Frailty is associated with the clinical expression of neuropsychological deficits in older adults.

BACKGROUND AND PURPOSE: The aim was to determine whether frailty is associated with the relationship between neuropsychological markers and global cognition in older adults. METHODS: Cross-sectional analyzes were conducted of baseline data from three large cohort studies: National Alzheimer's Coordinating Center (NACC), Rush Memory and Aging Project (MAP) and Alzheimer's Disease Neuroimaging Initiative (ADNI). Studies recruited North American participants along the spectrum of cognitive functioning (44% no cognitive impairment at baseline). A frailty index was computed in each dataset. Frailty indices, neuropsychological tests (including measures of processing speed, episodic, semantic and working memory) and Mini-Mental State Examination (MMSE) scores were the variables of interest, with age, sex, education and apolipoprotein E ε4 evaluated as confounders. RESULTS: Across all studies, 23,819 participants aged 55-104 (57% female) were included in analyzes. Frailty index scores were significantly and inversely associated with MMSE scores and significantly moderated relationships between neuropsychological test scores and MMSE scores. In participants with higher frailty index scores, lower neuropsychological test scores were more strongly associated with lower MMSE scores (standardized interaction coefficients ranged from -0.19 to -1.17 in NACC, -0.03 to -2.27 in MAP and -0.04 to -0.38 in ADNI, depending on the neuropsychological test). These associations were consistent across the different databases and were mostly independent of the composition of frailty indices (i.e., after excluding possible symptoms of dementia). CONCLUSIONS: Amongst older Americans, frailty is associated with the cognitive expression of neuropsychological deficits. Implementation of frailty assessment in routine neurological and neuropsychological practice should be considered to optimize care outcomes for older adults.

Managing "socially admitted" patients in hospital: a qualitative study of health care providers' perceptions.

BACKGROUND: Emergency departments are a last resort for some socially vulnerable patients without an acute medical illness (colloquially known as "socially admitted" patients), resulting in their occupation of hospital beds typically designated for patients requiring acute medical care. In this study, we aimed to explore the perceptions of health care providers regarding patients admitted as "social admissions." METHODS: This qualitative study was informed by grounded theory and involved semistructured interviews at a Nova Scotia tertiary care centre. From October 2022 to July 2023, we interviewed eligible participants, including any health care clinician or administrator who worked directly with "socially admitted" patients. Virtual or in-person individual interviews were audio-recorded and transcribed, then independently and iteratively coded. We mapped themes on the 5 domains of the Quintuple Aim conceptual framework. RESULTS: We interviewed 20 nurses, physicians, administrators, and social workers. Most identified as female (n = 11) and White (n = 13), and were in their mid to late career (n = 13). We categorized 9 themes into 5 domains: patient experience (patient description, provision of care); care team well-being (moral distress, hierarchy of care); health equity (stigma and missed opportunities, prejudices); cost of care (wait-lists and scarcity of alternatives); and population health (factors leading to vulnerability, system changes). Participants described experiences caring for "socially admitted" patients, perceptions and assumptions underlying "social" presentations, system barriers to care delivery, and suggestions of potential solutions. INTERPRETATION: Health care providers viewed "socially admitted" patients as needing enhanced care but identified individual, institutional, and system challenges that impeded its realization. Examining perceptions of the people who care for "socially admitted" patients offers insights to guide clinicians and policy-makers in caring for socially vulnerable patients.

Extremes of baseline cognitive function determine the severity of delirium: a population study.

Although delirium is a significant clinical and public health problem, little is understood about how specific vulnerabilities underlie the severity of its presentation. Our objective was to quantify the relationship between baseline cognition and subsequent delirium severity. We prospectively investigated a population-representative sample of 1510 individuals aged ≥70 years, of whom 209 (13.6%) were hospitalized across 371 episodes (1999 person-days assessment). Baseline cognitive function was assessed using the modified Telephone Interview for Cognitive Status, supplemented by verbal fluency measures. We estimated the relationship between baseline cognition and delirium severity [Memorial Delirium Assessment Scale (MDAS)] and abnormal arousal (Observational Scale of Level of Arousal), adjusted by age, sex, frailty and illness severity. We conducted further analyses examining presentations to specific hospital settings and common precipitating aetiologies. The median time from baseline cognitive assessment to admission was 289 days (interquartile range 130 to 47 days). In admitted patients, delirium was present on at least 1 day in 45% of admission episodes. The average number of days with delirium (consecutively positive assessments) was 3.9 days. Elective admissions accounted for 88 bed days (4.4%). In emergency (but not elective) admissions, we found a non-linear U-shaped relationship between baseline global cognition and delirium severity using restricted cubic splines. Participants with baseline cognition 2 standard deviations below average (z-score = -2) had a mean MDAS score of 14 points (95% CI 10 to 19). Similarly, those with baseline cognition z-score = + 2 had a mean MDAS score of 7.9 points (95% CI 4.9 to 11). Individuals with average baseline cognition had the lowest MDAS scores. The association between baseline cognition and abnormal arousal followed a comparable pattern. C-reactive protein ≥20 mg/l and serum sodium <125 mM/l were associated with more severe delirium. Baseline cognition is a critical determinant of the severity of delirium and associated changes in arousal. Emergency admissions with lowest and highest baseline cognition who develop delirium should receive enhanced clinical attention.

Development and validation of a frailty index for use in the osteoarthritis initiative.

BACKGROUND: The Osteoarthritis Initiative (OAI) evaluates the development and progression of osteoarthritis. Frailty captures the heterogeneity in aging. Use of this resource-intensive dataset to answer aging-related research questions could be enhanced by a frailty measure. OBJECTIVE: To: (i) develop a deficit accumulation frailty index (FI) for the OAI; (ii) examine its relationship with age and compare between sexes, (iii) validate the FI versus all-cause mortality and (iv) compare this association with mortality with a modified frailty phenotype. DESIGN: OAI cohort study. SETTING: North America. SUBJECTS: An FI was determined for 4,755/4,796 and 4,149/4,796 who had a valid FI and frailty phenotype. METHODS: Fifty-nine-variables were screened for inclusion. Multivariate Cox regression evaluated the impact of FI or phenotype on all-cause mortality at follow-up (up to 146 months), controlling for age and sex. RESULTS: Thirty-one items were included. FI scores (0.16 ± 0.09) were higher in older adults and among females (both, P < 0.001). By follow-up, 264 people had died (6.4%). Older age, being male, and greater FI were associated with a higher risk of all-cause mortality (all, P < 0.001). The model including FI was a better fit than the model including the phenotype (AIC: 4,167 vs. 4,178) and was a better predictor of all-cause mortality than the phenotype with an area under receiver operating characteristic curve: 0.652 vs. 0.581. CONCLUSION: We developed an FI using the OAI and validated it in relation to all-cause mortality. The FI may be used to study aging on clinical, functional and structural aspects of osteoarthritis included in the OAI.

A process evaluation of the NIDUS-Professional dementia training intervention for UK homecare workers.

INTRODUCTION: This process evaluation was conducted in parallel to the randomised controlled feasibility trial of NIDUS-Professional, a manualised remote dementia training intervention for homecare workers (HCWs), delivered alongside an individualised intervention for clients living with dementia and their family carers (NIDUS-Family). The process evaluation reports on: (i) intervention reach, dose and fidelity; (ii) contexts influencing agency engagement and (iii) alignment of findings with theoretical assumptions about how the intervention might produce change. METHODS: We report proportions of eligible HCWs receiving any intervention (reach), number of sessions attended (dose; attending ≥4/6 main sessions was predefined as adhering), intervention fidelity and adherence of clients and carers to NIDUS-Family (attending all 6-8 planned sessions). We interviewed HCWs, managers, family carers and facilitators. We integrated and thematically analysed, at the homecare agency level, qualitative interview and intervention recording data. RESULTS: 32/141 (23%) of eligible HCWs and 7/42 (17%) of family carers received any intervention; most who did adhered to the intervention (89% and 71%). Intervention fidelity was high. We analysed interviews with 20/44 HCWs, 3/4 managers and 3/7 family carers, as well as intervention recordings involving 32/44 HCWs. All agencies reported structural challenges in supporting intervention delivery. Agencies with greater management buy-in had higher dose and reach. HCWs valued NIDUS-Professional for enabling group reflection and peer support, providing practical, actionable care strategies and increasing their confidence as practitioners. CONCLUSION: NIDUS-Professional was valued by HCWs. Agency management, culture and priorities were key barriers to implementation; we discuss how to address these in a future trial.

Feasibility and acceptability of NIDUS-professional, a training and support intervention for homecare workers caring for clients living with dementia: a cluster-randomised feasibility trial.

INTRODUCTION: In the first randomised controlled trial of a dementia training and support intervention in UK homecare agencies, we aimed to assess: acceptability of our co-designed, manualised training, delivered by non-clinical facilitators; outcome completion feasibility; and costs for a future trial. METHODS: This cluster-randomised (2:1) single-blind, feasibility trial involved English homecare agencies. Intervention arm agency staff were offered group videocall sessions: 6 over 3 months, then monthly for 3 months (NIDUS-professional). Family carers (henceforth carers) and clients with dementia (dyads) were offered six to eight complementary, individual intervention sessions (NIDUS-Family). We collected potential trial measures as secondary outcomes remotely at baseline and 6 months: HCW (homecare worker) Work-related Strain Inventory (WRSI), Sense of Competence (SoC); proxy-rated Quality of Life (QOL), Disability Assessment for Dementia scale (DAD), Neuropsychiatric Inventory (NPI) and Homecare Satisfaction (HCS). RESULTS: From December 2021 to September 2022, we met agency (4 intervention, 2 control) and HCWs (n = 62) recruitment targets and recruited 16 carers and 16/60 planned clients. We met a priori progression criteria for adherence (≥4/6 sessions: 29/44 [65.9%,95% confidence interval (CI): 50.1,79.5]), HCW or carer proxy-outcome completion (15/16 (93.8% [69.8,99.8]) and proceeding with adaptation for HCWs outcome completion (46/63 (73.0% [CI: 60.3,83.4]). Delivery of NIDUS-Professional costs was £6,423 (£137 per eligible client). WRSI scores decreased and SoC increased at follow-up, with no significant between-group differences. For intervention arm proxy-rated outcomes, carer-rated QOL increased, HCW-rated was unchanged; carer and HCW-rated NPI decreased; DAD decreased (greater disability) and HCS was unchanged. CONCLUSION: A pragmatic trial is warranted; we will consider using aggregated, agency-level client outcomes, including neuropsychiatric symptoms.

Interpretable machine learning for high-dimensional trajectories of aging health.

We have built a computational model for individual aging trajectories of health and survival, which contains physical, functional, and biological variables, and is conditioned on demographic, lifestyle, and medical background information. We combine techniques of modern machine learning with an interpretable interaction network, where health variables are coupled by explicit pair-wise interactions within a stochastic dynamical system. Our dynamic joint interpretable network (DJIN) model is scalable to large longitudinal data sets, is predictive of individual high-dimensional health trajectories and survival from baseline health states, and infers an interpretable network of directed interactions between the health variables. The network identifies plausible physiological connections between health variables as well as clusters of strongly connected health variables. We use English Longitudinal Study of Aging (ELSA) data to train our model and show that it performs better than multiple dedicated linear models for health outcomes and survival. We compare our model with flexible lower-dimensional latent-space models to explore the dimensionality required to accurately model aging health outcomes. Our DJIN model can be used to generate synthetic individuals that age realistically, to impute missing data, and to simulate future aging outcomes given arbitrary initial health states.

Development and validation of a hospital frailty risk measure using Canadian clinical administrative data.

BACKGROUND: Accessible measures specific to the Canadian context are needed to support health system planning for older adults living with frailty. We sought to develop and validate the Canadian Institute for Health Information (CIHI) Hospital Frailty Risk Measure (HFRM). METHODS: Using CIHI administrative data, we conducted a retrospective cohort study involving patients aged 65 years and older who were discharged from Canadian hospitals from Apr. 1, 2018, to Mar. 31, 2019. We used a 2-phase approach to develop and validate the CIHI HFRM. The first phase, construction of the measure, was based on the deficit accumulation approach (identification of age-related conditions using a 2-year look-back). The second phase involved refinement into 3 formats (continuous risk score, 8 risk groups and binary risk measure), with assessment of their predictive validity for several frailty-related adverse outcomes using data to 2019/20. We assessed convergent validity with the United Kingdom Hospital Frailty Risk Score. RESULTS: The cohort consisted of 788 701 patients. The CIHI HFRM included 36 deficit categories and 595 diagnosis codes that cover morbidity, function, sensory loss, cognition and mood. The median continuous risk score was 0.111 (interquartile range 0.056-0.194, equivalent to 2-7 deficits); 35.1% (n = 277 000) of the cohort were found at risk of frailty (≥ 6 deficits). The CIHI HFRM showed satisfactory predictive validity and reasonable goodness-of-fit. For the continuous risk score format (unit = 0.1), the hazard ratio (HR) for 1-year risk of death was 1.39 (95% confidence interval [CI] 1.38-1.41), with a C-statistic of 0.717 (95% CI 0.715-0.720); the odds ratio for high users of hospital beds was 1.85 (95% CI 1.82-1.88), with a C-statistic of 0.709 (95% CI 0.704-0.714), and the HR of 90-day admission to long-term care was 1.91 (95% CI 1.88-1.93), with a C-statistic of 0.810 (95% CI 0.808-0.813). Compared with the continuous risk score, using a format of 8 risk groups had similar discriminatory ability and the binary risk measure had slightly weaker performance. INTERPRETATION: The CIHI HFRM is a valid tool showing good discriminatory power for several adverse outcomes. The tool can be used by decision-makers and researchers by providing information on hospital-level prevalence of frailty to support system-level capacity planning for Canada's aging population.

How to construct a frailty index from an existing dataset in 10 steps.

BACKGROUND: The frailty index is commonly used in research and clinical practice to quantify health. Using a health deficit accumulation model, a frailty index can be calculated retrospectively from data collected via survey, interview, performance test, laboratory report, clinical or administrative medical record, or any combination of these. Here, we offer a detailed 10-step approach to frailty index creation, with a worked example. METHODS: We identified 10 steps to guide the creation of a valid and reliable frailty index. We then used data from waves 5 to 12 of the Health and Retirement Study (HRS) to illustrate the steps. RESULTS: The 10 steps are as follows: (1) select every variable that measures a health problem; (2) exclude variables with more than 5% missing values; (3) recode the responses to 0 (no deficit) through 1 (deficit); (4) exclude variables when coded deficits are too rare (< 1%) or too common (> 80%); (5) screen the variables for association with age; (6) screen the variables for correlation with each other; (7) count the variables retained; (8) calculate the frailty index scores; (9) test the characteristics of the frailty index; (10) use the frailty index in analyses. In our worked example, we created a 61-item frailty index following these 10 steps. CONCLUSIONS: This 10-step procedure can be used as a template to create one continuous health variable. The resulting high-information variable is suitable for use as an exposure, predictor or control variable, or an outcome measure of overall health and ageing.

The frailty index based on laboratory test data as a tool to investigate the impact of frailty on health outcomes: a systematic review and meta-analysis.

The frailty index (FI) quantifies frailty as deficit accumulation. It has been adapted to employ laboratory test data (FI-Lab). Our objective was to systematically review and meta-analyse the FI-Lab's ability to predict mortality. Secondary objectives were to review the FI-Lab's association with adverse health outcomes and whether FI-Lab scores differed between the sexes. A systematic literature search was carried out using six online databases to identify studies that measured the FI-Lab in humans. Hazard ratios (HRs) were combined in a meta-analysis to create a pooled risk estimate for mortality. Of the 1,201 papers identified, spanning January 2010 until 11 July 2022, 38 were included. FI-Lab scores per 0.01 unit increase predicted mortality overall (HR = 1.04; 95% confidence interval (CI) = 1.03-1.05) and for studies with a mean age of 81+ years (HR = 1.04; 95% CI = 1.03-1.05). The quality of evidence for these meta-analyses are moderate and high, respectively. Further, higher FI-Lab scores were associated with more frequent adverse health outcomes. Sex differences in FI-Lab scores varied, with no consistent indication of a sex effect. The FI-Lab is associated with mortality and with a variety of adverse health outcomes. No consistent sex differences in FI-Lab scores were observed, with several studies in disagreement. Notably, these conclusions were most relevant to older (65+ years old) individuals; further evidence in younger people is needed in both clinical and population representative studies.

External validation of the hospital frailty risk score among hospitalised home care clients in Canada: a retrospective cohort study.

BACKGROUND: The Hospital Frailty Risk Score (HFRS) is scored using ICD-10 diagnostic codes in administrative hospital records. Home care clients in Canada are routinely assessed with Resident Assessment Instrument-Home Care (RAI-HC) which can calculate the Clinical Frailty Scale (CFS) and the Frailty Index (FI). OBJECTIVE: Measure the correlation between the HFRS, CFS and FI and compare prognostic utility for frailty-related outcomes. DESIGN: Retrospective cohort study. SETTING: Alberta, British Columbia and Ontario, Canada. SUBJECTS: Home care clients aged 65+ admitted to hospital within 180 days (median 65 days) of a RAI-HC assessment (n = 167,316). METHODS: Correlation between the HFRS, CFS and FI was measured using the Spearman correlation coefficient. Prognostic utility of each measure was assessed by comparing measures of association, discrimination and calibration for mortality (30 days), prolonged hospital stay (10+ days), unplanned hospital readmission (30 days) and long-term care admission (1 year). RESULTS: The HFRS was weakly correlated with the FI (ρ 0.21) and CFS (ρ 0.28). Unlike the FI and CFS, the HFRS was unable to discriminate for 30-day mortality (area under the receiver operator characteristic curve (AUC) 0.506; confidence interval (CI) 0.502-0.511). It was the only measure that could discriminate for prolonged hospital stay (AUC 0.666; CI 0.661-0.673). The HFRS operated like the FI and CFI when predicting unplanned readmission (AUC 0.530 CI 0.526-0.536) and long-term care admission (AUC 0.600; CI 0.593-0.606). CONCLUSIONS: The HFRS identifies a different subset of older adult home care clients as frail than the CFS and FI. It has prognostic utility for several frailty-related outcomes in this population, except short-term mortality.

Interrupting bedtime to reverse frailty levels in acute care: a study protocol for the Breaking Bad Rest randomized controlled trial.

BACKGROUND: Hospitalized older patients spend most of the waking hours in bed, even if they can walk independently. Excessive bedrest contributes to the development of frailty and worse hospital outcomes. We describe the study protocol for the Breaking Bad Rest Study, a randomized clinical trial aimed to promoting more movement in acute care using a novel device-based approach that could mitigate the impact of too much bedrest on frailty. METHODS: Fifty patients in a geriatric unit will be randomized into an intervention or usual care control group. Both groups will be equipped with an activPAL (a measure of posture) and StepWatch (a measure of step counts) to wear throughout their entire hospital stay to capture their physical activity levels and posture. Frailty will be assessed via a multi-item questionnaire assessing health deficits at admission, weekly for the first month, then monthly thereafter, and at 1-month post-discharge. Secondary measures including geriatric assessments, cognitive function, falls, and hospital re-admissions will be assessed. Mixed models for repeated measures will determine whether daily activity differed between groups, changed over the course of their hospital stay, and impacted frailty levels. DISCUSSION: This randomized clinical trial will add to the evidence base on addressing frailty in older adults in acute care settings through a devices-based movement intervention. The findings of this trial may inform guidelines for limiting time spent sedentary or in bed during a patient's stay in geriatric units, with the intention of scaling up this study model to other acute care sites if successful. TRIAL REGISTRATION: The protocol has been registered at clinicaltrials.gov (identifier: NCT03682523).

Relationship of body mass index with frailty and all-cause mortality among middle-aged and older adults.

BACKGROUND: Parallel to growth of aging and obese populations, the prevalence of metabolic diseases is rising. How body mass index (BMI) relates to frailty and mortality across frailty levels is controversial. We examined the associations of high BMI with frailty and mortality and explored the effects of percent body fat on these associations. METHODS: We included 29,937 participants aged ≥50 years from the 2001-2006 National Health and Nutrition Examination Survey (NHANES) cohorts (N=6062; 53.7% females) and from wave 1 (2004) of Survey of Health, Ageing and Retirement in Europe (SHARE) (N=23,875; 54% females). BMI levels were categorized as: normal: 18.5-24.9 kg/m2, overweight: 25.0-29.9, obese grade 1: 30.0-34.9, and obese grade 2 or 3: >35.0. A frailty index (FI) was constructed excluding nutrition-related items: 36 items for NHANES and 57 items for SHARE. We categorized the FI using 0.1-point increments: FI ≤ 0.1 (non-frail), 0.1 < FI ≤ 0.2 (very mildly frail), 0.2 < FI ≤ 0.3 (mildly frail), and FI > 0.3 (moderately/severely frail). Percent body fat was measured using DXA for NHANES participants. All-cause mortality data were obtained until 2015 for NHANES and 2017 for SHARE to estimate 10-year mortality risk. All analyses were adjusted for age, sex, educational, marital, employment, and smoking statuses. RESULTS: Mean age of participants was 63.3±10.2 years for NHANES and 65.0±10.0 years for SHARE. In both cohorts, BMI levels ≥25 kg/m2 were associated with higher frailty, compared to normal BMI. In SHARE, having a BMI level greater than 35 kg/m2 increased mortality risk in participants with FI≤0.1 (HR 1.31, 95%CI 1.02-1.69). Overweight participants with FI scores >0.3 were at lower risk for mortality compared to normal BMI [NHANES (0.79, 0.64-0.96); SHARE (0.71, 0.63-0.80)]. Higher percent body fat was associated with higher frailty. Percent body fat significantly mediated the relationship between BMI levels and frailty but did not mediate the relationship between BMI levels and mortality risk. CONCLUSIONS: Being overweight or obese is associated with higher frailty levels. In this study, we found that being overweight is a protective factor of mortality in moderately/severely frail people and obesity grade 1 may be protective for mortality for people with at least a mild level of frailty. In contrast, obesity grades 2 and 3 may be associated with higher mortality risk in non-frail people. The relationship between BMI and frailty is partially explained by body fat.

The impact of cardiovascular health and frailty on mortality for males and females across the life course.

BACKGROUND: The effect of frailty and poor cardiovascular health on mortality for males and females is not fully elucidated. We investigated whether the combined burden of frailty and poor cardiovascular health is associated with all-cause and cardiovascular disease (CVD) mortality by sex and age. METHODS: We analyzed data of 35,207 non-institutionalized US residents aged 20-85 years old (mean age [standard deviation]: 46.6 [16.7 years], 51.4% female, 70.8% White, 10.3% Black, 13.2% Hispanic) from the National Health and Nutrition Examination Survey (1999-2015). Cardiovascular health was measured with the American Heart Association's Life's Simple 7 score (LS7). A 33-item frailty index (FI) was constructed to exclude cardiovascular health deficits. We grouped the FI into 0.1 increments (non-frail: FI < 0.10, very mildly frail: 0.1 ≤ FI < 0.20, mildly frail: 0.20 ≤ FI < 0.30, and moderately/severely frail: FI ≥ 0.30) and LS7 into tertiles (T1[poor] = 0-7, T2[intermediate] = 8-9, T3[ideal] = 10-14). All-cause and CVD mortality data were analyzed up to 16 years. All regression models were stratified by sex. RESULTS: The average FI was 0.09 (SD 0.10); 29.6% were at least very mildly frail, and the average LS7 was 7.9 (2.3). Mortality from all-causes and CVD were 8.5% (4228/35,207) and 6.1% (2917/35,207), respectively. The median length of follow-up was 8.1 years. The combined burden of frailty and poor cardiovascular health on mortality risk varied according to age in males (FI*age interaction p = 0.01; LS7*age interaction p < 0.001) but not in females. In females, poor FI and LS7 combined to predict all-cause and CVD mortality in a dose-response manner. All-cause and CVD mortality risk was greater for older males (60 and 70 years old) who were at least mildly frail and had intermediate cardiovascular health or worse (hazard ratio [lower/higher confidence interval ranges] range: all-cause mortality = 2.02-5.30 [1.20-4.04, 3.15-6.94]; CVD-related mortality = 2.22-7.16 [1.03-4.46, 4.49-11.50]) but not for younger males (30, 40, and 50 years old). CONCLUSIONS: The combined burden of frailty and LS7 on mortality is similar across all ages in females. In males, this burden is greater among older people. Adding frailty to assessments of overall cardiovascular health may identify more individuals at risk for mortality and better inform decisions to implement preventative or treatment approaches.

Frailty and Risk of Dementia in Mild Cognitive Impairment Subtypes.

Risk factors for developing dementia from mild cognitive impairment (MCI) probably differ between MCI subtypes. We investigated how frailty relates to dementia risk in amnestic MCI (a-MCI; n = 2,799) and non-amnestic MCI (na-MCI; n = 629) in the National Alzheimer's Coordinating Center database. Although higher frailty increased dementia risk for people with either a-MCI or na-MCI, the larger risk was in na-MCI (interaction hazard ratio = 1.35 [95% confidence interval = 1.15-1.59], p < 0.001). Even after the onset of clinically significant cognitive impairment, poor general health, quantified by a high degree of frailty, is a significant risk for dementia. ANN NEUROL 2021;89:1221-1225.

Frailty, lifestyle, genetics and dementia risk.

OBJECTIVE: To optimise dementia prevention strategies, we must understand the complex relationships between lifestyle behaviours, frailty and genetics. METHODS: We explored relationships between frailty index, healthy lifestyle and polygenic risk scores (all assessed at study entry) and incident all-cause dementia as recorded on hospital admission records and death register data. RESULTS: The analytical sample had a mean age of 64.1 years at baseline (SD=2.9) and 53% were women. Incident dementia was detected in 1762 participants (median follow-up time=8.0 years). High frailty was associated with increased dementia risk independently of genetic risk (HR 3.68, 95% CI 3.11 to 4.35). Frailty mediated 44% of the relationship between healthy lifestyle behaviours and dementia risk (indirect effect HR 0.95, 95% CI 0.95 to 0.96). Participants at high genetic risk and with high frailty had 5.8 times greater risk of incident dementia compared with those at low genetic risk and with low frailty (HR 5.81, 95% CI 4.01 to 8.42). Higher genetic risk was most influential in those with low frailty (HR 1.31, 95% CI 1.22 to 1.40) but not influential in those with high frailty (HR 1.09, 95% CI 0.92 to 1.28). CONCLUSION: Frailty is strongly associated with dementia risk and affects the risk attributable to genetic factors. Frailty should be considered an important modifiable risk factor for dementia and a target for dementia prevention strategies, even among people at high genetic risk.

The GOAL-Hem journey: Shared decision making and patient-centred outcomes.

INTRODUCTION: GOAL-Hem is a novel, haemophilia-specific, patient-centred outcome measure (PCOM) based on goal attainment scaling, allowing people with haemophilia (PwH) to set and monitor the attainment of individualized goals for treatment. AIM: To provide a thorough overview of the creation, validation, and development of GOAL-Hem. METHODS: Clinician workshops were held to develop a haemophilia-specific goal menu. Qualitative data from semistructured interviews with PwH and their caregivers guided further revisions to the goal menu (i.e., goal domains and descriptors). A feasibility study was performed including a 12-week, prospective, noninterventional evaluation involving clinicians and PwH at four US haemophilia treatment centres. Finally, the Patient Voice Study gathered feedback from PwH and their caregivers via an online survey, interviews, and a focus group. RESULTS: The feasibility study validated GOAL-Hem with successful outcomes in construct/content validity and responsiveness, including a large effect in patient- and clinician-rated goal attainments. The Patient Voice Study led to significant refinement of GOAL-Hem goals and descriptors, resulting in a more straightforward and relatable menu for PwH and their caregivers. Overall, GOAL-Hem captured qualitative data in areas important to PwH and employed quantitative methods to evaluate meaningful changes in those areas. The individualized tool was well equipped to handle the complex and chronic nature of haemophilia and was endorsed by PwH, their caregivers, and clinicians. CONCLUSION: The GOAL-Hem development journey may serve as a roadmap for other PCOMs in a variety of settings, including clinical studies, haemophilia treatment centres for care planning, and as a tool to gather real-world evidence.

Impact of oral anticoagulation on the association between frailty and clinical outcomes in people with atrial fibrillation: nationwide primary care records on treatment analysis.

AIMS: People with atrial fibrillation (AF) frequently live with frailty, which increases the risk of mortality and stroke. This study reports the association between oral anticoagulation (OAC) and outcomes for people with frailty, and whether there is overall net benefit from treatment in people with AF. METHODS AND RESULTS: Retrospective open cohort electronic records study. Frailty was identified using the electronic frailty index. Primary care electronic health records of 89 996 adults with AF and CHA2DS2-Vasc score of ≥2 were linked with secondary care and mortality data in the Clinical Practice Research Database (CPRD) from 1 January 1998 to 30 November 2018. The primary outcome was a composite of death, stroke, systemic embolism, or major bleeding. Secondary outcomes were stroke, major bleeding, all-cause mortality, transient ischaemic attack, and falls. Of 89 996 participants, 71 256 (79.2%) were living with frailty. The prescription of OAC increased with degree of frailty. For patients not prescribed OAC, rates of the primary outcome increased alongside frailty category. Prescription of OAC was associated with a reduction in the primary outcome for each frailty category [adjusted hazard ratio, 95% confidence interval, no OAC as reference; fit: vitamin K antagonist (VKA) 0.69, 0.64-0.75, direct oral anticoagulant (DOAC) 0.42, 0.33-0.53; mild frailty: VKA 0.52, 0.50-0.54, DOAC 0.57, 0.52-0.63; moderate: VKA 0.54, 0.52-0.56, DOAC 0.57, 0.52-0.63; severe: VKA 0.48, 0.45-0.51, DOAC 0.58, 0.52-0.65], with cumulative incidence function effects greater for DOAC than VKA. CONCLUSION: Frailty among people with AF is common. The OAC was associated with a reduction in the primary endpoint across all degrees of frailty.

The impact of an exercise intervention on frailty levels in hospitalised older adults: secondary analysis of a randomised controlled trial.

BACKGROUND: physical activity reduces frailty in community-dwelling older adults. How exercise influences frailty in hospitalised older adults requires additional investigation. OBJECTIVES: (i) to examine the impact of an exercise intervention on frailty in older adults admitted to an acute care ward, and (ii) to determine the impact of baseline frailty on the effectiveness of this intervention. SETTING/PARTICIPANTS: this is a secondary analysis of a randomised controlled clinical trial that tested an intensive exercise intervention in ≥75-year-old adults admitted to an acute care ward. METHODS: the intervention included two daily sessions of moderate-intensity exercises (control received usual care). A 63-item Frailty Index (FI) was constructed, and three groups were formed: <0.2, 0.2-0.29 and ≥0.3. Other outcomes included Short Physical Performance Battery (SPPB) and Barthel Index (BI). RESULTS: a total of 323 individuals were included. The mean age was 87.1 years (± 4.8 standard deviation [SD]) and 56.3% were females. The intervention group improved FI from 0.26 (± 0.10 SD) to 0.20 (± 0.10 SD), whereas the control group FI worsened from 0.25 (± 0.1 SD) to 0.27 (± 0.10 SD). After stratifying by baseline FI, SPPB and depression improved in the intervention group across all levels of frailty; FI, BI and quality of life only improved in individuals with a baseline FI ≥ 0.2. CONCLUSIONS: frailty improves with an intensive individualised exercise intervention, especially in those with high baseline levels of frailty. In addition, frailty is a useful outcome when examining the impact of an intervention of hospitalised older adults.

Frailty indices based on self-report, blood-based biomarkers and examination-based data in the Canadian Longitudinal Study on Aging.

BACKGROUND: Frailty can be operationalised using the deficit accumulation approach, which considers health deficits across multiple domains. We aimed to develop, validate and compare three different frailty indices (FI) constructed from self-reported health measures (FI-Self Report), blood-based biomarkers (FI-Blood) and examination-based assessments (FI-Examination). METHODS: Up to 30,027 participants aged 45-85 years from the baseline (2011-2015) comprehensive cohort of the Canadian Longitudinal Study on Aging were included in the analyses. Following standard criteria, three FIs were created: a 48-item FI-Self Report, a 23-item FI-Blood and a 47-item FI-Examination. In addition a 118-item FI-Combined was constructed. Mortality status was ascertained in July 2019. RESULTS: FI-Blood and FI-Examination demonstrated broader distributions than FI-Self Report. FI-Self Report and FI-Blood scores were higher in females, whereas FI-Examination scores were higher in males. All FI scores increased nonlinearly with age and were highest at lower education levels. In sex and age-adjusted models, a 0.01 increase in FI score was associated with a 1.08 [95% confidence interval (CI): 1.07,1.10], 1.05 (1.04,1.06), 1.07 (1.05,1.08) and a 1.13 (1.11,1.16) increased odds of mortality for FI-Self Report, FI-Blood, FI-Examination and FI-Combined, respectively. Inclusion of the three distinct FI types in a single model yielded the best prognostic accuracy and model fit, even compared to the FI-Combined, with all FIs remaining independently associated with mortality. CONCLUSION: Characteristics of all FIs were largely consistent with previously established FIs. To adequately capture frailty levels and to improve our understanding of the heterogeneity of ageing, FIs should consider multiple types of deficits including self-reported, blood and examination-based measures.