Search

Frailty is a state that is closely associated with adverse health outcomes in the aging process. The frailty index (FI), which measures frailty in terms of cumulative deficits, has been widely used for frailty assessment in elderly people, and its advantage of self-reported information collection makes it applicable to a broader group of elderly people. Our study aims to simplify the Frailty Index Assessment Scale, while maintaining its reliability and accuracy, to easily and quickly assess frailty in elderly people. In this study, participants (age ≥ 65 years) from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which had 13,339, 372 and 1214 participants in 2008, 2011, and 2014, respectively, were used. The 2008 dataset was split into 80% for training and 20% for internal validation, and the data from 2011 to 2014 as external validation. In order to obtain effective predictors, we used Lasso regression, Boruta algorithm and random forest classifier score for feature selection. We used six models for predictive model construction and evaluated the models in the validation dataset. Model performance was measured by area under the curve (AUC), accuracy and F1 score. Logistic regression was found to be the best performing and most interpretable algorithm with AUC, accuracy and F1 of 0.974, 0.932 and 0.880 for the validation dataset, respectively. The AUCs for the external independent validation dataset were 0.963 and 0.977, respectively. Subgroup analysis showed that the model had good predictive power in both males and females. The predictive power was stronger among the elderly people over 80 years old, with AUC, accuracy and F1 of 0.973,0.914, and 0.893, respectively. The model also obtained good predictive power in the case of FI measured by different indicators. The model showed good robustness in the follow-up assessment of frailty status in elderly people, with the AUC remaining above 0.95 and accuracy above 0.9 over the long-term follow-up. Using machine learning techniques, we have successfully developed a simple frailty assessment prediction model based on 10 key features to shorten the frailty assessment scale with near full-scale accuracy. A user-friendly website was created to facilitate the application of this prediction model (https://healthy-aging.shinyapps.io/Frailty_Assessment/). [ABSTRACT FROM AUTHOR]

This commentary examines the study "Frailty and Its Association with Long-Term Mortality Among Community-Dwelling Older Adults Aged 75 Years and Over" by Lewis et al. The retrospective cohort study utilized data from a primary healthcare provider in Israel to investigate frailty using the Frailty Index (FI) and its correlation with long-term mortality. Nearly half of the older adult cohort was identified as frail, with a strong association between higher frailty levels and increased mortality risk. The commentary emphasizes the importance of routine frailty screening in clinical practice and health policy. Integrating FI calculations into electronic health records can facilitate timely care for high-risk individuals. However, presenting frailty data must be managed carefully and in conjunction with patients' preferences to avoid stigmatizing and negatively influencing clinical decisions. While the FI is a valuable tool, it should complement, not replace, other assessments that provide a more holistic view of the patient's health. Furthermore, the commentary strongly advocates for a more comprehensive approach to patient care, emphasizing that non-geriatricians must also be proficient in recognizing and managing frailty. Effectively addressing frailty can lead to significant cost savings for healthcare systems, reduced burden on healthcare facilities, and decreased need for long-term care. [ABSTRACT FROM AUTHOR]

Background: Although some recent studies have examined the health of female Gulf War (GW) deployed and non-deployed GW era veterans, these all relied on self-report, which can be inaccurate and subject to recall bias. This study investigated the current health of GW deployed and non-deployed GW era female and male veterans using Veterans Health Administration (VHA) electronic health records (EHR). Methods: We performed a cohort study of deployed GW and non-deployed GW era veterans, identified from a list from the Defense Manpower Data Center (DMDC). We used the VA-Frailty Index (VA-FI), calculated with VHA administrative claims and EHR, as a proxy measure of current health. Results: We identified 402,869 veterans (351,496 GW deployed; 51,3373 non-deployed GW era; 38,555 female) in VHA databases. Deployed female veterans had the highest VA-FI (i.e., were frailest) despite being younger than deployed and non-deployed male veterans and non-deployed female veterans. Compared with deployed male veterans, deployed females were more likely to be pre-frail, mildly, and moderately frail. Health differences between deployed and non-deployed female veterans were more prominent among older (60+ years) than younger (<60 years) veterans. Conclusions: Mirroring reports from recent, smaller survey studies of users and non-users of VA health care, findings from this cohort study indicate that deployed female GW veterans who use VA health care are frailer and have more health deficits than non-deployed female GW era and deployed male GW veterans. Because deployed female GW veterans appear to have additional health care needs, this may warrant increased outreach from women's clinics at VA hospitals. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer is the 5th most common malignancy worldwide. Surgical treatment for the disease can often be highly morbid, especially in elderly patients. The modified 5-item frailty index (mFI-5), a recently developed tool for assessing patient frailty, has been shown to be an effective predictor of post-operative outcomes in various surgical fields. This study aims to assess the utility of the mFI-5 in predicting adverse postoperative outcomes following gastrectomy for gastric cancer. Methods: The National Surgical Quality Improvement Program (NSQIP) database was queried for patients who underwent partial or total gastrectomy for gastric cancer between 2011 and 2021. The mFI-5 score was calculated based on the presence of hypertension, congestive heart failure, diabetes mellitus, chronic obstructive pulmonary disease, and partially or fully dependent functional status. Patients were stratified into 3 groups according to mFI-5 score (mFI-5 = 0, mFI-5 = 1, mFI-5 ≥ 2). Univariate analysis and multivariate logistic regression were used to evaluate the association between mFI-5 score and post-operative outcomes. Results: 7438 patients were identified (mFI-5 = 0: 3032, mFI-5 = 1: 2805, mFI-5 ≥ 2: 1601). mFI-5 ≥ 2 was an independent predictor of overall complications (OR 1.43, p < 0.001), serious complications (OR 1.42, p < 0.001), pneumonia (OR 1.43, p = 0.010), MI (OR 2.91, p = 0.005), and readmission within 30 days (OR 1.33, p = 0.008). Patients with higher frailty were more likely to experience unplanned intubation (OR 2.06, p < 0.001; OR 2.47, p < 0.001), failure to wean from the ventilator (OR 1.68, p = 0.003; OR 2.00, p < 0.001), acute renal failure (OR 3.25, p = 0.003; OR 3.27, p = 0.005), 30-day mortality (OR 1.73, p = 0.009; OR 1.94, p = 0.004), and non-home discharge (OR 1.34, p = 0.001; OR 1.74, p < 0.001) relative to non-frail patients. Conclusion: Higher frailty, as indicated by an increased mFI-5 score, raises the risk of serious post-operative complications in patients with gastric cancer undergoing gastrectomy. The mFI-5 has the potential to help identify high-risk patients and enhance pre-operative discussions and optimization. [ABSTRACT FROM AUTHOR]

Aging studies in mammalian models often depend on natural lifespan data as a primary outcome. Tools for lifespan prediction could accelerate these studies and reduce the need for veterinary intervention. Here, we leveraged large-scale longitudinal frailty and lifespan data on two genetically distinct mouse cohorts to evaluate noninvasive strategies to predict life expectancy in mice. We applied a modified frailty assessment, the Fragility Index, derived from existing frailty indices with additional deficits selected by veterinarians. We developed an ensemble machine learning classifier to predict imminent mortality (95% proportion of life lived [95PLL]). Our algorithm represented improvement over previous predictive criteria but fell short of the level of reliability that would be needed to make advanced prediction of lifespan and thus accelerate lifespan studies. Highly sensitive and specific frailty-based predictive endpoint criteria for aged mice remain elusive. While frailty-based prediction falls short as a surrogate for lifespan, it did demonstrate significant predictive power and as such must contain information that could be used to inform the conclusion of aging experiments. We propose a frailty-based measure of healthspan as an alternative target for aging research and demonstrate that lifespan and healthspan criteria reveal distinct aspects of aging in mice. [ABSTRACT FROM AUTHOR]

Purpose: Frailty and age-related eye diseases are common in older people; however, whether there is a causal link remains unknown. We aimed to explore the causal associations between the frailty index (FI) and ophthalmic traits and identify modifiable mediators. Methods: Linkage disequilibrium score regression and two-sample Mendelian randomization were applied to identify genetic correlations and causal associations between FI and ophthalmic traits. Summary data for FI was obtained from a genome-wide association study that included 175,226 individuals of European ancestry. Summary-level statistics for ophthalmic traits were obtained from relative GWASs. Summary-level data for cardiovascular risk factors, inflammatory biomarkers, and the central nervous system were used to identify the possible mediators. Results: FI had a significant genetic correlation with 10 ophthalmic traits. Per SD increment of FI, the odds ratio was 1.329 (95% CI, 1.123, 1.573; P = 9.5 × 10–4) for cataracts, 1.825 (95% CI, 1.115, 2.986; P = 0.016) for keratitis, 1.798 (95% CI, 1.039, 3.11; P = 0.036) for disorders of vitreous body and 1.478 (95% CI, 1.005, 2.173; P = 0.046) for disorders of sclera, cornea, iris and ciliary body. The MR effect estimates of FI on ophthalmic traits were attenuated after adjusting for mental disorders, type 2 diabetes, triglyceride, and interleukin-8 (IL-8) levels. Conclusion: This study reports a genetic correlation and causal association between FI and ophthalmic traits, in which mental disorders, type 2 diabetes, triglycerides, and IL-8 may play a mediating role. These findings highlight a possible method to reduce the risk of FI-related ophthalmic diseases. [ABSTRACT FROM AUTHOR]

\nIntroduction: We aimed to explore the predictive value of pre-stroke frailty index (FI) on functional dependency and mortality 3 years after stroke. Methods: Based on the Rockwood 36-item FI score, we calculated the pre-stroke FI from medical conditions recorded at baseline in the multicenter prospective Nor-COAST study 2015–2017. Participants with a FI score and a modified Rankin scale (mRS) 0–6 3 years post-stroke were included in this study. We used logistic regression analysis with unfavorable mRS (over 2 vs. 0–2) at 3 years, or dead within 3 years, as dependent variable, and frailty and pre-stroke mRS, one at a time, and simultaneously, as predictors. The analyses were carried out unadjusted and adjusted for the following variables one at a time: Age, sex, years of education, stroke severity at admission, infections treated with antibiotics and stroke progression. We report odds ratio (OR) per 0.10 increase in FI. Results: At baseline, the 609 included patients had mean age 72.8 (standard deviation [SD] 11.8), 261 (43%) were females, and had a FI mean score of 0.16 (SD 0.12), range 0–0.69. During 3 years, 138 (23%) had died. Both the FI, and pre-stroke mRS, were strong predictors for unfavorable mRS (OR 4.1 and 2.7) and dead within 3 years (OR 2.2 and 1.7). Only adjusting for age affected the result. The OR for pre-stroke mRS decreased relatively more than the OR for FI when entered as predictors simultaneously. Conclusions: FI is a stronger predictor than premorbid mRS for prognostication after stroke. Stroke is a leading cause of dead and disability in the world. It is an acute condition prevalent in older populations. As more older adults surviving previously fatal strokes, the prevalence of stroke survivors with different functional and cognitive impairments increase. There is a great heterogeneity in outcome after stroke, even in milder strokes. We know less of what predict poor outcome. While increasing age in general is associated with poor outcome, at individual plan the relationship with age is more uncertain. Frailty is a concept gaining more attention over the recent years. It is defined as a condition of vulnerability associated with an increased risk of adverse health outcomes such as functional decline and mortality. Frail people have an increased risk of developing disease when something extraordinary occurs. Less is known about the relationship between stroke and frailty. Frailty assessment is not yet part of routine stroke care. In this study, we explored the impact of pre-stroke frailty on functional dependency and mortality 3 years after stroke. We found that the degree of frailty before stroke had a huge impact on functional status and mortality 3 years after stroke, even when we adjusted for important factors, like stroke severity and age. This demonstrates the importance of implementing frailty measures as a routine tool in stroke medicine. It also underline the value of developing preventing mechanisms of frailty in the older population. [ABSTRACT FROM AUTHOR]

Background: Pancreatic Ductal Adenocarcinoma (PDAC) primarily affects older individuals with diminished physiological reserves. The Modified 5-Item Frailty Index (mFI-5) is a novel risk stratification tool proposed to predict postoperative morbidity and mortality. This study aimed to validate the mFI-5 for predicting surgical outcomes in patients undergoing pancreatoduodenectomy (PD) for PDAC. Methods: Our retrospective PDAC database included patients who underwent PD between 2014 and 2023. Patients were stratified by mFI-5 scores (0 best − 5 worst), which assess preoperative CHF, diabetes mellitus, history of COPD or pneumonia, functional health status, and hypertension requiring medication. Associations between mFI-5 scores and outcomes, including postoperative complications and mortality, were analyzed using logistic regression, Cox proportional hazards models, and Kaplan-Meier survival analysis. Results: Among 250 PDAC patients undergoing PD, 142 (56.8%) had mFI-5 scores ≤ 1, and 25 (10%) had scores ≥ 3. No patients had scores > 4. Higher mFI-5 scores correlated with older age (p < 0.001) and tobacco use (p = 0.036). Multivariate analysis identified age (RR 1.02, p = 0.038), ASA class (ASA III; RR 2.61, p < 0.001; ASA IV; RR 2.63, p = 0.026), and moderate alcohol consumption (RR 0.56, p = 0.038) as frailty predictors. An mFI-5 score > 2 independently associated with higher mortality (HR 2.08, p = 0.026). Median overall survival was significantly lower for patients with mFI-5 scores > 2 than for those with scores ≤ 2 (21.3 vs. 42.1 months, p = 0.022). Conclusions: The mFI-5 is a valuable tool for predicting postoperative morbidity and mortality in PDAC patients undergoing PD. Integrating frailty assessment into preoperative evaluations can enhance patient selection and surgical outcomes. Future research should focus on incorporating frailty assessments into surgical planning and patient management to improve outcomes in this vulnerable population. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions This study aimed to investigate the association between use of proton pump inhibitors (PPI) and frailty index (FI), and to assess the causality relationship using Mendelian randomization (MR).A total of 9756 middle‐aged and older adults from the National Health and Nutrition Examination Survey were included. The FI was evaluated using a previously validated 49‐item deficit model to assess frailty status, which is one of the common approaches to measure overall health burden. We performed weighted multivariable‐adjusted linear regression to assess the association between PPI use and FI, and conducted a two‐sample MR to evaluate causality, employing various sensitivity analyses for robustness. The inverse variance weighted (IVW) method was used as the primary analysis.Multiple linear regression analysis revealed a positive association between PPI use and FI (β = 0.048, 95% confidence interval [CI]: 0.042–0.054, P < .001). This association was observed in both short‐term (≤ 1 year) and long‐term (> 1 year) PPI users (P for trend < 0.001). The MR study also revealed a positive association between PPI use and FI based on the IVW method (β = 1.183, 95% CI: 0.474–1.892, P = .001).While our findings suggest a potential link between PPI use and FI, they should be interpreted with caution due to the study's limitations. Although the MR analysis suggests a causal relationship, further research, particularly longitudinal studies, is needed to confirm these findings and better establish temporality. [ABSTRACT FROM AUTHOR]

Background: As the population ages, the occurrence of cognitive decline and dementia is continuously increasing. Frailty is a prevalent problem among older adults. Epidemiologic studies have shown a comorbidity between frailty and cognitive impairment. However, their relationship remains unclear. The frailty index is an important indicator for measuring frailty. This study aims to investigate the relationship between frailty index and cognitive dysfunction in older adults aged 60 years and older in the United States from the 2011-2014 National Health and Nutrition Examination Survey (NHANES). Methods: Community-dwelling older adults aged 60 years or older from 2011 to 2014 were extracted from the NHANES database. The frailty index was calculated using the formula: frailty index = total number of deficits present/total number of deficits measured. The Animal Fluency (AF), the Digit Symbol Substitution Test (DSST), the Consortium to Establish a Registry for Alzheimer's disease Delayed Recall (CERAD-DR), and Word Learning (CERADWL) were used to evaluate cognitive dysfunction. Firstly, weighted logistic regression analysis was used to explore the relationship between frailty index and cognitive dysfunction. Secondly, the influence of covariates on the frailty index was evaluated by subgroup analysis and interaction. Finally, the non-linear relationship is discussed by using the restricted cubic spline regression model. Results: Our study included a total of 2,574 patients, weighted logistic regression analysis, after adjusting for all covariates, showed that the frailty index was associated with every test score. The interaction showed that covariates had no significant effect on this association in AF. The association between the frailty index and AF in the restricted cubic spline regression model is non-linear. As the frailty index increased, the risk of AF reduction increased, suggesting a higher risk of cognitive dysfunction. Conclusion: In general, a high frailty index appears to be associated with an increased risk of cognitive dysfunction in the elderly. Consequently, protecting against cognitive decline necessitates making geriatric frailty prevention and treatment top priorities. [ABSTRACT FROM AUTHOR]

Introduction: Comparing frailty models in different settings that predict inhospital mortality might modify patient disposition and treatment, but models are often complex. Methods: In the following study, we selected all acutely admitted adult patients in 2020–2021 to the three internal medicine departments at a regional 400-bed hospital. We attempt to determine (a) if a new scale (Laniado-4 scale) that includes only three yes/no questions derived from the Norton scale and the presence of a urinary catheter performs as well as the graded Norton scale (including all five domains), in predicting inhospital mortality and (b) to determine the predictive value of a simple frailty index that includes the new scale as well as categories of age, serum albumin, and creatinine values. We calculated odds ratios with 95% confidence intervals and c-statistics for the various models predicting inhospital mortality. Results: The mean patient age was 73 ± 19 years, and 49.1% (5,665/11,542) were males. A Laniado-4 scale performed better than the Norton scale for predicting inhospital mortality. A simple frailty index ranging from 0 to ≥8 points was associated with rates of inhospital mortality that increased from 0 to 37.7%, with an odds ratio of 2.13 (2.03–2.25) per 1 index point. The c-statistic was 0.887 (0.881–0.893). Conclusions: We conclude the Laniado-4 scale performed better than the Norton scale in predicting inhospital mortality and that a simple frailty index that included the 4-question scale and categories of age, serum creatinine, and serum albumin performed as well or better than more complicated models. [ABSTRACT FROM AUTHOR]

Background: Previous observational studies have revealed a potentially robust bidirectional relationship between frailty and low back pain (LBP). However, the precise causal relationship remains unclear. Methods: To examine the potential causal association between frailty and LBP, we conducted bidirectional two-sample Mendelian randomization analysis (MR) study. Genetic data on frailty index (FI) and LBP were acquired from publicly available genome-wide association studies (GWAS). Various MR methodologies were utilized, such as inverse variance weighting (IVW), weighted median, and MR-Egger, to evaluate causality. Additionally, sensitivity analyses were conducted to evaluate the robustness of the findings. Results: Genetically predicted higher FI (IVW, odds ratio [OR] = 1.66, 95% CI 1.17–2.36, p = 4.92E-03) was associated with a higher risk of LBP. As for the reverse direction, genetic liability to LBP showed consistent associations with a higher FI (IVW, OR = 1.13, 95% CI 1.07–1.19, p = 2.67E-05). The outcomes from various MR techniques and sensitivity analyses indicate the robustness of our findings. Conclusion: Our research findings provide additional evidence bolstering the bidirectional causal relationship between frailty and LBP. [ABSTRACT FROM AUTHOR]

Background: Frailty in older people is a rising global health concern; therefore, monitoring prevalence estimates and presenting projections of future frailty are important for healthcare planning. Aim: To present current prevalence estimates of frailty and pre-frailty and future projections according to both dominant frailty models in a large population-based observational study including adults ≥ 70 years in Norway. Methods: In this population-based observational study, we included 9956 participants from the HUNT4 70 + study, conducting assessments at field stations, homes, and nursing homes. Frailty was assessed using Fried criteria and a 35-item frailty index (HUNT4-FI). Inverse probability weighting and calibration using post-stratification weights and aggregated register data for Norway according to age, sex, and education ensured representativeness, and population projection models were used to estimate future prevalence. Results: According to Fried criteria, the current prevalence rates of frailty and pre-frailty in people ≥ 70 years were 10.6% and 41.9%, respectively, and for HUNT4-FI 35.8% and 33.2%, respectively. Compared to previous European estimates we identified higher overall frailty prevalence, but lower prevalence in younger age groups. Projections suggest the number of Norwegian older adults living with frailty will close to double by 2040. Conclusion: Frailty in older people in Norway is more prevalent than previous European estimates, emphasising the imperative for effective interventions aimed to delay and postpone frailty and ensure healthcare system sustainability in an ageing population. Future planning should consider the great heterogeneity in health and functioning within the 70 + population. [ABSTRACT FROM AUTHOR]

Purpose: Dietary nitrate intake is inversely related to numerous contributors towards frailty, including cardiovascular disease and poor physical function. Whether these findings extend to frailty remain unknown. We investigated if habitual nitrate intake, derived from plants or animal-based foods, was cross-sectionally associated with frailty in women. Methods: Community-dwelling older Australian women (n = 1390, mean age 75.1 ± 2.7 years) completed a validated semi-quantitative food frequency questionnaire (FFQ). Nitrate concentrations in food were obtained from international nitrate databases. We adopted the Rockwood frailty index (FI) of cumulative deficits comprising 33 variables across multiple health domains (scored 0 to 1), which predicts increased hospitalisation and mortality risk. A FI ≥ 0.25 indicated frailty. Cross-sectional associations between nitrate intake (total plant and animal nitrate, separately) and frailty were analysed using multivariable-adjusted logistic regression models (including lifestyle factors), as part of restricted cubic splines. Results: A non-linear inverse relationship was observed between total plant nitrate intake and frailty. Compared to women with the lowest plant nitrate intake (Quartile [Q]1), women with greater intakes in Q2 (OR 0.69 95%CI 0.56–0.84), Q3 (OR 0.67 95%CI 0.50–0.90) and Q4 (OR 0.66 95%CI 0.45–0.98) had lower odds for frailty. A nadir in the inverse association was observed once intakes reached ~ 64 mg/d (median Q2). No relationship was observed between total animal nitrate and frailty. Conclusion: Community-dwelling older women consuming low amounts of plant-derived nitrate were more likely to present with frailty. Consuming at least one daily serving (~ 75 g) of nitrate-rich green leafy vegetables may be beneficial in preventing frailty. [ABSTRACT FROM AUTHOR]

The 5-factor modified Frailty Index (mFI-5) is a risk-stratification tool utilized to predict complications and mortality following major lower extremity (LE) amputation. However, its prognostic value for long-term mortality is unknown. The study aim was to assess whether a high mFI-5 score relates to long-term mortality following major LE amputation for chronic wounds. Patients ≥60 years who underwent major LE amputation from 2017 to 2021 were retrospectively reviewed. Data regarding demographics, comorbidities, perioperative factors, amputation type, and postoperative complications was collected and mFI-5 was calculated. Survival analysis was performed with Kaplan-Meier curves and differences were assessed with Log-Rank test. A total of 172 patients were identified. Mean age was 70.7 ± 8.0 years. Median time to ambulation was 3.7 months (IQR 4.0). By final follow-up of 17.5 ± 15.9 months, ambulatory rate was 51.7% (n = 89), overall mortality 36.0% (n = 62), 1-year mortality 14.0% (n = 24), and 3-year mortality 27.9% (n = 48). Patients with an mFI-5 of ≥4 (26.7%, n = 46) compared with patients with mFI-5 <4 (73.3%, n = 126) had a higher rate of prolonged postoperative LOS (34.8% vs 19.8%, p =.042), overall mortality (52.2% vs 30.2%, p =.008), 1-year mortality (23.9% vs 10.3%, p =.023), and 3-year mortality (45.7% vs 21.4%, p =.002). Multivariate analysis demonstrated mFI-5 was an independent predictor of 3-year mortality (OR 2.35, p =.043). At a threshold ≥4, the mFI-5 demonstrated utility in predicting long-term mortality. The value of this prognostic indicator is in its preoperative application of assessing risk of mortality, which should be utilized in conjunction with other measures. [ABSTRACT FROM AUTHOR]

Current scoring systems for short-term prognosis in patients with acute myocardial infarction (AMI) lack coverage of risk factors and have limitations in risk stratification. The aim of this study was to develop a novel assessment system based on laboratory indicators and frailty quantification to better infer short-term prognosis and risk indication in patients with AMI. Methods: A total of 365 patients with MI from January 2022 to June 2023 in Northern Jiangsu Province Hospital were included. The primary endpoint was all-cause mortality and major adverse cardiac events (MACE) during follow-up. A novel scoring model ranging from 0 to 12 was constructed, and the predictive ability of this scoring system was evaluated using the area under the receiver operating characteristic curve (AUC). Results: During follow-up, 68 patients experienced MACE. Five scoring indicators were selected through multivariate logistic regression analysis, resulting in a composite score with an AUC of 0.925, demonstrating good prognostic accuracy. Conclusion: The novel prognostic assessment system, which integrates age, Stress Hyperglycemia Ratio (SHR), Neutrophil to Lymphocyte Ratio (NLR), lactate, and frailty score, exhibits good predictive value for short-term MACE in patients with acute myocardial infarction and may enable more accurate risk classification for future use in MI patient risk management. [ABSTRACT FROM AUTHOR]

Background: Frailty is a common geriatric syndrome associated with adverse health outcomes in older adults. This study aimed to examine the association between frailty index and mortality in elderly residents of nursing homes in Iran. Methods: This historical cohort study used data extracted from the Sina Electronic Health Record System (SinaEHR®, Iran) and the national cause of death registry in Iran. The study population included 9199 adults aged ≥60 assessed for frailty in nursing homes across Iran from April 2021 to June 2022. They were followed up until August 2022. Frailty was defined as a score >3 on Fried’s 5-item index. We used multivariable logistic regression to determine adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for mortality-related factors. The chi-square test compared mortality across groups. Data were analyzed using Stata software, version 11 with P

Objective: To determine factors significantly associated with alternative discharge destination (ADCD) following lobectomy, including the modified 5-item Frailty Index (mFI-5). Methods: Patients in the 2017-2020 NSQIP who underwent elective lobectomy and were admitted from home were included, with ADCD defined as a patient who was discharged to any nonhome location. Four multivariable logistic regression models for ADCD were evaluated for predictive power. Model A was created from backward selection of variables significantly associated with ADCD in bivariate analyses, model B was the mFI-5, model C was mFI-5 and a minimally invasive approach, and model D was mFI-5 and age group. Results: Among the 15,868 patients, 687 (4.3%) experienced ADCD. Model A identified older age, hypertension, dyspnea, history of chronic obstructive pulmonary disease, and increased length of stay as significantly associated with ADCD. A minimally invasive approach was significantly protective of ADCD. Model A had the best predictive power of the models tested (C-statistic = 0.785). Model B, which assessed mFI-5 alone, had fair predictive power (C-statistic = 0.637). Adding surgical approach (C-statistic = 0.673; model C) or age group (C-statistic = 0.682; model D) as independent variables with mFI-5 improved model fit. Conclusions: Patients who were frail or age >75 years were more likely to have postlobectomy ADCD. Although the variables identified in model A better predict ADCD, consideration of surgical approach or age with mFI-5 can help surgeons anticipate discharge destination following lobectomy.

Abstract Frailty is a state that is closely associated with adverse health outcomes in the aging process. The frailty index (FI), which measures frailty in terms of cumulative deficits, has been widely used for frailty assessment in elderly people, and its advantage of self-reported information collection makes it applicable to a broader group of elderly people. Our study aims to simplify the Frailty Index Assessment Scale, while maintaining its reliability and accuracy, to easily and quickly assess frailty in elderly people. In this study, participants (age ≥ 65 years) from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which had 13,339, 372 and 1214 participants in 2008, 2011, and 2014, respectively, were used. The 2008 dataset was split into 80% for training and 20% for internal validation, and the data from 2011 to 2014 as external validation. In order to obtain effective predictors, we used Lasso regression, Boruta algorithm and random forest classifier score for feature selection. We used six models for predictive model construction and evaluated the models in the validation dataset. Model performance was measured by area under the curve (AUC), accuracy and F1 score. Logistic regression was found to be the best performing and most interpretable algorithm with AUC, accuracy and F1 of 0.974, 0.932 and 0.880 for the validation dataset, respectively. The AUCs for the external independent validation dataset were 0.963 and 0.977, respectively. Subgroup analysis showed that the model had good predictive power in both males and females. The predictive power was stronger among the elderly people over 80 years old, with AUC, accuracy and F1 of 0.973,0.914, and 0.893, respectively. The model also obtained good predictive power in the case of FI measured by different indicators. The model showed good robustness in the follow-up assessment of frailty status in elderly people, with the AUC remaining above 0.95 and accuracy above 0.9 over the long-term follow-up. Using machine learning techniques, we have successfully developed a simple frailty assessment prediction model based on 10 key features to shorten the frailty assessment scale with near full-scale accuracy. A user-friendly website was created to facilitate the application of this prediction model ( https://healthy-aging.shinyapps.io/Frailty_Assessment/ ).

Abstract This commentary examines the study “Frailty and Its Association with Long-Term Mortality Among Community-Dwelling Older Adults Aged 75 Years and Over” by Lewis et al. The retrospective cohort study utilized data from a primary healthcare provider in Israel to investigate frailty using the Frailty Index (FI) and its correlation with long-term mortality. Nearly half of the older adult cohort was identified as frail, with a strong association between higher frailty levels and increased mortality risk. The commentary emphasizes the importance of routine frailty screening in clinical practice and health policy. Integrating FI calculations into electronic health records can facilitate timely care for high-risk individuals. However, presenting frailty data must be managed carefully and in conjunction with patients’ preferences to avoid stigmatizing and negatively influencing clinical decisions. While the FI is a valuable tool, it should complement, not replace, other assessments that provide a more holistic view of the patient’s health. Furthermore, the commentary strongly advocates for a more comprehensive approach to patient care, emphasizing that non-geriatricians must also be proficient in recognizing and managing frailty. Effectively addressing frailty can lead to significant cost savings for healthcare systems, reduced burden on healthcare facilities, and decreased need for long-term care.

Abstract Background Uric acid (UA), the terminal breakdown product of purine metabolism, possesses contradictory roles, functioning both as an inflammatory mediator and as an antioxidant. Its clinical relevance, particularly in geriatric populations, remains a topic of ongoing debate. Aiming to elucidate whether circulating UA is detrimental or beneficial to human health, we investigate the association between serum UA concentrations and the frailty index—a comprehensive measure of biological aging in a nationally representative cohort of community‐dwelling older adults. Methods We conducted a population‐based, cross‐sectional study utilizing data from the Korea National Health and Nutrition Examination Survey. The sample included 4268 participants aged 65 years and above. A deficit accumulation frailty index (FI) was constructed using 38 items that assess physical, cognitive, psychological, and social domains. Based on the FI, participants were categorized into non‐frail (FI ≤ 0.15), pre‐frail (0.15 0.25). Serum UA levels were quantified through a colorimetric enzymatic assay. Results After controlling for confounders such as age, sex, socioeconomic status (including income and education level), lifestyle factors (smoking status), and medical history (hypertension, diabetes, dyslipidemia, stroke, cardiovascular diseases), and body mass index, serum UA levels were observed to be significantly higher in frail participants compared with their non‐frail counterparts (P

Introduction: For older adults, dysphagia is a serious problem that can occur after spinal cord injury (SCI), but its risk factors are unclear. This study aimed to identify risk factors for dysphagia in elderly patients (65 years) with cervical SCI. Methods: This multicenter study included 707 patients with cervical SCI (mean age 75.3 years). Univariate and multivariate analyses were conducted for patient characteristics and geriatric nutritional risk index (GNRI). Results: Dysphagia occurred in 69 patients (9.8%). The significant factors were as follows: male sex (odds ratio [OR] 3.43), GNRI

Purpose: To investigate the association between five dietary trajectories over 21 years and frailty in Norwegian older adults. Methods: This study used data from three surveys of the Tromsø Study. Diet was measured using food frequency questionnaires at baseline (Tromsø4, 1994–95), after 7 years (Tromsø5, 2001) and at the end of follow-up (Tromsø7, 2015–16). Survey-specific diet scores were constructed based on the Nordic Nutrition Recommendations 2023 and group-based trajectory modelling was used to derive dietary trajectories. At follow-up, frailty was assessed with a 41-item frailty index. Linear regression analysis was performed to assess the associations between dietary trajectories and frailty, adjusted for baseline variables. Results: Among the 715 participants, 55% were women, with an average age of 54 years at baseline and 74 years at follow-up. The dietary trajectories 'moderately healthy' and 'healthy increase' were associated with a lower frailty index score at follow-up (β = −0.02, 95% confidence interval (CI) = −0.04, −0.002, β = −0.03, 95% CI = −0.06, −0.007), compared with the 'unhealthy' trajectory. Conclusion: Our findings suggest that maintaining a moderately healthy to very healthy diet from mid-life into older age is associated with a lower risk of frailty and supports the promotion of a healthy diet from adulthood to facilitate healthy ageing. [ABSTRACT FROM AUTHOR]

Frailty has been linked to inflammation and changes in body composition, but the findings are inconsistent. To explore this, we used the Frailty Index (FI) definition to (1) investigate the association between levels of inflammatory markers (baseline) and change in FI score after 8 years of follow-up and (2) investigate the longitudinal associations between inflammatory markers, body composition, and frailty. Home-dwelling elderly (≥ 70 years) were invited to participate in the study and re-invited to a follow-up visit 8 years later. This study includes a total of 133 participants. The inflammatory markers included were high-sensitive C-reactive protein (hs-CRP), interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-α), and glycoprotein acetyls (Gp-acetyls). We used the body composition markers fat mass, fat-free mass, and waist circumference. The FI score consisted of 38 variables. Additional clinical assessments such as blood pressure and body mass index (BMI), as well as information about daily medications, were collected at both visits. Linear regression model and Spearman's rank correlation were used to investigate associations. We showed that the FI score increased after 8 years, and participants with higher hs-CRP levels at baseline had the largest change in the FI score. Changes in fat mass were significantly correlated with changes in hs-CRP and IL-6, and changes in waist circumference were significantly correlated with changes in TNF-α. The use of drugs increased during the 8 years of follow-up, which may have attenuated the associations between inflammation and frailty. However, elevated concentrations of hs-CRP in the elderly may be associated with an increased risk of frailty in subsequent years. [ABSTRACT FROM AUTHOR]

Abstract Background Insulin resistance is linked to an increased risk of frailty, yet the comprehensive relationship between the triglyceride glucose-body mass index (TyG-BMI), which reflects weight, and frailty, remains unclear. This relationship is investigated in this study. Methods Data from 9135 participants in the China Health and Retirement Longitudinal Study (2011–2020) were analysed. Baseline TyG-BMI, changes in the TyG-BMI and cumulative TyG-BMI between baseline and 2015, along with the frailty index (FI) over nine years, were calculated. Participants were grouped into different categories based on TyG-BMI changes using K-means clustering. FI trajectories were assessed using a group-based trajectory model. Logistic and Cox regression models were used to analyse the associations between the TyG-BMI and FI trajectory and frail incidence. Nonlinear relationships were explored using restricted cubic splines, and a linear mixed-effects model was used to evaluate FI development speed. Weighted quantile regression was used to identify the primary contributing factors. Results Four classes of changes in the TyG-BMI and two FI trajectories were identified. Individuals in the third (OR = 1.25, 95% CI: 1.10–1.42) and fourth (OR = 1.83, 95% CI: 1.61–2.09) quartiles of baseline TyG-BMI, those with consistently second to highest (OR = 1.49, 95% CI: 1.32–1.70) and the highest (OR = 2.17, 95% CI: 1.84–2.56) TyG-BMI changes, and those in the third (OR = 1.20, 95% CI: 1.05–1.36) and fourth (OR = 1.94, 95% CI: 1.70–2.22) quartiles of the cumulative TyG-BMI had greater odds of experiencing a rapid FI trajectory. Higher frail risk was noted in those in the fourth quartile of baseline TyG-BMI (HR = 1.42, 95% CI: 1.28–1.58), with consistently second to highest (HR = 1.23, 95% CI: 1.12–1.34) and the highest TyG-BMI changes (HR = 1.58, 95% CI: 1.42–1.77), and those in the third (HR = 1.10, 95% CI: 1.00-1.21) and fourth quartile of cumulative TyG-BMI (HR = 1.46, 95% CI: 1.33–1.60). Participants with persistently second-lowest to the highest TyG-BMI changes (β = 0.15, 0.38 and 0.76 respectively) and those experiencing the third to fourth cumulative TyG-BMI (β = 0.25 and 0.56, respectively) demonstrated accelerated FI progression. A U-shaped association was observed between TyG-BMI levels and both rapid FI trajectory and higher frail risk, with BMI being the primary factor. Conclusion A higher TyG-BMI is associated with the rapid development of FI trajectory and a greater frail risk. However, excessively low TyG-BMI levels also appear to contribute to frail development. Maintaining a healthy TyG-BMI, especially a healthy BMI, may help prevent or delay the frail onset.

Abstract Background The ageing process is characterized by a change of body composition with an increase of fat mass and a reduction of muscle mass. Above a certain threshold these alterations configure a condition named sarcopenic obesity (SO). SO is associated with physical frailty in Asian and Brazilian populations. SO impacts on physical frailty in other ethnic groups but its influence on general frailty which is multidimensional and includes cognitive, social and physical factors, remain insufficiently explored in the Italian population. Methods Frailty was measured in community dwelling Italian older adults enrolled in the FRASNET study with the frailty index (FI). The FI quantifies frailty as the ratio of the number of present health deficits to the total number of health deficits considered. Regression analyses were performed to assess the association between body composition categories and frailty. Classification and regression tree models were run to evaluate the frailty predictors. Results One Thousand One Hundred Fourteen participants of the FRASNET study were included in the present analysis. The sample was composed for the 60.5% by females and its median age was 72 years. The median FI score was 0.11 (IQR 0.07–0.20); 234 individuals (21%) were frail (FI ≥ 0.25). SO (B 0.074, 95% C.I. 0.05–0.1, p

Abstract Background With increasing trend of internet use in all age groups, whether internet use can prevent frailty in middle-aged and older adults remains unclear. Methods Five cohorts, including Health and Retirement Study (HRS), China Health and Retirement Longitudinal Study (CHARLS), the Survey of Health, Ageing and Retirement in Europe (SHARE), English Longitudinal Study of Aging (ELSA), and Mexican Health and Aging Study (MHAS), were used in this study. Internet use, social isolation, and frailty status was assessed using similar questions. The Generalized estimating equations models, random effects meta-analysis, COX regression, and mediation analysis were utilized. Results In the multicohort study, a total of 155,695 participants were included in main analysis. The proportion of internet use was varied across countries, ranging from 5.56% in China (CHARLS) to 83.46% in Denmark (SHARE). According to the generalized estimating equations models and meta-analysis, internet use was inversely associated with frailty, with the pooled ORs (95%CIs) of 0.72 (0.67,0.79). The COX regression also showed that participants with internet use had a lower risk of frailty incidence. Additionally, the association was partially mediated by social isolation and slightly pronounced in participants aged 65 and over, male, not working for payment, not married or partnered, not smoking, drinking, and not co-residence with children. Conclusions Our findings highlight the important role of internet use in preventing frailty and recommend more engagements in social communication and activities to avoid social isolation among middle-aged and older adults.

Abstract Although bilateral simultaneous total knee arthroplasty (BSTKA) is an effective treatment for bilateral knee osteoarthritis, safety concerns and lack of precise patient selection criteria persist. The purpose of this retrospective study was to determine the complication rate and the role of frailty in patient selection for BSTKA. We analyzed data from 434 patients who underwent BSTKA between February 2012 and January 2021, examining demographic factors and preoperative blood test results. Complications occurred in 77 patients (18%), with anemia requiring transfusion being the most common (26 patients, 5.9%). In the univariate analysis, age ≥ 75 years, age-adjusted Charlson Comorbidity Index ≥ 5, age-adjusted 5-factor modified Frailty Index (aamFI-5) ≥ 3, hemoglobin ≤ 11.0 g/dL, albumin ≤ 3.5 g/dL, estimated glomerular filtration rate

Abstract Purpose Frailty is a vulnerable state to stressors due to the loss of physiological reserve as a result of multisystem dysfunction. The physiological and laboratory-based frailty index (FI-Lab), depending on laboratory values and vital signs, is a powerful tool to capture frailty status. The aim of this study was to assess the relationship between FI-Lab and in-hospital mortality in patients with septic shock. Methods Baseline data for patients with sepsis in the intensive care unit were retrieved from the Critical Care Medicine Database (MIMIC-IV, v2.2). The primary outcome was mortality during hospitalization. The propensity score matching (PSM) method was used to analyze the basic conditions during hospitalization between groups.The FI-Lab was analysed for its relationship with in-hospital mortality using logistic regression according to continuous and categorical variables, respectively, and described using the restricted cubic spline (RCS). Survival was compared between groups using Kaplan-Meier (KM) curves. Subgroup analyses were used to improve the stability of the results. Results A total of 9219 patients were included. A cohort score of 1803 matched patients was generated after PSM. The analyses showed that non-surviving patients with septic shock in the ICU had a high FI-Lab index (P

Background Currently, research on the factors influencing the health status of older adults with multimorbidity in China is scattered, and it is difficult to give a comprehensive consideration from a holistic perspective, and the contribution of factors leading to health disparities is not explored, resulting in the ineffectiveness of current health management often programs in older adults with multimorbidity. Objective By introducing a health bifactor model, this study aims to understand the endogenous and exogenous influencing factors and their contributions to the health of older adults with multimorbidity and provide a practical basis for developing precise health management plans for older adults with multimorbidity. Methods In this study, using the China Health and Retirement Longitudinal Survey (CHARLS) 2018 data and introducing the two-factor model of health developed from the Grossman health production function (including both endogenous and exogenous aspects of health determinants). First, the Wilcoxon rank sum test was used to analyze whether there were differences in the health status of older adults with multimorbidity by gender. Secondly, the OLS regression model was used to analyze the mechanism of the two-factor model of health on the health of older adults with multimorbidity. Finally, the Shapley value method was further used to decompose the contribution of health endogenous factors to their health. Results The study found that factors such as still drinking alcohol, having no disease control methods, being satisfied with medical services, having a high level of education, having a pension, not using health services, attending free health checks, caring for grandchildren and being satisfied with their children's relationship were more likely to improve the health of older people with multiple chronic conditions. The results of the Shapley decomposition showed that socioeconomic status was the most important factor in the full sample, while family health support, health-related behaviors, and health-related behaviors were the most important factors. Coping strategies was the next most important, and social health resources was the least influential. In the gender subgroup analysis, socioeconomic status remained the most important factor; for older men with multiple chronic illnesses, health-related behaviors were the next most important factor; for older women with multiple chronic illnesses, coping strategies were the next most important. Conclusion The health status of older men with multimorbidity is better than that of women, socioeconomic status is the most important factor affecting the health of older adults with multimorbidity, and the remaining four dimensions have different contributions to the health differences between men and women. It is recommended that precise health management should be implemented according to the size of the contribution of each dimension of different health endogenous factors to improve the health status of older adults with multimorbidity with maximum benefit.

Background: Insulin resistance is linked to an increased risk of frailty, yet the comprehensive relationship between the triglyceride glucose-body mass index (TyG-BMI), which reflects weight, and frailty, remains unclear. This relationship is investigated in this study. Methods: Data from 9135 participants in the China Health and Retirement Longitudinal Study (2011–2020) were analysed. Baseline TyG-BMI, changes in the TyG-BMI and cumulative TyG-BMI between baseline and 2015, along with the frailty index (FI) over nine years, were calculated. Participants were grouped into different categories based on TyG-BMI changes using K-means clustering. FI trajectories were assessed using a group-based trajectory model. Logistic and Cox regression models were used to analyse the associations between the TyG-BMI and FI trajectory and frail incidence. Nonlinear relationships were explored using restricted cubic splines, and a linear mixed-effects model was used to evaluate FI development speed. Weighted quantile regression was used to identify the primary contributing factors. Results: Four classes of changes in the TyG-BMI and two FI trajectories were identified. Individuals in the third (OR = 1.25, 95% CI: 1.10–1.42) and fourth (OR = 1.83, 95% CI: 1.61–2.09) quartiles of baseline TyG-BMI, those with consistently second to highest (OR = 1.49, 95% CI: 1.32–1.70) and the highest (OR = 2.17, 95% CI: 1.84–2.56) TyG-BMI changes, and those in the third (OR = 1.20, 95% CI: 1.05–1.36) and fourth (OR = 1.94, 95% CI: 1.70–2.22) quartiles of the cumulative TyG-BMI had greater odds of experiencing a rapid FI trajectory. Higher frail risk was noted in those in the fourth quartile of baseline TyG-BMI (HR = 1.42, 95% CI: 1.28–1.58), with consistently second to highest (HR = 1.23, 95% CI: 1.12–1.34) and the highest TyG-BMI changes (HR = 1.58, 95% CI: 1.42–1.77), and those in the third (HR = 1.10, 95% CI: 1.00-1.21) and fourth quartile of cumulative TyG-BMI (HR = 1.46, 95% CI: 1.33–1.60). Participants with persistently second-lowest to the highest TyG-BMI changes (β = 0.15, 0.38 and 0.76 respectively) and those experiencing the third to fourth cumulative TyG-BMI (β = 0.25 and 0.56, respectively) demonstrated accelerated FI progression. A U-shaped association was observed between TyG-BMI levels and both rapid FI trajectory and higher frail risk, with BMI being the primary factor. Conclusion: A higher TyG-BMI is associated with the rapid development of FI trajectory and a greater frail risk. However, excessively low TyG-BMI levels also appear to contribute to frail development. Maintaining a healthy TyG-BMI, especially a healthy BMI, may help prevent or delay the frail onset. [ABSTRACT FROM AUTHOR]

Background: Frailty is a severe, common co-morbidity associated with congestive heart failure (CHF). This retrospective cohort study assesses the association between frailty and the risk of mortality in critically ill CHF patients. Methods: Eligible patients with CHF from the Medical Information Base for Intensive Care IV database were retrospectively analyzed. The frailty index based on laboratory tests (FI_Lab) index was calculated using 33 variables to assess frailty status. The primary outcomes were in-hospital mortality and oneyear mortality. The secondary outcomes were the incidence of acute kidney injury (AKI) and the administration of renal replacement therapy (RRT) in patients with concurrent AKI. Survival disparities among the FI_Lab subgroups were estimated with Kaplan-Meier survival analysis. The association between the FI_Lab index and mortality was examined with Cox proportional risk modeling. Results: A total of 3273 adult patients aged 18 years and older were enrolled in the study, with 1820 men and 1453 women included. The incidence rates of in-hospital mortality and one-year mortality rate were 0.96 per 1,000 person-days and 263.8 per 1,000 person-years, respectively. Multivariable regression analysis identified baseline FI_Lab > 0.45 as an independent risk factor predicting in-Abbreviations: AKI, acute kidney injury; APS III, acute physiology score III; CCI, Charlson comorbidity index; CHF, congestive heart failure; CI, confidential interval; FI_Lab, frailty index based on laboratory tests; HR, hazard ratio; ICU, intensive care unit; IDI, integrated discrimination improvement; IQR, interquartile range; LODS, logistic organ dysfunction system; MIMIC-IV, medical information mart for intensive care IV; NRI, net reclassification improvement; OASIS, Oxford acute severity of illness score; OR, odds ratio; RRT, renal replacement therapy; SAPS II, simplified acute physiology score II; SD, standard deviation; SIRS, systemic inflammatory response syndrome; SOFA, sequential organ failure assessment. hospital mortality (odds ratio = 3.221, 95% CI 2.341-4.432, p < 0.001) and one-year mortality (hazard ratio=2.152, 95% CI: 1.730-2.678, p < 0.001). In terms of predicting mortality, adding FI_Lab to the six disease severity scores significantly improved the overall performance of the model (all p < 0.001). Conclusions: We established a positive correlation between the baseline FI_Lab and the likelihood of adverse outcomes in critical CHF patients. Given its potential as a reliable prognostic tool for such patients, further validation of FI_Lab across multiple centers is recommended for future research. [ABSTRACT FROM AUTHOR]

Advanced age is an independent risk factor for cardiovascular diseases in both sexes. This is thought to be due, in part, to age-dependent cellular, structural, and functional changes in the heart, a process known as cardiac aging. An emerging view is that cardiac aging leads to the accumulation of cellular and subcellular deficits that increase susceptibility to cardiovascular diseases. Still, people age at different rates, with those aging rapidly considered frail. Evidence suggests that frailty, rather than simply age, is a major risk factor for cardiovascular disease and predicts adverse outcomes in those affected. Recent studies in mouse models of frailty show that many adverse changes associated with cardiac aging are more prominent in mice with a high degree of frailty. This suggests that frailty sets the stage for late life cardiovascular diseases to flourish and raises the possibility that treating frailty may treat cardiovascular diseases. These studies show that ventricular dysfunction increases with frailty in males only, whereas atrial dysfunction increases with frailty in both sexes. These results may shed light on the reasons that men and women can be susceptible to different cardiovascular diseases as they age, and why frail individuals are especially vulnerable to these disorders. [ABSTRACT FROM AUTHOR]

Background: The ageing process is characterized by a change of body composition with an increase of fat mass and a reduction of muscle mass. Above a certain threshold these alterations configure a condition named sarcopenic obesity (SO). SO is associated with physical frailty in Asian and Brazilian populations. SO impacts on physical frailty in other ethnic groups but its influence on general frailty which is multidimensional and includes cognitive, social and physical factors, remain insufficiently explored in the Italian population. Methods: Frailty was measured in community dwelling Italian older adults enrolled in the FRASNET study with the frailty index (FI). The FI quantifies frailty as the ratio of the number of present health deficits to the total number of health deficits considered. Regression analyses were performed to assess the association between body composition categories and frailty. Classification and regression tree models were run to evaluate the frailty predictors. Results: One Thousand One Hundred Fourteen participants of the FRASNET study were included in the present analysis. The sample was composed for the 60.5% by females and its median age was 72 years. The median FI score was 0.11 (IQR 0.07–0.20); 234 individuals (21%) were frail (FI ≥ 0.25). SO (B 0.074, 95% C.I. 0.05–0.1, p < 0.001) and pre-sarcopenia (without obesity B 0.03, 95% C.I, 0.007–0.044, p < 0.001, with obesity B 0.11, 95% C.I. 0.05–0.16, p < 0.001) were associated with frailty. Fat mass percentage predicted frailty in people aged 65–70 years whereas, muscle strength predicted general frailty in people aged 70–81 years. Conclusion: Pre-sarcopenia and SO represent potentially treatable predictors of frailty. [ABSTRACT FROM AUTHOR]

Background: With increasing trend of internet use in all age groups, whether internet use can prevent frailty in middle-aged and older adults remains unclear. Methods: Five cohorts, including Health and Retirement Study (HRS), China Health and Retirement Longitudinal Study (CHARLS), the Survey of Health, Ageing and Retirement in Europe (SHARE), English Longitudinal Study of Aging (ELSA), and Mexican Health and Aging Study (MHAS), were used in this study. Internet use, social isolation, and frailty status was assessed using similar questions. The Generalized estimating equations models, random effects meta-analysis, COX regression, and mediation analysis were utilized. Results: In the multicohort study, a total of 155,695 participants were included in main analysis. The proportion of internet use was varied across countries, ranging from 5.56% in China (CHARLS) to 83.46% in Denmark (SHARE). According to the generalized estimating equations models and meta-analysis, internet use was inversely associated with frailty, with the pooled ORs (95%CIs) of 0.72 (0.67,0.79). The COX regression also showed that participants with internet use had a lower risk of frailty incidence. Additionally, the association was partially mediated by social isolation and slightly pronounced in participants aged 65 and over, male, not working for payment, not married or partnered, not smoking, drinking, and not co-residence with children. Conclusions: Our findings highlight the important role of internet use in preventing frailty and recommend more engagements in social communication and activities to avoid social isolation among middle-aged and older adults. [ABSTRACT FROM AUTHOR]

Purpose: Frailty in HIV is extensively explored in epidemiological and clinical studies; it is infrequently assessed as an outcome in routine care. The focus on health-related quality of life (HRQL) measures in HIV presents a unique opportunity to understand frailty at a larger scale. The objective was to identify the extent to which generic and HIV-related HRQL measures capture information relevant to frailty. Methods: A systematic mapping review using directed and summative content analyses was conducted. An online search in PubMed/Medline identified publications on frailty indices and generic and HIV-related HRQL measures. Directed content analysis involved identifying contributors, components, and consequences of frailty from the frailty indices based on the International Classification of Functioning, Disability, and Health framework. Summative content analysis summarized the results numerically. Results: Electronic and hand search identified 447 review publications for frailty indices; nine reviews that included a total of 135 unique frailty indices. The search for generic and HIV-related HRQL measures identified 2008 records; five reviews that identified 35 HRQL measures (HIV-specific: 17; generic: 18). Of the 135 frailty indices, 88 cover more than one frailty dimension and 47 cover only physical frailty. Contributors to frailty, like sensory symptoms and nutrition, are extensively covered. Components of frailty such as physical capacity, cognitive ability, and mood are also extensively covered. Consequences of frailty namely self-rated health, falls, hospitalization, and health services utilization are incomprehensively covered. HRQL measures are informative for contributing factors, components of frailty, and a consequence of frailty. Conclusion: HRQL items and measures show a strong potential to operationalize multidimensional frailty and physical frailty. The study suggests that these measures, connected to evidence-based interventions, could be pivotal in directing resources toward vulnerable populations to mitigate the onset of frailty. [ABSTRACT FROM AUTHOR]

Despite the increasing prevalence of cervical odontoid fractures in older adults, the treatment strategy is controversial. The objectives of the current study are to investigate the prognosis and complications of cervical odontoid fractures in elderly patients and to identify factors associated with worsening of ambulation after 6 months. This multicenter, retrospective study included 167 patients aged 65 years or older with odontoid fractures. Patient demographic and treatment data were investigated and compared according to the treatment strategy. To determine associations with worsening ambulation after 6 months, we focused on the treatment strategies (nonsurgical treatment [collar immobilization or halo vest], conversion to surgery, or initial surgery) and patients' background. Patients who received nonsurgical treatment were significantly older, and patients who underwent surgery had more Anderson-D'Alonzo type 2 fractures. Of the patients initially treated nonsurgically, 26% later underwent surgery. Numbers of complications, including death, and degrees of ambulation after 6 months did not differ significantly among treatment strategies. Patients who had worsened ambulation after 6 months were significantly more likely to be older than 80 years, to have needed assistance with walking before injury, and to have cerebrovascular disease. Multivariable analysis showed that a score of ≥2 on the 5-item modified frailty index (mFI-5) was significantly associated with worsening ambulation. Preinjury mFI-5 scores of ≥2 were significantly associated with worsening ambulation 6 months after treatment of cervical odontoid fractures in older adults. [ABSTRACT FROM AUTHOR]

The association between frailty and psychiatric disorders has been reported in observational studies. However, it is unclear whether frailty facilitates the appearance of psychiatric disorders or vice versa. Therefore, we conducted a bidirectional Mendelian randomization (MR) study to evaluate the causality. Independent genetic variants associated with frailty index (FI) and psychiatric disorders were obtained from large genome-wide association studies (GWAS). The inverse variance weighted method was utilized as the primary method to estimate causal effects, followed by various sensitivity analyses. Multivariable analyses were performed to further adjust for potential confounders. The present MR study revealed that genetically predicted FI was significantly and positively associated with the risk of major depressive disorder (MDD) (odds ratio [OR] 1.79, 95 % confidence interval [CI] 1.48–2.15, P = 1.06 × 10−9), anxiety disorder (OR 1.61, 95 % CI 1.19–2.18, P = 0.002) and neuroticism (OR 1.38, 95 % CI 1.18–1.61, P = 3.73 × 10−5). In the reverse MR test, genetic liability to MDD (beta 0.232, 95 % CI 0.189–0.274, P = 1.00 × 10−26) and neuroticism (beta 0.128, 95 % CI 0.081–0.175, P = 8.61 × 10−8) were significantly associated with higher FI. Multivariable analyses results supported the causal association between FI and MDD and neuroticism. Restriction to European populations, and sample selection bias. Our study suggested a bidirectional causal association between frailty and MDD neuroticism, and a positive correlation of genetically predicted frailty on the risk of anxiety disorder. Developing a deeper understanding of these associations is essential to effectively manage frailty and optimize mental health in older adults. • Genetically predicted FI was positively associated with the risk of MDD, anxiety disorder and neuroticism. • Genetic liability to MDD and neuroticism were significantly associated with higher FI. • Multivariate MR analysis supported the causal association between FI and MDD, and between FI and neuroticism. [ABSTRACT FROM AUTHOR]

Background and Objectives: Frailty has become a public health challenge in China. To investigate the association of foods consumption and physical activity with prefrailty and frailty among older Chinese adults in urban communities. Methods and Study Design: In a cross-sectional study from February to July 2023, 1183 older adults aged between 65y-88y were enrolled from urban communities in Chongqing and Shandong province, China. Frailty Index (FI) was applied to measure prefrailty and frailty. Partial proportional odds model was used to assess the association between foods consumption, physical activity and prefrailty/frailty. Results: Higher Dietary Diversity Score (DDS), (OR=0.61, 95% CI=0.46-0.80; OR=0.47, 95% CI=0.28-0.79), Consuming animalbased foods ≥2 times/day (OR=0.62, 95% CI=0.47-0.82; OR=0.54, 95% CI=0.33-0.88), soy products ≥2 times/week (OR=0.69, 95% CI=0.53-0.89; OR=0.51, 95% CI=0.31-0.84), fresh vegetables ≥2 times/day (OR=0.42, 95% CI=0.31-0.57; OR=0.41, 95% CI=0.23-0.72), and nuts ≥2 times/week (OR=0.71, 95% CI=0.55- 0.91; OR=0.52, 95% CI=0.32-0.85) was associated with a lower risk of prefrailty and frailty. In addition, higher frequency and longer duration of walking (OR=0.61, 95% CI=0.42-0.88; OR=0.63, 95% CI=0.48-0.81), exercise (OR=0.48, 95% CI=0.35-0.64; OR=0.44, 95% CI=0.32-0.61) per week were significantly associated with lower risk of prefrailty. Furthermore, higher frequency and longer duration of walking (OR=0.42, 95% CI=0.25-0.72; OR=0.46, 95% CI=0.29-0.74), and housework (OR=0.39, 95% CI=0.24-0.65; OR=0.57, 95% CI=0.34-0.96) per week, were significantly associated with lower frailty. Conclusions: Higher DDS and higher frequency of animal- based foods, soy products, fresh vegetables, and nuts consumption is significantly associated with lower risk of prefrailty and frailty. Additionally, walking and exercising are significantly associated with lower risk of prefrailty, while walking and doing housework is significantly associated with lower frailty. [ABSTRACT FROM AUTHOR]

Background and Objectives: Observational research findings have demonstrated correlations between diet and the process of aging. Nevertheless, there remains uncertainty regarding possible disruption caused by confounding variables. To elucidate the connections between diet and aging, we employed the Mendelian randomization analysis. Methods and Study Design: The exposure factor was the daily diet, whereas accelerated aging was measured through telomere length, facial aging (FA), frailty index (FI), and senescence-associated secretory phenotypes (SASPs), representing the outcome factors. The primary analysis employed IVW analysis, with additional MR-Egger and Weighted Median analyses conducted to assess the reliability of the findings. Furthermore, we analyzed the heterogeneity and pleiotropy of the results. Results: The results revealed that the consumption of salad/raw vegetables and oily fish exhibited a negative correlation with FA, whereas coffee intake showed a positive correlation with FA. On the other hand, the intake of cheese, oily fish, dried fruit, and cereal showed negative associations with FI. Additionally, coffee, alcohol, and pork intake were positively associated with FI. Lastly, the intake of bread exhibited a positively correlated with SASPs, while the intake of cheese and coffee showed a negative correlation with SASPs. Conclusions: Our study revealed that the consumption of cheese, vegetables, oily fish, dried fruit, bread, coffee, and alcohol was associated with the aging process. Interestingly, our findings suggest that coffee intake may accelerate aging, whereas intake of oily fish may delay the aging process. However, it is important to note that further well-designed prospective studies are required to validate our findings in the future. [ABSTRACT FROM AUTHOR]

Background The frailty index (FI) is commonly used to estimate frailty in end-stage kidney disease (ESKD) patients. The Clinical Frailty Scale (CFS) is a less time-consuming alternative. We aimed to determine the test performance of the CFS for pre-dialysis and dialysis patients and patients receiving conservative therapy from the Dialysis Centre Apeldoorn. Methods In this cross-sectional study, haemodialysis, peritoneal dialysis, pre-dialysis patients and patients receiving conservative therapy from the Dialysis Centre Apeldoorn were included and subjected to frailty assessment. Nephrologists not familiar with the CFS completed the frailty score after medical consultation. The sensitivity, specificity and area under the curve (AUC) of the CFS were determined. The FI was used as the gold standard. Results Included were 144 patients, of whom 60 (41.7%) were considered frail according to the FI. The mean age was 67.4 ± 13.5 years and 56 (38.9%) were female. The cut-off point of the CFS for 'vulnerable' (CFS ≥4) had a sensitivity of 63.3%, a specificity of 81.0% and an AUC of 0.72. The cut-off point of the CFS for 'frail' (CFS ≥5) had a sensitivity of 50.0%, a specificity of 91.7% and an AUC of 0.71. Conclusions The CFS is a quick and easy-to-use tool for the determination of frailty in ESKD patients with a high prevalence of frailty. Nevertheless, the sensitivity of the CFS in the present study was considered too low to implement into daily clinical practice. The sensitivity might be increased by training nephrologists in the use of the CFS. [ABSTRACT FROM AUTHOR]

Background Poor cardiovascular health (CVH) and physical frailty were reported to increase mortality risk, but their joint effects have not been fully elucidated. Objectives We aimed to explore the separate and joint effects of CVH and frailty on mortality based on two perspectives of Life's Essential 8 (LE8) and Framingham Risk Score (FRS). Methods 21 062 participants in the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018 were involved in this study. CVH was evaluated by the LE8 and FRS, and categorized into low, moderate and high CVH groups. Cox proportional hazard models were applied to estimate the separate and joint associations of CVH and frailty index (FI) with all-cause, cardiovascular disease (CVD) and cancer mortality. Results Over a median follow-up period of 87 months (95% CI: 86.0–88.0), 2036 deaths occurred. The separate linear dose–response relationships between CVH, frailty and mortality were observed (nonlinear P  > .05). The combination of low CVH/frailty was negatively associated with all-cause mortality [hazard ratio (HR) and 95%CI: low LE8*FI, 5.30 (3.74, 7.52); high FRS*FI, 4.34 (3.20, 5.88)], CVD mortality [low LE8*FI, 6.57 (3.54, 12.22); high FRS*FI, 7.29 (3.92, 13.55)] and cancer mortality [low LE8*FI, 1.99 (1.14, 3.25); high FRS*FI, 2.32 (1.30, 4.15)], with high CVH/fit group as reference. Further stratified analyses showed that the combined burden of mortality from frailty and low CVH was greater among the young and females. Conclusions Low CVH and frailty were independently and jointly correlated with greater risk of all-cause, CVD and cancer deaths, especially among the young and females. [ABSTRACT FROM AUTHOR]

Purpose: Frailty is common in critically ill patients but the timing and optimal method of frailty ascertainment, trajectory and relationship with care processes remain uncertain. We sought to elucidate the trajectory and care processes of frailty in critically ill patients as measured by the Clinical Frailty Scale (CFS) and Frailty Index (FI). Methods: This is a multi-centre prospective cohort study enrolling patients ≥ 50 years old receiving life support > 24 h. Frailty severity was assessed with a CFS, and a FI based on the elements of a comprehensive geriatric assessment (CGA) at intensive care unit (ICU) admission, hospital discharge and 6 months. For the primary outcome of frailty prevalence, it was a priori dichotomously defined as a CFS ≥ 5 or FI ≥ 0.2. Processes of care, adverse events were collected during ICU and ward stays while outcomes were determined for ICU, hospital, and 6 months. Results: In 687 patients, whose age (mean ± standard deviation) was 68.8 ± 9.2 years, frailty prevalence was higher when measured with the FI (CFS, FI %): ICU admission (29.8, 44.8), hospital discharge (54.6, 67.9), 6 months (34.1, 42.6). Compared to ICU admission, aggregate frailty severity increased to hospital discharge but improved by 6 months; individually, CFS and FI were higher in 45.3% and 50.6% patients, respectively at 6 months. Compared to hospital discharge, 18.7% (CFS) and 20% (FI) were higher at 6 months. Mortality was higher in frail patients. Processes of care and adverse events were similar except for worse ICU/ward mobility and more frequent delirium in frail patients. Conclusions: Frailty severity was dynamic, can be measured during recovery from critical illness using the CFS and FI which were both associated with worse outcomes. Although the CFS is a global measure, a CGA FI based may have advantages of being able to measure frailty levels, identify deficits, and potential targets for intervention. [ABSTRACT FROM AUTHOR]

Background: Frailty has been associated with mental illness (MI) observational studies, but the causal relationship between these factors remains uncertain. We aimed to assess the bidirectional causality between frailty and MI by two-sample Mendelian randomization (MR) analyses. Methods: To investigate the causal relationship among them, summary statistics of frailty index (FI) and six types of MI: anxiety, depression, affective disorder, mania, schizophrenia, and obsessive-compulsive disorder (OCD) were included in this MR study. This MR analysis was performed using inverse variance weighting (IVW), MR-Egger regression, and weighted median. The stability of the results was evaluated using Cochran’s Q test, MR-Egger intercept test, Funnel Plots, and leave-one-out analysis. Results: Genetic predisposition to FI was significantly associated with increased anxiety (odds ratio [OR] = 1.62, 95% confidence interval [CI] 1.13-2.33, P = 8.18E03), depression (OR = 1.88, 95% CI 1.30-2.71, P = 8.21E-04), affective disorder (OR = 1.70, 95% CI 1.28-2.27, P = 2.57E-04). However, our study findings do not demonstrate a causal relationship between FI and mania (OR = 1.02, 95% CI 0.99-1.06, P = 2.20E-01), schizophrenia (OR = 1.02, 95% CI 0.07-0.86, P = 9.28E-01). In particular, although the IVW results suggest a potential causal relationship between FI and OCD (OR = 0.64, 95% CI 0.07-0.86, P = 2.85E-02), the directions obtained from the three methods we employed ultimately show inconsistency. Therefore, the result must be interpreted with caution. The results of the reverse MR analysis indicated a statistically significant and causal relationship between anxiety (OR = 1.06, 95% CI 1.01-1.11, P = 2.00E-02), depression (OR = 1.14, 95% CI 1.04-1.26, P = 7.99E-03), affective disorder (OR = 1.15, 95% CI 1.09-1.21, P = 3.39E-07), and schizophrenia (OR = 1.02, 95% CI 1.01-1.04, P = 1.70E-03) with FI. However, our findings do not provide support for a link between mania (OR = 1.46, 95% CI 0.79-2.72, P = 2.27E-01), OCD (OR = 1.01, 95% CI 1.00-1.02, P = 2.11E-01) and an increased risk of FI. Conclusion: The MR results suggest a potential bidirectional causal relationship between FI and anxiety, depression, and affective disorder. Schizophrenia was found to be associated with a higher risk of FI. The evidence was insufficient to support a causal relationship between Fl and other Ml. These findings offer new insights into the development of effective management strategies for frailty and MI. [ABSTRACT FROM AUTHOR]

Purpose: Frailty is a vulnerable state to stressors due to the loss of physiological reserve as a result of multisystem dysfunction. The physiological and laboratory-based frailty index (FI-Lab), depending on laboratory values and vital signs, is a powerful tool to capture frailty status. The aim of this study was to assess the relationship between FI-Lab and in-hospital mortality in patients with septic shock. Methods: Baseline data for patients with sepsis in the intensive care unit were retrieved from the Critical Care Medicine Database (MIMIC-IV, v2.2). The primary outcome was mortality during hospitalization. The propensity score matching (PSM) method was used to analyze the basic conditions during hospitalization between groups.The FI-Lab was analysed for its relationship with in-hospital mortality using logistic regression according to continuous and categorical variables, respectively, and described using the restricted cubic spline (RCS). Survival was compared between groups using Kaplan-Meier (KM) curves. Subgroup analyses were used to improve the stability of the results. Results: A total of 9219 patients were included. A cohort score of 1803 matched patients was generated after PSM. The analyses showed that non-surviving patients with septic shock in the ICU had a high FI-Lab index (P<0.001). FI-Lab, whether used as a continuous or categorical variable, increased with increasing FI-Lab and increased in-hospital mortality (P<0.001).Subgroup analyses showed similar results. RCS depicts this non-linear relationship. KM analysis shows the cumulative survival time during hospitalisation was significantly lower as FI-Lab increased (log-rank test, P<0.001). Conclusion: Elevated FI-Lab is associated with increased in-hospital mortality in patients with septic shock. [ABSTRACT FROM AUTHOR]

Aims: Frailty is highly prevalent in patients with heart failure (HF), but a concordant definition of this condition is lacking. The Heart Failure Association of the European Society of Cardiology (HFA‐ESC) proposed in 2019 a new multi‐domain definition of frailty, but it has never been validated. Methods and results: Patients from the HELP‐HF registry were stratified according to the number of HFA‐ESC frailty domains fulfilled and to the cumulative deficits frailty index (FI) quintiles. Prevalence of frailty and of each domain was reported, as well as the rate of the composite of all‐cause death and HF hospitalization, its single components, and cardiovascular death in each group and quintile. Among 854 included patients, 37 (4.3%), 206 (24.1%), 365 (42.8%), 217 (25.4%), and 29 (3.4%) patients fulfilled zero, one, two, three, or four domains, respectively, while 179 patients had a FI < 0.21 and were considered not frail. The 1‐year risk of adverse events increased proportionally to the number of domains fulfilled (for each criterion increase, all‐cause death or HF hospitalization: hazard ratio [HR] 1.43, 95% confidence interval [CI] 1.27–1.62; all‐cause death: HR 1.72, 95% CI 1.46–2.02, HF hospitalizations: subHR 1.21, 95% CI 1.04–1.31; cardiovascular death: HR 1.77, 95% CI 1.45–2.15). Consistent results were found stratifying the cohort for FI quintiles. The FI as a continuous variable demonstrated higher discriminative ability than the number of domains fulfilled (area under the curve = 0.68 vs. 0.64, p = 0.004). Conclusion: Frailty in patients at risk for advanced HF, assessed via a multi‐domain approach and the FI, is highly prevalent and identifies those at increased risk of adverse events. The FI was found to be slightly more effective in identifying patients at increased risk of mortality. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is a common malignant tumor that primarily affects the elderly population. Surgery is one of the main treatment modalities for CRC. Frailty is a prevalent characteristic among the elderly and a leading cause of mortality. The frailty index (FI) is a comprehensive tool for assessing patients' frailty status, quantifying indicators such as weight loss, fatigue, and nutritional status, to reflect the degree of frailty. In recent years, the FI has undergone modifications to more accurately evaluate the risk of surgical complications and prognosis in CRC patients. This review summarizes the methods for frailty assessment, the development and modifications of the FI, and compiles the research findings and applications of the FI in predicting surgical complications, postoperative recovery, and survival rates in CRC patients. Furthermore, limitations in the current modified frailty index (mFI) and future research directions are discussed. This review provides essential references for further understanding the role of frailty in CRC patients and the clinical application of the mFI. [ABSTRACT FROM AUTHOR]

Background: Recent studies have reported an association between presurgical frailty and postoperative delirium. However, it remains unclear whether the frailty‐delirium relationship differs by measurement tool (e.g., frailty index vs. frailty phenotype) and whether frailty is associated with delirium, independent of preoperative cognition. Methods: We used the successful aging after elective surgery (SAGES) study, a prospective cohort of older adults age ≥70 undergoing major non‐cardiac surgery (N = 505). Preoperative measurement of the modified mini‐mental (3MS) test, frailty index and frailty phenotype were obtained. The confusion assessment method (CAM), supplemented by chart review, identified postoperative delirium. Delirium feature severity was measured by the sum of CAM‐severity (CAM‐S) scores. Generalized linear models were used to determine the relative risk of each frailty measure with delirium incidence and severity. Subsequent models adjusted for age, sex, surgery type, Charlson comorbidity index, and 3MS. Results: On average, patients were 76.7 years old (standard deviation 5.22), 58.8% of women. For the frailty index, the incidence of delirium was 14% in robust, 17% in prefrail, and 31% in frail patients (p < 0.001). For the frailty phenotype, delirium incidence was 13% in robust, 21% in prefrail, and 27% in frail patients (p = 0.016). Frailty index, but not phenotype, was independently associated with delirium after adjustment for comorbidities (relative risk [RR] 2.13, 95% confidence interval [CI] 1.23–3.70; RR 1.61, 95% CI 0.77–3.37, respectively). Both frailty measures were associated with delirium feature severity. After adjustment for preoperative cognition, only the frailty index was associated with delirium incidence; neither index nor phenotype was associated with delirium feature severity. Conclusion: Both the frailty index and phenotype were associated with the development of postoperative delirium. The index showed stronger associations that remained significant after adjusting for baseline comorbidities and preoperative cognition. Measuring frailty prior to surgery can assist in identifying patients at risk for postoperative delirium. See related Editorial by Callahan and Kuchel in this issue. [ABSTRACT FROM AUTHOR]

The aim of this article is to provide frailty education that is relevant to the orthopaedic surgeon. An ageing population has led to an increase in the number of orthopaedic operations in patients living with frailty. Accumulating evidence suggests that a patient's outcome is better estimated by measuring their frailty score rather than their chronological age. If a patient lives with frailty, they are much more susceptible to complications and mortality. This article will explain how to identify frailty, what complications are associated with frailty and when, and what, interventions can be used to help reduce complications. It will also educate on current British Orthopaedic Association and Centre for Perioperative Guidelines for patients living with frailty, for both trauma and elective patients. [ABSTRACT FROM AUTHOR]

Objectives: Carotid intima-media-thickness (cIMT) is predictive of future cardiovascular events, increases with chronological age, and greater in males. The accumulation of health deficits (or frailty) is a marker of biological age. However, normative cIMT values are lacking and would be an important comparative tool for healthcare providers and researchers. This study aimed to establish sex-specific normative cIMT values across chronological age and frailty levels (i.e. biological age). Methods: Frailty and right common cIMT data were extracted from the Canadian Longitudinal Study of Aging baseline comprehensive cohort of middle-aged and older adults (n = 10,209; 5000 females). cIMT was assessed via high-resolution ultrasound. Frailty was determined using a 52-item frailty index. Ordinary least squares and quantile regressions were conducted between age (years or frailty index) with cIMT (average or maximum), separately for males and females. Results: In both sexes, average and maximum cIMT increased with higher chronological age and frailty. Both cIMT metrics increased non-linearly (quadratic-cIMT term) with advancing age (β-coefficients for quadratic and linear terms: all, p < 0.001), except for the linear relationship between average and maximum cIMT with chronological age among males (p < 0.001). Sex-specific normative average and maximum cIMT values were established (1st–99th percentiles, 5% increments), separately for chronological and biological ages. Conclusions: This is the largest sample of adults to establish normative cIMT outcomes that includes older adults. The chronological age and frailty-related normative cIMT outcomes will serve as a useful resource for healthcare professionals and researchers to establish "normal" age- and sex-specific cIMT values. [ABSTRACT FROM AUTHOR]