For large-scale surveys such as the National Health and Aging Trends Study (NHATS), investigators may wish to combine data from two (or more) cohorts in a single analysis to obtain larger sample sizes. Unfortunately, it is not possible to combine the 2011 and 2015 NHATS cohorts while retaining the sample weights. We applied Bayesian hierarchical models with poststratification as an alternative strategy for obtaining population-based estimates from NHATS. As proof of principle, we compared prevalence estimates of frailty obtained from our Bayesian approach with those obtained from the 2011 and 2015 cohorts using the NHATS sample weights. Once validated, we applied our strategy to combine the cohorts into a single analytical dataset without overlap of participants, and generated Bayesian estimates of frailty for the combined cohort. Estimates from the Bayesian model closely matched the weighted NHATS estimates. The ability to combine cohorts while generating population-based estimates will allow investigators to address questions that require larger sample sizes, thereby enhancing the value of NHATS to the scientific community.

Background In longitudinal studies of older persons, complete ascertainment of mortality is needed to minimize potential biases. To ascertain mortality in the National Health and Aging Trends Study (NHATS), investigators most commonly use its Sensitive files, which include month and year of death on most decedents who had not dropped out of the study. Because losses to follow-up are not insubstantial, ascertainment of mortality is likely incomplete. Methods We used linked Medicare data as the reference standard to determine the extent by which mortality is underestimated in NHATS through use of its Sensitive files. Ascertainment of mortality was compared between the 2 strategies over 10 years for 7 608 members of the 2011 cohort and 5 years for 7 498 members of the 2015 cohort. Results The Sensitive files did not identify a large number of decedents, leading to suboptimal sensitivity, ranging from 61.3% (2011 cohort, 10 years) to 75.5% (2015 cohort, 5 years). Some non-decedents were also misclassified as dead using the Sensitive files. Cumulative mortality rates were modestly lower for this ascertainment strategy, although the number of participants at risk decreased markedly over time. Mortality incidence rates were also modestly lower for this strategy, with incidence rate ratios ranging from 0.88 (2011 cohort, 10 years) to 0.94 (2011 cohort, 5 years). Conclusions Use of the NHATS Sensitive files leads to incomplete ascertainment and, to a lesser degree, misclassification of mortality. Caution may be warranted when interpreting results of longitudinal analyses in NHATS that evaluate mortality using the Sensitive files.

Homeownership is a key social determinant of health, and its absence has been associated with poor self-rated health and hospitalization among older persons. However, the associations between homeownership status and subsequent mortality and incident geriatric conditions remain understudied among community-living older Americans. Using data from the 2015 cohort of the National Health and Aging Trends Study (NHATS)—a nationally representative study of Medicare beneficiaries aged 65 years or older—we evaluated whether homeownership status is associated with mortality and the incidence of frailty, disability, and dementia over a 5-year follow-up period. Mortality was determined from linked Medicare records, while the geriatric outcomes were determined using annual NHATS surveys. Homeownership status was classified as non-homeowners (renters or those in other housing arrangements) versus homeowners. We applied time-varying Cox proportional hazards models with homeownership status as a time-dependent variable, adjusting for demographic and socioeconomic factors to estimate hazard ratios (HR) and 95% confidence intervals (CI). NHATS survey weights were used to generate nationally representative estimates. Among the 7499 participants (representing 40,728,543 older Americans) in 2015, 26.0% were non-homeowners. Over the 5-year follow-up period, being a non-homeowner was significantly associated with higher mortality (HR = 1.64, 95% CI = 1.50-1.80) and higher incidence of frailty (HR = 1.39; 95% CI = 1.14-1.69), disability (HR = 1.44; 95% CI = 1.23-1.69), and dementia (HR = 1.84, 95% CI = 1.49-2.26). Overall, these findings highlight non-homeownership as an important yet underrecognized risk factor for mortality and geriatric outcomes among community-living older Americans.

BackgroundCounty-level contextual disadvantage is a novel social determinant of health (SDOH) for older persons. No prior study has evaluated the national incidence of geriatric conditions according to county-level contextual disadvantage among older persons. Our objective was to estimate the incidence of frailty, probable dementia, and disability over a 5-year period on the basis of county-level contextual disadvantage among community-living older Americans.MethodsThis prospective, nationally representative longitudinal study used data from the 2015 cohort of the National Health and Aging Trends Study (NHATS), linked to various publicly available, geographically based contextual datasets. County-level disadvantage was assessed using the Geriatric Index of County-Level Multi-Dimensional Contextual Disadvantage (GERi-County), which included nine contextual indicators from these linked datasets. Data on frailty, probable dementia, and activities of daily living (ADL) disability were obtained from the NHATS annual assessments (2015-2020).ResultsTotally 7499 participants were included in the analysis, representing 40,728,543 community-living older Americans. The 5-year incidence rates per 1000 person-years were significantly higher in the disadvantaged compared to the non-disadvantaged counties: 52.8 (95% confidence interval (CI), 41.6-64.0) versus 40.3 (95% CI, 37.2-43.3) for frailty; 29.9 (95% CI, 25.4-34.3) versus 21.2 (95% CI, 19.0-23.4) for probable dementia; and 78.1 (95% CI, 70.2-86.0) versus 62.5 (95% CI, 58.2-66.8) for ADL disability. For participants who lived versus did not live in disadvantaged counties, the age- and sex-adjusted HRs were 1.38 (95% CI, 1.08-1.75) for frailty, 1.53 (95% CI, 1.25-1.86) for probable dementia, and 1.30 (95% CI, 1.13-1.49) for ADL disability.ConclusionsCommunity-living older Americans who reside in disadvantaged counties have a higher incidence of frailty, probable dementia, and ADL disability over a 5-year follow-up period compared to their non-disadvantaged counterparts. Findings underscore the vital, underappreciated role that county-level social contextual disadvantage plays on clinically meaningful outcomes in older persons in the U.S.

Studying and defining social contextual disadvantage in community-living older persons is vitally important, yet no composite indices of social disadvantage have been developed and validated specifically for the geriatric population. The current study aims to create two novel composite indices representing state- and county-level social contextual disadvantage in older (≥65 years) persons in the United States (US), and to evaluate whether disparities in mortality exist between index-defined disadvantaged and non-disadvantaged groups. Publicly-available state- and county-level (2006-2014) contextual factors from all 50 US states and 3132 counties were used to create indices of social contextual disadvantage. Associations of disadvantage-status with mortality (2010-2019) were assessed by negative binomial models. We found mortality rates were significantly higher in index-defined disadvantaged states/counties compared with non-disadvantaged ones for 2010-2015 and 2014-2019. For both periods, compared with non-disadvantaged states, the disadvantaged states had at least 11% increased mortality risk. At the county-level, the disadvantaged counties had an approximately 10% increased mortality risk. The findings suggest that the two indices of state- and county-level contextual disadvantage in older persons may serve as useful tools for identifying place-based disadvantaged populations of older Americans and as multidimensional factors driving mortality disparities. State- and county-level social contextual disadvantage should be considered when formulating public health policies and interventions aimed at reducing health disparities.

Importance:Estimates of active and disabled life expectancy, defined as the projected number of remaining years without and with disability in essential activities of daily living, are commonly used by policymakers to forecast the functional well-being of older persons. Objective:To determine how estimates of active and disabled life expectancy differ based on exposure to intervening illnesses and injuries (or events). Design, Setting, and Participants:This prospective cohort study was conducted in south-central Connecticut from March 1998 to December 2021 among 754 community-living persons aged 70 years or older who were not disabled. Data were analyzed from January 25 to September 18, 2024. Exposures:Exposure to intervening events, which included critical illness, major elective and nonelective surgical procedures, and hospitalization for other reasons, was assessed each month. Main Outcomes and Measures:Disability in 4 essential activities of daily living (bathing, dressing, walking, and transferring) was ascertained each month. Active and disabled life expectancy were estimated using multistate life tables under a discrete-time Markov process assumption. Results:The study included 754 community-living older persons who were not disabled (mean [SD] age, 78.4 [5.3] years; 487 female [64.6%]; 67 Black [8.9%], 4 Hispanic [0.5%], 682 non-Hispanic White [90.5%], and 1 other race [0.1%]). Within 5-year age increments from 70 to 90 years, active life expectancy decreased monotonically as the number of admissions for critical illness and other hospitalization increased. For example, at age 70 years, sex-adjusted active life expectancy decreased from 14.6 years (95% CI, 13.9-15.2 years) in the absence of a critical illness admission to 11.3 years (95% CI, 10.3-12.2 years), 8.1 years (95% CI, 6.3-9.9 years), and 4.0 years (95% CI, 2.6-5.7 years) in the setting of 1, 2, or 3 or more critical illness admissions, respectively. Corresponding values for other hospitalization were 19.4 years (95% CI, 18.0-20.8 years), 13.5 years (95% CI, 12.2-14.7 years), 10.0 years (95% CI, 8.9-11.2 years), and 7.0 years (95% CI, 6.1-7.9 years), respectively. Consistent monotonic reductions were observed for sex-adjusted estimates in active life expectancy for nonelective but not elective surgical procedures as the number of admissions increased; for example, at age 70 years, estimates of active life expectancy were 13.9 years (95% CI, 13.3-14.5 years), 11.7 years (95% CI, 10.5-12.8 years), and 9.2 years (95% CI, 7.4-11.0 years) for 0, 1, and 2 or more nonelective surgical admissions, respectively; corresponding values were 13.4 years (95% CI, 12.8-3-14.1 years), 14.6 years (95% CI, 13.5-15.5 years), and 12.6 years (95% CI, 11.5-13.8 years) for elective surgical admissions. Sex-adjusted disabled life expectancy decreased as the number of admissions increased for critical illness and other hospitalization but not for nonelective or elective surgical procedures; for example, at age 70 years, disabled life expectancy decreased from 4.4 years (95% CI, 3.5-5.8 years) in the absence of other hospitalization to 3.4 years (95% CI, 2.8-4.1 years), 3.4 years (95% CI, 2.7-4.2 years), and 2.3 years (95% CI, 1.9-2.8 years) in the setting of 1, 2, or 3 or more other hospitalizations, respectively. Conclusions and Relevance:This study found that active life expectancy among community-living older persons who were not disabled was considerably diminished in the setting of serious intervening illnesses and injuries. These findings suggest that prevention and more aggressive management of these events, together with restorative interventions, may be associated with improved functional well-being among older persons.

BACKGROUND:In the National Health and Aging Trends Study (NHATS), use of its Sensitive files leads to incomplete ascertainment of mortality, largely because of losses to follow-up. To account for these losses, we compared two censoring approaches for evaluating mortality. METHODS:In a hybrid approach, most participants were censored at the time of last contact, while the remainder were censored at the time of last completed interview. In the other approach, all participants were censored at the time of last completed interview (LCI). All-cause mortality was evaluated among 7608 and 7498 community-living members of the 2011 (over 10 years) and 2015 (over 5 years) cohorts based on the Sensitive files, with linked Medicare data serving as the reference standard. RESULTS:Using the hybrid and LCI approaches, the median (IQR) follow-up times among nondecedents were 7.7 (5.9-8.7) and 8.8 (6.3-9.9) years shorter for the Sensitive files than Medicare data in the 2011 cohort. The corresponding values in the 2015 cohort were 2.9 (1.8-3.8) and 4.0 (2.2-4.9) years. For both cohorts, cumulative mortality based on the Sensitive files relative to the Medicare data was modestly lower for the hybrid approach but comparable for the LCI approach. The incidence rate ratios (95% CI) for the Sensitive files relative to the Medicare data in the 2011 and 2015 cohorts, respectively, were 0.89 (0.87, 0.91) and 0.89 (0.86, 0.93) for the hybrid approach and 0.98 (0.95, 1.00) and 0.97 (0.94, 1.00) for the LCI approach. However, the numbers of participants at risk for death overtime were considerably smaller for the latter than the former approach. CONCLUSIONS:When evaluating mortality using the NHATS Sensitive files, investigators should consider censoring all participants who are lost to follow-up at the time of the last completed interview, recognizing potential trade-offs in terms of reductions in power and precision.

ImportanceAlthough neighborhood socioeconomic disadvantage has become the standard for evaluating contextual socioeconomic deprivation at the Census-block level, little is known about its prevalence or association with long-term mortality in nationally representative samples of older persons.ObjectivesTo estimate the prevalence of neighborhood disadvantage among a nationally representative sample of community-living older adults; to identify how prevalence estimates differ based on relevant demographic, socioeconomic, geographic, clinical, and geriatric characteristics; and to evaluate the association between neighborhood disadvantage and all-cause mortality.Design, Setting, and ParticipantsThis cohort study analyzed linked data of community-living persons aged 65 years or older in the contiguous US participating in the National Health and Aging Trends Study (NHATS) from 2011 to 2021. Data on demographic, socioeconomic, geographic, clinical, and geriatric characteristics were obtained primarily from the baseline NHATS assessment. NHATS survey weights were used for all analyses. Data analysis was conducted from February to July 2024.Main Outcomes and MeasuresNeighborhood disadvantage—the main measure for each of the 3 objectives—was assessed using the area deprivation index, which was dichotomized at the worst quintile (defined as the worst 2 deciles). Ascertainment of mortality over 10 years was 100% complete.ResultsAmong the 7505 participants, with a weighted mean (SD) age of 75.3 (7.4) years, 56.8% were female, 6.6% were Hispanic, 8.2% were non-Hispanic Black, and 81.7% were non-Hispanic White individuals. The prevalence of neighborhood disadvantage was 15.8% (95% CI, 14.9%-16.7%), but it differed greatly across multiple subgroups. The largest differences after adjustment for age and sex were observed for non-Hispanic Black compared with non-Hispanic White participants (rate ratio [RR], 3.11; 95% CI, 2.56-3.79); those with less than a high school diploma vs college degree or higher educational level (RR, 3.47; 95% CI, 2.75-4.39); and those in several Census divisions, with an RR as high as 7.31 (95% CI, 2.98-17.90) for West South Central vs Pacific. The mortality rates were 48.5% (95% CI, 44.6%-52.1%) and 43.5% (95% CI, 42.2%-44.7%) among participants in a disadvantaged and a nondisadvantaged neighborhood. Neighborhood disadvantage was associated with mortality after adjustment for demographic characteristics (hazard ratio [HR], 1.25; 95% CI, 1.11-1.40) but not after further adjustment for socioeconomic characteristics (HR, 1.11; 95% CI, 0.98-1.25).Conclusions and RelevanceIn this cohort study of community-living older adults, population-based estimates of neighborhood disadvantage differed greatly across multiple subgroups. This contextual indicator of socioeconomic deprivation was associated with long-term mortality, but the association was diminished and no longer significant after accounting for individual-level socioeconomic characteristics.

Importance Nationally representative estimates of hospital readmissions within 30 and 180 days after major surgery, including both fee-for-service and Medicare Advantage beneficiaries, are lacking. Objectives To provide population-based estimates of hospital readmission within 30 and 180 days after major surgery in community-living older US residents and examine whether these estimates differ according to key demographic, surgical, and geriatric characteristics. Design, Setting, and Participants A prospective longitudinal cohort study of National Health and Aging Trends Study data (calendar years 2011-2018), linked to records from the Centers for Medicare & Medicaid Services (CMS). Data analysis was conducted from April to August 2023. Participants included community-living US residents of the contiguous US aged 65 years or older who had at least 1 major surgery from 2011 to 2018. Data analysis was conducted from April 10 to August 28, 2023. Main Outcomes and Measures Major operations and hospital readmissions within 30 and 180 days were identified through data linkages with CMS files that included both fee-for-service and Medicare Advantage beneficiaries. Data on frailty and dementia were obtained from the annual National Health and Aging Trends Study assessments. Results A total of 1780 major operations (representing 9 556 171 survey-weighted operations nationally) were identified from 1477 community-living participants; mean (SD) age was 79.5 (7.0) years, with 56% being female. The weighted rates of hospital readmission were 11.6% (95% CI, 9.8%-13.6%) for 30 days and 27.6% (95% CI, 24.7%-30.7%) for 180 days. The highest readmission rates within 180 days were observed among participants aged 90 years or older (36.8%; 95% CI, 28.3%-46.3%), those undergoing vascular surgery (45.8%; 95% CI, 37.7%-54.1%), and persons with frailty (36.9%; 95% CI, 30.8%-43.5%) or probable dementia (39.0%; 95% CI, 30.7%-48.1%). In age- and sex-adjusted models with death as a competing risk, the hazard ratios for hospital readmission within 180 days were 2.29 (95% CI, 1.70-3.09) for frailty and 1.58 (95% CI, 1.15-2.18) for probable dementia. Conclusions and Relevance In this nationally representative cohort study of community-living older US residents, the likelihood of hospital readmissions within 180 days after major surgery was increased among older persons who were frail or had probable dementia, highlighting the potential value of these geriatric conditions in identifying those at increased risk.

Background Cognitive decline may be an early indicator of major health issues in older adults, though research using population-based data is lacking. Researchers objective was to assess the relationships between distinct cognitive trajectories and subsequent health outcomes, including health status, depressive symptoms, and mortality, using a nationally representative cohort. Methods Data were drawn from the National Health and Aging Trends Study. Global cognition was assessed annually between 2011 and 2018. The health status of 4 413 people, depressive symptoms in 4 342 individuals, and deaths among 5 955 living respondents were measured in 2019. Distinct cognitive trajectory groups were identified using an innovative Bayesian group-based trajectory model. Ordinal logistic, Poisson, and logistic regression models were used to examine the associations between cognitive trajectories and subsequent health outcomes. Results Researchers identified five cognitive trajectory groups with distinct baseline values and subsequent changes in cognitive function. Compared with the group with stably high cognitive function, worse cognitive trajectories (ie, lower baseline values and sharper declines) were associated with higher risks of poor health status, depressive symptoms, and mortality, even after adjusting for relevant covariates. Conclusions Among older adults, worse cognitive trajectories are strongly associated with subsequent poor health status, high depressive symptoms, and high mortality risks. Regular screening of cognitive function may help to facilitate early identification and interventions for older adults susceptible to adverse health outcomes.

OBJECTIVES:To evaluate the relationship between distressing symptoms and changes in disability after major surgery and to determine whether this relationship differs according to the timing of surgery (nonelective vs elective), sex, multimorbidity, and socioeconomic disadvantage. BACKGROUND:Major surgery is a common and serious health event that has pronounced deleterious effects on both distressing symptoms and functional outcomes in older persons. METHODS:From a cohort of 754 community-living persons, aged 70 or older, 392 admissions for major surgery were identified from 283 participants who were discharged from the hospital. The occurrence of 15 distressing symptoms and disability in 13 activities were assessed monthly for up to 6 months after major surgery. RESULTS:Over the 6-month follow-up period, each unit increase in the number of distressing symptoms was associated with a 6.4% increase in the number of disabilities [adjusted rate ratio (RR): 1.064; 95% CI: 1.053, 1.074]. The corresponding increases were 4.0% (adjusted RR: 1.040; 95% CI: 1.030, 1.050) and 8.3% (adjusted RR: 1.083; 95% CI: 1.066, 1.101) for nonelective and elective surgeries. Based on exposure to multiple (ie, 2 or more) distressing symptoms, the adjusted RRs (95% CI) were 1.43 (1.35, 1.50), 1.24 (1.17, 1.31), and 1.61 (1.48, 1.75) for all, nonelective, and elective surgeries. Statistically significant associations were observed for each of the other subgroups with the exception of individual-level socioeconomic disadvantage for the number of distressing symptoms. CONCLUSIONS:Distressing symptoms are independently associated with worsening disability, providing a potential target for improving functional outcomes after major surgery.

BACKGROUND:Among older persons, neighborhood disadvantage is a granular and increasingly used social determinant of health and functional well-being. The frequency of transitions into or out of a disadvantaged neighborhood over time is not known. These transitions may occur when a person moves from one location to another or when the Neighborhood Atlas, the data source for the area deprivation index (ADI) that is used to identify disadvantaged neighborhoods at the census-block level, is updated. METHODS:From a prospective longitudinal study of community-living persons, aged 70 years or older in South Central Connecticut, neighborhood disadvantage was ascertained every 18 months for 22 years (from March 1998 to March 2020). ADI scores higher than the 80th state percentile were used to distinguish neighborhoods that were disadvantaged (81-100) from those that were not (1-80). RESULTS:At baseline, 205 (29.3%) of the 699 participants were living in a disadvantaged neighborhood. Changes in neighborhood disadvantage during 14 consecutive 18-month intervals were relatively uncommon, ranging from 1.5% to 11.8%. Nearly 80% of participants had no change in neighborhood disadvantage and less than 4% had more than one change over a median follow-up of more than 9 years. Overall, the rate of transitions into or out of neighborhood disadvantage was only 2.7 per 100 person-years. These transitions were most common when the Neighborhood Atlas was updated (2013, 2015, 2018, and 2020). Comparable results were observed when decile changes in ADI scores during the 18-month intervals were evaluated. CONCLUSIONS:In longitudinal studies of older persons with extended follow-up, it may not be necessary to update information on disadvantaged neighborhoods in circumstances when it is possible, and the degree of misclassification of neighborhood disadvantage should be relatively low in circumstances when updated information cannot be obtained.

Objectives: The number of older adults struggling to maintain adequate housing is growing. Prior studies have used various criteria to measure housing insecurity; however, no standardized definition exists to date. Using a multidimensional approach, our study sought to calculate population-based estimates of various forms of housing insecurity among community-living older Americans and determine how these estimates differ across key characteristics. Methods: This study utilized data from the 2011 round of the National Health and Aging Trends Study (NHATS), a prospective longitudinal study of Medicare beneficiaries aged 65 years or older. Three key forms of housing insecurity were operationalized: poor housing affordability (PHA), poor housing quality (PHQ), and poor neighborhood quality (PNQ). Population-based estimates of these forms of housing insecurity were calculated using analytic sampling weights and stratified by age, gender, race and ethnicity, frailty status, and dementia status. Results: Totally 6466 participants were included in the analysis, representing 29,848,119 community-living older Americans. The mean (standard deviation) age was 77.3 (7.7) years; by weighted percentages, 56.0% identified as female, 81.3% as White, 8.2% Black, and 7.1% Hispanic. At least one form of housing insecurity was identified in 38.5% of older Americans. Individually, the prevalence of PHA was 14.8%, PHQ 24%, and PNQ 12.5%. The prevalence of at least one form of housing insecurity was higher among persons of color (62.9% Black and 66% Hispanic vs White; p < 0.001), those with frailty (40.9% pre-frail and 49.4% frail vs robust; p < 0.001), and those with cognitive impairment (48.1% possible and 51% probable dementia vs no dementia; p < 0.001). Discussion: Nearly one in three community-living older Americans experience at least one form of housing insecurity. This was most common among vulnerable subgroups. Our multidimensional approach to defining various forms of housing insecurity can be used for future studies focused on improving social determinants of health among high-risk older adults.

Background: This study aims to quantitatively assess use of the NSQIP surgical risk calculator (NSRC) in contemporary surgical practice and to identify barriers to use and potential interventions that might increase use.Materials and methods: We performed a cross-sectional study of surgeons at seven institutions. The primary outcomes were self-reported application of the calculator in general clinical practice and specific clinical scenarios as well as reported barriers to use.Results: In our sample of 99 surgeons (49.7% response rate), 73.7% reported use of the NSRC in the past month. Approximately half (51.9%) of respondents reported infrequent NSRC use (<20% of preoperative discussions), while 14.3% used it in =40% of preoperative assessments. Reported use was higher in nonelective cases (30.2% vs 11.1%) and in patients who were =65 years old (37.1% vs 13.0%), functionally dependent (41.2% vs 6.6%), or with surrogate consent (39.9% vs 20.4%). NSRC use was not associated with training status or years in practice. Respondents identified a lack of influence on the decision to pursue surgery as well as concerns regarding the calculator's accuracy as barriers to use. Surgeons suggested improving integration to workflow and better ed-ucation as strategies to increase NSRC use.Conclusions: Many surgeons reported use of the NSRC, but few used it frequently. Surgeons reported more frequent use in nonelective cases and frail patients, suggesting the calculator is of greater utility for high-risk patients. Surgeons raised concerns about perceived accuracy and suggested additional education as well as integration of the calculator into the electronic health record.

Background: Initiation of oncologic care is often delayed, yet little is known about delays in hepatopancreatobiliary (HPB) cancers or their impact. This retrospective cohort study describes trends in time to treatment initiation (TTI), assesses the association between TTI and survival, and identifies predictors of TTI in HPB cancers. Methods: The National Cancer Database was queried for patients with cancers of the pancreas, liver, and bile ducts between 2004 and 2017. Kaplan-Meier survival analysis and Cox regression were used to investigate the association between TTI and overall survival for each cancer type and stage. Multivariable regression identified factors associated with longer TTI. Results: Of 318,931 patients with HPB cancers, median TTI was 31 days. Longer TTI was associated with increased mortality in patients with stages I-III extrahepatic bile duct (EHBD) cancer and stages I- II pancreatic adenocarcinoma. Patients treated within 3-30, 31-60, and 61-90 days had median survivals of 51.5, 34.9, and 25.4 months (log-rank P<0.001), respectively, for stage I EHBD cancer, and 18.8, 16.6, and 15.2 months for stage I pancreatic cancer, respectively (P<0.001). Factors associated with increased TTI included stage I disease (+13.7 days vs. stage IV, P<0.001), treatment with radiation only (beta=+13.9 days, P<0.001), Black race (+4.6 days, P<0.001) and Hispanic ethnicity (+4.3 days, P<0.001). Conclusions: Some HPB cancer patients with longer time to definitive care experienced higher mortality than patients treated expeditiously, particularly in non-metastatic EHBD cancer. Black and Hispanic patients are at risk for delayed treatment. Further research into these associations is needed.

Objective: To identify the factors associated with days away from home in the year after hospital discharge for major surgery. Background: Relatively little is known about which older persons are susceptible to spending a disproportionate amount of time in hospitals and other health care facilities after major surgery. Methods: From a cohort of 754 community-living persons, aged 70+ years, 394 admissions for major surgery were identified from 289 participants who were discharged from the hospital. Candidate risk factors were assessed every 18 months. Days away from home were calculated as the number of days spent in a health care facility. Results: In the year after major surgery, the mean (SD) and median (interquartile range) number of days away from home were 52.0 (92.2) and 15 (0–51). In multivariable analysis, 5 factors were independently associated with the number of days away from home: age 85 years and older, low score on the Short Physical Performance Battery, low peak expiratory flow, low functional self-efficacy, and musculoskeletal surgery. Based on the presence versus absence of these factors, the absolute mean differences in the number of days away from home ranged from 31.2 for age 85 years and older to 53.5 for low functional self-efficacy. Conclusions: The 5 independent risk factors can be used to identify older persons who are particularly susceptible to spending a disproportionate amount of time away from home after major surgery, and a subset of these factors can also serve as targets for interventions to improve quality of life by reducing time spent in hospitals and other health care facilities.

Objective: The objective of this study was to estimate the incidence and cumulative risk of major surgery in older persons over a 5-year period and evaluate how these estimates differ according to key demographic and geriatric characteristics. Background: As the population of the United States ages, there is considerable interest in ensuring safe, high-quality surgical care for older persons. Yet, valid, generalizable data on the occurrence of major surgery in the geriatric population are sparse. Methods: We evaluated data from a prospective longitudinal study of 5571 community-living fee-for-service Medicare beneficiaries, aged 65 or older, from the National Health and Aging Trends Study from 2011 to 2016. Major surgeries were identified through linkages with Centers for Medicare and Medicaid Services data. Population-based incidence and cumulative risk estimates incorporated National Health and Aging Trends Study analytic sampling weights and cluster and strata variables. Results: The nationally representative incidence of major surgery per 100 person-years was 8.8, with estimates of 5.2 and 3.7 for elective and nonelec-tive surgeries. The adjusted incidence of major surgery peaked at 10.8 in persons 75 to 79 years, increased from 6.6 in the non-frail group to 10.3 in the frail group, and was similar by sex and dementia. The 5-year cumulative risk of major surgery was 13.8%, representing nearly 5 million unique older persons, including 12.1% in persons 85 to 89 years, 9.1% in those ≥90 years, 12.1% in those with frailty, and 12.4% in those with probable dementia. Conclusions: Major surgery is a common event in the lives of community-living older persons, including high-risk vulnerable subgroups.

Background: Over half of surgeries in the United States are performed on older adults. The aims of this study were to quantify geriatric-relevant discussion topics and assessments during the consent process and to assess the need for a structured approach to consent older patients. Methods: General surgery residents at a single institution answered questions about content of the informed consent process and preoperative assessment in adult and geriatric (> 65) patients. Questions addressed frequency of geriatric- relevant discussions, assessments and consultations for the two patient groups. Results: Part 1 was completed by 66/75 residents (88.0%). Most residents received training in informed consent during medical school or residency (95%). Common avenues for training were direct observation of attending surgeons or senior residents (85%), followed by didactic teaching (47%) and independent reading (30%). Only three residents (two PGY1s and one PGY2) reported receiving specific training in how to achieve informed consent in older patients. Part 2 was completed by 47/56 eligible residents (83.9%). Postoperative expectations (85.1%), living situation (53.2%), postoperative goals (53.2%), and advanced directives (42.6%) were most commonly discussed. Cognitive testing (19.1%), geriatrics consults (14.9%), and frailty scores (4.3%) were rarely addressed. There were no correlations between discussion of this information with resident age, level in residency, self-identified gender, or self-identification as a member of a racial or ethnic minority. Conclusions: Geriatric-relevant topics and assessments occurred sporadically during the resident-led informed consent process and were more common with senior residents. Training in geriatric relevant informed consent rarely occurs during residency. These results, if generalizable across surgical training sites, highlight the need for a structured curriculum to address geriatric-relevant perioperative concerns.

Objective To identify the rates and possible predictors of alcohol withdrawal syndrome (AWS) among adult trauma patients.Methods This is a retrospective review of all adult patients (18 years or older) included in the 2017 and 2018 American College of Surgeons Trauma Quality Program Participant User File (PUF). The main outcomes were rates and predictors of AWS.Results 1 677 351 adult patients were included in the analysis. AWS was reported in 11 056 (0.7%). The rate increased to 0.9% in patients admitted for more than 2 days and 1.1% in those admitted for more than 3 days. Patients with AWS were more likely to be male (82.7% vs. 60.7%, p<0.001), have a history of alcohol use disorder (AUD) (70.3% vs. 5.6%, p<0.001) and have a positive blood alcohol concentration (BAC) on admission (68.2% vs. 28.6%, p<0.001). In a multivariable logistic regression, history of AUD (OR 12.9, 95% CI 12.1 to 13.7), cirrhosis (OR 2.1, 95% CI 1.9 to 2.3), positive toxicology screen for barbiturates (OR 2.1, 95% CI 1.6 to 2.7), tricyclic antidepressants (OR 2.2, 95% CI 1.5 to 3.1) or alcohol (OR 2.5, 95% CI 2.4 to 2.7), and Abbreviated Injury Scale head score of ≥3 (OR 1.7, 95% CI 1.6 to 1.8) were the strongest predictors for AWS. Conversely, only 2.7% of patients with a positive BAC on admission, 7.6% with a history of AUD and 4.9% with cirrhosis developed AWS.Conclusion AWS after trauma was an uncommon occurrence in the patients in the PUF, even in higher-risk patient populations.Level of evidence IV: retrospective study with more than one negative criterion.