Predicting Mortality and Adverse Outcomes: Comparing the Frailty Index to General Prognostic Indices.

BACKGROUND: Mortality prediction models are useful to guide clinical decision-making based on prognosis. The frailty index, which allows prognostication and personalized care planning, has not been directly compared with validated prognostic models. OBJECTIVE: To compare the discrimination of mortality, disability, falls, and hospitalization between a frailty index and validated prognostic indices. DESIGN: Secondary Analysis of the National Health and Aging Trends Study. PARTICIPANTS: Seven thousand thirty-three Medicare beneficiaries 65 years or older. MEASUREMENTS: We measured a deficit-accumulation frailty index, Schonberg index, and Lee index at the 2011 baseline assessment. Primary outcome was mortality at 5 years. Secondary outcomes were decline in activities of daily living (ADL), decline in instrumental activities of daily living (IADL), fall, and hospitalization at 1 year. We used C-statistics to compare discrimination between indices, adjusting for age and sex. RESULTS: The study population included 4146 (44.8%) with age ≥ 75 years, with a median frailty index of 0.15 (interquartile range 0.09-0.25). A total of 1385 participants died (14.7%) and 2386 (35.2%) were lost to follow-up. Frailty, Schonberg, and Lee indices predicted mortality similarly: C-statistics (95% confidence interval) were 0.78 (0.77-0.80) for frailty index; 0.79 (0.78-0.81) for Schonberg index; and 0.78 (0.77-0.80) for Lee index. The frailty index had higher C-statistics for decline in ADL function (frailty index, 0.80 [0.78-0.83]; Schonberg, 0.74 [0.72-0.76]; Lee, 0.74 [0.71-0.77]) and falls (frailty index, 0.66 [0.65-0.68]; Schonberg, 0.61 [0.58-0.63]; Lee, 0.61 [0.59-0.63]). C-statistics were similar for decline in IADL function (frailty index, 0.61 [0.59-0.63]; Schonberg, 0.60 [0.59-0.62]; Lee, 0.60 [0.58-0.62]) and hospitalizations (frailty index, 0.68 [0.66-0.70]; Schonberg, 0.68 [0.66-0.69]; Lee, 0.65 [0.63-0.67]). CONCLUSIONS: A deficit-accumulation frailty index performs as well as prognostic indices for mortality prediction, and better predicts ADL disability and falls in community-dwelling older adults. Frailty assessment offers a unifying approach to risk stratification for key health outcomes relevant to older adults.

Accuracy of diagnosis and health service codes in identifying frailty in Medicare data.

BACKGROUND: Capturing frailty within administrative claims data may help to identify high-risk patients and inform population health management strategies. Although it is common to ascertain frailty status utilizing claims-based surrogates (e.g. diagnosis and health service codes) selected according to clinical knowledge, the accuracy of this approach has not yet been examined. We evaluated the accuracy of claims-based surrogates against two clinical definitions of frailty. METHODS: This cross-sectional study was conducted in a Health and Retirement Study subsample of 3097 participants, aged 65 years or older and with at least 12-months of continuous fee-for-service Medicare enrollment. We defined 18 previously utilized claims-based surrogates of frailty from Medicare data and evaluated each against clinical reference standards, ascertained from a direct examination: a deficit accumulation frailty index (FI) (range: 0-1) and frailty phenotype. We also compared the accuracy of the total count of 18 claims-based surrogates with that of a validated claims-based FI model, comprised of 93 claims-based variables. RESULTS: 19% of participants met clinical criteria for the clinical frailty phenotype. The mean clinical FI for our sample was 0.20 (standard deviation 0.13). Hospital Beds and associated supplies was the claims-based surrogate associated with the highest clinical FI (mean FI 0.49). Claims-based surrogates had low sensitivity ranging from 0.01 (cachexia, adult failure to thrive, anorexia) to 0.38 (malaise and fatigue) and high specificity ranging from 0.79 (malaise and fatigue) to 0.99 (cachexia, adult failure to thrive, anorexia) in discriminating the clinical frailty phenotype. Compared with a validated claims-based FI, the total count of claims-based surrogates demonstrated lower Spearman correlation with the clinical FI (0.41 [95% CI 0.38-0.44] versus 0.59 [95% CI, 0.56-0.61]) and poorer discrimination of the frailty phenotype (C-statistics 0.68 [95% CI, 0.66-0.70] versus 0.75 [95% CI, 0.73-0.77]). CONCLUSIONS: Claims-based surrogates, selected according to clinical knowledge, do not accurately capture frailty in Medicare claims data. A simple count of claims-based surrogates improves accuracy but remains inferior to a claims-based FI model.

Comparative utility of frailty to a general prognostic score in identifying patients at risk for poor outcomes after aortic valve replacement.

BACKGROUND: Current guidelines recommend considering life expectancy before aortic valve replacement (AVR). We compared the performance of a general mortality index, the Lee index, to a frailty index. METHODS: We conducted a prospective cohort study of 246 older adults undergoing surgical (SAVR) or transcatheter aortic valve replacement (TAVR) at a single academic medical center. We compared performance of the Lee index to a deficit accumulation frailty index (FI). Logistic regression was used to assess the association of Lee index or FI with poor outcome, defined as death or functional decline with severe symptoms at 12 months. Discrimination was assessed using C-statistics. RESULTS: In the overall cohort, 44 experienced poor outcome (31 deaths, 13 functional decline with severe symptoms). The risk of poor outcome by Lee index quartiles was 6.8% (reference), 17.9% (odds ratio [OR], 3.0; 95% confidence interval, [0.9-10.2]), 20.0% (OR 3.4; [1.0-11.4]), and 34.0% (OR 7.1; [2.2-22.6]) (p-for-trend = 0.001). Risk of poor outcome by FI quartiles was 3.6% (reference), 10.3% (OR 3.1; [0.6-15.8]), 25.0% (OR 8.8; [1.9-41.0]), and 37.3% (OR 15.8; [3.5-71.1]) (p-for-trend< 0.001). The Lee index predicted the risk of poor outcome in the SAVR cohort Lee index (quartiles 1-4: 2.1, 4.0, 15.4, and 20.0%; p-for-trend = 0.04), but not in the TAVR cohort (quartiles 1-4: 27.3, 29.0, 21.3, 35.4%; p-for-trend = 0.42). In contrast, the FI did not predict the risk of poor outcome well in the SAVR cohort (quartiles 1-4: 2.3, 4.4, 15.8, and 0%; p-for-trend = 0.24), however in the TAVR cohort (quartiles 1-4: 9.1, 14.3, 29.7, and 40.7%; p-for-trend = 0.004). Compared to the Lee index, an FI demonstrated higher C-statistics in the overall (Lee index versus FI: 0.680 versus 0.735; p = 0.03) and TAVR (0.560 versus 0.644; p = 0.03) cohorts, but not SAVR cohort (0.724 versus 0.766; p = 0.09). CONCLUSIONS: While a general mortality index Lee index predicted death or functional decline with severe symptoms at 12 months well among SAVR patients, the FI derived from a multi-domain geriatric assessment better informs risk-stratification for high-risk TAVR patients.

Evaluation of geriatrics education at a Chinese University: A survey of attitudes and knowledge among undergraduate medical students.

Despite widespread reforms in medical education across China, nationally there has been no mandate or movement toward systemically incorporating geriatrics into curricula. To what degree medical students are trained and have exposure to geriatric topics remains unclear. We surveyed 190 medical students during their final year of medical school at a Chinese medical university, graduating from reformed and also traditional curricula. The survey was comprised of a subjective assessment of attitudes and reported knowledge, as well as an objective assessment of knowledge via a multiple choice test. Student attitudes were favorable toward geriatrics, with 91% supporting the addition of specialized clinical experiences to the curriculum. Students generally reported low exposure to geriatrics, with no statistically significant differences between reform and traditional curricula. There was a statistically significant difference in performance on the multiple choice test between curricula but at a degree unlikely to be practically significant. Students had very favorable attitudes toward geriatrics as a field and specialty; however scored poorly on competency exams, with the lowest performance around diagnosis and treatment of specific geriatric conditions. Our results suggest that there is a need and desire for increased geriatric-oriented learning at Chinese medical schools.

MicroRNA-9 and microRNA-326 regulate human dopamine D2 receptor expression, and the microRNA-mediated expression regulation is altered by a genetic variant.

The human dopamine receptor D2 (DRD2) has been implicated in the pathophysiology of schizophrenia and other neuropsychiatric disorders. Most antipsychotic drugs influence dopaminergic transmission through blocking dopamine receptors, primarily DRD2. We report here the post-transcriptional regulation of DRD2 expression by two brain-expressed microRNAs (miRs), miR-326 and miR-9, in an ex vivo mode, and show the relevance of miR-mediated DRD2 expression regulation in human dopaminergic neurons and in developing human brains. Both miRs targeted the 3'-UTR (untranslated region) of DRD2 in NT2 (neuron-committed teratocarcinoma, which endogenously expresses DRD2) and CHO (Chinese hamster ovary) cell lines, decreasing luciferase activity measured by a luciferase reporter gene assay. miR-326 overexpression reduced DRD2 mRNA and DRD2 receptor synthesis. Both antisense miR-326 and antisense miR-9 increased DRD2 protein abundance, suggesting an endogenous repression of DRD2 expression by both miRs. Furthermore, a genetic variant (rs1130354) within the DRD2 3'-UTR miR-targeting site interferes with miR-326-mediated repression of DRD2 expression. Finally, co-expression analysis identified an inverse correlation of DRD2 expression with both miR-326 and miR-9 in differentiating dopaminergic neurons derived from human induced pluripotent stem cells (iPSCs) and in developing human brain regions implicated in schizophrenia. Our study provides empirical evidence suggesting that miR-326 and miR-9 may regulate dopaminergic signaling, and miR-326 and miR-9 may be considered as potential drug targets for the treatment of disorders involving abnormal DRD2 function, such as schizophrenia.

Mobility Device Use and Frailty Progression in Community-Dwelling Older Adults With Mobility Limitations.

Objective: Examine the association between mobility device use and changes in a frailty index (FI) over one year in community-dwelling older adults with mobility limitations. Methods: Analyses utilized 2015-2016 data from the National Health and Aging Trends Study community-dwelling older adults (n = 3934). We calculated a validated 40-item deficit accumulation frailty index (FI) in 2015 and 2016 and compared one year change in FI in older adults with/without canes or walkers using multivariable logistic regression. Analyses were repeated with stratification by baseline frailty. Results: Device use was not associated with worsening frailty in the overall cohort, but was associated with worsening frailty in non-frail individuals when stratified by baseline frailty. Discussion: Device use does not worsen frailty in individuals who are frail at baseline. Device users who were not frail at baseline experienced worsening frailty suggesting additional contributing factors to their frailty aside from mobility limitations.

Claims-Based Frailty Index and Its Relationship With Commonly Used Clinical Frailty Measures.

BACKGROUND: The relationship of claims-based frailty index (CFI), a validated measure to identify frail individuals using Medicare data, and frailty measures used in clinical practice has not yet been fully explored. METHODS: We identified community-dwelling participants of the 2015 National Health and Aging Trends Study (NHATS) whose CFI scores could be calculated using linked Medicare claims. We calculated 9 commonly used clinical frailty measures from their NHATS in-person examination: Study of Osteoporotic Fracture Index (SOF), FRAIL Scale, Frailty Phenotype, Clinical Frailty Scale (CFS), Vulnerable Elder Survey-13 (VES-13), Tilburg Frailty Indicator (TFI), Groningen Frailty Indicator (GFI), Edmonton Frail Scale (EFS), and 40-item Frailty Index (FI). Using equipercentile method, CFI scores were linked to clinical frailty measures. C-statistics and test characteristics of CFI to identify frailty as defined by each clinical frailty measure were calculated. RESULTS: Of the 3 963 older adults, 44.5% were ≥75 years, 59.4% were female, and 82.3% were non-Hispanic White. A CFI of 0.25 was equipercentile to the following clinical frailty measure scores: SOF 1.4, FRAIL 1.8, Phenotype 1.8, CFS 5.4, VES-13 5.7, TFI 4.6, GFI 5.0, EFS 6.0, and FI 0.26. The C-statistics of using CFI to identify frailty as defined by each clinical measure were ≥0.70, except for CFS and VES-13. The optimal CFI cutpoints to identify frailty per clinical frailty measure ranged from 0.212 to 0.242, with sensitivity and specificity of 0.37-0.83 and 0.66-0.84, respectively. CONCLUSIONS: Understanding the relationship of CFI and commonly used clinical frailty measures can enhance the interpretability and potential utility of CFI.

Association of drug therapy with the risk of incident frailty: a systematic review.

Medication is a potential factor influencing frailty. However, the relationship between pharmaceutical treatments and frailty remains unclear. Therefore, we conducted the present systematic review to summarize the association between drug therapy and the risk of incident frailty in older adults. We systematically searched the MEDLINE electronic database for articles indexed between January 1, 2000, and December 31, 2021, for randomized controlled trials (RCTs) and cohort studies reporting frailty changes associated with drug therapy. A total of 6 RCTs and 13 cohort studies involving 211,948 participants were identified, and their treatments were categorized into six medication classes: analgesics, cardiometabolic medication, chemotherapy, central nervous system (CNS)-active medication, hormonal therapy, and nutritional supplements. While the analysis revealed that only CNS-active medications were associated with an elevated risk of frailty, other medication classes also affected frailty; however, this is not conclusively attributable to a class-wide effect.

Design Considerations for Embedded Pragmatic Clinical Trials of Advance Care Planning Interventions for Persons Living With Dementia.

Advance care planning (ACP) is an important part of comprehensive care for persons living with dementia (PLWD). While many trials have established the efficacy of ACP in improving end-of-life communication and documentation of care preferences, there remains a gap in clinical usage. Embedded pragmatic clinical trials (ePCTs) may facilitate the uptake of evidence-based care into existing healthcare by deploying efficacious ACP interventions into real-world settings. However rigorous conduct of ePCTs of ACP for PLWD presents several unique methodological considerations. Here we describe a framework for the construction of these research studies, with a focus on distinguishing between the target of study: the PLWD, their care partners, or both. We outline specific considerations at each step of the research study process including 1) participant identification/eligibility, 2) participant recruitment/enrollment, 3) intervention implementation, and 4) outcome selection/ascertainment. These considerations are weighed in further detail by describing the approaches from three published trials. Specifically, we consider how potential challenges were overcome by tradeoffs in study design. Finally, we offer directions for future growth to advance ePCTs for ACP among PLWD and catalyze future research.

Frailty and Time at Home After Post-Acute Care in Skilled Nursing Facilities.

OBJECTIVES: To examine the association of a claims-based frailty index with time at home, defined as the number of days alive and spent out of hospital or skilled nursing facility (SNF). DESIGN: Cohort Study. SETTING AND PARTICIPANTS: A 5% Medicare random sample of fee-for-service beneficiaries, who had continuous part A and B enrollment in the prior 6 months, that were discharged from a short SNF admission in 2014‒2016. METHODS: Frailty was measured with a validated claims-based frailty index (CFI) (range: 0‒1, higher scores indicating worse frailty) and categorized into nonfrail (CFI <0.25), mild frailty (CFI 0.25‒0.34), and moderate-to-severe frailty (CFI ≥0.35). We measured home time in the 6 months following SNF discharge (range: 0‒182 days with higher values representing more days at home and thus a better outcome). We used logistic regression to assess the association between frailty and short home time, defined as <173 days, adjusting for age, sex, race, region, a comorbidity index, clinical SNF admission characteristics in the Minimum Data Set, and SNF characteristics. RESULTS: In our sample of 144,708 beneficiaries (mean age, 80.8 years, 64.9% female, 85.9% white) who were discharged to community after SNF stay, the mean CFI was 0.26 (standard deviation, 0.07). The mean home time was 165.6 (38.1) days in nonfrail, 154.4 (47.4) days in mild frailty, 145.0 (52.0) days in moderate-to-severe frailty group. After full model adjustments, moderate to severe frailty was associated with a 1.71 (95% CI 1.65‒1.78) higher odds of having short time at home in the 6 months following SNF discharge. CONCLUSION AND IMPLICATIONS: Higher CFI is associated with short time at home in Medicare beneficiaries who are discharged to the community after post-acute SNF stay. Our results support the utility of CFI in identifying SNF patients who need additional resources and interventions to prevent health decline and poor quality of life.

Change in a Claims-Based Frailty Index, Mortality, and Health Care Costs in Medicare Beneficiaries.

BACKGROUND: A claims-based frailty index (CFI) allows measurement of frailty on a population scale. Our objective was to examine the association of changes in CFI over 12 months with mortality and Medicare costs. METHODS: We used a 5% sample of fee-for-service Medicare beneficiaries. We estimated CFI (range: 0­1: nonfrail (<0.25), mildly frail (0.25­0.34), moderately-to-severely frail (≥0.35) on January 1, 2015 and January 1, 2016. Beneficiaries were categorized as having a large decrease (-<0.045), small decrease (-≤0.045-0.015), stable (±0.015), small increase (>0.015-0.045), or large increase (>0.045). We used Cox proportional hazards model to estimate hazard ratio (HR) for mortality adjusting for age, sex, and 2015 CFI value and compared total Medicare costs from January 1, 2016 to December 31, 2016. RESULTS: The study population included 995 664 beneficiaries (mean age 77 years, 56.8% female). In nonfrail (n = 906 046), HR (95% confidence interval [CI]) ranged from 0.71 (0.67-0.75) for a large decrease to 2.75 (2.68-2.33) for a large increase. In moderate-to-severely frail beneficiaries (n = 16 527), the corresponding HR (95% CI) ranged from 0.63 (0.57-0.70) to 1.21 (1.06-1.38). The mean total Medicare cost per member per year (standard deviation) was from $12 149 ($83 508) in nonfrail beneficiaries to $61 155 ($345 904) in moderate-to-severely frail beneficiaries. CONCLUSIONS: One-year changes in CFI are associated with elevated mortality risk and health care costs across all levels of frailty.

Claims-Based Frailty Index as a Measure of Dementia Severity in Medicare Claims Data.

BACKGROUND: Dementia severity is unavailable in administrative claims data. We examined whether a claims-based frailty index (CFI) can measure dementia severity in Medicare claims. METHODS: This cross-sectional study included the National Health and Aging Trends Study Round 5 participants with possible or probable dementia whose Medicare claims were available. We estimated the Functional Assessment Staging Test (FAST) scale (range: 3 [mild cognitive impairment] to 7 [severe dementia]) using information from the survey. We calculated CFI (range: 0-1, higher scores indicating greater frailty) using Medicare claims 12 months prior to the participants' interview date. We examined C-statistics to evaluate the ability of the CFI in identifying moderate-to-severe dementia (FAST stage 5-7) and determined the optimal CFI cut-point that maximized both sensitivity and specificity. RESULTS: Of the 814 participants with possible or probable dementia and measurable CFI, 686 (72.2%) patients were ≥75 years old, 448 (50.8%) were female, and 244 (25.9%) had FAST stage 5-7. The C-statistic of CFI to identify FAST stage 5-7 was 0.78 (95% confidence interval: 0.72-0.83), with a CFI cut-point of 0.280, achieving the maximum sensitivity of 76.9% and specificity of 62.8%. Participants with CFI ≥0.280 had a higher prevalence of disability (19.4% vs 58.3%) and dementia medication use (6.0% vs 22.8%) and higher risk of mortality (10.7% vs 26.3%) and nursing home admission (4.5% vs 10.6%) over 2 years than those with CFI <0.280. CONCLUSIONS: Our study suggests that CFI can be useful in identifying moderate-to-severe dementia from administrative claims among older adults with dementia.

Restricted mean survival time versus conventional effect summary for treatment decision-making: A mixed-methods study.

BACKGROUND: Treatment effect is typically summarized in terms of relative risk reduction or number needed to treat ("conventional effect summary"). Restricted mean survival time (RMST) summarizes treatment effect in terms of a gain or loss in event-free days. Older adults' preference between the two effect summary measures has not been studied. METHODS: We conducted a mixed methods study using a quantitative survey and qualitative semi-structured interviews. For the survey, we enrolled 102 residents with hypertension at five senior housing facilities (mean age 81.3 years, 82 female, 95 white race). We randomly assigned respondents to either RMST-based (n = 49) or conventional decision aid (n = 53) about the benefits and harms of intensive versus standard blood pressure-lowering strategies and compared decision conflict scale (DCS) responses (range: 0 [no conflict] to 100 [maximum conflict]; <25 is associated with implementing decisions). We used a purposive sample of 23 survey respondents stratified by both their random assignment and DCS from the survey. Inductive qualitative thematic analysis explored complementary perspectives on preferred ways of summarizing treatment effects. RESULTS: The mean (standard deviation) total DCS was 22.0 (14.3) for the conventional decision aid group and 16.7 (14.1) for the RMST-based decision aid group (p = 0.06), but the proportion of participants with a DCS <25 was higher in the RMST-based group (26 [49.1%] vs 34 [69.4%]; p = 0.04). Qualitative interviews suggested that, regardless of effect summary measure, older individuals' preference depended on their ability to clearly comprehend quantitative information, clarity of presentation in the visual aid, and inclusion of desired information. CONCLUSIONS: When choosing a blood pressure-lowering strategy, older adults' perceived uncertainty may be reduced with a time-based effect summary, although our study was underpowered to detect a statistically significant difference. Given highly variable individual preferences, it may be useful to present both conventional and RMST-based information in decision aids.

Balancing Benefit and Harm of Intensive Blood Pressure Lowering Based on Individual Outcome Profile Analysis.

BACKGROUND: Intensive blood pressure lowering prevents major adverse cardiovascular events, but some patients experience serious adverse events. Examining benefit-harm profiles may be more informative than analyzing major adverse cardiovascular events and serious adverse events separately. METHODS: We analyzed data from the Systolic Blood Pressure Intervention Trial (n = 9361), comparing intensive treatment (systolic blood pressure target <120 mm Hg) to standard treatment (<140 mm Hg). A 4-year hierarchical outcome profile was defined for each participant: 1) alive with neither major adverse cardiovascular events nor serious adverse events (most desirable); 2) alive with serious adverse events only; 3) alive with major adverse cardiovascular events only; 4) alive with both events; and 5) deceased (least desirable). We compared 4-year outcome profiles between the treatment groups in the entire population and by frailty subgroups defined using physical frailty phenotype (non-frail, pre-frail, and frail). RESULTS: The proportion who died were lower with intensive treatment than standard treatment (5% vs 6%). A higher proportion of the intensive treatment group was alive with serious adverse events and no major adverse cardiovascular events (36% vs 33%), and a lower proportion were alive with both events (6% vs 5%) than the standard treatment group. The outcome profiles were more favorable among those with physical frailty phenotype who were treated with intensive treatment vs standard treatment, but outcome profiles were similar between the treatment groups among non-frail or pre-frail participants. CONCLUSIONS: This post hoc proof-of-concept analysis demonstrates the utility of the outcome profile analysis that simultaneously examines the benefit and harm of the treatment.

A crosswalk of commonly used frailty scales.

BACKGROUND: Several validated scales have been developed to measure frailty, yet the direct relationship between these measures and their scores remains unknown. To bridge this gap, we created a crosswalk of the most commonly used frailty scales. METHODS: We used data from 7070 community-dwelling older adults who participated in National Health and Aging Trends Study (NHATS) Round 5 to construct a crosswalk among frailty scales. We operationalized the Study of Osteoporotic Fracture Index (SOF), FRAIL Scale, Frailty Phenotype, Clinical Frailty Scale (CFS), Vulnerable Elder Survey-13 (VES-13), Tilburg Frailty Indictor (TFI), Groningen Frailty Indicator (GFI), Edmonton Frailty Scale (EFS), and 40-item Frailty Index (FI). A crosswalk between FI and the frailty scales was created using the equipercentile linking method, a statistical procedure that produces equivalent scoring between scales according to percentile distributions. To demonstrate its validity, we determined the 4-year mortality risk across all scales for low-risk (equivalent to FI <0.20), moderate-risk (FI 0.20 to <0.40), and high-risk (FI ≥0.40) categories. RESULTS: Using NHATS, the feasibility of calculating frailty scores was at least 90% for all nine scales, with the FI having the highest number of calculable scores. Participants considered frail on FI (cutpoint of 0.25) corresponded to the following scores on each frailty measure: SOF 1.3, FRAIL 1.7, Phenotype 1.7, CFS 5.3, VES-13 5.5, TFI 4.4, GFI 4.8, and EFS 5.8. Conversely, individuals considered frail according to the cutpoint of each frailty measure corresponded to the following FI scores: 0.37 for SOF, 0.40 for FRAIL, 0.42 for Phenotype, 0.21 for CFS, 0.16 for VES-13, 0.28 for TFI, 0.21 for GFI, and 0.37 for EFS. Across frailty scales, the 4-year mortality risks between the same categories were similar in magnitude. CONCLUSION: Our results provide clinicians and researchers with a useful tool to directly compare and interpret frailty scores across scales.

Recent developments in frailty identification, management, risk factors and prevention: A narrative review of leading journals in geriatrics and gerontology.

Frailty is an age-related clinical condition characterised by an increased susceptibility to stressors and an elevated risk of adverse outcomes such as mortality. In the light of global population ageing, the prevalence of frailty is expected to soar in coming decades. This narrative review provides critical insights into recent developments and emerging practices in frailty research regarding identification, management, risk factors, and prevention. We searched journals in the top two quartiles of geriatrics and gerontology (from Clarivate Journal Citation Reports) for articles published between 01 January 2018 and 20 December 2022. Several recent developments were identified, including new biomarkers and biomarker panels for frailty screening and diagnosis, using artificial intelligence to identify frailty, and investigating the altered response to medications by older adults with frailty. Other areas with novel developments included exercise (including technology-based exercise), multidimensional interventions, person-centred and integrated care, assistive technologies, analysis of frailty transitions, risk-factors, clinical guidelines, COVID-19, and potential future treatments. This review identified a strong need for the implementation and evaluation of cost-effective, community-based interventions to manage and prevent frailty. Our findings highlight the need to better identify and support older adults with frailty and involve those with frailty in shared decision-making regarding their care.

Feasibility of Measuring Frailty and Patient-Reported Outcomes During and After Post-Acute Skilled Nursing Facility Rehabilitation.

Functional status and quality of life are not routinely assessed after skilled nursing facility (SNF) discharge. We determined feasibility of measuring frailty among adults ≥65 years admitted to SNF after hospitalization, and post-discharge outcomes. We calculated a frailty index (non-frail [≤0.25], mild frailty [0.26-0.35], moderate [0.36-0.45], and severe [>0.45]). After SNF discharge, we conducted serial telephone interviews measuring ability to perform functional activities and Patient Reported Outcome Measurement Information System (PROMIS) scores. Overall of 68 screened patients, 42 were eligible, and 24 (57.1%) eligible patients were enrolled. Of these, 5 (20.8%) were admitted after elective hospitalizations, 17 (70.8%) were female, and 11 (45.8%) had moderate-to-severe frailty. Frailty was measured in all participants in a mean 32.1 minutes. At 90 days, a total of three participants died, and two were lost to follow-up. Post-discharge functional status varied by frailty, with moderate-to-severe frailty having persistent impairment and lower PROMIS scores (worse quality of life) compared to those with no or mild frailty (38.2 [13.7] vs. 47.3 [8.1] p = .04). Measuring frailty and quality of life in older patients admitted to SNF is feasible. Furthermore, measuring frailty may help identify those at particularly high risk of poor recovery and lower quality of life after discharge.

Frailty and Differences in Self-Reported Sexual Functioning Among Older Females and Males in National Social life, Health and Aging Project.

OBJECTIVE: To understand the association of frailty with females' and males' self-reported sexual functioning. METHODS: Logistic regression on 5 domains of sexual function by frailty status (robust, pre-frail, frail) were analyzed from 2058 respondents to National Social Life, Health, and Aging Project (2010-2011). RESULTS: Females had similar frailty profiles to males, but more often reported low overall sexual functioning (12.9% v. 4.0%). Compared to robust, pre-frail and frail males had higher odds of sexual function-related: anxiety (pre-frail OR 1.91 95% CI [1.33, 2.74]; frail OR 2.13 95% CI [1.03, 4.41]), negative changes (pre-frail: OR 1.40, 95% CI [1.00, 1.96]; frail: OR 2.42, 95% CI [1.51, 3.89]), and erectile dysfunction (pre-frail: OR 1.81, 95% CI [1.23,2.68]; frail: 2.00, 95% CI [1.00,4.02]); frail females had 1.69 times higher odds (95% CI [1.16,2.48]) of negative changes. DISCUSSION: Frailty may be a clinical indicator of sexual functioning decline for males more than females.