Journal of the American Geriatrics Society

We describe six-month functional status, hospitalization, and mortality among 23,632 cases of Long Covid in skilled nursing facilities (SNFs) in the US, primarily experienced by adults over 65 years old. We describe outcomes across seven medications used to treat Covid-19 including functional status (ADLs).

ObjectiveIdentify subgroups of postoperative older adults using electronic health record data. Summary of Background DataPostoperative older adults represent a vulnerable population who may benefit from tailored postoperative care pathways. Identifying clinical subgroups can inform the development of these pathways. MethodsRetrospective cohort study of postoperative adults >65 years (N=2,036) from a single healthcare system. Latent class analysis was used to identify patient subgroups based on measures of frailty, mobility, activities of daily living, and general health status. Hospital outcomes were described among each subgroup, including extended lengths of stay (LOS) (>0.5 SD beyond mean LOS by surgical category), discharge disposition (i.e., home versus non-home discharge), and utilization (weekly visit frequency) of physical therapy (PT) and occupational therapy (OT). ResultsWe identified 3 subgroups that we labeled Low Frailty-High Mobility (LF-HM), High Frailty-Low Mobility (HF-LM), and Low Frailty-Low Mobility (LF-LM), representing 15.3%, 27.6%, and 57.1% of the cohort, respectively. Discharge to home was highest among the LF-HM group (99%), followed by LF-LM (96%), and HF-LM (77%). Extended LOS was most common among the HF-LM group (27%), followed by LF-LM (18%), and LF-HM (6%). PT and OT visit frequencies were highest in the HF-LM group followed by the LF-LM and LF-HM groups. ConclusionsThis study identified 3 subgroups of postoperative older adults using routinely collected patient data. These groups may help to identify patients with increased odds of non-home discharge, extended LOS, and higher utilization of PT and OT and may inform the development of tailored postoperative care pathways for older adults.

BackgroundPre-injury frailty among older trauma patients is a predictor of increased morbidity and mortality. We sought to determine the relationship between frailty status and the care trajectories of older adult patients who underwent frailty screening in the emergency department (ED). MethodsUsing a retrospective cohort design of a single institutional trauma database, we pooled data on trauma patients, 65 years and older, who had frailty screening at ED presentation (N=987). The predictor variable was frailty status, measured as either robust, pre-frail, or frail. The outcome variables were measures of clinical care trajectory: inpatient admission, length of hospital stay, home discharge, and discharge to rehabilitation. We controlled for age, sex, race/ethnicity, body mass index, Charlson Comorbidity Index, injury type and severity, and Glasgow Coma Scale score. We performed multivariable logistic and quantile regressions to measure the influence of frailty on post-trauma care trajectories. ResultsThe mean (SD) age of the study population was 81 (9.0) years and the population was predominantly female (66%) and non-Hispanic White (64%). Compared to older adult trauma patients classified as robust, those categorized as frail had 2.8 (95% CI: 1.75 - 4.40), 0.4 (95% CI: 0.27 - 0.63), and 2.1 (95% CI: 1.38 - 3.27) times the adjusted odds of hospital admission, home discharge, and discharge to rehabilitation, respectively. Those classified as pre-frail (Adjusted MD: 1.0; 95% CI: 0.46 - 1.54) and frail (Adjusted MD: 2.0; 95% CI: 1.35 - 2.65) had longer lengths of hospital stay compared to those classified as robust. ConclusionPre-injury frailty is a predictor of care trajectories for older-adult trauma patients.

Background: Advance care planning (ACP) documentation, including living wills and durable power of attorney (DPOA), is intended to support goal concordant end of life care. However, it is unknown if comprehensive documentation confers additional benefits, and how these associations vary across clinical contexts. Methods: We used 2010 to 2022 Health and Retirement Study exit interview data to examine associations between ACP documentation and end of life care among U.S. adults aged 50 years and older. Documentation was categorized as none, one document (living will or DPOA), or two documents (both). Outcomes included intensive care unit (ICU) use, life sustaining treatment, hospice enrollment, and out-of-hospital death. Modified Poisson regression models were used to estimate adjusted risk ratios (aRRs), and temporal trends in documentation were assessed using joinpoint regression. Results: Among 5,622 decedents representing 23.2 million individuals, 42.7% had two documents and 28.9% had none, documentation increased substantially around 2014. Compared with no documentation, having any documentation was associated with lower likelihood of life-sustaining treatment (aRR=0.85, 95% CI: 0.74 to 0.98) and higher likelihood of hospice enrollment (aRR=1.43, 95% CI: 1.28 to 1.60) and out-of-hospital death (aRR=1.11, 95% CI: 1.06 to 1.18), but not ICU use. Having two documents showed similar patterns, with modest differences compared with one document after adjustment. Associations were stronger among decedents with expected death and attenuated among those with unexpected death. Conclusions: Comprehensive ACP documentation is associated with less aggressive end of life care and greater hospice use, though the incremental benefits of two documents are modest. Findings highlight the importance of documentation within care planning processes and the clinical context.

Background/ObjectivesCoronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state and increased thrombotic risk in infected individuals. Several complex and varied coagulation abnormalities were proposed for this association1. Acetylsalicylic acid(ASA, aspirin) is known to have inflammatory, antithrombotic properties and its use was reported as having potency to reduce RNA synthesis and replication of some types of coronaviruses including human coronavirus-299E (CoV-229E) and Middle East Respiratory Syndrome (MERS)-CoV 2,3. We hypothesized that chronic low dose aspirin use may decrease COVID-19 mortality relative to ASA non-users. MethodsThis is a retrospective, observational cohort analysis of residents residing at Veterans Affairs Community Living Centers from December 13, 2020, to September 18, 2021, with a positive SARS-CoV-2 PCR test. Low dose aspirin users had low dose (81mg) therapy (10 of 14 days) prior to the positive COVID date and were compared to aspirin non-users (no ASA in prior 14 days). The primary outcome was mortality at 30 and 56 days post positive test and hospitalization. ResultsWe identified 1.823 residents who had SARS-CoV-2 infection and 1,687 residents were eligible for the study. Aspirin use was independently associated with a reduced risk of 30 days of mortality (adjusted HR, 0.60, 95% CI, 0.40-0.90) and 56 days of mortality (adjusted HR, 0.67, 95% CI, 0.47-0.95) ConclusionChronic low dose aspirin use for primary or secondary prevention of cardiovascular events is associated with lower COVID-19 mortality. Although additional randomized controlled trials are required to understand these associations and the potential implications more fully for improving care, aspirin remains a medication with known side effects and clinical practice should not change based on these findings.

BackgroundFrailty is a geriatric syndrome characterized by an increased vulnerability to stressors and increased risk of adverse clinical outcomes. While older patients with acute stroke are routinely screened for prestroke disability using the modified Rankin Scale (mRS), because of its known association with stroke outcomes, prestroke frailty is still rarely assessed. The Clinical Frailty Scale (CFS) is a popoular tool for retrospective frailty assessment in the acute setting. The study hypothesis was that prestroke frailty measured with CFS was associated with stroke outcome of older patients independent of prestroke disability assessed with mRS. MethodsWe recruited 4086 individuals aged [≥]65 years consecutively admitted with acute stroke to an Italian hospital. Prestroke disability (mRS [≥]3) was assessed at admission. Prestroke CFS was retrospectively assessed using information from the medical records. Logistic models determined the association of CFS with poor functional outcome, prolonged discharge, unfavorable discharge setting, and poor rehabilitation potential. Cox models determined the association of CFS with 30-day and 1-month mortality. All models were adjusted for prestroke disability and other major confounders. ResultsParticipants were median age 81 years (25th-75th percentile, 75-87 years), 55.0% female, 82.6% with ischemic stroke, and 26.3% with prestroke disability. Overall prevalence of prestroke frailty (CFS [≥]4) was 41.6%. Multivariable-adjusted logistic models showed that CFS was associated with increasing risk of all outcomes except prologed discharge. In severe frailty (CFS 7-8), OR (95%CI) was 3.44 (2.33-5.07) for poor functional outcome, 0.53 (0.38-0.75) for prolonged discharge, 1.89 (0.36-263) for unfavourable discharge, and 6.24 (3.80-10.26) for poor rehabilitation potential (reference CFS 1-3). In multivariable adjusted-Cox models, CFS was unrelated to 30-day mortality but HR (95%CI) of 1-year mortality was significant for both CFS 4-6 (1.70, 1.36-2.11) and CFS 7-8 (1.69, 1.25-2.30). ConclusionsPrestroke frailty measured with CFS was associated with higher risk of several adverse outcomes even after adjustment for prestroke disability and other major confounders.

BackgroundFrailty and multimorbidity are common in older adults and contribute substantially to prolonged hospitalizations, readmissions, and mortality. Yet, existing prediction models often fail to integrate frailty-specific biomarkers and lack interpretability for routine clinical use. ObjectivesTo develop and internally validate an interpretable, machine learning-enhanced logistic regression model to predict prolonged hospital length of stay (LOS) among frail older adults with multimorbidity, and to identify key predictors to guide individualized inpatient care. MethodsWe conducted a retrospective study of 440 hospitalized adults aged [≥]65 years with multimorbidity ([≥]2 chronic conditions) and frailty (Frailty Index [≥]0.25) at a tertiary geriatric department between January 2022 and December 2023. Fourteen demographic, clinical, and biochemical variables were analysed. Feature selection employed Elastic Net regularization, Extreme Gradient Boosting with SHAP value analysis, and the Boruta algorithm to ensure robust predictor identification. A multivariable logistic regression model was trained and internally validated using stratified 10-fold cross-validation and 1,000 bootstrap iterations. Discrimination (AUC-ROC), calibration, and clinical utility (decision curve analysis) were assessed. ResultsEight predictors age, diabetes, hypertension, prior stroke, serum albumin, HDL cholesterol, systolic blood pressure, and neutrophil-to-lymphocyte ratio--were retained in the final model. The model achieved good discrimination (AUC = 0.770, 95% CI 0.688-0.853) and acceptable calibration (Hosmer-Lemeshow {chi}{superscript 2} = 14.86, p = 0.062). Cross-validation (mean AUC 0.687 {+/-} 0.072) and bootstrap correction (AUC 0.672) confirmed internal stability. Serum albumin was the strongest protective factor, while elevated neutrophil-to-lymphocyte ratio and prior stroke were significant risk factors. ConclusionsThis interpretable model accurately predicts prolonged hospital stay in frail older adults with multimorbidity using routinely available clinical data. Its transparent design supports integration into electronic health records for real-time risk stratification, facilitating targeted discharge planning and personalized geriatric care.

ObjectivesEvaluate neurocognitive health and its response to interventions in older, obese patients with heart failure with preserved ejection fraction (HFpEF). BackgroundNeurocognitive dysfunction may be an underrecognized feature of HFpEF that responds to weight-loss interventions. MethodsWe first compared detailed baseline cognitive testing (Uniform Data Set version 3 and Rey Auditory Verbal Learning Test [RAVLT]), and brain volumes and cerebral blood flow (CBF) from 3T magnetic resonance imaging between older patients with HFpEF (n=46) and healthy age-matched controls (HC; n=22). The HFpEF patients were then randomized to a 20-week caloric restriction (CR) intervention with either aerobic-only (CR+AT; n=23) or aerobic+resistance exercise training (CR+AT+RT; n=23), and repeated cognitive testing and neuroimaging post-intervention. Cognitive scores were normalized to national data and transformed to z-scores for global, memory, attention, executive function, visuospatial, and language fluency domains. ResultsCompared to HC, participants with HFpEF had significantly lower baseline global cognitive performance, and lower global, visuospatial processing and language fluency domain z-scores than normative means. Following the diet and exercise intervention, there were significant improvements in global (+0.6 [95% CI: 0.3, 0.8]) and category fluency (+0.2 [95% CI: -0.004, 0.3]) z-scores, and in RAVLT immediate (+0.6 [95% CI: 0.1, 1.0] points) and delayed (0.9 [95% CI: 0.2, 1.6] points) recall. Only CR+AT+RT was associated with improved phonemic fluency z-score (+0.4 [95% CI: 0.1, 0.7]). There were no significant intervention effects on brain volumes or CBF. ConclusionsOlder, obese patients with chronic HFpEF have significant cognitive deficits that are ameliorated by diet and exercise interventions.

BackgroundMobility loss is common in hospitalized older adults, and resources to prevent mobility loss are finite. Our goal was to develop a rapid, universal screening tool that identifies individuals at risk of losing the ability to walk during hospitalization on the first hospital day. Second, we determined if the model could inform the use of mobility-preserving interventions. MethodsWe included patients admitted to a general medical service, aged [&ge;]65 years, who could walk on admission (Braden Scale Activity subset >=3). Patients were considered to have a new mobility impairment if the activity score was <3 on discharge. We used predictors available on the first hospital day to develop (2017-18) and validate (2019) a prediction model. We determined the association between predicted risk and therapy use in the validation cohort to highlight the models clinical utility. Results5542 patients were included (median age 76yrs, 48% women); 7.6% were discharged unable to walk. The model included six predictors: age, marital status, medication administrations, Glasgow Coma Scale verbal score, serum albumin, and urinary catheter presence. In the validation cohort, the model discriminated well (c-statistic 0.75) and was strongly associated with hospital-acquired mobility loss (lowest decile 1%, highest decile 24%). In the validation cohort, therapy consultation ordering increased linearly with predicted risk; however, observed mobility loss increased exponentially. ConclusionThe Day-1 Mobility Loss model predicts the risk of mobility loss in hospitalized older adults on the first hospital day. Further, it identifies at-risk older adults who may benefit from mobility interventions.

BackgroundThe COVID-19 pandemic has greatly affected nursing home residents (NHRs), a vulnerable group with high rates of illness and death. While vaccination is essential for reducing infections and severe outcomes in the short term, it is important to understand how long antibody levels and neutralizing activity last. This understanding will help us create effective public health strategies for the long term. According to current CDC guidelines, individuals over the age of 65 should receive a booster dose six months after their previous vaccination. MethodsThis observational retrospective cohort study analyzed post-vaccination serum from samples with up to 400 days of follow-up from 697 NHRs and 127 healthcare workers (HCWs) across Northeast Ohio and Rhode Island. Analyses were conducted to model decay rates of both neutralizing and binding antibody titers and the impact of previous exposures to SARS-CoV-2 on these decay rates. ResultsResults indicate that NHRs show Wuhan and Omicron BA.4/5 neutralizing and binding antibody titers diminish significantly from 2 weeks to 12 months post-vaccination. NHRs with prior infection show higher peak antibody titers and slower decay than those naive to infection. Antibody levels after vaccination for infection-naive NHR residents lagged HCW and NHR with prior infection, but then decayed at a similar rate. ConclusionThe immunologic findings in this cohort of NHR are in line with the existing real-world clinical effectiveness data in older individuals and support the CDC recommendation of a bi-annual vaccination to reduce severe COVID-19 outcomes in persons age 65 and older.

ObjectivesTo evaluate rates of treatment for depression and identify resident- and facility-level predictors of pharmacotherapy among long-term care (LTC) residents in the United States. DesignRetrospective, observational study. Setting and ParticipantsElectronic health record data from 1,675,873 LTC residents in the PointClickCare Life Sciences database (January-April 2025) were reviewed and 358,425 skilled nursing facility residents with a documented depression diagnosis were identified. MethodsResidents were classified as treated/untreated based on having a medication order for pharmacological depression treatment within medication classes recommended by the American Psychological Association. Descriptive analyses incorporated demographic and clinical characteristics, and multivariable logistic regression estimated odds of treatment. ResultsOverall, 81.7% of residents diagnosed with depression had [&ge;]1 pharmacological depression treatment order. Selective serotonin reuptake inhibitors (59.8%) and miscellaneous antidepressants (42.3%) were the most frequently used classes. Treatment rates were similar across depression diagnoses. Higher odds of receiving treatment were observed among residents also diagnosed with vascular dementia and those with hyperlipidemia medication orders. Lower odds were noted among residents who were Black or African American, had diabetes or hyperlipidemia diagnoses, or resided in facilities located in areas with poor socioeconomic status. Conclusions and ImplicationsMost residents with depression had at least one recommended pharmacologic therapy, although important disparities remain. Racial differences, comorbid conditions, and facility context continue to influence treatment access. These findings support the need for improved screening practices, greater attention to equity in prescribing, and strengthened clinical resources in socially vulnerable settings to enhance the quality of depression care in LTC facilities. Brief SummaryDepression is common in long-term care (LTC) and is associated with poor functional and clinical outcomes, however recent treatment patterns are not well understood. Using electronic health record data from 1,675,873 U.S. LTC residents between January and April 2025, 358,425 skilled nursing facility residents were identified with a documented depression diagnosis. The use of antidepressant medication was assessed based on medication order history and was aligned with American Psychological Association recommendations. Overall, 81.7% had at least one pharmacologic treatment order for depression; selective serotonin reuptake inhibitors (59.8%) and miscellaneous antidepressants (42.3%) were most frequently used. After adjusting for covariates, lower odds of treatment were observed among Black or African American residents and among residents in facilities located in more socioeconomically vulnerable areas. These findings highlight persistent inequities in depression pharmacotherapy in LTC and support efforts to strengthen depression assessment and ensure equitable access to evidence-informed treatment across facilities.

ObjectiveTo evaluate whether home-based extended rehabilitation for older people with frailty after hospitalisation with an acute illness or injury can improve physical health-related quality of life and is cost-effective. Trial designPragmatic, multi-centre, individually randomised controlled parallel group superiority trial with economic evaluation and embedded process evaluation. SettingRecruitment from 15 NHS Trusts in England, with home-based intervention delivery. ParticipantsEligible participants were 65 years or older with mild/moderate/severe frailty (score of 5-7 on Clinical Frailty Scale) admitted to hospital with acute illness/injury, then discharged home directly, or from intermediate care (post-acute care) rehabilitation services. Recruitment took place December 2017 to August 2021, with follow-up to August 2022. InterventionsParticipants were randomly assigned (1.28:1) to the Home-based Older Peoples Exercise (HOPE) programme - a 24-week home-based manualised, progressive exercise intervention as extended rehabilitation, or usual care (control). Participants were not masked to allocation. Main outcome measuresPrimary outcome was physical health-related quality of life, measured using the physical component summary (PCS) of the modified Short Form 36-item health questionnaire (SF36) at 12 months. Secondary outcomes at six and 12 months included physical and mental health-related quality of life, functional independence, death, hospitalisations and care home admissions. Researchers involved in data collection were masked to allocation. ResultsWe randomised 740 participants (410 HOPE, 330 control) across 15 sites. 479 (64.7%) participants completed 12-month follow-up. 188 HOPE participants (45.9%) completed 24 weeks of intervention delivery. Over half of participants completed more than 75% of prescribed exercises. Intention-to-treat analyses showed no evidence that HOPE was superior to control for 12-month PCS score (adjusted mean difference -0.22, 95% CI -1.47 to 1.03; p = 0.73). There was some evidence of a higher rate of all-cause hospitalisations in the control arm (incidence rate ratio 1.12, 95% CI 1.00 to 1.25; p = 0.05), but no differences in other outcomes. The process evaluation found the intervention was largely delivered as intended and proved acceptable to most participants. The economic analysis showed HOPE plus usual care costs of GB{pound}1,401 with 0.024 QALY improvement compared to the control. Incremental cost-effectiveness ratio GB{pound}58,375. LimitationsThe HERO trial was delivered during especially challenging circumstances that included the COVID-19 pandemic. We examined outcomes taking account of this but detected no difference in primary or secondary outcomes, providing reassurance that COVID-19 was unlikely to have influenced trial results. ConclusionsBased on our findings, we do not recommend routine commissioning of extended rehabilitation for older people with frailty after discharge home from hospital or intermediate care, following an acute admission with a medical illness or injury. Trial registrationISRCTN-13927531 (19/04/2017).

BackgroundLimitations in activities of daily living have widespread implications for the well-being of older adults. However, the relation between performance-based physical function and self-reported functional impairment is inconsistent. MethodsThe cohort included 6,282 White women and 310 Black women aged 65 and older participating in the Study of Osteoporotic Fractures (SOF) from 1986 to 2010 who reported no limitations in any Instrumental Activities of Daily Living (IADL) at baseline. Approximately every two to six years, participants self-reported their physical limitations and trained interviewers assessed common measures of physical performance (i.e., usual gait speed, grip strength, and chair stand time). We used Cox proportional hazards models using age as the time scale to calculate hazard ratios between individual and summary measures of physical performance and incident IADL limitations. ResultsOver follow-up, 4,193 White women and 118 Black women developed IADL impairment (IR = 451.34 and 361.52 per 10,000 person-years, respectfully). Usual gait speed was associated with IADL limitations in both race cohorts (slowest gait vs. fastest gait HR: 3.83, 95% CI: 3.41 - 4.31; HR: 2.59, 95% CI: 1.42 - 4.73). For every one-point increase in summary performance score, rate of IADL limitations was lower for both White women and Black women (HR: 0.79, 95% CI: 0.78-0.80; HR: 0.87, 95% CI: 0.81 - 0.94). ConclusionIn this longitudinal study, women with poorer performance in individual and summary measures of physical function had an increased rate of incident IADL limitations over follow-up compared to women with the best performance. These findings confirm previous research using cross-sectional data.

ObjectivesThe older population requiring long-term care (LTC) exhibits heterogeneity in physical and cognitive functions; however, an established classification is lacking. We aimed to identify distinct subgroups of older adults with LTC needs using unsupervised machine learning and to examine differences in their prognoses. DesignRetrospective cohort study. Setting and participantsUsing survey data for care-need certification (linked to LTC and medical insurance claims) in City A, Japan, we identified community-dwelling adults aged [&ge;] 65 years who started LTC. Data from City B were used for validation of clustering. MethodsWe applied latent class analysis to group the participants in City A, based on all 74 items (38 on physical functions, 9 on cognitive functions, 15 on behavioral problems, and 12 on medical procedures) in the Japanese standardized care-needs certification survey. Then, we examined the association between the identified subtypes and four outcomes, including death, hospitalization, nursing home admission, and care-need level deterioration, using regression models. ResultsAmong 3,841 participants in City A (median age, 83 years; 59.3% female), five subtypes were identified: (i) mild physical, (ii) mild cognitive, (iii) moderate physical, (iv) moderate multicomponent, and (v) severe multicomponent. The results of clustering were replicated in City B. Compared with the mild physical subtype, the severe multicomponent subtype showed the highest risk of death (adjusted hazard ratio [aHR] 2.56; 95% confidence interval [CI] 2.02-3.24), and nursing home admission (aHR 5.91; 95% CI 4.57-7.63). The moderate physical subtype showed a higher risk of hospitalization (aHR 1.32; 95% CI 1.16-1.49), and the moderate multicomponent subtype was more likely to experience care-need deterioration (adjusted odds ratio 1.67; 95% CI 1.26-2.22). Conclusions and ImplicationsThis study identified five subtypes of older adults who started LTC. These findings inform individualized care decisions and tailored planning of medical and LTC services.

BackgroundPotentially inappropriate medications (PIMs) are known to be associated with adverse outcomes in older adults, yet evidence among those with dyslipidemia--who often experience polypharmacy--remains limited. MethodsWe conducted a nationwide, retrospective cohort study in South Korea using the Health Insurance Review and Assessment Service (HIRA) claims linked to national death records. Adults aged [&ge;]65 years with [&ge;]2 dyslipidemia diagnoses between January and June 2018 were classified as exposed to PIMs per the Drug Utilization Review (DUR) list and followed from a landmark date (July 1, 2018) through June 30, 2024 for all-cause mortality. The primary objective was to compare mortality between the PIM and non-PIM groups; comparisons were conducted using an unadjusted Cox model, an adjusted Cox model, and a propensity score-matched (PSM) cohort (propensity scores estimated via logistic regression including all baseline covariates). Balance was assessed using standardized mean differences, and proportional hazards were checked with scaled Schoenfeld residuals. ResultsOf 943,332 participants, 1.7% received at least one potentially inappropriate medication (PIM) at baseline. Over 6 years, the Kaplan-Meier cumulative mortality was 14.2% in the PIM group versus 11.9% in the non-PIM group (absolute risk difference, 2.3 percentage points; relative risk, 1.19). PIM exposure was significantly associated with increased six-year all-cause mortality risk in both propensity score-matched (HR, 1.12; 95% CI, 1.05-1.19) and multivariable-adjusted analyses (HR, 1.10; 95% CI, 1.05-1.15; both p < 0.001). In subgroup analyses, compared with a single PIM, multiple PIMs showed a numerically higher but non-significant risk (HR, 1.11; 95% CI, 0.79-1.56). ConclusionsAmong older adults with dyslipidemia, PIM prescriptions were associated with a 12% increased risk of all-cause mortality in the PSM cohort. These findings support cautious prescribing and regular medication reviews to minimize risk in this high-risk population.

BackgroundFrailty assessment in the Emergency Department (ED) is essential for identifying older adults at risk of adverse outcomes. The 20-item Clinical-Functional Vulnerability Index (IVCF-20) is a rapid, multidimensional screening tool widely used in Brazilian primary care, but its predictive validity in the ED has not been established. We aimed to evaluate the ability of the IVCF-20 to predict 180-day mortality and other adverse outcomes in older adults admitted to a public ED. MethodsObservational cohort study comprising patients aged [&ge;]60 years consecutively admitted through the ED of a University Hospital in Brazil. Baseline frailty was assessed with the IVCF-20 and categorized as robust (0-6), pre-frail (7-14), mild-to-moderate (15-29), and severe frail (30-40). The Clinical Frailty Scale (CFS), a validated frailty tool in the ED, was also applied. The primary outcome was 180-day mortality; secondary outcomes included in-hospital and 90-day mortality, prolonged length of stay, home care referral, and ED revisit or hospital readmission. Logistic regression estimated associations between frailty and 180-day mortality, Kaplan-Meier curves illustrated survival across frailty levels. ROC analyses evaluated secondary outcomes. ResultsA total of 310 patients with a median age of 72 years, 58.1% were male. Frailty prevalence ranged from 53.9% (IVCF-20) to 60.1% (CFS). The IVCF-20 score was independently associated with 180-day mortality (adjusted OR = 1.06; 95% CI = 1.02-1.10; p = 0.002). Severely frail participants had an 8.4-fold higher risk of death than robust individuals (adjusted OR = 8.37; 95% CI = 2.20-31.81). Kaplan-Meier curves showed a graded mortality increase across IVCF-20 categories. Both instruments predicted secondary outcomes, though CFS demonstrated slightly better discrimination for mortality. ConclusionsIVCF-20 predicted 180-day mortality, home care referral, and ED revisit/readmission. Its rapid, judgment-free format supports its feasibility for frailty screening at the ED.

ObjectivesAntithrombotic drugs--anticoagulants and thrombolytics-- may interact with anti-amyloid monoclonal antibodies (mAbs) to increase intracranial hemorrhage risk, so expert guidance recommends against their co-prescription. We aimed to estimate how many people with mild cognitive impairment (MCI) or dementia develop a new cardiovascular indication for antithrombotic drugs. MethodsIn a longitudinal cohort of adults [&ge;]65 years old from the Health and Retirement Study (2010-2020) with linked Medicare claims and no prior indication for anticoagulants, cognition was categorized as normal, MCI, or dementia. We fit Fine-Gray separate survival models accounting for competing risk of death to estimate 1-year incidence of atrial fibrillation (AF), deep vein thrombosis (DVT), pulmonary embolism (PE), acute myocardial infarction (MI), and stroke. ResultsAmong 12,373 participants (mean age 73 years, 59% female), for MCI, 1-year incidence was 1.7% for AF, 1.2% for DVT, 0.4% for PE, 1.2% for AMI, 2.0% for stroke, and 5.7% for any indication. In dementia, 1-year rates were 1.7% for AF, 1.8% for DVT, 0.3% for PE, 1.0% for AMI, 2.4% for stroke, and 6.7% for any indication. DiscussionOur finding inform shared decision-making about the tradeoffs of anti-amyloid mAbs.

BackgroundAge-related muscle dysfunction is a major contributor to disability, frailty, and poor clinical outcomes in older adults. Muscle mass and strength provide limited insight into the multifactorial nature of muscular decline. Skeletal Muscle Function Deficit (SMFD) framework integrates multiple domains muscle mass, quality, strength, and power to capture a broader spectrum of age-related muscle dysfunction. ObjectiveTo develop and validate a composite SMFD score and evaluate its association with key geriatric outcomes in older adults. MethodsThis study used data from the InCHIANTI longitudinal cohort (1998-2018), including 1,035 participants and 3,196 total assessments. The SMFD score (range 0-20) was computed by assigning quintile-based values of muscle area, density, strength, and lower limb power. Associations with disability in basic and instrumental activities of daily living (BADL/IADL), frailty phenotype, poor physical performance (SPPB <7), hospitalization, falls number, and major chronic diseases were analyzed using mixed-effects models, adjusting for age, sex, fat area, and multimorbidity. ResultsThe SMFD score declined significantly over time and was independently associated with lower risk of BADL (OR 0.57), IADL (OR 0.70), frailty (OR 0.72), poor performance (OR 0.68), hospitalization (OR 0.96), and falls number (OR 0.96). Higher SMFD scores were also inversely associated with the prevalence and incidence of Parkinsons disease, stroke, and hip osteoarthritis. ConclusionsThe SMFD score is a valid, multidimensional measure that predicts adverse outcomes in older adults more effectively than traditional sarcopenia, dynapenia, and powerpenia. It holds promise for use in clinical assessment, risk stratification, and targeted interventions.

BackgroundBody composition strongly influences clinical outcomes in older adults, yet body mass index (BMI) lacks discriminatory power, and standard tools such as bioelectrical impedance analysis (BIA), dual-energy X-ray absorptiometry are not routinely accessible. Deep learning enables scalable, opportunistic assessment of body composition from chest radiographs (CXRs), one of the most widely available imaging modalities. Methods and FindingsUsing the Inception-V3 architecture, we developed a deep-learning model using 107,568 paired CXR and BIA records (2016-2018). The model was temporally validated on a separate dataset of 77,655 records (2014-2015). Our model predicted skeletal muscle mass (SMM) and fat mass (FM) with high accuracy (SMM: Pearson r = 0.967, MAE 1.40 kg; FM: r = 0.924, MAE 1.61 kg). In a cohort of 5,932 older adults (aged [&ge;]65years), a 1-SD increase in CXR-predicted skeletal muscle index (SMI) was associated with a significant reduction in 10-year all-cause mortality (Hazard Ratio [HR] 0.65 [95% CI 0.58-0.73] for men; 0.80 [0.67-0.97] for women). In an external validation of 925 geriatric clinic patients, predicted SMI also showed comparable associations with geriatric parameters, including lower odds of sarcopenia (per 1 SD increase: 0.29 [0.22-0.38] for men; 0.25 [0.18-0.34] for women) and frailty (0.62 [0.48-0.78] for men; 1.00 [0.81-1.23] for women). These associations were more robust than those of BMI. Key limitations include the retrospective, single-center design and the use of a relatively healthy screening population. ConclusionA deep learning model applied to routine CXRs enables accurate estimation of skeletal muscle and fat mass, demonstrating prognostic and functional relevance comparable to BIA measurements. This approach may serve as a practical, low-cost tool for risk stratification and long-term care planning, particularly in older adults.

BackgroundPre-frailty and frailty prevalence is increasing in the Western Pacific, resulting in substantial morbidity and mortality in older populations. Modelling frameworks are required to estimate the prevalence of frailty and potential impacts of ongoing population-level nutritional interventions. MethodsUsing a microsimulation sociodemographic model of 3,353,032 individuals from 1990 to 2050, and data from the Singapore Longitudinal Ageing Study 2 of 3,270 participants, we developed a Bayesian multistate model of robust, pre-frailty and frailty stages with estimated transition probabilities by age, ethnicity, and gender for each body-mass index (BMI) category. We then explored four scenarios where weight management interventions are applied that modify the annual distribution of underweight, normal weight, overweight, obese I and obese II individuals. FindingsBetween 2011 and 2050, the overall prevalence of pre-frailty and frailty increased from 44{middle dot}2% to 46.9%, and from 3{middle dot}2% to 11{middle dot}3% respectively. Reductions of 811 pre-frail individuals (95% CrI: 624-1,127) and 36,202 frail individuals (22,109- 41,124) were estimated when underweights shifted to normal weights, 5,787 (3,670- 7,707) and 55,777 (32,683-80,941) when obese II moved to obese I, and 22,045 (18,430-23,487) and 62,847 (40,165-91,517) when both groups shifted respectively. Total healthcare utilization decreases by 6{middle dot}9% (4.3%-8{middle dot}1%) with the latter intervention. InterpretationFrailty prevalence is projected to substantially increase by 2050 where large-scale weight management interventions could be utilised to avert cases of both pre-frailty and frailty in older individuals. FundingThis research was supported by the Population Health Metrics and Analytics project, the Ministry of Health and National Innovation Challenge (NIC Ageing), Healthy Longevity Catalyst Awards (HLCA) MOH-HLCA22Feb-0007.