Journal of the American Geriatrics Society

BackgroundVestibular complaints are common in older adults and are linked to imbalance and falls. Some older adults show impaired vestibular perception despite preserved peripheral-reflex ("vestibular agnosia"). Yet it remains unclear if vestibular agnosia is independently linked to imbalance and falls in otherwise healthy older adults. We therefore investigated the prevalence of vestibular agnosia in community-dwelling older adults, and examined its association to balance and prospective falls. MethodsVestibular perceptual thresholds were measured during yaw-plane rotational chair testing. Postural sway and instrumented Timed-Up-and-Go were assessed using wearable sensors, and falls were recorded prospectively over six-month. Vestibular agnosia was identified using K-means clustering. Multivariable regressions examined associations between perceptual thresholds and balance outcomes; logistic and negative binomial regressions evaluated associations with prospective falls. ResultsAmong 166 participants (75.4 years; 81.9% female), 18.7% were classified as having vestibular agnosia. These individuals had worse cognition and somatosensation. Elevated (i.e. worse) vestibular perceptual thresholds were independently associated with greater sway velocity when standing on foam with eyes-open (adjusted {beta}=0.002, p=0.03). Associations with other balance outcomes were attenuated after adjustment. Vestibular perceptual thresholds were not associated with prospective falls (odds of [≥]1 fall: adjusted OR=0.99, p=0.65; fall counts: adjusted IRR=1.02, p=0.35). ConclusionsApproximately one-fifth of healthy older adults exhibit vestibular agnosia. While elevated perceptual thresholds are independently associated with poorer balance, they did not predict falls. Vestibular perceptual testing provides complementary insight into age-related balance impairment, although its utility in fall-risk prediction requires further investigation. Key PointsO_LIApproximately one-fifth of healthy older adults had vestibular agnosia (impaired vestibular perception despite intact peripheral function) C_LIO_LIOlder adults with vestibular agnosia have poorer cognition, reduced lower limb somatosensation, and higher anxiety. C_LIO_LIHigher (i.e. worse) vestibular perceptual thresholds were independently associated with greater sway velocity when standing on foam (eyes open). C_LIO_LIHigher vestibular perceptual thresholds were only associated with slower TUG performance and greater eyes-closed foam sway in unadjusted models. C_LIO_LIVestibular perceptual thresholds did not predict prospective falls over 6 months. C_LI

Background Older adults' walking has so far been evaluated using standardised assessments of walking capacity within a clinical setting. By taking the evaluation out of the laboratory into the real world, this study provides first evidence of the ability of Digital Mobility Outcomes (DMOs) to detect changes over time and the Minimal Important Difference (MID) in patients after proximal femoral fracture (PFF). This will guide the implementation of DMOs in research and clinical care. Methods For this multicenter prospective cohort study, 381 community-dwelling older adults were included within one year after sustaining a PFF and assessed at two time points, separated by six months. Walking activity and gait DMOs were measured using a single wearable device worn on the lower back for up to seven days. A global impression of change question and three mobility-related outcome measures (Late-Life Function and Disability Instrument; Short Physical Performance Battery; 4m gait speed) were used as anchor variables. To assess each DMOs ability to detect changes, we calculated the standardized mean change as effect size. For estimating MIDs, both distribution-based and anchor-based methods were applied, followed by triangulation by experts if at least three anchor-based estimates were available per DMO, resulting in single-point estimates. Results All three anchor variables demonstrated substantial changes. Overall, 10 out of 24 available DMOs showed large and 7 DMOs moderate positive effects in the expected direction of the respective anchors. Seven DMOs showed no or only small effects. For 12 DMOs, at least three anchor-based estimates were available, enabling MID triangulation. MIDs for walking activity DMOs per day were: a walking duration of 10 minutes, a step count of 1,000 steps, 50 walking bouts (WB), and 15 WBs in WBs over 10 seconds. For gait DMOs, depending on the walking bout length, MIDs for walking speed were between 0.04 m/s and 0.08 m/s, and MIDs for cadence between 4 and 6 steps/minute. Almost all DMOs showed a strong ability to detect improvement in mobility, but rarely in detecting decline. Conclusions For the first time, MIDs are presented for real-world DMOs in PFF patients. These MIDs inform sample size requirements and interpretation of intervention effects for clinical trials, thereby providing guidance and reassurance for clinicians and regulatory bodies.

Structured AbstractO_ST_ABSBACKGROUNDC_ST_ABSPatient reports are the standard when examining subjective cognitive decline (SCD). Recent research suggests that informant and clinician reports may also be associated with cognition. This study examined differences between patient, informant, and clinician definitions of SCD and their relationship to cognition. METHODSData from 4290 older adults (n=1690 normal controls, NC; n=840 mild cognitive impairment, MCI; n=1760 Alzheimers disease, AD) were examined from the National Alzheimers Coordinating Center. Linear models examined the relationships between SCD status using the three definitions and cognition at baseline and over time. RESULTSIn NC, informant and clinician SCD were associated with worse cognition at baseline, with patient and clinician SCD associated with worse cognition over time. All definitions were associated with worse cognition at baseline and over time in MCI and AD. DISCUSSIONOur findings suggest the importance of examining different SCD definitions, especially the inclusion of clinician SCD.

INTRODUCTIONAgitation is a common and burdensome neuropsychiatric symptom in dementia that fluctuates from day to day, but objective tools for short-term risk stratification are limited. We examined whether nocturnal physiological signals from unobtrusive under-mattress sensors predict next-day daytime agitation and whether associations differ for agitation occurrence versus severity. METHODSWe extracted cardiorespiratory, movement, and sleep-proxy features from two long-term care cohorts (N=55; 333 nights) and one external home-monitoring cohort (N=18; 803 nights). A two-part mixed-effects framework was used to model next-day agitation episodes. RESULTSLower nocturnal respiratory rate and greater activity instability independently predicted higher odds of next-day agitation occurrence. Associations were stronger for motor than verbal agitation. Respiration-related predictors were validated externally. Conversely, no nocturnal features significantly predicted agitation severity. DISCUSSIONPassive sleep monitoring identified reproducible, physiologically interpretable markers of next-day agitation occurrence, supporting the potential of under-mattress sensing for short-term risk stratification and more proactive dementia care.

Gait variability is a critical functional indicator of dynamic balance and neurocognitive decline in health. Its translation into clinical practice is, however, challenged by a lack of age-related normative trajectories and reference values under real-world ecological settings. Furthermore, the conventional metrics used to estimate gait variability (Coefficient of Variation, CV; Standard Deviation, SD) have a fundamental methodological flaw: the inherent sensitivity of conventional metrics to the statistical outliers and environmental noise in real-world walking. In this study, we mitigate this factor by applying a robust statistical framework to quantify gait variability. Analysing a large-scale cohort of community-dwelling older adults (n=2,193), we first demonstrate that free-living gait data follows a heavy-tailed distribution, necessitating the use of robust estimators like the Robust Coefficient of Variation (RCV-MAD) and Median Absolute Deviation (MAD). Leveraging these metrics, we established the normative trajectory and reference values of real-world gait variability across the ageing lifespan, revealing a distinct, age-dependent increase in spatio-temporal fluctuations, indicating a decline in rhythmicity and steadiness with age. We further demonstrated the clinical utility of these robust metrics: RCV-MAD consistently yielded larger effect sizes than conventional CV in discriminating between fallers and non-fallers across all gait parameters. Furthermore, we illustrate the potential of long-term unsupervised monitoring to capture intrinsic variability during real-world walking. Validated for consistency and reliability, this robust framework provides the necessary ecological validity to transform gait variability into a standardised, rapid clinical metric for assessing functional decline at an early timepoint.

BackgroundIntrinsic capacity (IC) is a key marker of healthy ageing, which captures an individuals physical and mental capacities, measured across five domains: cognitive, locomotor, psychological, vitality, and sensory. Although genetic factors are known to influence both general IC and its individual domains, existing IC indices have been developed primarily using phenotypic data, without accounting for the underlying biological architecture across domains. In this study, we developed a multi-trait polygenic score (Mt-PGS) model for IC by integrating polygenic scores derived from a broad set of phenotypes spanning the five IC domains and examined its validity. MethodsUsing data from 13,085 participants of the Canadian Longitudinal Study on Aging (CLSA), we computed PGSs for 63 phenotypes related to IC domains. A supervised machine-learning model was applied to develop a mt-PGS model for IC and identify the optimal set of polygenic predictors. The validity of the mt-PGS IC score was evaluated by comparing it with a phenotype-based IC score and by examining its association with mortality. ResultsOur analysis identified PGSs for 33 phenotypes with non-zero coefficients, jointly explaining 2.23% of the variance in IC. Several of the strongest contributors were most closely aligned with vitality-related phenotypes in the literature (including body mass index, grip strength, fat-free mass, diastolic blood pressure, and chronic obstructive pulmonary disease), acknowledging cross-domain relevance, and that predictors from all five IC domains were represented. The mt-PGS IC score was consistent with the phenotype-based IC score, positively correlated with the phenotype-based IC score and was inversely associated with mortality (OR = 0.04; 95% CI: 0.005 - 0.379). ConclusionOur findings support the multisystem biological basis of IC, demonstrating that an mt-PGS model integrating diverse phenotypes is associated with the phenotype-based IC score. PGSs for the phenotypes frequently related to vitality in the literature were the strongest predictors, recognizing that several of these phenotypes may span multiple domains, and that all domains contributed to the model. If replicated across different ancestries and settings, these findings may serve as a foundation for future research for the potential integration of genetic information into IC frameworks.

Adaptation to physiological stress is fundamental to health but varies widely among individuals. In humans, this heterogeneity is evident in markedly different gains in fitness in response to identical exercise training. The molecular determinants of this variable "trainability" remain poorly understood. Here we identify insulin-like growth factor binding protein-7 (IGFBP7), a senescence-associated secreted protein, as a circulating constraint on exercise adaptation. Plasma proteomics in older adults enrolled in a randomized exercise trial revealed that IGFBP7 levels inversely predicted fitness gains after one year of high-intensity interval training despite similar baseline fitness. In mice, genetic deletion of IGFBP7 markedly amplified training-induced gains in exercise capacity across distinct training protocols, whereas somatic overexpression abolished this advantage. In the UK Biobank, lower IGFBP7 levels were associated with reduced mortality and multiple incident age-related diseases, mirroring the breadth of ties between fitness and healthspan. Together, these findings identify circulating IGFBP7 as a molecular brake on physiological plasticity in response to exercise, linking training responsiveness, aging biology, and health outcomes.

BackgroundAdvances in wearable devices and machine-learning-based ECG analysis enable highly accurate detection of atrial fibrillation (AF) outside traditional clinical settings, leading to increasing identification of asymptomatic AF. However, the prognostic significance of AI-detected asymptomatic AF and its implications for downstream cardiovascular risk remain unclear. In contrast to clinically diagnosed AF, evidence guiding risk stratification and further evaluation in this population is limited. We therefore investigated the association between AI-detected asymptomatic AF and incident cardiovascular outcomes in a large population-based cohort. MethodsWe applied a validated open-source ECG-based deep learning model for atrial fibrillation detection (AI-AF) to 12-lead ECG recordings from participants in the UK Biobank. Participants with AI-detected AF on ECG and no prior clinical AF diagnosis were classified as asymptomatic AF (c). Kaplan-Meier curves and log-rank tests were used to compare the incidence of ischemic stroke and major adverse cardiovascular events (MACE: myocardial infarction, ischemic stroke, or cardiovascular death) across AF subgroups. Cox proportional hazards models were used to evaluate the association between AI-AF risk and incident MACE, adjusting for age, sex, current smoking, systolic blood pressure, total and HDL cholesterol, and prevalent type 2 diabetes. Follow-up was administratively censored at 6 years. ResultsThe study included 96,531 participants with mean [SD] age of 65 [8] years; 52% female; median follow-up [IQR] of 4.7 [1.6-7.2] years. ECG data were available for 64,029 participants and an additional 32,502 participants with clinically diagnosed atrial fibrillation (AF) without ECG recordings were included. Among participants without prior clinical AF and with available ECGs, 2,399 were classified as asympAF based on AI detection, while 58,879 were AF-free. Over 6 years of follow-up, the incidence of ischemic stroke was significantly higher in participants with asympAF compared with AF-free individuals (1.5% vs 0.52%, p = 7x10-7) and significantly lower than in participants with clinically diagnosed AF (1.5% vs 3.4%, p = 2x10-5). Similar patterns were observed for myocardial infarction and cardiovascular death. Using a more liberal AI-AF threshold corresponding to a 15% false-positive rate (asympAF15) yielded consistent findings: participants classified as asympAF15 had a 62% higher risk of incident MACE in adjusted Cox PH models (hazard ratio 1.6, 95% CI 1.2-2.2) over six years. ConclusionAI-detected asymptomatic AF identified individuals at elevated risk of ischemic stroke and major adverse cardiovascular events. As ischemic stroke is a hallmark complication of atrial fibrillation, these findings support the hypothesis that AI-ECG models may capture subclinical AF-related risk not detected by conventional clinical assessment. This approach may help extend the window for preventive interventions in populations without clinically diagnosed AF.

INTRODUCTIONDementia reflects vascular and neurodegenerative processes in late life, yet studies often examine risks and outcomes individually. This study tested whether the cumulative burden of risks relates to structural brain pathology and cognition, and whether brain markers mediate these associations. METHODSCross-sectional data were drawn from 38,414 older adults in the National Alzheimers Coordinating Center database. A composite score summed ten binary risk factors: hypertension, diabetes, hypercholesterolemia, alcohol misuse, smoking, depression, obesity, hearing loss, vision loss, and low education. Outcomes included white matter hyperintensities (WMH), infarcts, hippocampal atrophy, global cognition, cognitive status, delayed recall, and semantic fluency. RESULTSHigher burden was associated with poorer global cognition, greater clinical severity, worse memory and fluency, and higher odds of WMHs, infarcts, and hippocampal atrophy. Structural equation models identified hippocampal atrophy as the primary mediator, with smaller effects for WMHs and infarcts. DISCUSSIONFindings support multidomain prevention strategies targeting clustered modifiable risks.

BackgroundPostoperative delirium (POD) is a common complication of surgery. It is associated with a number of detrimental effects, including mortality and healthcare costs. We sought to determine whether common comorbidity indices are predictors of POD. MethodsUsing the Medical Information Mart for Intensive Care (MIMIC)-IV database, we identified 8022 abdominal surgery procedures across 7212 adult patients. We calculated both the Charlson comorbidity index (CCI) and the Elixhauser comorbidity index (ECI) for each procedure and used logistic regression to predict postoperative delirium, which was defined as delirium within 30 days following the procedure. ResultsModels based on either the CCI and ECI were predictive of postoperative delirium (area under the receiver-operator characteristic curve (AUC-ROC) of 0.622 and 0.652, respectively). However, the addition of other factors known to be associated with delirium improved model performance (AUC-ROC of 0.680). ConclusionsBoth the CCI and ECI are predictors of postoperative delirium in patients undergoing abdominal surgery. Addition of factors known to be associated with delirium renders additional predictive value and should be included in models that predict postoperative delirium.

Biomarkers of aging, particularly DNA methylation-based clocks, have shown promise as tools to assess whether interventions may impact the rate of biological aging. Among possible interventions physical exercise has shown protective effects against many age-associated diseases, while time-restricted feeding (TRF), has shown metabolic benefits in preclinical models. The combined effect of exercise and TRF on aging biomarkers remains largely unexplored. In this 52-week four-armed, randomized, controlled trial (clinicaltrials.gov: NCT07207044) 240 healthy adults aged 65 and over will be allocated to four groups: combined cardio and strength training (EXE), TRF, combined EXE and TRF, or control. Participants will undergo assessments at baseline, 3, 6, and 12 months, with follow-ups at 2, 5, and 10 years. The primary outcome measure is DNA-methylation age with secondary measures including RNA-sequencing, metabolomics, inflammatory marker, microbiome analysis, cognitive and physical measures. By deeply phenotyping participants the Fasting And eXercise (FAXAge) study will provide novel insights into whether TRF, EXE, or a combination can slow or reverse biological aging in older adults.

BACKGROUNDDelirium is common in critically ill adults but often goes unrecognized and undertreated. Little is known about the perceptions of ICU nurse and physician leaders regarding ICU delirium detection and management and the potential role of objective continuous delirium monitoring to facilitate ICU delirium care. RESEARCH QUESTIONWhat are the perceptions of ICU leaders regarding the current challenges associated with delirium recognition and management and the potential benefits of continuous delirium monitoring? STUDY DESIGN AND METHODSWe conducted a blinded, cross-sectional, electronic survey of ICU leaders across the U.S., including physician directors and nursing managers with [≥]3 years of ICU leadership experience. We asked about perceptions of the effectiveness of current delirium clinical assessment tools, current delirium detection and management challenges, and how an objective, continuous delirium monitoring system might impact clinician practice and patient outcomes in their ICU. RESULTSAmong the 81 respondents (62 physicians, 19 nurses), most (76%) reported that recommended delirium assessment tools (CAM-ICU, ICDSC) are used in their ICUs, though there were mixed perceptions on how reliably they are conducted. A majority (63-90%) perceived that current bedside assessments delay and limit the recognition of ICU delirium. Nearly all (89%) agreed an objective delirium monitoring tool would be more clinically valuable than current delirium assessment tools and that it would support real-time, delirium management by clinicians. CONCLUSIONSICU leaders perceive that there are limitations to using clinical delirium assessment tools in ICU patients to effectively detect and manage ICU delirium. Most felt that an objective delirium monitor could facilitate delirium detection and potentially expedite appropriate delirium management in patients.

BackgroundFinancial strain has been linked to adverse cardiovascular outcomes, yet whether this association persists beyond objective socioeconomic resources remains unclear. We examined associations of financial strain with incident heart disease and all-cause mortality among US adults aged 50 years or older. MethodsProspective cohort study using the Health and Retirement Study (2006-2022). Among 7219 participants completing the Psychosocial Leave-Behind Questionnaire, the exposure was ongoing financial strain (high vs low/none). Incident heart disease was assessed among 4956 participants without baseline cardiovascular disease using cause-specific Cox and Fine-Gray models. All-cause mortality was modeled using sequential Cox regression. ResultsAmong 7219 participants (mean [SD] age, 67.5 [10.6] years; 58.6% female), 1423 (19.7%) reported high financial strain. Financial strain was associated with incident heart disease (cause-specific HR, 1.18; 95% CI, 1.02-1.37; P =.03; 1310 events), corroborated by Fine-Gray models (SHR, 1.16; 95% CI, 1.00-1.34). For all-cause mortality (3466 deaths), financial strain was associated after demographic and clinical adjustment (HR, 1.17; 95% CI, 1.07-1.28) but attenuated after further adjustment for income and wealth (HR, 1.10; 95% CI, 1.00-1.20; P =.051). The mortality association differed by age (interaction P =.001): HR, 1.25 (95% CI, 1.03-1.52) for adults younger than 65 years versus HR, 1.04 (95% CI, 0.94-1.16) for those 65 or older. ConclusionsFinancial strain was associated with incident heart disease independent of socioeconomic resources. The mortality association was attenuated by income and wealth adjustment but remained elevated among preretirement adults. Financial strain may be a clinically accessible marker of cardiovascular risk among working-age adults.

BackgroundPostoperative delirium is a common complication in surgical patients, and is associated with a multitude of negative outcomes, including mortality, dementia, and increased healthcare costs. Therefore, a better understanding of what factors contribute to postoperative delirium, especially those that can be easily obtained, is important. MethodsWe conducted a retrospective cohort study using patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Adult patients undergoing procedures in abdominal surgery who did not have pre-existing delirium were included in the study. Overall, we included 8022 procedures across 7212 patients. For each admission, we extracted values obtained from common blood tests, the Charlson and Elixhauser comorbidity score, and patient demographic information. We used stepwise logistic regression to identify predictive factors of postoperative delirium in this cohort. ResultsThe model isolated factors well known to be associated with postoperative delirium, such as age, comorbidity (as represented by the Elixhauser comorbidity score), and Parkinsons disease. The model also selected variables that are less studied, such as minimum preoperative platelets and maximum preoperative sodium levels. We hypothesize that the former is associated with postoperative delirium as a surrogate marker for inflammation as an acute phase reactant, and the second due to it being a marker for cerebral edema and altered neurotransmission. ConclusionPreoperative blood tests contain valuable information that can be used alongside patient demographics and past medical history to better predict the risk of postoperative delirium.

IntroductionThis clinical trial investigates the efficacy and safety of a personalized 15-day accelerated intermittent theta-burst stimulation (aiTBS) protocol, targeted at either the default mode network (DMN) or the fronto-parietal network (FPN), in individuals with mild Alzheimers disease (AD). Methods45 patients with mild AD were randomized 1:1:1 to receive 15 consecutive days of high-dose aiTBS (7200 pulses/day) targeting the DMN or FPN, or sham. The primary outcome was the change in ADAS-Cog after 15 days of treatment. ResultsBoth active aiTBS groups demonstrated significantly greater ADAS-Cog improvement than sham at the primary endpoint. Response rates for a clinically meaningful improvement ([≥]3-points on ADAS-Cog) were significantly higher in the active groups (DMN: 38%; FPN: 47%) than in the sham group (0%). The improvement in active groups was sustained at 3-month follow-up. DiscussionPersonalized aiTBS targeting the DMN or FPN produced clinically meaningful cognitive benefits in mild AD and was safe.

BackgroundQuality measurement in intensive care emphasizes task completion--whether assessments were documented and protocols followed. Electronic health record (EHR) systems capture these signals in real time, yet current metrics cannot distinguish task completion from cognitive clinical engagement. A prior analysis demonstrated that omission of orientation assessment predicted a 4.29-fold increase in hospital mortality among low-acuity ICU patients [1]. Whether combining this marker with routine task-completion data yields a computable phenotype with independent prognostic value has not been studied. ObjectiveTo define, validate, and characterize "discordant care"--a computable EHR phenotype defined as completion of [≥]6 of 8 routine nursing assessments without orientation assessment documentation--as a predictor of hospital mortality, distinguishing patient-level confounding from care process signal. MethodsRetrospective cohort study using MIMIC-IV v3.1 (2008-2022), including 46,004 adult ICU stays with SOFA scores 0-2 and length of stay [≥]24 hours in non-neurological ICUs. Primary exposure: discordant care, computed from structured nursing flowsheet data within 24 hours of admission. Primary outcome: hospital mortality. Progressive covariate adjustment included mechanical ventilation, sedation, and diagnosis. ResultsDiscordant care was present in 8891 patients (19.3%), with 69.7% mechanically ventilated versus 25.3% of concordant patients. Two overlapping signals were identified: a patient-level signal driven by ventilation/sedation (full adjustment OR 1.19, 95% CI 1.09-1.30) and a care process signal in non-ventilated patients (OR 2.14, 1.87-2.44; N=30,314). Among non-ventilated SOFA 0 patients, OR was 2.60 (2.13-3.18; N=16,295). The signal was present across all 7 major diagnosis categories. Quantitative bias analysis indicated unmeasured delirium could attenuate but likely not fully explain the non-ventilated signal. ConclusionsDiscordant care identifies two phenomena: a patient-level signal from ventilation/sedation and a care process signal where assessable patients receive routine care without cognitive engagement (OR 2.14-2.60). This care process signal is invisible to existing quality metrics and detectable in real time. Prospective validation with systematic delirium screening is needed.

BackgroundCardiovascular (CV) disease risk is increased in rheumatoid arthritis (RA) and is the leading cause of mortality. Improved CV risk stratification tools in RA could enhance use of preventative care and improve outcomes. MethodsWe previously studied biomarkers of CV disease - adiponectin, hsCRP, Lp(a), osteoprotegerin (OPG), high-sensitivity cardiac troponin T (hsTnT), serum amyloid A (SAA), YKL-40, soluble TNF receptor1 (sTNFR1) -- that were associated with CV risk. In the current study, these biomarkers were tested in an unrelated external cohort of RA patients followed at a single academic medical center without a history of CV events. CV events were identified through Medicare and Medicaid administrative data or through medical record review of self-reported events. Biomarkers were assessed at cohort entry among a nested cohort of cases and controls, matched 1:1 on sex and age. Analyses were conducted using conditional logistic regression. We examined whether the candidate biomarkers added to clinical CV risk factors improved model prediction, using the area under the curve (AUC) as well as the net reclassification index (NRI). ResultsFrom a cohort of 1,345 eligible patients with RA, we identified 123 patients with confirmed CV events. Cases and matched controls were typical of RA: median age 63 years, 77% women, RA disease duration 11 years, 72% seropositive, 85% used a biologic or conventional disease modifying anti-rheumatic drug, 58% non-steroidal anti-inflammatory drugs, and 30% oral glucocorticoids. From the candidate biomarkers, LASSO regression selected hsTnT and sTNFR1 as associated with CV events. The AUC for models that included only clinical risk factors was 0.758 (95% CI 0.689-0.829); after adding hsTnT and sTNFR1, the AUC increased to 0.802 (95% CI 0.718-0.998). The NRI of the model with biomarkers was 16.3%, with improvement only observed in patients who did not have CV events during follow-up. ConclusionsAdding selected biomarkers to clinical risk factors enhances the discrimination of models predicting CV events among patients with RA. These risk models require prospective testing to see if they have value in clinical practice decision-making regarding preventative care.

PurposeDespite strong evidence, real-world adoption of guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) remains suboptimal. The Get With The Guidelines-Heart Failure (GWTG-HF) program was designed to close gaps in care. We evaluated whether hospital participation in GWTG-HF is associated with greater GDMT intensity and improved outcomes. MethodsWe conducted a retrospective analysis (2013-2021) of Medicare beneficiaries with Part A and Part D hospitalized with HFrEF. Using a multiple baseline time series design, we compared changes in GDMT prescribing and outcomes at hospitals before and after GWTG-HF enrollment with hospitals that never participated. The primary outcome was a 90-day post-discharge prescription-fill GDMT score summarizing use and dose of beta blockers, renin-angiotensin system inhibitors (RASI; ACE inhibitor/ARB/ARNI), and mineralocorticoid receptor antagonists (MRA). Secondary outcomes included class-specific medication fills, achievement of [&ge;]50% target doses, and 30-day, 90-day, and 1-year all-cause and HF readmission and mortality. We adjusted for baseline hospital performance, patient characteristics, and temporal trends. ResultsAmong 1,274,863 Medicare beneficiaries hospitalized for HFrEF, 53.5% were treated at hospitals that never participated in GWTG-HF and 9.6% at hospitals that joined GWTG-HF before hospitalization. Unadjusted median GDMT scores increased from 3.0 in both groups to 4.0 in non-participating hospitals and 4.5 in GWTG-HF hospitals at 90 days (p<0.001). Hospital enrollment was associated with a higher 90-day GDMT score (+0.15 points; 95% CI 0.12-0.18; p<0.001), and greater use of beta blockers, RASI, and MRA, but not ARNI. HF readmission did not differ significantly; however, GWTG-HF participation was associated with lower all-cause mortality at 30 days (OR 0.95; 95% CI:0.92-0.98), 90 days (OR: 0.97; 95% CI: 0.95-0.99), and 1 year (0.97; 95% CI: 0.95-.0.99; all p<0.05). ConclusionHospital participation in GWTG-HF was associated with higher GDMT intensity and lower mortality, supporting structured quality programs to improve HFrEF care.

INTRODUCTIONRisks for postoperative cognitive dysfunction remain poorly understood. Traditional cognitive screening tools such as the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) are used for perioperative cognitive evaluation but have limited scope, whereas comprehensive in-person testing poses problems for long-term follow up. METHODSThis prospective cohort study assesses the feasibility of using a remotely performed comprehensive neurocognitive test battery, the Uniform Data Set tele-adapted neuropsychological battery version 3 (UDS v3.0 T-cog), administered at baseline and 1 week, 1 month, and 3 months postoperatively, to comprehensively study neurocognitive outcomes in older adults undergoing orthopedic joint arthroplasty. Patient satisfaction with T-cog was assessed through four survey questions evaluating technical issues, duration, willingness to participate in in-person assessment, and satisfaction with remote assessment at 3 months after surgery. Further assessment of pain and mood also included PROMIS scales, McGill Pain Questionnaire, and Pain Catastrophizing Scale, before and 3 months after surgery. RESULTS127 participants were enrolled, and out of 120 participants who completed baseline cognitive assessment and underwent surgery, 98 completed cognitive assessments at 3 months. At 3 months, 17% of participants showed an objective decline in cognitive function based on this comprehensive assessment. The remote assessment format was well-received with high participant satisfaction. The UDS v3.0 T-cog identified deficits in specific domains that would have been missed by brief screening instruments, supporting its values for perioperative use. DISCUSSIONThis is the first study to utilize this comprehensive remote cognitive assessment tool to study long-term cognitive function. The assessment can be combined with other preoperative outcome assessments in older adults undergoing surgery. HighlightsO_LICurrent detection of perioperative cognitive outcomes in older adults rely on in-person cognitive assessments that are varied in methodology and often lack sensitivity and specificity C_LIO_LIThe UDS v3.0 T-cog identified objective cognitive decline in 17% of patients after orthopedic arthroplasty while also detecting early non-memory cognitive decline through the more comprehensive test battery with high participant satisfaction and retention, supporting remote assessment feasibility. C_LIO_LIThese findings suggest that remote comprehensive cognitive assessments are an effective tool to provide early detection and risk stratification for perioperative neurocognitive dysfunction in older patients. C_LI

ObjectiveTo examine whether the association between smoking status and cardiovascular (CV) mortality differs by arterial stiffness, assessed by pulse pressure index (PPI), among U.S. adults without baseline cardiovascular disease (CVD). MethodsUsing data from the National Health and Nutrition Examination Survey (NHANES) 2005-2016, we analyzed 16,605 adults aged 40-79 years without baseline CVD, with mortality follow-up through December 31, 2019. PPI was calculated as (systolic blood pressure [SBP] - diastolic blood pressure [DBP])/SBP and split at the cohort median (0.415) as low versus high. Smoking status was classified as never, former, or current, yielding six joint PPI-smoking groups. Cox models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for CV mortality, adjusting for demographics and cardiometabolic risk factors. ResultsOver a median follow-up of 8.4 years, 518 CV deaths (3.1%) occurred. Among individuals with low PPI, former smokers had CV mortality comparable to never smokers (HR 0.86, 95% CI 0.56-1.33), whereas current smokers remained at elevated risk (HR 2.51, 95% CI 1.65-3.81). This pattern was not observed in the high PPI stratum, where both former and current smokers had significantly higher CV mortality than never smokers. ConclusionFormer smokers with low PPI had CV mortality similar to never smokers, whereas former smokers with high PPI remained at elevated risk. These findings suggest that the CV benefit of smoking cessation may be greatest when arterial stiffness is minimal, supporting early cessation before substantial vascular aging occurs.