Self-reported frailty is associated with low calcaneal bone mineral density in a multiracial population of community-dwelling elderly

Frailty phenotype as mediator between systemic inflammation and osteoporosis and fracture risks: A prospective study

BACKGROUND

Systemic inflammation and frailty have been implicated in osteoporosis (OP) and fracture risks; however, existing evidence remains limited and inconclusive. This study aimed to assess the associations of systemic inflammation and frailty phenotype with incident OP and fracture and to evaluate the mediating role of frailty phenotype.

METHODS

The present study analysed data from the UK Biobank, a comprehensive and representative dataset encompassing over 500 000 individuals from the general population. Baseline peripheral blood cell counts were employed to calculate the systemic inflammation markers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII). Frailty phenotype was assessed using five criteria, defined as frail (≥3 items met), pre-frail (1-2 items met) and non-frail (0 items met). OP and fracture events were confirmed through participants' health-related records. Multivariable linear and Cox regression models were utilized, along with mediation analysis.

RESULTS

Increased systemic inflammation was associated with increased risks of OP and fracture. The corresponding hazard ratios and 95% confidence intervals (CIs) for OP risk per standard deviation increase in the log-transformed NLR, PLR and SII were 1.113 (1.093-1.132), 1.098 (1.079-1.118) and 1.092 (1.073-1.111), and for fracture risk, they were 1.066 (1.051-1.082), 1.059 (1.044-1.075) and 1.073 (1.058-1.089), respectively. Compared with the non-frail individuals, the pre-frail and frail ones showed an elevated OP risk by 21.2% (95% CI: 16.5-26.2%) and 111.0% (95% CI: 98.1-124.8%), respectively, and an elevated fracture risk by 6.1% (95% CI: 2.8-9.5%) and 38.2% (95% CI: 30.7-46.2%), respectively. The systemic inflammation level demonstrated a positive association with frailty, with β (95% CI) of 0.034 (0.031-0.037), 0.026 (0.023-0.029) and 0.008 (0.005-0.011) in response to per standard deviation increment in log-transformed SII, NLR and PLR, respectively. The frailty phenotype mediated the association between systemic inflammation and OP/fracture risk. Subgroup and sensitivity analyses confirmed the robustness of these findings.

CONCLUSIONS

Systemic inflammation and frailty phenotype are independently linked to increased risks of OP and fracture. The frailty phenotype partially mediates the association between systemic inflammation and osteoporotic traits. These results highlight the significance of interventions targeting systemic inflammation and frailty in OP and fracture prevention and management.

Exploring causality between bone mineral density and frailty: A bidirectional Mendelian randomization study

OBJECTIVE

The bidirectional correlation between low bone mineral density (BMD) and frailty, despite its extensive documentation, still lacks a conclusive understanding. The objective of this Mendelian randomization (MR) study is to investigate the bidirectional causal relationship between BMD and frailty.

METHODS

We utilized summary statistics data for BMD at different skeletal sites-including heel BMD (e-BMD, N = 40,613), forearm BMD (FA-BMD, N = 8,143), femoral neck BMD (FN-BMD, N = 32,735), and lumbar spine BMD (LS-BMD, N = 28,489), alongside frailty index (FI, N = 175,226) data in participants of European ancestry. MR analysis in our study was conducted using well-established analytical methods, including inverse variance weighted (IVW), weighted median (WM), and MR-Egger approaches.

RESULTS

We observed negative causal estimates between genetically predicted e-BMD (IVW β = - 0.020, 95% confidence interval (CI) = - 0.038, - 0.002, P = 0.029) and FA-BMD (IVW β = -0.035, 95% CI = -0.066, -0.004, P = 0.028) with FI. However, the results did not reach statistical significance after applying the Bonferroni correction, with a significance threshold set at P < 0.0125 (0.05/4). There was no causal effect of FN-BMD (IVW β = - 0.024, 95% CI = -0.052, 0.004, P = 0.088) and LS-BMD (IVW β = - 0.005, 95% CI = -0.034, 0.024, P = 0.749) on FI. In the reverse Mendelian randomization (MR) analysis, we observed no causal effect of FI on BMD at various skeletal sites.

CONCLUSION

Our study provides support for the hypothesis that low BMD may be a potential causal risk factor for frailty, but further research is needed to confirm this relationship. However, our findings did not confirm reverse causality.

SLICC-Frailty Index and Its Association with Low Bone Mineral Density and Vertebral Fractures in Women with Systemic Lupus Erythematosus

The Systemic Lupus International Clinics (SLICC)-Frailty Index (FI) is associated with adverse outcomes in systemic lupus erythematosus (SLE). However, to our knowledge, its association with bone mineral density (BMD) and vertebral fractures (VF), has not been investigated using a standardized methods. Our aim was to evaluate the relationship between frailty assessed by SLICC-FI, and BMD and VF in Mestizo women with SLE. Adult women were included in this cross-sectional study. Information concerning the risk factors for VF and BMD in the lumbar spine and total hip was acquired. SLICC-FI was assessed at baseline. A semi-quantitative method was utilized to evaluate the prevalence of VF on lateral thoracolumbar radiographs. Univariate and multivariate regression analyses were performed adjusting for age, body mass index (BMI), SLE duration, cumulative glucocorticoid dose, bisphosphonate use, and BMD measurements. We included 202 women with SLE (mean age [SD] = 43.3 [13.6] years). The mean (SD) SLICC-FI value was 0.14 (0.09). Eleven (5.4%) patients were categorized as robust, 62 (30.7%) as relatively less fit, 84 (41.6%) as least fit, and 45 (22.3%) as frail. Both univariate and multivariate models showed associations between frailty (defined as SLICC-FI > 0.21) and prevalent VF in the entire population (OR 5.76, 95% CI 2.53-13.12; P < 0.001) and in the premenopausal group (OR 4.29, 95% CI; P = 0.047). We also found an association between the SLICC-FI and low BMD. In conclusion, frailty assessed by SLICC-FI might be associated with VF and low BMD in mestizo females with SLE.

Cardiometabolic Disorders Are Important Correlates of Vulnerability in Hospitalized Older Adults

With an increasingly aging population worldwide, the concept of multimorbidity has attracted growing interest over recent years, especially in terms of frailty, which leads to progressive multisystem decline and increased adverse clinical outcomes. The relative contribution of multiple disorders to overall frailty index in older populations has not been established so far. This study aimed to assess the association between the vulnerable elders survey-13 (VES-13) score, which is acknowledged to be one of the most widely used measures of frailty, and the most common accompanying diseases amongst hospitalized adults aged 60 years old and more. A total of 2860 participants with an average age of 83 years were included in this study. Multiple logistic regression with adjustment for age and nutritional status was used to assess the independent impact of every particular disease on vulnerability. Diabetes mellitus type 2, coronary artery disease, atrial fibrillation, heart failure, chronic kidney disease, osteoarthritis, fractures, eyes disorders, depression, dementia, pressure ulcers, and urinary incontinence were associated with higher scores of VES-13. Hospital admission of older subjects with those conditions should primarily draw attention to the risk of functional decline, especially while qualifying older patients for further treatment in surgery and oncology. At the same time, lipid disorders, gastrointestinal diseases, higher body mass index, and albumins level were related to a lower risk of being vulnerable, which may be attributed to a younger age and better nutritional status of those patients.

Assessing the roles of demographic, social, economic, environmental, health-related, and political factors on risk of osteoporosis diagnosis among older adults

Chronic stress from social/environmental pressures has been proposed to affect bone health through increased inflammation. We demonstrate that inflammation from prolonged stress does not cause changes to bone health through inflammation but instead impacts access to health care, social inequalities, and overall health, which in turn impact bone health.

PURPOSE

The study provides a comprehensive assessment of how determinants of health across demographic, psychological, mobility-related, health, environmental, and economic domains are associated with the diagnosis of osteoporosis and tests three hypotheses: (1) a diverse set of variables across domains will predict osteoporosis, (2) chronic inflammation as a result of stress (represented by high-sensitivity C-reactive protein) will not be associated with osteoporosis, and (3) the model developed will have high accuracy in predicting osteoporosis.

METHODS

Logistic regression and Cox proportional hazards models of osteoporosis diagnosis were estimated using data from 14,792 and 13,169 participants (depending on model) in the 2012-2016 waves of the Health and Retirement Study, including the Biomarker Study, the Contextual Data Resource, and validated measures of childhood socioeconomic status. Predictive accuracy was assessed using k-Nearest Neighbors Discriminant Analysis.

RESULTS

Demographic, environmental, and health-related factors were associated with osteoporosis diagnosis, and predictive accuracy of the models was good. High-sensitivity C-reactive protein was not associated with osteoporosis diagnosis.

CONCLUSION

Social determinants identified indicate access to health care, inequalities in the greater social environment (e.g., access to resources), and overall health (i.e., underlying medical conditions) are key components for developing osteoporosis and indicate underlying health inequities in this sample. There is a need to further address the interplay between primary health care and social determinants of health.

The contribution of musculoskeletal factors to physical frailty: a cross-sectional study

Background

Musculoskeletal conditions and physical frailty have overlapping constructs. We aimed to quantify individual contributions of musculoskeletal factors to frailty.

Methods

Participants included 347 men and 360 women aged ≥60 yr (median ages; 70.8 (66.1–78.6) and 71.0 (65.2–77.5), respectively) from the Geelong Osteoporosis Study. Frailty was defined as ≥3, pre-frail 1–2, and robust 0, of the following; unintentional weight loss, weakness, low physical activity, exhaustion, and slowness. Measures were made of femoral neck BMD, appendicular lean mass index (ALMI, kg/m²) and whole-body fat mass index (FMI, kg/m²) by DXA (Lunar), SOS, BUA and SI at the calcaneus (Lunar Achilles Insight) and handgrip strength by dynamometers. Binary and ordinal logistic regression models and AUROC curves were used to quantify the contribution of musculoskeletal parameters to frailty. Potential confounders included anthropometry, smoking, alcohol, prior fracture, FMI, SES and comorbidities.

Results

Overall, 54(15.6%) men and 62(17.2%) women were frail. In adjusted-binary logistic models, SI, ALMI and HGS were associated with frailty in men (OR = 0.73, 95%CI 0.53–1.01; OR=0.48, 0.34–0.68; and OR = 0.11, 0.06–0.22; respectively). Muscle measures (ALMI and HGS) contributed more to this association than did bone (SI) (AUROCs 0.77, 0.85 vs 0.71, respectively). In women, only HGS was associated with frailty in adjusted models (OR = 0.30 95%CI 0.20–0.45, AUROC = 0.83). In adjusted ordinal models, similar results were observed in men; for women, HGS and ALMI were associated with frailty (ordered OR = 0.30 95%CI 0.20–0.45; OR = 0.56, 0.40–0.80, respectively).

Conclusion

Muscle deficits appeared to contribute more than bone deficits to frailty. This may have implications for identifying potential musculoskeletal targets for preventing or managing the progression of frailty.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04795-4.

The Predictability of Frailty Associated with Musculoskeletal Deficits: A Longitudinal Study

We investigated and quantified the predictability of frailty associated with musculoskeletal parameters. This longitudinal study included 287 men aged ≥ 50 yr at baseline (2001-2006) from the Geelong Osteoporosis Study. Baseline musculoskeletal measures included femoral neck bone mineral density (BMD), appendicular lean mass index (ALMI, kg/m²) and whole-body fat mass index (FMI, kg/m²) and lower-limb strength. Frailty at the 15 yr-follow-up (2016-2019) was defined as ≥ 3 and non-frail as < 3, of the following: unintentional weight loss, weakness, low physical activity, exhaustion, and slowness. Binary regression models and AUROC curves quantified the attributable risk of musculoskeletal factors to frailty and their predictive ability. Potential confounders included anthropometry, smoking, alcohol, FMI, socioeconomic status and comorbidities. Forty-eight (16.7%) men were frail at 15 yr-follow-up. Musculoskeletal models were better predictors of frailty compared to the referent (confounders only) model (AUROC for musculoskeletal factors 0.74 vs 0.67 for the referent model). The model with the highest AUROC (0.74; 95% CI 0.66-0.82) included BMD, ALMI and muscle strength (hip abductors) and was better than the referent model that included only lifestyle factors (p = 0.046). Musculoskeletal parameters improved the predictability model as measured by AUROC for frailty after 15 years. In general, muscle models performed better compared to bone models. Musculoskeletal parameters improved the predictability of frailty of the referent model that included lifestyle factors. Muscle deficits accounted for a greater proportion of the risk for frailty than did bone deficits. Targeting musculoskeletal health could be a possible avenue of intervention in regards to frailty.

The association between a fracture risk tool and frailty: Geelong Osteoporosis Study

BACKGROUND

Frailty is characterised by age-related declines in physical, psychological and social functioning. Features of frailty overlap with risk factors for fragility fractures. The aim of this study was to investigate the association between the fracture risk assessment tool (FRAX®) and frailty.

METHODS

In cross-sectional analysis, frailty status was determined for participants aged 60-90 yr at 15-year follow-up of the Geelong Osteoporosis Study, using a modified Fried frailty phenotype. Using the FRAX on-line tool, scores for hip and major osteoporotic fracture (MOF) were calculated with and without bone mineral density (BMD). Using the area under Receiver Operating Characteristic (AUROC) curves, and FRAX scores calculated at the baseline visit for these participants, we investigated the association of FRAX and frailty 15 years later.

RESULTS

Forty-seven of 303 women (15.5%) and 41 of 282 men (14.5%) were frail at the 15-year visit. There was a gradient of increasing median FRAX scores from robust to frail. For example, for women, median MOF-FRAX without BMD increased from 5.9 for the robust to 7.5 for the pre-frail and 14.0 for the frail (p < 0.001). In secondary analyses, an association was observed between FRAX and frailty over 15 years, with the highest AUROC for women being 0.72 for MOF-FRAX with BMD, and for men, 0.76 hip-FRAX without BMD.

CONCLUSION

An association was observed between FRAX and frailty where frail men and women had higher FRAX-scores compared to the other groups. Preliminary data suggest that FRAX, with or without BMD, may be useful in enhancing the information on frailty. Further research using larger datasets will be required to explore this.

Frailty and the Prediction of Negative Health Outcomes: A Meta-Analysis

INTRODUCTION

Frailty is one of the most important concerns regarding our aging population. Evidence grows that the syndrome is linked to several important health outcomes. A general overview of frailty concepts and a comprehensive meta-analysis of their relation with negative health outcomes still lacks in literature, making it difficult for health care professionals and researchers to recognize frailty and the related health risks on the one hand and on the other hand to appropriately follow up the frailty process and take substantiated action. Therefore, this study aims to give an overview of the predictive value of the main frailty concepts for negative health outcomes in community-dwelling older adults.

METHODS

This review and meta-analysis assembles prospective studies regarding the relation between frailty and any potential health outcome. Frailty instruments were subdivided into frailty concepts, so as to make comprehensive comparisons. Odds ratios (ORs), hazard ratios (HRs), and relative risk (RR) scores were extracted from the studies, and meta-analyses were conducted in OpenMeta Analyst software.

RESULTS

In total, 31 articles retrieved from PubMed, Web of Knowledge, and PsycInfo provided sufficient information for the systematic review and meta-analysis. Overall, (pre)frailty increased the likelihood for developing negative health outcomes; for example, premature mortality (OR 2.34 [1.77-3.09]; HR/RR 1.83 [1.68-1.98]), hospitalization (OR 1.82 [1.53-2.15]; HR/RR 1.18 [1.10-1.28]), or the development of disabilities in basic activities of daily living (OR 2.05 [1.73-2.44]); HR/RR 1.62 [1.50-1.76]).

CONCLUSION

Overall, frailty increases the risk for developing any discussed negative health outcome, with a 1.8- to 2.3-fold risk for mortality; a 1.6- to 2.0-fold risk for loss of activities of daily living; 1.2- to 1.8-fold risk for hospitalization; 1.5- to 2.6-fold risk for physical limitation; and a 1.2- to 2.8-fold risk for falls and fractures. The analyses presented in this study can be used as a guideline for the prediction of negative outcomes according to the frailty concept used, as well as to estimate the time frame within which these events can be expected to occur.

Frailty and bone health in European men

Background

frailty is associated with an increased risk of fragility fractures. Less is known, however, about the association between frailty and bone health.

Methods

men aged 40-79 years were recruited from population registers in eight European centres for participation in the European Male Aging Study. Subjects completed a comprehensive assessment which included quantitative ultrasound (QUS) scan of the heel (Hologic-SAHARA) and in two centres, dual-energy bone densitometry (dual-energy x-ray absorptiometry, DXA). Frailty was defined based on an adaptation of Fried's phenotype criteria and a frailty index (FI) was constructed. The association between frailty and the QUS and DXA parameters was determined using linear regression, with adjustments for age, body mass index and centre.

Results

in total, 3,231 subjects contributed data to the analysis. Using the Fried categorisation of frailty, pre-frail and frail men had significantly lower speed of sound (SOS), broadband ultrasound attenuation (BUA) and quantitative ultrasound index (QUI) compared to robust men (P< 0.05). Similar results were seen using the FI after categorisation into 'high', 'medium' and 'low' levels of frailty. Using the Fried categorisation, frail men had lower femoral neck bone mineral density (BMD) compared to robust men (P < 0.05), but not lower lumbar spine BMD. Using the FI categorisation, a 'high' level of frailty (FI > 0.35) was associated with lower lumbar spine BMD (P < 0.05) when compared to those with low (FI < 0.2), but not lower femoral neck BMD. When analysed as a continuous variable, higher FI was linked with lower SOS, BUA and QUI (P < 0.05).

Conclusions

optimisation of bone health as well as prevention of falls should be considered as strategies to reduce fractures in frail older people.

Frailty as a predictor of fractures among community-dwelling older people: A systematic review and meta-analysis

PURPOSE

To identify prospective studies examining associations between frailty and fractures and to combine the risk measures to synthesize pooled evidence on frailty as a predictor of fractures among community-dwelling older people.

METHODS

A systematic literature search was conducted using five databases: Embase, MEDLINE, CINAHL Plus, PsycINFO, and the Cochrane Library for prospective studies on associations between frailty and fracture risk published from 2000 to August 2015 without language restriction. Odds ratios (OR) and hazard ratios (HR) extracted from the studies or calculated from available data were combined to synthesize pooled effect measures using random-effects or fixed-effects models. Heterogeneity, methodological quality, and publication bias were assessed. Meta-regression analyses were performed to explore the cause of high heterogeneity.

RESULTS

Of 1305 studies identified, six studies involving 96,564 older people in the community were included in this review. Frailty and prefrailty were significantly associated with future fractures among five studies with OR (pooled OR=1.70, 95% confidence interval (95% CI)=1.34-2.15, p<0.0001; pooled OR=1.31, 95% CI=1.18-1.46, p<0.00001, respectively) and four studies with HR (pooled HR=1.57, 95% CI=1.31-1.89, p<0.00001; pooled HR=1.30, 95% CI=1.12-1.51, p=0.0006, respectively). High heterogeneity was observed among five studies with OR of frailty (I(2)=66%). The studies from the United States were found to have a higher fracture risk than from those from other countries in a meta-regression model (regression coefficient=0.39, p=0.04). No evidence of publication bias was identified.

CONCLUSIONS

This systematic review and meta-analysis showed evidence that frailty and prefrailty are significant predictors of fractures among community-dwelling older people. Treating frailty may potentially lead to lowering fracture risks.

More than osteoporosis: age-specific issues in bone health

PURPOSE OF REVIEW

The interaction between fall and fracture risk factors is an area of increasing clinical relevance, but little information is known about the age-specific issues in bone health unique to HIV-infected adults. The present review will focus on what is known about falls and fall risk factors among HIV-infected adults, and then review the association between decreased muscle, increased adiposity, and frailty with both low bone mineral density (BMD) and falls.

RECENT FINDINGS

The rate of falls among middle-aged HIV-infected adults is similar to that of HIV-uninfected adults 65 years and older. Many of the clinical factors that contribute to low BMD overlap with risk factors for falls, resulting in a high risk of a serious fall among older adults with the greatest risk for a fracture. Low muscle mass, increased adiposity and metabolic syndrome, physical function impairment and frailty, common among older HIV-infected adults, contribute to an increased risk for low BMD and falls, and subsequently, may increase the risk of fracture among HIV-infected older adults.

SUMMARY

Interventions with dual benefit on reducing fall risk and improving BMD are likely to have the greatest impact on fracture prevention in the older, HIV-infected adult.

Frailty and osteoporosis in older women--a prospective study

Despite sharing common risk factors and biological pathways, the relationship between frailty and osteoporosis (OP) is not clear. This prospective study has shown that frailty defined by the Vulnerable Elders Survey can predict a decrease in bone mineral density after 1 year. Thus, frail older women should be assessed for osteoporosis.

INTRODUCTION

Frailty and OP share common risk factors such as age, sarcopenia, lack of physical activity, low body weight, and smoking. Despite shared risk factors and biological pathways, the relationship between frailty and OP is not clear. The purpose of our prospective study was to examine this relationship in a community sample of older women.

METHODS

A sample of 235 community-dwelling women was assessed for demographic, medical, frailty and OP status at baseline, and after at least 1 year. Frailty was assessed using the Cardiovascular Health study (CHS) frailty phenotype and using the Vulnerable Elders Survey (VES-13). OP was measured using dual photon absorptiometry bone mineral density (BMD). Descriptive statistics and regression models were used.

RESULTS

At baseline, 235 women with a mean age of 77.6 (SD = 5.4), body mass index (BMI) of 28.3 (SD = 5.2) kg/m(2), and BMD of 0.7 (SD = 0.2) g/cm(2)were assessed. No correlation was found between BMD and the CHS (BMD spine, r = 0.009, p = 0.889; BMD hips, r = 0.050, p = 0.473) or the VES-13 (BMD spine, r = 0.034, p = 0.605; BMD hips, r = -0.042, p = 0.537) frailty scales. One hundred fifty-two (63.9 %) women were assessed after 1 year. In a regression model, women who were frail at baseline (VES-13) were found to have a statistically significantly lower hip and spine BMD at follow-up (controlling for BMI) than women who were non-frail at baseline (p = 0.0393, hip; p = 0.0069, spine).

CONCLUSIONS

Frailty status as defined by the VES-13 predicts a decrease in BMD after 1 year.

Measures of frailty in population-based studies: an overview

Background

Although research productivity in the field of frailty has risen exponentially in recent years, there remains a lack of consensus regarding the measurement of this syndrome. This overview offers three services: first, we provide a comprehensive catalogue of current frailty measures; second, we evaluate their reliability and validity; third, we report on their popularity of use.

Methods

In order to identify relevant publications, we searched MEDLINE (from its inception in 1948 to May 2011); scrutinized the reference sections of the retrieved articles; and consulted our own files. An indicator of the frequency of use of each frailty instrument was based on the number of times it had been utilized by investigators other than the originators.

Results

Of the initially retrieved 2,166 papers, 27 original articles described separate frailty scales. The number (range: 1 to 38) and type of items (range of domains: physical functioning, disability, disease, sensory impairment, cognition, nutrition, mood, and social support) included in the frailty instruments varied widely. Reliability and validity had been examined in only 26% (7/27) of the instruments. The predictive validity of these scales for mortality varied: for instance, hazard ratios/odds ratios (95% confidence interval) for mortality risk for frail relative to non-frail people ranged from 1.21 (0.78; 1.87) to 6.03 (3.00; 12.08) for the Phenotype of Frailty and 1.57 (1.41; 1.74) to 10.53 (7.06; 15.70) for the Frailty Index. Among the 150 papers which we found to have used at least one of the 27 frailty instruments, 69% (n = 104) reported on the Phenotype of Frailty, 12% (n = 18) on the Frailty Index, and 19% (n = 28) on one of the remaining 25 instruments.

Conclusions

Although there are numerous frailty scales currently in use, reliability and validity have rarely been examined. The most evaluated and frequently used measure is the Phenotype of Frailty.

The frailty syndrome: a comprehensive review

The frailty syndrome is defined as unintentional weight and muscle loss, exhaustion, and declines in grip strength, gait speed, and activity. Evidence with respect to the clinical definition, epidemiology, mechanisms, interactions, assessment, prevention, and treatment of frailty in the older adult is reviewed.

The impact of frailty in the elderly on the outcome of surgery in the aged

As the population continues to age, we will continue to encounter issues involving aging and the elderly. Despite these issues, knowledge is expanding and evolving with new solutions to ongoing problems. Mechanistically, frailty at its root is a symptom of growing old, with cascades and circuitous feedback between organ systems at all levels. Clinically, frailty is as equally dynamic and its multifactorial nature represents a unique challenge to the surgical community and warrants the integration of geriatric assessment into clinical practice. Integration within clinical practice includes using an interdisciplinary approach, where surgeons work with anesthesiologists, geriatricians, nursing, rehabilitation, nutritionists, and other support staff to provide holistic assessment, efficient delivery, and higher quality of care. This in hand, recognition of frailty can occur in a timely fashion to initiate treatment, decreasing the risk of morbidity and mortality for improved surgical outcomes.