P < 0.001, 95% CI 0.65-0.81).

CONCLUSIONS

Our findings demonstrated that preoperative frailty in older patients was a predictor of acute and chronic post-surgical pain after TKA, suggesting that frailty assessment should become a necessary procedure before operations, especially in older patients.

The Difficulties of Managing Pain in People Living with Frailty: The Potential for Digital Phenotyping

Pain and frailty are closely linked. Chronic pain is a risk factor for frailty, and frailty is a risk factor for pain. People living with frailty also commonly have cognitive impairment, which can make assessment of pain and monitoring of pain management even more difficult. Pain may be sub-optimally treated in people living with frailty, people living with cognitive impairment and those with both these factors. Reasons for sub-optimal treatment in these groups are pharmacological (increased drug side effects, drug-drug interactions, polypharmacy), non-pharmacological (erroneous beliefs about pain, ageism, bidirectional communication challenges), logistical (difficulty in accessing primary care practitioners and unaffordable cost of drugs), and, particularly in cognitive impairment, related to communication difficulties. Thorough assessment and characterisation of pain, related sensations, and their functional, emotional, and behavioural consequences ("phenotyping") may help to enhance the assessment of pain, particularly in people with frailty and cognitive impairment, as this may help to identify who is most likely to respond to certain types of treatment. This paper discusses the potential role of "digital phenotyping" in the assessment and management of pain in people with frailty. Digital phenotyping is concerned with observable characteristics in digital form, such as those obtained from sensing-capable devices, and may provide novel and more informative data than existing clinical approaches regarding how pain manifests and how treatment strategies affect it. The processing of extensive digital and usual data may require powerful algorithms, but processing these data could lead to a better understanding of who is most likely to benefit from specific and targeted treatments.

The association of painful and non-painful morbidities with frailty: a cross sectional analysis of a cohort of community dwelling older people in England

INTRODUCTION

The association between chronic pain and frailty might indicate that pain is an independent driver of frailty but might alternatively be explained by inclusion within frailty identification tools of morbidities that commonly lead to chronic pain. This research examines the extent to which the association of pain with frailty might be attributed to morbidities.

METHODS

A cross-sectional analysis of older people in a UK cohort with or at risk of musculoskeletal problems or frailty (Investigating Musculoskeletal Health and Wellbeing study), used multivariable logistic regression and Z-tests to assess the degrees of associations of pain (McGill Pain Rating Index), and painful and non-painful morbidity counts with frailty (modified FRAIL questionnaire).

RESULTS

Data were from 2,185 participants, 56% female, median age 73 (range 60 to 96) years. 430 (20%) participants were classified as frail. In a fully adjusted standardised model, pain (aOR 2.07 (95%CI 1.83 to 2.33) and 'any' morbidity aOR (1.74 (95%CI 1.54 to 1.97) were both significantly associated with frailty. When morbidity was subclassified as painful or non-painful, painful (aOR 1.48 (95%CI 1.30 to 1.68) and non-painful (aOR1.39 (95%CI 1.24 to 1.56)) morbidities each were associated with frailty, as also was pain (aOR 2.07 (95%CI 1.83 to 2.34, p < 0.001).

CONCLUSIONS

Pain is associated with frailty, over and above any effect of painful and non-painful morbidities. This forms the justification for future research which focuses on pain management in the identification, prevention, and treatment of frailty.

To Be Frail or Not to Be Frail: This Is the Question-A Critical Narrative Review of Frailty

Many factors have contributed to rendering frailty an emerging, relevant, and very popular concept. First, many pandemics that have affected humanity in history, including COVID-19, most recently, have had more severe effects on frail people compared to non-frail ones. Second, the increase in human life expectancy observed in many developed countries, including Italy has led to a rise in the percentage of the older population that is more likely to be frail, which is why frailty is much a more common concern among geriatricians compared to other the various health-care professionals. Third, the stratification of people according to the occurrence and the degree of frailty allows healthcare decision makers to adequately plan for the allocation of available human professional and economic resources. Since frailty is considered to be fully preventable, there are relevant consequences in terms of potential benefits both in terms of the clinical outcome and healthcare costs. Frailty is becoming a popular, pervasive, and almost omnipresent concept in many different contexts, including clinical medicine, physical health, lifestyle behavior, mental health, health policy, and socio-economic planning sciences. The emergence of the new "science of frailty" has been recently acknowledged. However, there is still debate on the exact definition of frailty, the pathogenic mechanisms involved, the most appropriate method to assess frailty, and consequently, who should be considered frail. This narrative review aims to analyze frailty from many different aspects and points of view, with a special focus on the proposed pathogenic mechanisms, the various factors that have been considered in the assessment of frailty, and the emerging role of biomarkers in the early recognition of frailty, particularly on the role of mitochondria. According to the extensive literature on this topic, it is clear that frailty is a very complex syndrome, involving many different domains and affecting multiple physiological systems. Therefore, its management should be directed towards a comprehensive and multifaceted holistic approach and a personalized intervention strategy to slow down its progression or even to completely reverse the course of this condition.