Self-Reported Frailty Screening Tools: Comparing Construct Validity of the Frailty Phenotype Questionnaire and FRAIL

ObjectivesWe examined the construct validity of 2 self-reported frailty questionnaires, the Frailty Phenotype Questionnaire (FPQ) and FRAIL, against the Cardiovascular Health Study frailty phenotype (CHS-FP).DesignCross-sectional data analysis of longitudinal prospective cohort study.Settings and ParticipantsWe included data from 230 older adults (mean age: 67.2 ± 7.4 years) from the “Longitudinal Assessment of Biomarkers for characterization of early Sarcopenia and Osteosarcopenic Obesity in predicting frailty and functional decline in community-dwelling Asian older adults Study” (GeriLABS 2) recruited between December 2017 and March 2019.MethodsWe compared area under receiver operating characteristic curves (AUC), agreement, correlation, and predictive validity against outcome measures [Short Physical Performance Battery, 5 times repeat chair stand (RCS-5), Frenchay activities index, International Physical Activity Questionnaire, life-space assessment, Social Functioning Scale 8 (SFS-8), EuroQol-5 dimensions (utility value)] using logistic regression adjusted for age, gender, and vascular risk factors. We examined concurrent validity across robust versus prefrail/frail for inflammatory blood biomarkers [tumor necrosis factor receptor 1 and C-reactive protein (CRP)] and dual-energy x-ray absorptiometry body composition [bone mineral density (BMD); appendicular lean mass index (ALMI), and fat mass index (FMI)].ResultsPrevalence of prefrail/frail was 25.7%, 14.8%, and 48.3% for FPQ, FRAIL, and CHS-FP, respectively. Compared with FRAIL, FPQ had better diagnostic performance (AUC = 0.617 vs 0.531, P = .002; sensitivity = 37.8% vs 18.0%; specificity = 85.6% vs 88.2%) and agreement (AC1-Stat = 0.303 vs 0.197). FPQ showed good predictive validity [RCS-5: odds ratio (OR) 2.38; 95% CI: 1.17–4.86; International Physical Activity Questionnaire: OR 3.62; 95% CI:1.78–7.34; SFS-8: OR 2.11; 95% CI: 1.64–5.89 vs FRAIL: all P > .05]. Only FRAIL showed concurrent validity for CRP, compared with both FPQ and FRAIL for TNF-R1. FRAIL showed better concurrent validity for BMD, FMI, and possibly ALMI, unlike FPQ (all P > .05).Conclusions and ImplicationsOur results support complementary validity of FPQ and FRAIL in independent community-dwelling older adults. FPQ has increased case detection sensitivity with good predictive validity, whereas FRAIL demonstrates concurrent validity for inflammation and body composition. With better diagnostic performance and validity for blood biomarkers and clinical outcomes, FPQ has utility for early frailty detection in the community setting.     

Validating the Centre of Excellence on Longevity Self-AdMinistered (CESAM) Questionnaire: An Online Self-Reported Tool for Frailty Assessment of Older Adults

ObjectivesSubjective health measures are often used to assess frailty, but the validity of self-reported online tools to identify frailty remains to be established. We aimed to assess concurrent, known-groups, convergent and predictive validity of the Centre of Excellence on Longevity Self-AdMinistered (CESAM) questionnaire for frailty assessment of older adults in an outpatient setting.DesignCross-sectional analysis of 120 participants.Setting and ParticipantsParticipants of age ≥65 were recruited from an outpatient geriatric clinic. Individuals who had severe neurological, cognitive, or motor deficits were excluded.MethodsWe assessed concurrent validity with area under receiver operating characteristic curve (AUC) against the Frailty Index (FI) and Clinical Frailty Scale (CFS). We analyzed known-groups validity between CESAM scores with frailty status (CFS and FI), Modified Barthel Index (MBI), and modified Chinese Mini-Mental State Examination (mCMMSE) using 1-way analysis of variance. We evaluated convergent validity using correlations with MBI, the Lawton index, mCMMSE, and Geriatric Depression Scale (GDS). Associations between CESAM-identified frailty for clinician-diagnosed geriatric syndromes, and health-related quality of life (HRQoL) was analyzed using regression analysis.ResultsThe CESAM questionnaire demonstrated excellent diagnostic performance for frailty using FI ≥0.25 (AUC = 0.88; 95% CI: 0.82–0.94; P < .001) and CFS ≥4 (AUC = 0.78; 95% CI: 0.68–0.88; P < .001). CESAM scores increased significantly with increasing frailty (both CFS and FI), lower MBI, and lower mCMMSE scores (all P < .001), indicating concurrent validity. The moderate-good correlation of CESAM scores with MBI (r = ?0.61; P < 0.001), Lawton Index (r = ?0.54; P < .001), mCMMSE (r = ?0.53; P < .001) and GDS (r = 0.58; P < .001) supports convergent validity. Using a cutoff of ≥8 for frailty identification, CESAM-identified frailty was associated with cognitive impairment (OR = 3.7; 95% CI: 1.7–8.2; P = .001) depression (OR = 4.0; 95% CI: 1.7–9.6; P = .002), falls (OR = 3.1; 95% CI: 1.2–8.2; P = .021) and poorer HRQoL (β = ?0.1; 95% CI: ?0.2 to ?0.02; P = .017).Conclusion and ImplicationsOur results support the validity of an online self-reported tool to identify frailty and geriatric syndromes in an outpatient setting, an approach that is potentially applicable for remote screening of frailty.     

Utility of the Fatigue,Resistance, Ambulation,Illness, and Loss of weight Scale in Older Patients with Cardiovascular Disease

ObjectivesTo compare the Fried criteria for frailty diagnosis with the Frailty Screening Index (FSI) and the fatigue, resistance, ambulation, illness, and loss of weight (FRAIL) scale in older patients with cardiovascular disease (CVD).DesignWe conducted a retrospective 1-year follow-up cohort study of adult inpatients who participated in a cardiac rehabilitation program between June 2016 and September 2018.Setting and ParticipantsWe included 1472 Japanese patients age 65 years and older with CVD. After excluding 765 patients with incomplete frailty measurements, 707 patients were included in the analysis.MethodsFrailty and physical function were measured before hospital discharge according to each of the 3 definitions. Outcomes were all-cause mortality and physical dysfunction.ResultsThe prevalence of frailty according to the Fried criteria, the FRAIL scale, and the FSI was 213 (30.1%), 181 (25.6%), and 186 (26.3%), respectively. The FSI and the FRAIL scale showed moderate agreement with the Fried criteria [vs FSI: K = 0.52, 95% confidence interval (CI): 0.45–0.59; vs FRAIL scale: K = 0.45, 95% CI: 0.37–0.52; all P < .001]. We found a significant correlation between all-cause mortality and frailty assessed by all of the definitions, even after multivariate adjustment [FSI: hazard ratio (HR): 2.43, 95% CI: 1.30–4.58, P = .006; FRAIL scale: HR: 2.32, 95% CI: 1.21–4.45, P = .011; Fried criteria: HR: 1.99, 95% CI: 1.04–3.82, P = .038). However, the prediction accuracy of the FRAIL scale was higher than that of the FSI and comparable to that of the Fried criteria for physical dysfunction.Conclusions and ImplicationsThe FSI and the FRAIL scale showed moderate agreement with the Fried criteria regarding frailty diagnostic performance and had comparable prognostic value. However, only the FRAIL scale was as accurate as the Fried criteria in screening for physical dysfunction.     

Effects of a Multicomponent Frailty Prevention Program in Prefrail Community-Dwelling Older Persons: A Randomized Controlled Trial

ObjectiveTo examine the effects of a multicomponent frailty prevention program in community-dwelling older persons with prefrailty.DesignA randomized controlled trial.SettingA community elderly center in Hong Kong.ParticipantsPersons aged ≥50 years who scored 1-2 on a simple frailty questionnaire (FRAIL)MethodsParticipants (n = 127) were randomly assigned to a 12-week multicomponent frailty prevention program (exercise, cognitive training, board game activities) or to a wait-list control group. The primary outcomes were FRAIL scores, frailty status, and a combined frailty measure including subjective (FRAIL total score) and objective (grip strength, muscle endurance, balance, gait speed) measures. The secondary outcomes were verbal fluency assessed by dual-task gait speed, attention and memory assessed by digit span task, executive function assessed by the Frontal Assessment Battery, self-rated health, and life satisfaction. Assessments were conducted at baseline and at week 12.ResultsThe mean age of the participants was 62.2 years, and 88.2% were women. At week 12, the FRAIL score had decreased in the intervention group (−1.3, P < .001) but had increased in the control group (0.3, P < .01) (between-group differences P < .001). In addition, 83.3% and 1.6% of the intervention and control groups, respectively, had reversed from prefrailty to robust phenotype (between-group differences P < .001). Participants in the intervention group also had a greater reduction in the combined frailty score and greater improvements in muscle endurance, balance, verbal fluency, attention and memory, executive function, and self-rated health than those in the control group (all P < .05). There were no significant differences between the groups with respect to grip strength, gait speed, and life satisfaction.Conclusions and implicationsThe multicomponent frailty prevention program reduced frailty and improved physical and cognitive functions, and self-rated health in community-dwelling older persons with prefrailty. Findings can provide insights into the consideration of incorporating frailty prevention programs into the routine practice of community elderly services.     

FRAIL Scale also Predicts Long-Term Outcomes in Older Patients With Acute Coronary Syndromes

ObjectivesNo previous studies have assessed the role of the FRAIL scale in predicting long-term outcomes in older patients with acute coronary syndromes (ACS).Design, Setting and ParticipantsThe multicenter observational LONGEVO-SCA registry included unselected patients ≥80 years of age with ACS from 44 centers. A comprehensive geriatric assessment was performed during hospitalization.MeasuresFrailty was measured by the FRAIL scale. For the purpose of this study, main outcome measured was mortality or readmission at 24 months.ResultsA total of 498 patients were included. Mean age was 84.3 years. A total of 198 patients (33.1%) were prefrail and 135 (27.1%) frail. Patients who were prefrail and frail had a higher degree of comorbidities, and higher prevalence of disability, cognitive impairment, and nutritional risk. A total of 165 out of 498 patients (33.1%) died, and 331 patients (66.7%) died or were readmitted at 24 months. Both prefrailty and frailty were associated with a higher mortality compared with robust patients (P < .001). The incidence of mortality or readmission was also higher in patients who were prefrail or frail (P < .001). After adjusting for potential confounders, the association between frailty and mortality or readmission remained significant (hazard ratio 1.28 for prefrailty and hazard ratio 1.96 for frailty, P < .001). The FRAIL scale showed an optimal ability for predicting mortality or readmission (area under the receiver operating characteristics curve 0.86, 95% confidence interval 0.83‒0.89). The area under the receiver operating characteristics curve from the Global Registry of Acute Coronary Events risk score was 0.89. No significant differences were observed between both AUC values (P = .163).Conclusions and ImplicationsThe FRAIL scale independently predicted long-term outcomes in older patients with ACS. The predictive ability of this scale was comparable to the strongly recommended Global Registry of Acute Coronary Events risk score. Frailty assessment is mandatory for improving risk prediction in these complex patients.     

Validity and Utility of the Questionnaire-based FRAIL Scale in Older Patients with Heart Failure: Findings from the FRAGILE-HF

ObjectivesWe investigated whether the FRAIL scale questionnaire is consistent with the Fried criteria, predicts all-cause mortality, and reflects physical dysfunction in patients with heart failure (HF).DesignSecondary analysis of FRAGILE-HF, a cohort study that enrolled participants from 2016 to 2018 and followed-up for 1-year of discharge.Setting and ParticipantsA prospective multicenter cohort study in which 15 hospitals in Japan (8 university hospitals and 7 nonuniversity teaching hospitals) participated. We prospectively enrolled 1332 consecutive hospitalized patients ≥65 years old with HF and analyzed 1028 patients after excluding 304 patients with missing data on the FRAIL scale.MethodsThe FRAIL scale, the Fried model, and physical function were measured before discharge. The endpoint was all-cause mortality.ResultsAccording to the FRAIL scale, 459 (44.6%) and 491 (47.8%) were classified as frail and prefrail, respectively. The Kappa coefficient between the FRAIL scale and the Fried criteria were 0.39 [95% confidence interval (CI) 0.34–0.44; P < .001]. The area under the receiver-operating characteristic curves for frailty diagnosed by the Fried criteria of the FRAIL scale was 0.74 (95% CI 0.71–0.76; P < .001). A total of 118 deaths occurred during 1 year of follow-up. After adjusting for the MAGGIC risk score and log-BNP, The FRAIL scale predicted all-cause mortality (hazard ratio 1.17; 95% CI 1.01–1.36; P = .035). The FRAIL scale was also associated with various physical dysfunctions that correlated with poor prognosis.Conclusions and ImplicationsThe FRAIL scale had moderate consistency with the Fried criteria, predicted all-cause mortality, and reflected clinically important physical dysfunctions.     

Frailty in Nursing Homes—A Prospective Study Comparing the FRAIL-NH and the Clinical Frailty Scale

ObjectivesFrailty is common in nursing home (NH) residents, but its prevalence in German institutions is unknown. Valid and easy-to-use screening tools are needed to identify frail residents. We used the FRAIL-NH scale and the Clinical Frailty Scale (CFS) to (1) obtain the prevalence of frailty, (2) investigate the agreement between both instruments, and (3) evaluate their predictive validity for adverse health events in German NH residents.DesignProspective cohort study.Setting and participantsGerman NH residents (n = 246, age 84 ± 8 years, 67% female).MethodsFrailty status was categorized according to FRAIL-NH (nonfrail, frail, most frail) and CFS (not frail, mild to moderately frail, severely frail). Agreement between instruments was examined by Spearman correlation, an area under the receiver operating characteristic curve (AUC) with 95% CI, and sensitivity and specificity using the “most frail” category of FRAIL-NH as reference standard. Adverse health events (death, hospital admissions, falls) were recorded for 12 months, and multivariate cox and logistic regression models calculated.ResultsAccording to FRAIL-NH, 71.1% were most frail, 26.4% frail, and 2.5% nonfrail. According to CFS, 66.3% were severely frail, 26.8% mild to moderately frail, and 6.9% not frail. Both scales correlated significantly (r = 0.78; R² = 60%). The AUC was 0.92 (95% CI 0.88-0.96). Using a CFS cutoff of 7 points, sensitivity was 0.90 and specificity 0.92. The frailest groups according to both instruments had an increased risk of death [FRAIL-NH hazard ratio (HR) 2.19, 95% CI 1.21-3.99; CFS HR 2.56, 95% CI 1.43-4.58] and hospital admission [FRAIL-NH odds ratio (OR) 1.95, 95% CI 1.06-3.58; CFS OR 1.79, 95% CI 1.01-3.20] compared to less frail residents. The FRAIL-NH predicted recurrent faller status (OR 2.57, 95% CI 1.23-5.39).Conclusions and implicationsFrailty is highly prevalent in German NH residents. Both instruments show good agreement despite different approaches and are able to predict adverse health outcomes. Based on our findings and because of its simple administration, CFS may be an alternative to FRAIL-NH for assessing frailty in NHs.     

Comparison of the PROMIS Preference Score (PROPr) and EQ-5D-5L Index Value in General Population Samples in the United Kingdom,France, and Germany

ObjectivesThe Patient-Reported Outcome Measurement Information System (PROMIS) Preference score (PROPr) can be used to assess health state utility (HSU) and estimate quality-adjusted life-years in cost-effectiveness analyses. It is based on item response theory and promises to overcome limitations of existing HSU scores such as ceiling effects. The PROPr contains 7 PROMIS domains: cognitive abilities, depression, fatigue, pain, physical function, sleep disturbance, and ability to participate in social roles and activities. We aimed to compare the PROPr with the 5-level EQ-5D (EQ-5D-5L) in terms of psychometric properties using data from 3 countries.MethodsWe collected PROMIS-29 profile and EQ-5D-5L data from 3 general population samples (United Kingdom = 1509, France = 1501, Germany = 1502). Given that cognition is not assessed by the PROMIS-29, it was predicted by the recommended linear regression model. We compared the convergent validity, known-groups construct validity, and ceiling and floor effects of the PROPr and EQ-5D-5L.ResultsThe mean PROPr (0.48, 0.53, 0.48; P<.01) and EQ-5D-5L scores (0.82, 0.85, 0.83; P<.01) showed significant differences of similar magnitudes (d = 0.34; d = 0.32; d = 0.35; P<.01) across all samples. The differences were invariant to sex, income, occupation, education, and most conditions but not for age. The Pearson correlation coefficients between both scores were r = 0.74, r = 0.69, and r = 0.72. PROPr’s ceiling and floor effects both were minor to moderate. The EQ-5D-5L’s ceiling (floor) effects were major (negligible).ConclusionsBoth the EQ-5D-5L and the PROPr assessed by the PROMIS-29 show high validity. The PROPr yields considerably lower HSU values than the EQ-5D-5L. Consequences for quality-adjusted life-year measurements should be investigated in future research.     

The Hospital Frailty Risk Score Identifies Fewer Cases of Frailty in a Community-Based Cohort of Older Men Than the FRAIL Scale and Frailty Index

ObjectivesThe recently developed Hospital Frailty Risk Score (HFRS) allows ascertainment of frailty from administrative data. We aimed to compare the HFRS against the widely used FRAIL Scale and Frailty Index.DesignPopulation-based cohort study linked to Western Australian Hospital Morbidity Data Collection and Death Registrations.Setting and ParticipantsThe Health in Men Study with frailty determined at Wave 2 (2001/2004), mortality in the 1-year period following Wave 2, and disability at Wave 3 (2008). Participants were 4228 community-based men aged ≥75 years, followed until Wave 3.MeasurementsWe used multivariable regression to determine the association between each frailty measure and outcomes of length of stay (LOS), death, and disability. We also determined if the additional cases of frailty identified by one measure over the other was associated with these outcomes.ResultsOf 4228 men studied, the HFRS (n = 689) identified fewer men as frail than the FRAIL Scale (n = 1648) and Frailty Index (n = 1820). In the fully adjusted models, all 3 frailty measures were associated with longer LOS and mortality, whereas only the FRAIL Scale and Frailty Index were significantly associated with disability. The additional cases of frailty identified by the FRAIL Scale and Frailty Index had longer LOS and greater risks of death and disability. The fully adjusted hazard ratio for death among the additional cases of frailty identified by the FRAIL Scale (compared to being not frail on both HFRS and FRAIL Scale) was 2.14 (95% CI 1.48-3.08).Conclusions and ImplicationsThe HFRS is associated with adverse outcomes. However, it identified approximately 60% fewer men who were frail than the FRAIL Scale and Frailty Index, and the additional cases identified were also at high risks of adverse outcomes. Users of the HFRS should be aware of the differences with other frailty measures.     

Cross-Cultural Adaptation and Validation of the FRAIL Scale in Chinese Community-Dwelling Older Adults

Objective

To cross-culturally adapt and test the FRAIL scale in Chinese community-dwelling older adults.

Quick and Simple FRAIL Scale Predicts Incident Activities of Daily Living (ADL) and Instrumental ADL (IADL) Disabilities: A Systematic Review and Meta-analysis

Objectives

To quantitatively examine frailty defined by FRAIL scale as a predictor of incident disability risks by conducting a systematic review and meta-analysis.

The Clinical Potential of Frailty Indicators on Identifying Recurrent Fallers in the Community: The Mr. Os and Ms. OS Cohort Study in Hong Kong

ObjectivesTo compare the clinical value of 3 frailty indicators in a screening pathway for identifying older men and women who are at risk of falls.DesignA prospective cohort study.Setting and participantsFour thousand Chinese adults (2000 men) aged ≥65 years were recruited from the community in Hong Kong.MethodsThe Cardiovascular Health Study Criteria, the FRAIL scale, and the Study for Osteoporosis and Fracture Criteria (SOF) were included for evaluation. Fall history was used as a comparative predictor. Recurrent falls during the second year after baseline was the primary outcome. The area under the receiver operating characteristic curve (AUC) was used to evaluate the ability of the frailty indicators and fall history to predict recurrent falls. Independent predictors identified in logistic regression were put in the Classification and Regression Tree (CART) analysis to evaluate their performance in screening high-risk fallers.ResultsFall history predicts recurrent falls in both men and women (AUC: men = 0.681; women = 0.645) better than all frailty indicators (AUC ≤ 0.641). After adjusting for fall history, only FRAIL (AUC = 0.676) and SOF (AUC = 0.673) remained as significant predictors for women whereas no frailty indicator remained significant in men.FRAIL could classify older women into 2 groups with distinct chances of being a recurrent faller in people with no fall history (3.8% vs 7.5%), a single fall history (9.5% vs 37.5%), and history of recurrent falls (16.0% vs 30.8%). SOF has limited ability in identifying recurrent fallers in the group of older adults with a single fall history (no fall history: 3.9% vs 8.6%; single fall history: 10.2% vs 10.9%; history of recurrent falls: 16.5% vs 20.6%).Conclusions and implicationsSOF and FRAIL could provide some additional prediction value to fall history in older women but not men. FRAIL could be clinically useful in identifying older women at risk of recurrent falls, especially in those with a single fall history.     

Ability of Self-Reported Frailty Components to Predict Incident Disability,Falls, and All-Cause Mortality: Results From a Population-Based Study of Older British Men

Background

Frailty is a state of increased vulnerability to disability, falls, and mortality. The Fried frailty phenotype includes assessments of grip strength and gait speed, which are complex or require objective measurements and are challenging in routine primary care practice. In this study, we aimed to develop a simple assessment tool based on self-reported information on the 5 Fried frailty components to identify older people at risk of incident disability, falls, and mortality.

Frailty Predicts New and Persistent Depressive Symptoms Among Community-Dwelling Older Adults: Findings From Singapore Longitudinal Aging Study

ObjectiveThis study aimed to examine the cross-sectional and longitudinal relationships between physical frailty at baseline and depressive symptoms at baseline and at follow-up.DesignFour-year prospective study.SettingCommunities in the South East Region of Singapore.ParticipantsWe analyzed data of 1827 older Chinese adults aged 55 and above in the Singapore Longitudinal Aging Study-I.MeasurementsThe frailty phenotype (based on Fried criteria) was determined at baseline, depressive symptoms (Geriatric Depression Scale ≥5) at baseline and follow-ups at 2 and 4 years.ResultsThe mean age of the population was 65.9 (standard deviation 7.26). At baseline, 11.4% (n = 209) had depressive symptoms, 32.4% (n = 591) were prefrail and 2.5% (n = 46) were frail. In cross-sectional analysis of baseline data, the adjusted odds ratios (OR)s and 95% confidence intervals controlling for demographic, comorbidities, and other confounders were 1.69 (1.23–2.33) for prefrailty and 2.36 (1.08–5.15) for frailty, (P for linear trend <.001). In longitudinal data analyses, prospective associations among all participants were: prefrail: OR = 1.86 (1.08–3.20); frail: OR = 3.09 (1.12–8.50); (P for linear trend = .009). Among participants free of depressive symptoms at baseline, similar prospective associations were found: prefrail OR = 2.26 (1.12–4.57); frail: OR = 3.75 (1.07–13.16); (P for linear trend = .009).ConclusionThese data support a significant role of frailty as a predictor of depression in a relatively younger old Chinese population. Further observational and interventional studies should explore short-term dynamic and bidirectional associations and the effects of frailty reversal on depression risk.     

Frailty in Hospitalized Older Adults: Comparing Different Frailty Measures in Predicting Short- and Long-term Patient Outcomes

Objectives

Data for the assessment of frailty in acutely ill hospitalized older adults remains limited. Using the Frailty Index (FI) as “gold standard,” we compared (1) the diagnostic performance of 3 frailty measures (FRAIL, Clinical Frailty Scale [CFS], and Tilburg Frailty Indicator [TFI]) in identifying frailty, and (2) their ability to predict negative outcomes at 12 months after enrollment.

Three Nurse-administered Protocols Reduce Nutritional Decline and Frailty in Older Gastrointestinal Surgery Patients: A Cluster Randomized Trial

ObjectiveTo evaluate the effects of the modified Hospital Elder Life Program (mHELP) comprising 3 nurse-administered protocols in older patients undergoing gastrointestinal (GI) surgery.DesignCluster randomized trial.SettingTwo 36-bed GI wards at a university-affiliated medical center in Taiwan.ParticipantsOlder patients (≥65 years, N = 377) were recruited if they were scheduled for elective GI surgery with an expected length of hospital stay >6 days. After transferring to the GI ward after surgery, participants were randomly assigned to the mHELP or control group (1:1) by room rather than individually because most patient units are double- or triple-occupancy rooms.InterventionThe mHELP protocols (early mobilization, oral and nutritional assistance, and orienting communication) were administered daily with usual care by a trained nurse until hospital discharge. The control group received usual care only.MeasuresOutcomes were in-hospital nutritional decline, measured by body weight and Mini-Nutritional Assessment (MNA) scores, and Fried's frailty phenotype. Return of GI motility was examined as a potential mechanism contributing to observed outcomes.ResultsParticipants (mean age = 74.5 years; 56.8% male) primarily underwent colorectal (56.5%), gastric (21.2%), and pancreatobiliary (13.8%) surgery. Participants who received the mHELP [for a median of 7 days (interquartile range = 6–10 days)] had significantly lower in-hospital weight loss and decline in MNA scores (weight −2.1 vs −4.0 lb, P = .002; score −3.2 vs −4.0, P = .03) than the control group. The mHELP group also had significantly lower rates of incident frailty during hospitalization (12.0% vs 21.7%, P = .022), and persistent frailty (50.0% vs 92.9%, P = .03). Participants in the mHELP group had trends toward an accelerated return of GI motility.Conclusion and ImplicationsThe mHELP effectively reduced nutritional decline, prevented new frailty, and promoted recovery of frailty present before admission. These nurse-administered protocols might be useful in other settings, including conditions managed at home or in nursing facilities.     

Frailty and Clinical Outcomes in Heart Failure: A Systematic Review and Meta-analysis

ObjectiveFrailty is a known risk factor for adverse outcomes after cardiac interventions. However, the extent to which it increases the likelihood of adverse outcomes in heart failure (HF) patients remains unexplored. Therefore, we conducted this systematic review and meta-analysis to quantify the impact of frailty on prognosis in this patient population.DesignMeta-analysis.Setting and ParticipantsPubMed and Embase were searched for studies that investigated the relationship between frailty and outcomes in patients with HF. The search period was from the beginning of the databases through to December 3, 2017.MeasuresA total of 342 and 919 entries were retrieved from PubMed and Embase, respectively. Of these, 20 met our inclusion criteria and were therefore included.ResultsFrailty significantly increased the risk of all-cause mortality [hazard ratio (HR) = 1.59, 95% confidence interval (CI) = 1.39-1.82, P < .0001, I² = 55%] and hospitalizations (HR = 1.31, 95% CI = 1.21-1.42, P < .0001, I² = 0%). Moreover, it was predictive of all-cause mortality after ventricular assist device implantation for advanced HF (HR = 1.62, 95% CI = 1.35-1.94, P < .0001, I² = 2%).Conclusions/Implications: Frailty is a significant predictor of all-cause mortality and hospital readmissions in HF. Assessment and close monitoring of frailty status of heart failure patients can potentially better guide clinical management of this population.     

Differential Association of Frailty and Sarcopenia With Mortality and Disability: Insight Supporting Clinical Subtypes of Frailty

ObjectivesSarcopenia and frailty have been shown separately to predict disability and death in old age. Our aim was to determine if sarcopenia may modify the prognosis of frailty regarding both mortality and disability, raising the existence of clinical subtypes of frailty depending on the presence of sarcopenia.DesignA Spanish longitudinal population-based study.Setting and ParticipantsThe population consists of 1531 participants (>65 years of age) from the Toledo Study of Health Aging.MethodsSarcopenia and frailty were assessed following Foundation for the National Institutes of Health criteria and the Fried Frailty Phenotype, respectively. Mortality was assessed using the National Death Index. Functional status was determined using Katz index. We ran multivariate logistics and proportional hazards models adjusting for age, sex, baseline function, and comorbidities.ResultsMean age was 75.4 years (SD 5.9). Overall, 70 participants were frail (4.6%), 565 prefrail (36.9%), and 435 sarcopenic (28.4%). Mean follow-up was 5.5 and 3.0 years for death and worsening function, respectively. Furthermore, 184 participants died (12%) and 324 worsened their functioning (24.8%). Frailty and prefrailty were associated with mortality and remained significant after adjustment by sarcopenia [hazard risk (HR) 3.09, 95% confidence interval (CI) 1.84-5.18; P < .001; HR 1.58, 95% CI 1.12-2.24, P = .01]. However, the association of sarcopenia with mortality was reduced and became nonsignificant (HR 1.43, 95% CI 0.99-2.07, P = .057) when both frailty and sarcopenia were included in the same model. In the disability model, frailty and sarcopenia showed a statistically significant interaction (P = .016): both had to be present to predict worsening of disability.Conclusions and ImplicationsSarcopenia plays a relevant role in the increased risk of functional impairment associated to frailty, but that seems not to be the case with mortality. This finding raises the need of assessing sarcopenia as a cornerstone of the clinical work after diagnosing frailty.     

Alcohol Consumption and Risk of Incident Frailty: The English Longitudinal Study of Aging

BackgroundAlcohol consumption is a common modifiable lifestyle factor. Alcohol may be a risk factor for frailty, however, there is limited evidence in the literature.ObjectiveThe objectives of this study were to examine the association of alcohol consumption with the risk of incident frailty.MethodsThis is a prospective panel study of 2544 community-dwelling people aged 60 years and older in England. Frailty status defined by frailty phenotype criteria was measured at baseline and 4 years later. Participants free of frailty at baseline were divided into 5 groups based on quantity of self-reported alcohol consumption per week with cut-points at 0, 7, 14, and 21 UK units per week. Adjusted odds ratios (OR) were calculated for incident frailty according to the alcohol consumption using logistic regression models.ResultsCompared with the low consumption group (>0 and ≤7 units per week), incident frailty risk over 4 years was significantly higher among nondrinkers [OR 1.71, 95% confidence interval (CI) 1.12‒2.60, P value = .01], after controlling for sociodemographic confounders. In a supplementary analysis this became nonsignificant after further adjustment for baseline health status. Heavy drinkers (>21 units per week) had a significantly lower incident frailty risk (unadjusted OR 0.45, 95% CI 0.27‒0.75, P < .01), which became nonsignificant on adjustment for sociodemographic factors (OR 0.64, 95% CI 0.37‒1.13, P = .12).Conclusions/ImplicationsWe found that nondrinkers were more likely than those with low alcohol consumption to develop frailty, but this appeared to be explained by poorer baseline health status. No evidence was found for an association between high levels of alcohol consumption and becoming frail. Future studies with information on life-course history of alcohol use, especially for those classified as nondrinkers in old age, are warranted.     

Recovery from Coronavirus Disease 2019 among Older Adults in Post-Acute Skilled Nursing Facilities

ObjectivesTo examine functional outcomes of post-acute care for coronavirus disease 2019 (COVID-19) in skilled nursing facilities (SNFs).DesignRetrospective cohort.Setting and ParticipantsSeventy-three community-dwelling adults ≥65 years of age admitted for post-acute care from 2 SNFs from March 15, 2020, to May 30, 2020.Measure(s)COVID-19 status was determined from chart review. Frailty was measured with a deficit accumulation frailty index (FI), categorized into nonfrail, mild frailty, and moderate-to-severe frailty. The primary outcome was community discharge. Secondary outcomes included change in functional status from SNF admission to discharge, based on modified Barthel index (mBI) and continuous functional scale scored by physical (PT) and occupational therapists (OT).ResultsAmong 73 admissions (31 COVID-19 negative, 42 COVID-19 positive), mean [standard deviation (SD)] age was 83.5 (8.8) and 42 (57.5%) were female, with mean FI of 0.31 (0.01) with no differences by COVID-19 status. The mean length of SNF stay for rehabilitation was 21.2 days (SD 11.1) for COVID-19 negative with 20 (64.5%) patients discharged to community, compared to 23.0 (SD 12.2) and 31 (73.8%) among patients who tested positive for COVID-19. Among those discharged to the community, all groups improved in mBI, PT, and OT score. Those with moderate-to-severe frailty (FI >0.35) had lower mBI scores on discharge [92.0 (6.7) not frail, 81.0 (15.4) mild frailty, 48.6 (20.4) moderate-to-severe frailty; P = .002], lower PT scores on discharge [54.2 (3.9) nonfrail, 51.5 (8.0) mild frailty, 37.1 (9.7) moderate-to-severe frailty; P = .002], and lower OT score on discharge [52.9 (3.2) nonfrail, 45.8 (9.4) mild frailty, 32.4 (7.4) moderate or worse frailty; P = .001].Conclusions and ImplicationsOlder adults admitted to a SNF for post-acute care with COVID-19 had community discharge rates and functional improvement comparable to a COVID-19 negative group. However, those who are frailer at admission tended to have lower function at discharge.