Higher Risk Of Frailty Research Articles

Revascularization in frail patients with acute coronary syndromes: a retrospective longitudinal study.

Frailty is increasingly prevalent in people presenting with acute coronary syndrome (ACS). This high-risk group is typically excluded from trials of interventions in ACS, and there is uncertainty about the risks and benefits of invasive management. Patients with an ACS diagnosis between 2010 and 2015 in England were identified from Hospital Episode Statistics, with linked Office for National Statistics mortality data. Frailty was defined by the Hospital Frailty Risk Score. Causal inference analysis used regional variation in revascularization as an instrumental variable to estimate average treatment effects of revascularization on cardiovascular mortality up to 5 years in people presenting with ACS and low-, intermediate-, or high-risk frailty. The analysis included 565 378 ACS patients, of whom 11.6% (n = 65 522) were at intermediate risk and 4.7% (n = 26 504) were at high risk of frailty. Intermediate and high frailty risks were associated with reduced likelihood of echocardiography, invasive angiography, or revascularization and increased likelihood of mortality and major adverse cardiovascular events compared with low frailty risk. Cardiovascular death at 5 years was 78.6%, 77.3%, and 75.7% in people at low, intermediate, and high frailty risk, respectively. Instrumental variable analysis suggested that revascularization resulted in a higher absolute reduction in cardiovascular mortality in high and intermediate frail risk patients compared with low risk at 1-year post-ACS. Frailty is common in people presenting with ACS, where cardiovascular causes are the principal mode of death. Revascularization is associated with short- and long-term survival benefits in people at intermediate and high risk of frailty after adjustment for measured and unmeasured confounders.

A Neglected Point: Frailty in Older Adults with Differentiated Thyroid Cancer.

This study investigated the risk of frailty in older adults with differentiated thyroid cancer (DTC) and the effect of thyroid- stimulating hormone (TSH) levels on frailty. This single-center, cross-sectional study included 70 DTC patients aged ≥60 years with stable TSH levels during the previous year while receiving levothyroxine. Frailty was assessed using the fried frailty phenotype (FFP). Anterior thigh muscle thickness was measured by ultrasound, and the sonographic thigh adjustment ratio (STAR) index was calculated. Muscle strength was measured using a hand dynamometer. Physical activity was determined by the physical activity scale for the elderly (PASE). The median (interquartile range) age and follow-up time were 65 years (62 to 71) and 11 years (7.0 to 14.2), respectively. The median TSH level was 1.10 μIU/mL (0.49 to 1.62), and 58.6% of patients were prefrail/frail. Muscle mass and strength were reduced in 35.7% and 17.2% of patients, respectively. TSH levels were lower in those with prefrailty/frailty (P=0.002), low muscle mass (P=0.014), and low strength (P=0.037) than in their normal counterparts. TSH levels correlated negatively with FFP (P= 0.001) and positively with the STAR index (P=0.034). TSH below 1.325 μIU/mL was associated with an increased frailty risk (area under the curve=0.719; P=0.001). Low TSH, female sex, low handgrip strength, and low PASE leisure time scores emerged as independent predictors of frailty (P<0.05). Older adults with lower TSH levels due to DTC are at high frailty risk and have low muscle mass and strength. Therefore, TSH targets should be set based on a comprehensive evaluation with consideration of the risk-benefit ratio.

Impact of Frailty on COVID-19 Hospitalizations: Results from the California State Inpatient Database.

Frail patients are at greater risk of experiencing adverse clinical outcomes in any critical illness due to decreased physiologic reserves, greater susceptibility to the adverse effects of treatment, and greater needs for intensive care. In this study, we sought to assess the prevalence of frailty and associated adverse in-hospital outcomes among coronavirus disease 2019 (COVID-19) hospitalizations using the 2020 California State Inpatient Database (SID). For this study, we conducted a retrospective analysis of data from all COVID-19 hospital patients aged 18 years and older. We identified hospitalizations that were at high risk of frailty using the Hospital Frailty Risk Score. The primary outcome of our study was in-hospital mortality, and the secondary outcomes were prolonged length of stay, vasopressor use, mechanical ventilation, and intensive care unit admission. The prevalence of frailty was 44.3% among COVID-19 hospitalizations. Using propensity score matching analysis, we found that the odds of mortality (odds ratio [OR] 4.54, 95% confidence interval [CI] 4.28-4.82), prolonged length of stay (OR 2.81, 95% CI 2.70-2.90), vasopressor use (OR 8.65, 95% CI 7.45-10.03), mechanical ventilation (OR 6.90, 95% CI 6.47-7.35), and intensive care unit admission (OR 7.17, 95% CI 6.71-7.66) were significantly higher among the group of frail patients. Our findings show that frailty could be used for assessing and risk stratifying patients for improved hospital outcomes.

Development of a Frailty Prediction Model Among Older Adults in China: A Cross-Sectional Analysis Using the Chinese Longitudinal Healthy Longevity Survey.

To identify the risk factors associated with frailty among older adults in China and develop a predictive model for assessing their frailty risk. Secondary cross-sectional analysis. The 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) provided data for this study. A total of 9006 participants were included in the analysis. Their general demographic, socioeconomic status and health behaviour risk factors were collected in the CLHLS. Frailty was assessed using the Frailty Index. A visual nomogram model was constructed based on independent predictors identified using multivariate analysis. The nomogram's discrimination and calibration capabilities were evaluated using the C-statistics and calibration curves. A 1000-times resampling enhanced bootstrap method was performed for internal validation of the nomogram. The results showed that living in rural settings, having a primary education level, having a spouse, having basic living security, smoking, drinking, exercising and social activities were protective factors against frailty. Increasing age, being underweight or obese, adverse self-assessed economic status and poor sleep quality were risk factors of frailty. The AUC values of the internal validation set were 0.830. The calibration curve was close to ideal. The Brier score was 0.122. The above results showed that the nomogram model had a good predictive performance. A simple and fast frailty risk prediction model was developed in this study to help healthcare professionals screen older adults at high risk of frailty in China. The frailty risk prediction model will assist healthcare professionals in risk management and decision-making and provide targeted frailty prevention interventions. Screening high-risk older adults and early intervention can reduce the risk of adverse outcomes and save medical expenses for older adults and society, thereby realising cost-effective planning of health resources and healthy ageing. No patient or public contribution. This study was a cross-sectional, secondary analysis of the CLHLS data.

Prehabilitation in Patients at Risk of Poorer Outcomes Following Total Knee Arthroplasty: A Systematic Review

IntroductionWhile total knee arthroplasty (TKA) is a generally successful procedure, 10 to 30% of patients still report suboptimal outcomes after surgery. Prehabilitation may offer potential benefits to improve poorer outcomes, although its effectiveness remains uncertain. Our study aimed to assess the efficacy of prehabilitation interventions on patients at risk of poor outcomes following TKA. MethodThere were six electronic databases searched up until December 2023. All randomized controlled trials (RCTs) comparing prehabilitation versus usual care in adult patients with osteoarthritis undergoing primary TKA and at risk of poorer outcomes were included. There were four reviewers who independently extracted data and assessed the risk of bias for each study. ResultsThe 13 included studies assessed prehabilitation among patients at risk of poor outcomes, identified with various factors including range of motion deficit, functional limitations, high body mass index, psychological factors, frailty, older age, central sensitization, and high risk of discharge to inpatient rehabilitation. The interventions were initiated across a wide range, from four to 277 days before surgery. The efficacy of exercise therapy and multidisciplinary rehabilitation remains inconclusive due to limited, low-quality evidence. The results failed to indicate that various forms of non-exercise therapy, including education, psychological intervention, and weight loss therapy, were effective in improving outcomes after TKA. The included studies have major limitations such as small sample size, inappropriate comparators, substantial clinical heterogeneity in intervention characteristics, inadequate blinding for providers and participants, a lack of justification for identifying patients at risk of poor recovery, and a lack of appropriate interventions for managing modifiable factors. ConclusionWhile our finding fails to show that non-exercise therapy is effective, results of exercise therapy and multidisciplinary rehabilitation remain inconclusive. Further high-quality research is warranted to establish evidence on modifiable factors predictive of poorer postoperative outcomes and investigate how they can be effectively managed.

Differences in Health Care Expenditures by Cancer Patients During Their Last Year of Life: A Registry-Based Study.

During the last year of life, persons with cancer should probably have similar care needs and costs, but studies suggest otherwise. A study of direct medical costs (excluding costs for expensive prescription drugs) was performed based on registry data in Stockholm County, which covers 2.4 million inhabitants, for all deceased persons with cancer during 2015-2021. The data were mainly analyzed with the aid of multiple regression models, including Generalized Linear Models (GLMs). In a population of 20,431 deceased persons with cancer, the costs increased month by month (p < 0.0001). Higher costs were mainly associated with lower age (p < 0.0001), higher risk of frailty, as measured by the Hospital Frailty Risk Scale (p < 0.0001), and having a hematological malignancy. In a separate model, where those 5% with the highest costs were identified, these variables were strengthened. Sex and socio-economic groups on an area level had little or no significance. Systemic cancer treatments during the last month of life and acute hospitals as place of death had only a moderate impact on costs in adjusted models. Higher costs are mainly related to lower age, higher frailty risk and having a hematological malignancy, and the effects are both statistically and clinically significant despite the fact that expensive drugs were not included. On the other hand, the costs were mainly comparable in regard to sex or socio-economic factors, indicating equal care.

Analysis of the potential profile and influencing factors for oral frailty in olderly patients with dental implants

ObjectiveTo investigate the current state of oral frailty in oldely patients with require dental implants, analyze influencing factors in the characteristics of oral frailty across different patient categories, and provide a reference for clinical staff to identify high-risk groups and develop proactive management strategies.MethodsBetween January 2024 and March 2024, 654 patients with dental implants were selected using convenience sampling from six secondary and tertiary stomatological hospitals in Jiangsu and Zhejiang provinces. Data were collected via a general information questionnaire and the Oral Frailty Index-8. The latent profiles of oral frailty were examined, and univariate and Logistic regression analyses were conducted to determine the impact of various factors on these profiles.ResultsIn this cross-sectional study, 605 valid questionnaires were returned, yielding an effective rate of 92.58%. The mean oral frailty score was 6.64 ± 1.21, with the sample comprising 223 males and 382 females, averaging 72.54 ± 6.33 years old. Oral frailty was categorized into three latent profiles: high (20.50%), moderate (53.72%), and low (25.78%) frailty groups. Factor analysis indicated that age, gender, education level, family income, number of implants, and dyslipidemia significantly predicted the classification of these profiles (P < 0.05).ConclusionOral frailty in oldely patients with dental implants exhibits heterogeneity and is influenced by age, sex, education level, family income, number of implants, and dyslipidemia. Clinical staff should recognize the characteristics of different patient categories and implement proactive measures for those at high risk of oral frailty to enhance their quality of life.

Fragilidad del adulto mayor con enfermedad renal crónica. Un estudio observacional de centro único

Introduction: Frailty in the elderly (AM) increases morbidity and mortality. This condition is highly prevalent in Chronic Kidney Disease (CKD) and, together with frailty, greatly affects physical, cognitive, and emotional capacity. The study aimed to determine frailty in older adults with CKD in a reference center in Cuenca-Ecuador. Methods: The present observational study was conducted at the “José Carrasco Arteaga” Hospital from September 2020 to April 2021. Older adults with a diagnosis of CKD were included; patients with disabilities, severe cognitive impairment, and those with palliative care were excluded. The direct source variables are demographic, clinical, physical activity, functional capacity, mood, mental state, and frailty. The sample was probabilistic. The Chi2 test is used to compare percentages. Results: 79 cases are analyzed. The MA had 38% frailty, 36.7% were pre-frail, and 25.3% were robust. A more significant proportion of 'young' AM was observed in patients classified as robust. A more substantial proportion of robust patients were receiving clinical treatment, while patients in the hemodialysis program were classified as frail. The most significant proportion of robust patients had mild degrees of renal failure, while frail patients were classified as CKD grades 4 and 5. Physical activity was active primarily in robust patients and mostly passive in patients with frailty. Conclusion: Conclusion: there is a high prevalence of frailty in this population group, especially in women and those between 75 and 85 years old. The results suggest that CKD in older adults is associated with a higher risk of frailty, dependence, and comorbidities, which underlines the importance of implementing multidisciplinary and personalized interventions to improve the quality of life and prognosis of these patients.

Association between dietary diversity changes and frailty among Chinese older adults: findings from a nationwide cohort study

BackgroundDietary diversity has been suggested as a potential preventive measure against frailty in older adults, but the effect of changes in dietary diversity on frailty is unclear. This study was conducted to examine the association between the dietary diversity score (DDS) and frailty among older Chinese adults.MethodsA total of 12,457 adults aged 65 years or older were enrolled from three consecutive and nonoverlapping cohorts from the Chinese Longitudinal Healthy Longevity Survey (the 2002 cohort, the 2005 cohort, and the 2008 cohort). DDS was calculated based on nine predefined food groups, and DDS changes were assessed by comparing scores at baseline and the first follow-up survey. We used 39 self-reported health items to assess frailty. Cox proportional hazard models were performed to examine the association between DDS change patterns and frailty.ResultsParticipants with low-to-low DDS had the highest frailty incidence (111.1/1000 person-years), while high-to-high DDS had the lowest (41.1/1000 person-years). Compared to the high-to-high group of overall DDS pattern, participants in other DDS change patterns had a higher risk of frailty (HRs ranged from 1.25 to 2.15). Similar associations were observed for plant-based and animal-based DDS. Compared to stable DDS changes, participants with an extreme decline in DDS had an increased risk of frailty, with HRs of 1.38 (1.24, 1.53), 1.31 (1.19, 1.44), and 1.29 (1.16, 1.43) for overall, plant-based, and animal-based DDS, respectively.ConclusionsMaintaining a lower DDS or having a large reduction in DDS was associated with a higher risk of frailty among Chinese older adults. These findings highlight the importance of improving a diverse diet across old age for preventing frailty in later life.

2346 Modified hospital frailty risk score (mHFRS) as a tool to identify frail hospitalised older adults

Abstract Introduction Frailty is common in hospitalised older adults. This study compared efficacy of a modified Hospital Frailty Risk Score (mHFRS) to standard HFRS and Clinical Frailty Scale (CFS) to determine whether mHFRS can be used to identify frail hospitalised patients. Methods Anonymised retrospective review of Electronic Health Records was undertaken in patients = &amp;gt; 65 years old attending the Emergency Department (ED) and admitted to hospital 1st July 2022 to 31st March 2023. mHFRS utilises 2 prior emergency admissions within 2 years to generate a frailty risk score, whereas HFRS requires an index admission plus 2 prior emergency admissions. Hospitalisation outcomes and predictive models were evaluated with correlation and measures of agreement between CFS and HFRS, CFS and mHFRS using Spearman’s rank correlation and Cohen’s kappa. Results Of 3042 patients, CFS categorised 1635 patients as non-frail (CFS 1–4) and 1407 as frail (CFS 5–9). Using mHFRS, only 1623 patients could be categorised and of these, 608 were deemed low, 657 intermediate and 358 high risk of frailty. Frail patients were older (81.8 years, SD 8.41 vs 75.3 years, SD 7.20, p = &amp;lt;.001), had significantly longer LOS (52.5% % vs 31.5%, p = &amp;lt;0.001), higher 30-day unplanned hospital readmissions (18.5% vs 9.9%, p = &amp;lt;0.001), and higher in-patient (6.1% vs 2.0%, p &amp;lt; 0.001), 30-day (9.1% vs 2.3%, p &amp;lt; 0.001), and 90-day (15.8% vs 5.1%, p &amp;lt; 0.001) mortality. mHFRS achieved comparable association with hospitalisation outcomes compared to CFS &amp; HFRS. Cohens’s kappa, showed fair agreement across HFRS and mHFRS, κ of 0.235 0.243 respectively. mHFRS was less sensitive at identifying frail patients but had better specificity to identify non frail patients. Conclusion mHFRS is a comparable frailty screening tool that doesn’t require clinical assessment but is standardised and easy to use in those who can be scored.

A high hospital frailty risk score indicates an increased risk for complications following surgical treatment of proximal humerus fractures

BackgroundApproximately 70 % of proximal humerus fractures (PHF) occur after the age of 60. High complication rates have been described in correlation with the treatment of PHF. Major risk factors for the outcome might be frailty, mobility and comorbidities of patients at the time of hospital admission. The aim of this study was to create risk adjusted quality indicators for surgical treatment of proximal humerus fractures based on German claims data and to evaluate the impact of the Hospital Frailty Risk Score (HFRS) on risk adjustment. MethodsRetrospective claims data (2015–2021) were used to create risk adjusted quality indicators for eight outcomes by clustered multivariable logistic regression. The comparison of different risk adjustment model performances was done by ROC-AUC and Standardized Mortality/Morbidity Ratios. ResultsIn total, N = 34,912 patients (median age 75 years, 80.3 % female) were included. The most common surgical procedure was open reduction and internal fixation with plate osteosynthesis with 39.7 %, followed by reverse shoulder arthroplasty with 25.3 %. The most influential risk factor for all outcomes was a high HFRS with an Odds Ratio of 2.0 (95 %-Confidence Interval 1.8–2.3) for any secondary surgery (365 days) up to an Odds Ratio of 17.6 (95 %-Confidence Interval 14.9–20.8) for general complications during the index stay. ConclusionComparative quality reporting for the surgical treatment of PHF appears feasible with the developed models for risk adjustment using claims data. Preoperative evaluation of HFRS in PHF can contribute to risk assessment, and individual patient management. It therefore enables personalized treatment decisions.

Association between complete blood count-derived inflammatory markers and the risk of frailty and mortality in middle-aged and older adults.

This study aimed to evaluate the association between six complete blood count (CBC)-derived inflammatory markers [neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), systemic inflammatory response index (SIRI), and pan-immune inflammation value (PIV)] and the risk of frailty and mortality. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Mortality was identified using the National Death Index until December 31, 2019. Multiple logistic regression analysis was conducted to evaluate the association between six CBC-derived inflammatory markers and frailty. The Cox regression model assessed the association between six CBC-derived inflammatory markers and mortality in frail populations. Restricted cubic spline (RCS) was used to visualize the association of the six CBC-derived inflammatory markers with mortality risk. The predictive value of CBC-derived inflammatory markers for mortality was further assessed using a random survival forest (RSF) approach. This study analyzed data from a total of 16,705 middle-aged and older participants. Among them, 6,503 participants were frail, with a mortality rate of 41.47%. Multiple logistic regression analysis showed that NLR, MLR, PLR, SII, SIRI, and PIV were positively associated with frailty risk. The Cox regression model revealed that participants in the highest quartile had a significantly increased risk of death compared to those in the lowest quartile: NLR (HR = 1.73, 95% CI:1.54, 1.94), MLR (HR = 1.71, 95% CI:1.51, 1.93), PLR (HR = 1.28, 95%CI: 1.15, 1.43), SII (HR = 1.50, 95%CI:1.34, 1.68), SIRI (HR = 1.88, CI 95%:1.67, 2.12), PIV (HR = 1.55, 95%CI:1.38, 1.73). Random survival forest (RSF) analyses demonstrated that MLR had the highest predictive value for mortality risk middle-aged and older adult frail participants. The results suggest that CBC-derived inflammatory markers are associated with a higher risk of frailty as well as mortality in the middle and old-aged population of the United States.

Group-based trajectories of potentially preventable hospitalisations among older adults after a hip fracture

SummaryKey predictors of three trajectory group membership of potentially preventable hospitalisations were age, the number of comorbidities, the presence of chronic obstructive pulmonary disease and congestive heart failure, and frailty risk at the occurrence of hip fracture. These predictors of their trajectory group could be used in targeting prevention strategies.PurposeAlthough older adults with hip fracture have a higher risk of multiple readmissions after index hospitalisation, little is known about potentially preventable hospitalisations (PPH) after discharge. This study examined group-based trajectories of PPH during a five-year period after a hip fracture among older adults and identified factors predictive of their trajectory group membership.MethodsThis retrospective cohort study was conducted using linked hospitalisation and mortality data in New South Wales, Australia, between 2013 and 2021. Patients aged ≥ 65 years who were admitted after a hip fracture and discharged between 2014 and 2016 were identified. Group-based trajectory models were derived based on the number of subsequent PPH following the index hospitalisation. Multinominal logistic regression examined factors predictive of trajectory group membership.ResultsThree PPH trajectory groups were revealed among 17,591 patients: no PPH (89.5%), low PPH (10.0%), and high PPH (0.4%). Key predictors of PPH trajectory group membership were age, number of comorbidities, dementia, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), frailty risk, place of incident, surgery, rehabilitation, and length of hospital stay. The high PPH had a higher proportion of patients with ≥ 2 comorbidities (OR: 1.86, 95% confidence interval (CI): 1.04–3.32) and COPD (OR: 2.97, 95%CIs: 1.76–5.04) than the low PPH, and the low and high PPHs were more likely to have CHF and high frailty risk as well as ≥ 2 comorbidities and COPD than the no PPH.ConclusionsIdentifying trajectories of PPH after a hip fracture and factors predictive of trajectory group membership could be used to target strategies to reduce multiple readmissions.

The independent and combined effects of physical activity and depressive symptoms on frailty in community-dwelling older adults: A cross-sectional study.

To investigate the independent and combined effects of physical activity (PA) and depressive symptoms on the risk of frailty in community-dwelling older adults. Older adults face a high risk of frailty which is commonly used to predict adverse health outcomes in older patients. Engaging in PA and without depressive symptoms are crucial factors to prevent frailty. It is essential to investigate the independent and combined effects of these two variables on the risk of frailty. We included 3392 community-dwelling older adults. The FRAIL Scale was used to assess older adults' frail status (robust, prefrail and frail). Multiple logistic regression was utilized to examine the independent and combined effects of PA and depressive symptoms on the risk of prefrailty and frailty. The combined effects were visualized by marginal plots. The prevalence of prefrailty and frailty in older adults were 42.16% and 10.58%. Compared with the group of "Light physical activity and With depressive symptoms", "Vigorous physical activity and Without depressive symptoms" had the lowest risk of prefrailty and frailty. Older adults who do not engage in PA or have depressive symptoms increased the risk of frailty, but older adults with depressive symptoms could lower the risk of frailty through PA. It is effective to reduce the risk of frailty by directing older adults to do moderate physical activity, although they have depressive symptoms. The focus should also be on older adults with depressive symptoms, who have at least more than twice and fourfold risk of prefrailty and frailty compared to those without. This study offers insights for future interventions aimed at preventing frailty in older adults. This study adhered to the STROBE checklist. Older adults participated in this study and completed questionnaires.

Comparative study of the risk prediction model of early postoperative frailty in elderly enterostomy patients based on machine learning methods.

Based on machine learning method, four types of early postoperative frailty risk prediction model of enterostomy patients were constructed to compare the performance of each model and provide the basis for preventing early postoperative frailty of elderly patients with enterostomy. The prospective convenience sampling method was conducted and 362 early postoperative enterostomy patients were selected in three hospitals from July 2020 to November 2023 in Shanghai, four different prediction models of Support Vector Machine (SVM), Bayes, XG Boost, and Logistic regression were used and compared the test effects of the four models (MCC, F1, AUC, and Brier index) to judge the classification performance of the four models in the data of this study. A total of 21 variables were included in this study, and the predictors mainly covered demographic information, stoma-related information, quality of life, anxiety and depression, and frailty. The validated models on the test set are XGBoost, Logistic regression, SVM prediction model, and Bayes on the MCC and F1 scores; on the AUC, XGBoost, Logistic regression, Bayes, and SVM prediction model; on the Brier scores, Bayes, Logistic regression, and XGBoost. XGBoost based on machine learning method is better than SVM prediction model, Logistic regression model and Bayes in sensitivity and accuracy. Quality of life in the early postoperative period can help guide clinical patients to identify patients at high risk of frailty and reduce the incidence of early postoperative frailty in elderly patients with enterostomy.

Exploring the correlates of frailty among hospitalized older adults: A cross-sectional study in a Saudi teaching hospital.

Frailty is an important public health concern associated with aging. It increases the risk of adverse clinical outcomes, such as falls, late-life dependency, hospitalization, disability, and mortality. The objectives of this study were to estimate the prevalence of frailty and to identify factors associated with frailty among older adults (≥65 years) admitted to King Abdulaziz University Hospital, Jeddah, Saudi Arabia. This cross-sectional study was conducted at King Abdulaziz University Hospital. The data were collected during the months of January and February 2022 and included demographic characteristics, comorbidities, length of stay, and hospital mortality. Frailty status of participants was assessed using the Clinical Frailty Scale. A total of 147 patients (aged ≥ 65 years) were included in our study. The prevalence rates of frailty and non-frailty were 71.4% and 28.6%, respectively. Frail patients had higher comorbidity index (P = .003), polypharmacy (P = .003), heart failure (P = .001), and prolonged hospital stays (P = .007). The results of the multiple logistic regression revealed that the tall patients had a lower risk of frailty (odds ratio = 0.0089, 95% confidence interval: 0.0001-0.7588, P = .042) and patients with higher comorbidity indexes had higher risk of frailty (odds ratio = 1.4907, 95% confidence interval: 1.1449-1.9927, P = .004). In this study, more than two-thirds of the hospitalized older patients were classified as frail. High comorbidity index, heart failure, and polypharmacy were strong predictors of frailty. Patients with frailty were more likely to have a prolonged hospital stay than those without frailty. Therefore, early detection of frailty and proper intervention are essential for improving health outcomes in this vulnerable population.

Association between added sugars and frailty in U.S. adults: a cross-sectional study from the National Health and Nutrition Examination Survey 2007-2018.

There are various detrimental effects of excessive added sugar consumption on health, but the association of added sugars with frailty remains elusive. We aimed to examine the association between added sugar intake and frailty among American adults in the present cross-sectional study. This cross-sectional study is based on the National Health and Nutrition Examination Survey (NHANES) database. Data from NHANES spanning from 2007 to 2018 on frailty, added sugars, and covariates were collected. Added sugars were categorized into quartiles according to the recommended percentages by institutions. Weighted multivariable logistic regression was used to analyze the relationship between frailty and added sugars. Subgroup analysis was conducted based on sex, age, body mass index (BMI), smoking, alcohol consumption, hypertension, and diabetes status. This study included 16,381 participants, with 13,352 (81.51%) in the non-frailty group and 3,029 (18.49%) in the frailty group. We found that added sugars were positively associated with frailty, and subgroup analysis showed that participants who were male, over the age of 60, had a low BMI, had previously smoked and consumed alcohol, had no hypertension, or had diabetes mellitus (DM) were more likely to be frail. Added sugar intake was positively associated with frailty. Subgroup analysis showed that the association was strongest in males, those aged >60, those with a low BMI, former smokers, former alcohol consumers, and people with no hypertension or DM. When added sugars are classified by energy percentage, populations with more than 25% of their energy coming from added sugars have similar results, with a higher prevalence of frailty. Added sugars are positively associated with a higher risk of frailty, and the association is stable among different populations.

Prediction model related to 6-year risk of frailty in older adults aged 65 years or above in China

Objective: To develop a prediction tool for 6-year incident risk of frailty among Chinese older adults aged 65 years or above. Methods: Data from the Chinese Longitudinal Healthy Longevity Survey from 2002 to 2018 was used, including 13 676 older adults aged 65 years or above who were free of frailty at baseline. Key predictors of frailty were identified via the least absolute shrinkage and selection operator (LASSO) method, and were thereafter used to predict the incident frailty based on the Cox proportional hazards regression model. The model was internally validated by 2 000 Bootstrap resamples and evaluated for the performance of discrimination and calibration using the area under the receiver operating characteristic curve (AUC) and calibration curve, respectively. The net benefit of the developed prediction tool was evaluated by decision-curve analysis. Results: The M(Q1, Q3) age and follow-up time of the participants were 81.0 (71.0, 90.0) years and 6.0 (4.1, 9.2) years, respectively. A total of 4 126 older persons (30.2%) were recorded with frailty incidents during the follow-up, with the corresponding incidence density of 41.8/1 000 person-years. A total of 15 key predictors of frailty were selected by LASSO, namely, age, sex, race, education years, meat consumption, tea drinking, performing housework, raising domestic animals, playing cards or mahjong, and baseline status of visual function, activities of the daily living score, instrumental activities of the daily living score, hypertension, heart disease, and self-rated health. The prediction model was internally validated with an AUC of 0.802, with the max Youden's index of 0.467 at a risk threshold of 19.0%. The calibration curve showed high consistency between predicted probabilities and observed proportions of frailty events. The decision curve indicated that higher net benefits could be obtained via the prediction model than did strategies based on intervention in all or none participants for any risk threshold less than 59%, and the model-based net benefit was estimated to be 0.10 at a risk threshold of 19.0%. Conclusions: The herein developed 6-year incident risk prediction model of frailty, based on easily accessible questionnaires and physical examination variables, has good predictive performance. It has application potential in identifying populations at high risk of incident frailty.

Impact of frailty on hospitalized patients with prostate cancer: A retrospective analysis.

e23054 Background: The impact of Hospital frailty risk score on outcomes in hospitalized patients with prostate cancer has not been previously studied. This research aimed to examine the association between frailty and prostate cancer outcomes. Methods: This retrospective study utilized hospitalization data from the National Inpatient Sample (NIS) between January 1, 2020, and December 31, 2020. Data of patients with a primary or secondary discharge diagnosis of prostate cancer (ICD10-CM codes C61.0, D07.5, and Z85.46) were obtained. The objective was to evaluate the correlation between frailty and prostate cancer. Multivariate analysis was performed, stratified by race, age, Charlson index, median annual income in the patient's zip code, hospital bed size, teaching status, and census division of the hospital. Results: A total of 51,980 hospitalizations for prostate cancer were identified, with 72.7% in the intermediate to high frailty score (IHFS) group and 27.3% in the low frailty score (LFS) group. The IHFS group had a higher unadjusted in-hospital mortality rate than the LFS group (5.85% vs. 1.2%). Patients with IHFS had increased odds of adjusted mortality compared to those with LFS (adjusted odds ratio [aOR] = 4.45, 95% Cl [3.80-5.22], P &lt; 0.01). Hispanic and Black race patients also had increased odds of adjusted mortality compared to Caucasian race patients (aOR = 1.42, 95%CI [1.19-1.70], P &lt; 0.01); aOR = 1.16, 95%CI [1.00-1.32], P = 0.037, respectively). Additionally, the IHFS group had longer lengths of stay (5.65 ± 0.038 vs. 3.26 ± 0.28 days) and higher adjusted total costs ($66,107 ± 850 vs. $64,308 ± 1066) compared to the LFS group. Conclusions: Patients with prostate cancer and a high hospital frailty risk score exhibited significantly higher mortality rates, longer lengths of stay, and increased total adjusted costs. Frailty assessment plays a crucial role in predicting outcomes in patients with prostate cancer. Physicians can use frailty assessment to stratify patients based on risk and improve their ability to anticipate consequences.

High Throughput Plasma Proteomics and Risk of Heart Failure and Frailty in Late Life

ImportanceHeart failure (HF) and frailty frequently coexist and may share a common pathobiology, although the underlying mechanisms remain unclear. Understanding these mechanisms may provide guidance for preventing and treating both conditions.ObjectiveTo identify shared pathways between incident HF and frailty in late life using large-scale proteomics.Design, Setting, and ParticipantsIn this cohort study, 4877 aptamers (Somascan v4) were measured among participants in the community-based longitudinal Atherosclerosis Risk In Communities (ARIC) cohort study at visit 3 (V3; 1993-1995; n = 10 638) and at visit 5 (V5; 2011-2013; n = 3908). Analyses were externally replicated among 3189 participants in the Cardiovascular Health Study (CHS). Data analysis was conducted from February 2022 to June 2023.ExposuresProtein aptamers, measured at study V3 and V5.Main Outcomes and MeasuresOutcomes assessed included incident HF hospitalization after V3 and after V5, prevalent frailty at V5, and incident frailty between V5 and visit 6 (V6; 2016-2017; n = 4131). Frailty was assessed using the Fried criteria. Analyses were adjusted for age, gender, race, field center, hypertension, diabetes, smoking status, body mass index, estimated glomerular filtration rate, prevalent coronary heart disease, prevalent atrial fibrillation, and history of myocardial infarction. Mendelian randomization (MR) analysis was performed to assess potential causal effects of candidate proteins on HF and frailty.ResultsA total of 4877 protein aptamers were measured among 10 638 participants at V3 (mean [SD] age, 60 [6] years; 4886 [46%] men). Overall, 286 proteins were associated with incident HF after V3 (822 events; P < 1.0 × 10−5), 83 of which were also associated with incident after V5 (336 events; P < 1.7 × 10−4). Among HF-free participants at V5 (n = 3908; mean [SD] age, 75 [5] years; 1861 [42%] men), 48 of 83 HF-associated proteins were associated with prevalent frailty (223 cases; P < 6.0 × 10−4), 18 of which were also associated with incident frailty at V6 (152 cases; P < 1.0 × 10−3). These proteins enriched fibrosis and inflammation pathways and demonstrated stronger associations with incident HF with preserved ejection fraction (HFpEF) than HF with reduced ejection fraction. All 18 proteins were associated with both prevalent frailty and incident HF in CHS. MR identified potential causal effects of several proteins on frailty and HF.Conclusions and RelevanceIn this study, the proteins associated with risk of HF and frailty enrich for pathways related to inflammation and fibrosis as well as risk of HFpEF. Several of these proteins could potentially contribute to the shared pathophysiology of frailty and HF.