Journal of the American Geriatrics Society

Burn trauma disproportionately impacts older adults, yet existing burn severity models emphasize age, total body surface area (TBSA), and inhalation injury without accounting for geriatric-specific vulnerabilities such as frailty. We conducted a retrospective cohort study of 326 geriatric patients admitted with burn injuries between 2020 and 2024 to evaluate how TBSA, burn location, inhalation injury, renal insufficiency, comorbidities, and functional dependence in activities of daily living (ADLs) and instrumental activities of daily living (IADLs) affect in- hospital mortality and discharge disposition. Based on multivariable logistic regression and chi- square analyses, TBSA, as expected, emerged as the strongest predictor across models. Each 1% increase in TBSA was associated with a 7% increase in the odds of in-hospital mortality (p=0.006) and a 12 to 19% increase in odds of post-acute care placement (p<0.001). Inhalation injury and renal insufficiency were also independently associated with increased odds of both mortality and post-acute care disposition, whereas respiratory comorbidity predicted mortality alone. Functional status demonstrated outcome-specific prognostic value: ADL dependence predicted mortality, while IADL dependence predicted discharge disposition. Patients with some ADL dependence had five-fold higher odds of in-hospital mortality (p=0.011), while some (OR=2.48, p= 0.039) and full IADL dependence (OR=2.61, p=0.025) were associated with higher odds of post-acute care placement. Integrating structured functional assessments that distinguish basic from instrumental limitations alongside established burn severity metrics may enhance prognostication and guide individualized care planning for older adults with burn injuries.

Postoperative resilience varies widely among older adults, yet the biological drivers of recovery remain unclear. We evaluated whether preoperative immune profiles, measured in plasma and through ex vivo whole blood stimulation, predict resilience to the acute stress of total knee arthroplasty. A total of 152 adults (greater or equal to 60 years) in the PRIME KNEE cohort underwent elective total knee arthroplasty and had available blood samples for measurement of 45 immune biomarkers, quantified in plasma and in whole blood stimulated ex vivo for 24 hours with lipopolysaccharide (LPS) or influenza antigen (FLU). Resilience was assessed using Expected Recovery Differential (ERD) and Resilience Trajectory (RT) across pain severity, pain interference, lower extremity physical activities of daily living (LE PADLs), and step counts. An exploratory stability selection framework using LASSO identified biomarker predictors of postoperative outcomes. Plasma and stimulated biomarkers showed broadly similar predictive performance. A shared set of biomarkers, including LBP, leptin, TNFR1, CD30, and LIF, was consistently selected across models. Immune predictors explained ~12-24% of the variance in resilience outcomes. Distinct immune signatures emerged for pain versus functional recovery: pain related predictors mapped to local inflammatory and neuroimmune pathways, whereas function related predictors reflected systemic inflammatory load and cytokine signaling. Preoperative immune biomarkers, whether measured in plasma or after ex vivo stimulation, capture meaningful variance in postoperative resilience. The divergence between pain related and function related immune signatures highlights biologically distinct pathways underlying different dimensions of recovery and supports further development of immune based perioperative risk assessment.

The VACS 2.0 Frailty Index was developed using the VA health records system to identify frailty and predict mortality in older Veterans that were living with HIV. Systemic inflammatory indices have been associated with frailty, but little is known about the association between frailty and immunosenescence. We aim to investigate the potential link between soluble inflammatory indices, T cell expression of exhaustion and senescence markers, and frailty as measured by the VACS 2.0 index. We analyzed a one-time blood draw for plasma levels of inflammatory indices, T cell subsets and expression of exhaustion and senescence markers, and calculated VACS 2.0 index scores in a cohort of 30 older (>65 years) Veteran participants. We found that VACS 2.0 scores correlated with the number of prescribed medications in the older Veterans. Soluble TNF receptor levels strongly correlated with VACS 2.0 frailty scores. How these soluble TNF receptors are generated and whether they mechanistically contribute to frailty warrants further investigation.

Background: Wheeled walkers can improve safety during walking, but improper use may increase fall risk among frail older adults. No suitable tool exists to assess safe indoor wheeled walker use in this population. This study aimed to develop and validate a video-based expert assessment tool. Methods: Based on the literature and expert consensus, seven problematic indoor situations were identified, and an assessment tool with five safety criteria per situation was developed (maximum score = 35). Fifty participants (mean age 83.9 years, 64% women) from a geriatric rehabilitation clinic and a nursing home were video-recorded while using a rollator. Expert ratings were compared with nursing staff ratings, self-ratings, and the Timed Up and Go test to evaluate validity. Intra- and inter-rater reliability were determined from independent ratings by two physiotherapists and a repeated expert rating after seven days. Sensitivity to change was assessed after two weeks of rehabilitation, and feasibility by the time required for assessment. Results: The expert score of rater 1 at baseline was 28.5 points, and assessment required a mean of 17.5 minutes. Intra-rater reliability was excellent (ICC = 0.98) and inter-rater reliability was good (ICC = 0.80). Validity analyses showed the strongest association with nursing staff assessments (r = 0.74) and a moderate association with the Timed Up and Go test (r = -0.45). After two weeks, patients improved by an average of 2.38 points (8.4% of baseline score). Conclusions: The new instrument demonstrated high reliability, acceptable validity, sensitivity to change, and good feasibility for assessing safe wheeled walker use in frail older adults. Trial registration number and date of registration: DRKS00038358, 07/11/2025

Background Insomnia symptoms are common in older adults. While observational studies suggest physical activity (PA) timing affects health outcomes, its effect on sleep remains unclear. We compared morning versus evening PA effects on insomnia severity and sleep quality in older adults with insomnia symptoms. Methods Eligible participants were aged 60 to 80 years with (sub)clinical insomnia (Insomnia Severity Index [ISI] score [&ge;]10). In a randomized cross-over trial, participants engaged in coached PA in the morning (10:00 - 11:00) or evening (19:30 - 20:30) for 14 days each. ISI scores were assessed post-intervention. Objective sleep parameters; duration, latency, efficiency, and timing, were assessed with a Withings Sleep Analyzer under the mattress. Subjective sleep quality was reported daily via smartphone app. Salivary dim light melatonin onset (DLMO) was measured on the final day of each intervention. Results Of 37 participants (mean ISI 14.3 {+/-} 3.3), 27 completed the study (mean age 69.8 {+/-} 5; 63% women). ISI scores improved after both morning ({Delta} - 2.5; 95% CI: - 1.14, - 3.83) and evening ({Delta} - 2.0; 95% CI: - 0.63, - 3.38) activity relative to baseline, but were not different between interventions. Compared to evening activity, sleep midpoint occurred earlier with morning activity (03:40 vs 04:00; {Delta} - 20 min; 95% CI: - 31, - 8). No differences in subjective sleep quality or DLMO were found. Exploratory analyses suggested insomnia scores improved specifically in late chronotypes following morning activity. Conclusions While morning vs. evening PA timing did not impact most sleep quality measures, it influenced sleep timing. Larger studies are needed to define optimal and personalized PA timing for improving sleep.

OBJECTIVE: Bladder cancer (BC) is predominantly a disease of older, comorbid adults, and radical cystectomy (RC), which is the gold standard treatment, carries considerable morbidity. We sought to determine the impact of baseline dementia and frailty on the care trajectory beyond the immediate postoperative period. We hypothesized that frail patients and those with dementia undergoing RC for BC will have poorer care trajectories. METHODS AND MATERIALS: We identified Medicare beneficiaries [&ge;] 66 years old who underwent RC for BC in 2017 with 12 months of pre- and post-RC enrollment. Frailty and dementia were characterized using validated, claims-based measures. Associations between baseline frailty and dementia with postoperative care trajectory outcomes were determined using Fine-Gray competing risk models. RESULTS: We identified 3,600 beneficiaries of whom 11.6% were frail and 3.4% met criteria for dementia. Patients with dementia were more likely to be frail, comorbid, and not receive standard-of-care neoadjuvant chemotherapy. Frailty was independently associated with [&ge;] 2 transitions in care level after index discharge from RC and skilled nursing facility (SNF) admissions within 1 year of RC, exposure to intensive post-RC interventions, including dialysis and feeding tube placement, and poorer survival. Dementia remained associated with SNF admissions regardless of frailty level. CONCLUSIONS: Among a contemporary cohort of older adults undergoing RC for BC, preoperative dementia and frailty were independently associated with poorer care trajectory beyond the immediate postoperative period after RC. Our work highlights a role for preoperative geriatric assessment in identifying and optimizing patients at greatest risk.

Objective: Alzheimer's disease (AD) is a leading cause of death and disability, and treatment options for Alzheimer's disease and related dementias (ADRD) remain limited. We applied a data-driven, mechanism-agnostic Medication-Wide Association Study Plus (MWAS+) framework to identify candidate medications associated with ADRD using longitudinal electronic health record data and explainable artificial intelligence (AI). Methods: We used Veterans Health Administration electronic health record data from January 1999 to May 2022. The initial study population comprised 8,424,715 Veterans aged 65 years or older. Cases were defined by ADRD-related diagnosis codes or ADRD-related medication prescriptions, and controls were free of ADRD diagnosis and ADRD-related medication use. After exclusions and matching on sex, race, age at first encounter, and duration of follow-up, the primary analytic cohort included 505,817 matched case-control pairs (1:1; 1,011,634 Veterans). Longitudinal features were extracted from historical data up to 1 year before the index date and aggregated into 1-year intervals. We developed an upgraded Hybrid Value-Aware Transformer (HVAT 2.0) to jointly learn from longitudinal and nonlongitudinal clinical data while incorporating numerical values associated with clinical concepts, including cumulative medication dose. To enhance interpretability, we applied a medication-specific impact score method to estimate model-derived associations between medication exposure and ADRD risk. Findings: The model demonstrated stable performance across data partitions, with area under the receiver operating characteristic curve values of 0.791 in the training set, 0.772 in the validation set, and 0.775 in the testing set. Metolazone and varenicline were identified as the top 2 candidate medications with negative impact scores, suggesting potentially protective associations with new-onset ADRD. The impact score was -0.196 per unit of cumulative dose for metolazone (1800 mg) and -0.134 per unit for varenicline (280 mg). Although individual-level impact scores varied, most exposed patients had negative scores, including 12,020 of 12,480 metolazone users (96%) and 8,341 of 8,786 varenicline users (95%). Implications: This study demonstrates the feasibility of combining a medication-wide association framework, longitudinal dose-aware modeling, and explainable AI to identify candidate medications for ADRD from real-world electronic health record data. The findings should be interpreted as signals for hypothesis generation rather than evidence of causality. This framework may support prioritization of repurposing candidates for expert review, follow-up cohort validation, and future clinical investigation.

Background: Regular exercise is a highly effective yet underutilized strategy to reduce cardiometabolic disease burden. Whether brief structured exercise programs confer lasting cardiometabolic benefits remains unclear. The STRRIDE-Prediabetes Reunion study examined legacy effects of exercise training on cardiorespiratory fitness, body composition, and cardiometabolic health. Methods: Seventy-three participants (71.3 {+/-} 7.2 years; 64% women; 77% White) completed Reunion assessments ~11 years after completing one of four 6-month interventions differing in exercise amount, intensity, and inclusion of diet-induced weight loss. Linear mixed effects models evaluated longitudinal trajectories; secondary analyses examined baseline-adjusted associations among short-term intervention response and Reunion outcomes. Results: Abdominal adiposity improved across all groups from baseline to Reunion, with waist circumference decreasing ~3 cm over the follow-up period. In contrast, cardiorespiratory fitness and fat-free mass declined significantly. A significant group by time interaction was observed for total fat mass (p=0.01), with continued fat mass reductions observed in women randomized to high amount exercise. After baseline adjustment, greater short-term intervention response was associated with more favorable Reunion outcomes across fitness, body composition, and cardiometabolic domains; fat-free mass showed the strongest association ({beta}=0.84, p<0.0001). Conclusions: In older adults with prediabetes, the STRRIDE-Prediabetes interventions produced several legacy health effects persisting more than a decade later. Legacy effects differed by sex and exercise dose, and short-term intervention response relative to baseline was associated with long-term outcomes, supporting targeted exercise strategies to preserve cardiometabolic health and functional independence with aging.

Background: Depression and heart disease frequently co-occur in the aging population and are associated with functional decline and poor health outcomes. Understanding how depressive symptoms relate to different aspects of physical function among adults with heart disease may help identify high-risk subgroups. Objective: To examine the association of depressive symptoms with self-reported and observed physical function measures among participants with heart disease in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study and assess whether associations differ by sex and race?sex groups. Methods: We conducted a cross-sectional analysis using data from REGARDS study second in-home visit (2013?2016). Depressive symptoms were measured with the 10-item Center for Epidemiologic Studies Depression scale (CES D 10), considering scores ?10 as clinically significant. Physical function measures were instrumental activities of daily living (IADL), activities of daily living (ADL), chair stand time (5 repetitions), and gait speed. Linear regression models estimated associations of depressive symptoms with function, adjusting for sociodemographic, health behavior, antidepressant medications, body mass index, and social support. Effect modification by sex and race?sex group was evaluated. Results: Among 3,055 participants, 11.7% had CES D 10 ?10. Compared to CES-D-10 scores <10, CES D 10 ?10 was associated with more limitations in IADL (1.84 points; 95% CI 1.62, 2.06), ADL (0.43 points; 95% CI 0.34, 0.52) and slower chair stand time (0.88 second; 95% CI 0.07, 1.69); associations with gait speed were modest (?0.04 meters/second; 95% CI ?0.08, -0.01). Women had a stronger association between CES-D-10 and ADL (0.49 points; 95% CI 0.35, 0.64) than men (0.33 points; 95% CI 0.21, 0.44; p for interaction = 0.01). Interaction between CES D 10 and race?sex groups was not statistically significant. Conclusions: Among adults with heart disease, clinically significant depressive symptoms were associated with lower physical function, particularly among women.

Background. The emergency department in the United States of America functions as a residual access point for healthcare and social services for populations including rural communities, the uninsured, mental health and addiction patients, and the unhoused. The workforce variable that determines unit function (experience density, the concentration of accumulated clinical judgment within a unit workforce) is not measured in hospital accounting systems. Objective. To document workforce composition changes in U.S. emergency nursing across the 2018 and 2022 cycles of the National Sample Survey of Registered Nurses (NSSRN), and to specify falsifiable predictions for the 2026 cycle. Methods. We analyzed NSSRN public-use files using a four-way ED definition extending Castner et al. (2024) and a hospital-bedside-restricted comparator. Variance estimation used jackknife replicate weights for 2018 and Successive Differences Replication for 2022. Burnout was operationalized using the Norful et al. (2023) leaving-reasons proxy across cycles, with sensitivity analysis using the 2022 direct burnout item. Results. A 15-year trajectory (2008-2022) documents progressive experience-density compression: the ED's 15+ year veteran cohort fell from 41.9% to 28.0% over the decade preceding the pandemic, a loss of nearly a third of the senior cohort and a 19.6% decline in mean experience density, before recovering modestly to 33.3% as veteran nurses remained through the pandemic acute phase, leaving the ED as the youngest hospital setting throughout. Hospital non-ED bedside nurses lost senior tenure between cycles (mean 15.65[-&gt;]14.06 years since first licensure; 15+ year share 43.5%[-&gt;]38.7%), while ED nurses retained their senior tail (mean 11.60[-&gt;]12.58). Burnout endorsement rose sharply in both populations (non-ED 27.3%[-&gt;]46.0%; ED 34.2%[-&gt;]61.2%), with the ED-vs-non-ED gap more than doubling. Controlling for tenure, ED status was not independently associated with burnout in 2018 (OR 1.15, 95% CI 0.83-1.59) but was strongly associated in 2022 (OR 1.92, 95% CI 1.44-2.55; p<.001). The direct burnout item showed a parallel pattern (OR 2.92, 95% CI 1.62-5.28). Conclusions. A pandemic-era setting-specific burnout effect emerged in emergency nursing that workforce-composition controls cannot explain. The 2022 cycle establishes a pre-exit baseline against which the 2026 NSSRN will serve as the falsifiable test of post-Omicron veteran exit. Nursing pipeline replacement lag exceeds the interval before 2026 data arrives; the consequences of inaction fall on populations dependent on ED-based residual access.

Background Cardiovascular-kidney-metabolic (CKM) syndrome integrates adiposity, metabolic risk, kidney dysfunction, and cardiovascular disease in a prevention-oriented framework. National estimates across 1999-2023 NHANES and future burden remain limited. Methods We analyzed US adults aged 20 years from 11 NHANES cycles, 1999-2000 through August 2021-August 2023. CKM stage 0-4 was assigned using harmonized examination, laboratory, medication, and questionnaire data. Prevalence was survey-weighted and standardized to the 2010 US Census adult population. Decade trends used survey-weighted logistic regression adjusted for age, sex, and race and ethnicity. Exploratory 2040 and 2050 projections combined NHANES prevalence models with US Census projections under population-aging-only, trend-continuation, and risk-improvement scenarios. Results Among 62,890 eligible adults, 62,888 had sufficient CKM data. In 2021-2023, age-standardized prevalence was 87.9% (95% CI, 86.5%-89.4%) for CKM stage 1 and 62.0% (95% CI, 60.1%-63.8%) for stages 2-4. Stage 2 accounted for 50.1% (95% CI, 48.2%-51.9%) and stages 3-4 for 11.9% (95% CI, 11.0%-12.7%). From 1999-2000 to 2021-2023, any CKM increased by 4.6 percentage points (95% CI, 2.4 to 6.9; P<0.001), whereas stages 2-4 changed by 2.1 percentage points (95% CI, 5.1 to 0.8; P=0.156). In adjusted decade models, any CKM increased (OR, 1.28; 95% CI, 1.19-1.38; P<0.001), while stages 2-4 showed no significant linear trend (OR, 0.95; 95% CI, 0.89-1.01; P=0.084). Excess adiposity and diabetes increased, dyslipidemia declined, and hypertension, chronic kidney disease, and clinical cardiovascular disease were stable. With population aging alone, projected stages 2-4 burden rose from 164.8 million adults in 2023 to 193.7 million in 2050; under risk improvement, it was 147.7 million. Conclusions CKM syndrome remained highly prevalent among US adults. Although later stages did not increase significantly, population aging may expand the absolute care burden unless broad risk improvement occurs.

Background Chronic pain is common in adults aged 85 years and older (85+) and is associated with detrimental outcomes. Chronic pain guidelines advise first line management with non-pharmacological measures; paracetamol and non-steroidal anti-inflammatory drugs are the preferred analgesics. Challenges in accessing non-pharmacological therapies for adults aged 85+, and the presence of multimorbidity and polypharmacy, mean that opioid medication is often prescribed for chronic pain despite the potential for opioid-related adverse effects and guidance identifying long-term opioids for chronic pain as a potentially inappropriate prescription. Aim This study aims to explore patient, caregiver, and healthcare professional perspectives on the prescription of opioid medications for pain management for chronic pain in adults aged 85+ to support development of resources for optimising opioid prescribing. Design and Setting In this qualitative study, participants were recruited through primary care, in the community or in care home settings. Method 36 semi-structured interviews were conducted with care home residents and community dwellers aged 85+ (n=12), caregivers (informal and care home staff) (n=12), and healthcare professionals (n=12). Interviews were transcribed and analysed using reflexive thematic analysis. Results Four themes were developed: contextual complexity, satellite influences, balancing act, and pragmatic prescribing. Using opioids in adults aged 85+ is a balancing act to support patients best possible quality of life within their unique circumstances whilst using the pain management tools available. Conclusion Opioids continue to have an important role in pain management in adults aged 85+ largely due to paucity of alternatives and the drive to support quality of life.

Aging is accompanied by a progressive decline in physiological function that contributes to chronic disease development. Biological clocks estimated from high-dimensional clinical and biological measurements may provide more granular tracking of the aging processes. Current biological clocks, however, have limited cross-ancestry generalizability and clinical applicability. Here, we developed a multi-ancestry biological clock (ClinBAG) using 22 routine blood and anthropometric biomarkers in 14,328 age- and sex-balanced individuals from the All of Us Research Program. We tested the association of ClinBAG with 434 traits and evaluated its ability to predict incident disease in 152,733 non-overlapping individuals. We also conducted genome-wide association studies in European (N=74,675), African (N=22,315), and Admixed American ancestry individuals (N=19,940). Among 190 neurological phenotypes, elevated ClinBAG was associated with cognitive decline, increased incidence of dementia (HR=1.020, p=1.6x10-5) and Parkinson's disease (HR=1.014, p=0.023), and decreased risk of migraine (HR=0.991, p=8.7x10-4). We also identified common (NPRL3) and ancestry-specific genetic loci (HBB in African-ancestry and FADS1/FADS2 in European-ancestry) for ClinBAG. Single-cell enrichment revealed that ClinBAG-associated genes are overexpressed in double-negative (DN) T cells in an age-dependent manner. This study presents a clinically applicable multi-ancestry biological age clock predicting neurological disease risk. Our findings also uncover population-specific genetic drivers, particularly involving erythropoiesis and DN T-cell-mediated neuroinflammation.

Background Elevated resting heart rate (RHR) predicts mortality in older adults, primarily through cardiovascular disease (CVD). Prior cohort evidence suggests that RHR also predicts mortality in younger adults, but whether this association operates through cardiovascular or non-cardiovascular pathways has not been directly tested. Methods and Results We analyzed 3291 adults aged 20 to 49 years from NHANES 1999-2004 linked to mortality data through 2019 (median follow-up, 17.8 years; 120 deaths). RHR and heart rate reserve (HRR) were modeled per 10-bpm increment using Cox regression adjusted for demographic, lifestyle, and comorbidity covariates. Each 10-bpm RHR increase was associated with higher all-cause mortality (hazard ratio [HR], 1.26; 95% CI, 1.07-1.50; P=.007), driven by non-CVD mortality (HR, 1.28; 95% CI, 1.07-1.55; P=.009) rather than CVD mortality (HR, 1.15; 95% CI, 0.77-1.71; P=.51). A behavioral/external composite (accidents and NCHS residual causes, including suicide and liver disease) reached significance (HR, 1.35; P=.02), whereas a disease-oriented composite did not (P=.20). The association was absent before age 35 (HR, 0.98; P=.88) but pronounced at ages 35-39 (HR, 2.60; P=.001). HRR was not associated with any outcome. Conclusions In young US adults, elevated RHR predicted mortality through non-cardiovascular rather than cardiovascular pathways, concentrated among behavioral and external causes. The association emerged at age 35, below current screening thresholds. HRR under submaximal conditions carried no prognostic value. RHR in young adults may reflect global health vulnerability rather than cardiovascular risk alone.

Introduction Cardiovascular disease (CVD) remains Vietnam's leading cause of mortality, yet no comprehensive national analysis of burden trends and future projections exists. This study characterizes Vietnam's CVD burden from 1990 to 2023 and projects burden through 2050. Methods Using Global Burden of Disease 2023 data, we analyzed CVD prevalence, incidence, mortality, and disability-adjusted life years (DALYs) in Vietnam from 1990 to 2023, stratified by sex and age. Joinpoint regression quantified temporal trends. Decomposition analysis separated contributions of population growth, aging, and epidemiological change. ARIMA modeling, validated against pre-pandemic and COVID 19 periods, projected burden through 2050. Results Despite age-standardized CVD prevalence below global estimates, stroke mortality and DALYs rates exceeded global benchmarks. Age-standardized CVD mortality (ASMR) declined significantly (average annual percentage change [APC]:-1.34%), yet absolute deaths nearly doubled from 121,611 to 223,068. Population aging contributed 140.9% to observed mortality increases while epidemiological improvements averted over 102,000 deaths. Male age-standardized CVD mortality was approximately twice that of females. High systolic blood pressure remained the leading attributable risk factor, while high BMI and alcohol use showed the largest rank escalations. CVD incidence reversed its declining trend during 2019 - 2023 (APC:+0.69%). By 2050, ASMR are projected to decline by 51.0% (218.8 to 107.1 per 100,000 [95%CI: 64.1 - 150.2]), while absolute deaths are projected to increase by 43.4% (206,677 to 296,335 [95%CI: 272,323 - 320,348]). Conclusions Vietnam faces a demographic paradox of improving age-specific outcomes alongside a rising absolute burden driven by population aging, demanding urgent reorientation toward aging-specific prevention, hypertension control, and chronic cardiovascular care.

Clonal hematopoiesis of indeterminate potential (CHIP) represents the age-related expansion of hematopoietic stem cells with preleukemic mutations. However, its association with all-cause and cause-specific mortality has not been well characterized in older adults. We aimed to evaluate whether CHIP is associated with all-cause and cause-specific mortality in a population of older women in the United States. Our study included 6,704 participants in the Women?s Health Initiative Long Life Study (WHI-LLS) without hematologic malignancy. The co-primary exposures were any CHIP (variant allele frequency [VAF] [&ge;] 2%) and large CHIP (VAF [&ge;] 10%), and the primary outcome was all-cause mortality. Multivariable-adjusted Cox proportional hazards models tested the associations of CHIP and CHIP subtypes with all-cause and cause-specific mortality. Any CHIP and large CHIP were independently associated with all-cause mortality, with multivariable-adjusted hazard ratios (aHRs) of 1.12 (95% confidence interval [CI] 1.04-1.21; P = 0.003) and 1.28 (95% CI 1.15-1.43; P < 0.001), respectively. In gene-specific analyses, non-DNMT3A CHIP was associated with all-cause mortality (aHR: 1.22 [95% CI: 1.12-1.34], P < 0.001), while DNMT3A CHIP was not (aHR: 1.07 [95% CI: 0.98-1.18], P = 0.13). Furthermore, large CHIP was associated with cardiovascular (aHR: 1.29 [95% CI: 1.08-1.55], P = 0.006), cancer (aHR: 1.49 [95% CI: 1.11-2.02], P = 0.009), and neurologic (aHR: 1.40 [95% CI: 1.07-1.84], P = 0.02) death. In this cohort of older women, CHIP, particularly large clones and non-DNMT3A CHIP, was associated with all-cause and cause-specific mortality. These findings suggest that clonal size and subtype may differentially influence mortality risk.

Background: Heart failure (HF) is a major contributor to inpatient hospital utilization, with persistently high 30-day readmission rates. Existing prediction tools are frequently restricted to primary-diagnosis HF admissions, potentially excluding clinically relevant HF-related hospitalizations. Objectives: To develop and validate risk prediction models using machine learning (ML)-based risk prediction models to predict 30-day readmissions among patients with HF using the Kansas Health Information Network, a statewide health information exchange. Methods: This retrospective cohort study analyzed HF hospitalizations using predictors including demographics, comorbidities, laboratory results, medications, clinical quality metrics for diabetes and kidney disease management, and prior healthcare utilization. Five ML models, including regularized logistic regression, random forest, extreme gradient boosting, categorical boosting, and deep neural network, were trained using stratified 5-fold cross-validation. Model performance was evaluated on an independent test set using the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), misclassification rate (MCR), and Brier score. Results: Among 2,734 HF patients, the 30-day readmission rate was 27%. The XGBoost model achieved the best discrimination (AUROC=0.75; AUPRC=0.58; MCR=0.21). Patients in the highest-risk decile had a positive predictive value of 76%, accounted for approximately one-third of all 30-day readmissions, and had a 3.3-fold enrichment compared with baseline risk. The key predictors included prior hospital utilization, diabetes and kidney disease management indicators, and comorbidity burden. Conclusions: Risk stratification using routinely collected clinical data identified a subgroup at elevated risk for 30-day readmission. These findings support the potential role of data-driven risk prediction to inform targeted transitional care.

Familial longevity, quantified using the Longevity Relatives Count (LRC) score indicating the proportion of ancestral long-lived family members, associates with a pronounced 13 years delayed onset of cardiometabolic disease (CMD). Understanding the molecular basis of familial longevity therefore provides critical insights into mechanisms of cardiometabolic resilience. However, the combined metabolomics and proteomics profile associated with the delayed CMD onset observed in such long-lived family members is not understood yet. Hence, we integrated plasma metabolomics and proteomics in 495 participants from the Leiden Longevity Study to identify molecular signatures associated with (a contrast in) the LRC score. Metabolomics profiling captured 429 features, including amino acid derivatives, nucleosides, and lipid mediators, while proteomics quantified 374 proteins related to cardiovascular, metabolic, and inflammatory pathways. Three within-family analysis approaches were examined and overlapping findings were interpreted. We identified ten metabolites and nine proteins that are associated with increased familial longevity, exemplified by a high LRC score. High LRC scoring individuals exhibited lower levels of amino acid derivatives (prolylhydroxyproline, 5-hydroxy-tryptophan, asymmetric dimethylarginine), nucleosides (2-methylguanosine, 7-methylguanosine, pseudouridine), N-acetylneuraminic acid and quinolinic acid, indicating optimized extracellular matrix integrity, vascular function, and reduced neuroinflammatory activity. Lipid mediators, including elevated 6-keto-PGF1a and reduced 9-HOTrE/alpha-linolenic acid ratio, reflected preserved endothelial homeostasis and attenuated inflammatory signaling. At the proteome level, strong ancestral familial longevity is associated with immune regulators (RETN, NPPB, IGSF8), extracellular matrix components (EFEMP1, EPHB4), and adhesion/signaling molecules (LRP11, ICAM3, KIT, ADGRG2), highlighting coordinated regulation of inflammation, tissue remodeling, and regenerative capacity. Multi-omics pathway analyses indicated convergence on amino acid and nucleotide metabolism, lipid signaling, extracellular matrix remodeling, and receptor-mediated communication. Collectively, these multi-omics systemic signatures define a molecular framework of ancestral familial longevity characterized by reduced inflammation, preserved tissue integrity, and enhanced metabolic and regenerative processes. Our findings provide mechanistic insight into the biology of familial longevity and potentially cardiometabolic resilience.

Background The study aimed to estimate healthcare costs associated with malnutrition in Swedish older adults. Methods We conducted a cohort study using data from the population-based Swedish National Study on Aging and Care in Kungsholmen (SNAC-K, N = 2982), a geriatric inpatient cohort of complex patients (N = 7680), and a cohort of individuals with cognitive impairment from the Swedish Register of Cognitive/Dementia Disorders (SveDem, N = 64192). At risk of malnutrition and malnutrition were ascertained by the Mini-Nutritional Assessment in SNAC-K and the geriatric inpatient cohort. In SveDem, body mass index was used for identifying malnutrition. Healthcare resource use was derived from regional and national registers. Associations between malnutrition and healthcare costs in 2024 Swedish kronor (SEK) were analyzed using two-part models and generalized linear regression models, adjusting for demographic and clinical factors. Findings In the community, at risk of malnutrition and malnutrition were associated with an increase in annual healthcare costs of 2267 SEK (95% CI: 64,4469) and 1846 SEK (95% CI: -6802,10493), respectively. In geriatric patients, healthcare costs over 6 months in individuals at risk of malnutrition and individuals with malnutrition were 60205 SEK (45613,74798) and 86619 SEK (68362,104875) higher than those without malnutrition. In people with cognitive impairment, malnutrition was associated with higher annual healthcare costs (22170 SEK, 95% CI: 15152,29188). Interpretation Both at risk of malnutrition and malnutrition are associated with higher healthcare costs in Swedish older adults. The study findings are important for informing future economic evaluations of malnutrition interventions in Swedish older adults.

Aim: The global population of older adults is growing, and older age is linked to higher bleeding risk. Although guidelines discourage aspirin for primary prevention in healthy older adults due to bleeding harms outweighing benefits, many continue taking it without a clear indication. It remains unclear whether all older adults face uniform aspirin-related bleeding risk or if certain subgroups are more vulnerable. Methods: We analyzed data from 19,114 ASPREE trial participants to develop machine learning models using 116 baseline variables. Random forest (RF) and random survival forest (RSF) models predicted 5-year bleeding risk, and participants were stratified into low, intermediate, and high-risk groups based on the 20th and 80th percentiles of predicted risk. We assessed heterogeneity of treatment effect (HTE) by testing treatment-by-risk group interactions on the relative scale using Fine-Gray models, and on the absolute scale using observed 5-year cumulative incidence rates. Results: Over a median follow-up of 4.7 years, 626 major bleeding events occurred. The RF model had moderate discrimination (AUC = 0.65, 95% CI: 0.63-0.67) and good calibration (Brier = 0.032, 95% CI: 0.029-0.034). Statistically significant HTE was observed on the relative scale, with the greatest relative increase in bleeding risk seen in the low-risk group (subdistribution hazard ratio = 2.26, 95% CI: 1.27-4.01). On the absolute scale, low-risk participants experienced higher bleeding with aspirin (absolute risk difference (ARD) = 1.17%, 95% CI: 0.37-1.95), but heterogeneity in ARDs was not statistically significant (Cochran's Q p > 0.45). Similar findings were observed when using the RSF model. Conclusion: Participants at lowest baseline bleeding risk experienced the greatest relative increase in bleeding risk with aspirin therapy. We found statistically significant heterogeneity in treatment effects on the relative but not absolute scale. These findings support an individualized, risk-based approach to aspirin therapy decision-making in older adults.