Identification Of Older Adults Research Articles

Effects of changing criteria on improving interRAI assessment for elder abuse: analysis of a national dataset from Aotearoa New Zealand

ObjectivesGlobally, one in six older adults in the community will be a victim of abuse (elder abuse; EA). Despite these horrific statistics, EA remains largely undetected and under-reported. Available screening...

Depressive Symptoms are Associated with Decline Over Time in Verbal Fluency Performance in Female but Not Male Community-Dwelling Older Adults

ABSTRACT Objective The current study was designed to examine associations between depressive symptoms and longitudinal declines in category and letter fluency performance in a gender-stratified sample of older adults. Method Participants were community-residing older adults (females: n = 289; males: n = 233) followed annually (2011–2018) as part of a cohort study conducted at Albert Einstein College of Medicine in New York. Depressive symptoms were assessed using the Geriatric Depression Scale (GDS). Standard forms assessed category and letter fluency performance. Participants were dementia-free during study enrollment. Results The presence of baseline depressive symptoms suggestive of subclinical depression was associated with a worse longitudinal decline in category fluency performance in female but not male participants. These associations remained significant when excluding participants with prevalent and incident mild cognitive impairment and incident dementia. Irrespective of gender, letter fluency performance did not decline over time and was not influenced by the presence of depressive symptoms. Discussion The present study’s results can aid in identification of older adults who may be at greater risk for cognitive decline, and add to the limited literature examining the influence of gender on longitudinal associations between depressive symptoms and verbal fluency performance.

Multimorbidity pattern and risk of dementia in later life: an 11-year follow-up study using a large community cohort and linked electronic health records

BackgroundSeveral long-term chronic illnesses are known to be associated with an increased risk of dementia independently, but little is known how combinations or clusters of potentially interacting chronic conditions may...

Identification of older adults' needs as future users of autonomous shuttles: A serious game co-creation approach for inclusiveness

Automated vehicles are potential disrupters of the mobility system and are expected to address inclusive mobility issues. Yet, the transition to their full implementation in cities is expected to face numerous challenges. While companies and governments interested in their future implementation have conducted pilots to understand better their implementation in cities, there is still a limited understanding of potential users' needs. This understanding becomes even more limited when considering vulnerable groups. To address this gap, we have developed a novel Serious Game named "A shuttle for everyone". We use it as a co-creation method to engage potential users, in this case, older adults in the Noordrand-Brussels region, Belgium. This study case contributes to the co-creation and transport literature as there is scarce research focused on developing new inclusive mobility public services. Three game sessions with older adults took place. The key identified needs are related to comfort, safety, ease of use, and accessibility. Our results confirm and complete previous automated vehicle studies. We can confirm that our Serious Game as a co-creation method has facilitated anticipatory needs identification. Understanding users' needs contribute to improving design and can help to create policy recommendations that aim for an inclusive implementation of automated vehicle mobility services.

Factors Associated with Frailty Transitions among the Old-Old in Community: A Prospective Cohort Study

Background: The identification of older adults with different frailty transitions, especially the old-old, is beneficial for stratified management. However, the factors associated with frailty transition in the elderly have not been fully elucidated. This study aimed to explore frailty transitions and associated factors among older adults. Methods: The participants were all from a prospective cohort study of older adults aged ≥75 years in a continuing care retirement community in Beijing, China. Frailty states were assessed using FRAIL at baseline and 1-year follow-up. The association between factors, including comprehensive geriatric assessment and laboratory indicators such as serum albumin and highsensitivity C-reactive protein (hsCRP), and frailty transitions were explored by binary logistic regression. The predicted value of the factors associated with frailty transitions was analyzed using the receiver operating characteristic curve (ROC), and the area under the ROC curve (AUC) was calculated. Results: A total of 183 older adults (mean age: 83.9±4.4 years; females, 59%) completed the frailty state assessment at baseline and 1-year followup. After adjusting for age and sex, walking speed(odds ratio [OR], 0.01; 95%confidence interval [CI]: 0.002-0.12),timed up-and-go (TUG) test(OR:1.08, 95% CI: 1.02-1.15), short physical performance battery(OR:0.79, 95% CI :0.68-0.92), serum albumin (OR:0.78, 95% CI:0.64-0.94), and serum hsCRP (OR:1.21, 95% CI:1.00-1.47) were associated with worsening of the frailty state. Cognitive function (OR:6.73, 95% CI:1.15-39.19) was associated with improving the frailty state. ROC analysis showed that low walking speed (AUC:0.81), long TUG test time(AUC:0.77), low Short Physical Performance Battery (SPPB)score (AUC:0.75), low serum albumin (AUC:0.68), and high serum hsCRP(AUC:0.80) could predict the decline in frailty state. Good cognitive function (AUC: 0.69) predicted an improvement in the frailty state. Conclusions: Frailty is dynamic. The frailty state of the old-old with poor physical function, low serum albumin, and high serum hsCRP was more likely to decline, but it was more likely to improve with good cognitive function. Walking speed, TUG test, SPPB, serum albumin, serum hsCRP, and cognitive function may predict frailty transitions among the old-old.

Home-Dwelling Older Adults' Day-to-Day Community Interactions: A Qualitative Study.

Background: Many home-dwelling older adults present abnormal behaviours related to dementia or to non-dementia cognitive impairment (e.g., agitation, anxiety, apathy, etc.). Because many older adults live at home alone or are able to hide any signs of abnormal behaviours from others, the non-healthcare workers who interact with older adults on a daily basis are key actors in detecting those behaviours and orienting older adults towards appropriate support services. To the best of our knowledge, no studies to date have explored the daily interactions experienced between older adults and the various non-healthcare workers whom they regularly encounter in the community. This work aimed to identify the non-healthcare workers who are regularly in direct contact with older adults during their day-to-day activities and then develop specific training for these workers on the subject of abnormal behaviours among the elderly. Methods: This qualitative and ethnographic study asked 21 home-dwelling older adults aged 65 years old or more to answer open-ended questions. Sixteen had no self-reported cognitive impairments, and five had a probable or diagnosed slight cognitive impairment or mild-to-moderate dementia. A thematic analysis of the data was carried out. Results: The non-healthcare workers who spent the most time with older adults with and without reported cognitive impairments were those working in cafés or tea rooms and leisure or activity centres. Conclusions: In view of the significant amounts of contact between home-dwelling older adults and non-healthcare workers, it seems necessary and sensible to increase non-healthcare workers’ knowledge about abnormal behaviours, especially by offering them training. The proactive detection and identification of older adults’ abnormal behaviours by non-healthcare workers will ensure earlier care and reduce avoidable hospitalisations, institutionalisations and costs linked to geriatric healthcare.

Association of Low Muscle Mass With Cognitive Function During a 3-Year Follow-up Among Adults Aged 65 to 86 Years in the Canadian Longitudinal Study on Aging

Cross-sectional studies have shown that combined low muscle mass and strength are associated with cognitive impairment. Whether low muscle mass, reflective of physiologic reserve, is independently associated with faster cognitive decline remains unknown. To investigate the associations between low muscle mass and cognitive decline in 3 distinct domains among adults aged at least 65 years. The Canadian Longitudinal Study on Aging is a prospective population-based cohort study of community-dwelling adults. Enrollment occurred from 2011 to 2015 with a 3-year follow-up. Analyses for this study were conducted on those aged at least 65 years from April 24 to August 12, 2020. Appendicular lean soft tissue mass (ALM) was assessed by dual energy x-ray absorptiometry. Low ALM was identified using the sex-specific Canadian cut points. Memory was assessed using the Rey auditory verbal learning test. Executive function was assessed using the mental alternation test, Stroop high interference (words/dot) test, the animal fluency test, and the controlled oral word association test. Psychomotor speed was assessed using computer-administered choice reaction time. Composite scores by domain were created. Of 8279 participants, 4003 (48%) were female, 8005 (97%) were White, and the mean (SD) age was 72.9 (5.6) years. A total of 1605 participants (19.4%) had low ALM at baseline. Participants with low ALM were older, had lower body mass index and physical activity level. The presence of low ALM at baseline was associated with faster 3-year cognitive decline in executive functions and psychomotor speed from multiple linear regressions. After adjusting for covariates including age, level of education, percentage body fat, and handgrip strength, low ALM remained independently associated with executive function decline (standardized β: -0.032; P = .03) only. Low ALM was not associated with memory. This cohort study found longitudinal associations between low ALM and cognition in aging. Identification of older adults with low muscle mass, a targetable modifiable factor, may help estimate those at risk for accelerated executive function decline. Further longer-term investigation of associations is warranted.

Dual‐task gait and mild behavioral impairment: Findings on the interface between non‐cognitive dementia markers in the COMPASS‐ND study

AbstractBackgroundMild behavioral impairment (MBI) and poor dual‐task gait performance are non‐cognitive markers for dementia. Both MBI and dual‐task gait performance have been associated with an increased risk of cognitive decline, but to our knowledge the relationship between them has yet to be investigated.MethodCross‐sectional data from 193 non‐demented participants (10 cognitively normal, 48 subjective cognitive decline, 135 mild cognitive impairment; MCI) in the COMPASS‐ND study (February 2020 release) were analyzed. MBI was approximated using the Neuropsychiatric Inventory Questionnaire (NPI‐Q) using a published algorithm. Dual‐task gait cost (DTGC), operationalized as the percentage difference between dual‐task and preferred walking speeds, was assessed under three cognitive tasks: animal naming, counting backwards by one, and serial seven subtractions. Multivariable linear regression was used to determine the association between global MBI burden and DTGC, adjusting for age, sex, years of education, and Montreal Cognitive Assessment (MoCA) score, or diagnosis. Models were additionally fitted for the subgroup of participants with MCI alone. Mediation analyses were conducted using bootstrapping to determine if the association between MBI and DTGC was mediated by global cognition (MoCA), executive function (Trail Making B), verbal (Rey Auditory Verbal Learning Test) or working (Digit Span) memory.ResultParticipants on average were 72.4 years old (52.8% female) and had completed 15.8 years of education. MBI symptoms were observed in 46.6% of participants. Greater overall MBI burden was associated with reduced gait speed and higher DTGC for all three gait conditions in MCI, and in all participants without dementia when controlling for diagnosis or MoCA (Table 1), except for DTGC under animal naming conditions when controlling for MoCA. The associations between MBI and DTGC were mediated by executive function but not global cognition, verbal or working memory (Table 2).ConclusionIn this group of older adults at risk but without dementia (SCD and MCI spectrum), MBI is associated with DTGC, which in itself is a dementia risk marker. Our findings support the role of these non‐cognitive dementia markers in the detection of at‐risk individuals. Identification of older adults at risk of incident dementia may be enhanced by considering MBI and DTGC in conjunction.

58 Using Machine Learning to Predict Hospital Disposition With Geriatric Emergency Department Innovations Intervention

The geriatric emergency department innovations (GEDI) program is a nurse-based geriatric assessment and care coordination program that reduces preventable admissions for older adults and decreases Medicare expenditures. All adults age 65+ in the ED are currently eligible, but only 5% of older adults receive GEDI care due to resource limitations. Currently available geriatric screenings to identify older adults likely to benefit from programs like GEDI perform poorly in the ED. The objective of this study was to predict likelihood of hospitalization accurately and consistently with and without GEDI care using machine learning models to better target the GEDI program. We performed a cross sectional observational study of ED records from (1/2010 to 3/2018). Using propensity score matching, GEDI patients were matched to non-GEDI patients. Logistic regression, random forest, support vector machine, gradient boosting, and neural network techniques were used to predict hospital admission using demographic data, medical history, ED visit chief complaint, vitals, and geographic data. Hospital admission was then predicted with and without GEDI assessment during the ED visit. Visits were classified into one group with a predicted change in hospital disposition with the GEDI assessment and another group with no predicted change in disposition with GEDI assessment. In this second analysis feature importance was performed on the tree-based models. Final model performance was reported as the area under the curve (AUC) using receiver operating characteristic models for the test data. We included 55,056 patients age 65+ who accounted for 134, 361 ED visits. Of these, 3, 860 visits were included in the training set and 10, 142 in the testing set to predict hospital admission. 5, 071 visits were used in the training and testing sets to predict change in disposition with GEDI. The random forest model had the best performance with an AUC of 0.81 (95% CI 0.79-0.83). In the random forest model, 9, 756 (96.2%) ED visits were predicted to have no change in disposition with GEDI assessment, and 386 (3.8%) ED visits were predicted to have a change in disposition with GEDI assessment (Table 1). Of those with a predicted change in disposition from admitted to discharged with GEDI assessment the top 5 most influential variables out of 86 variables with their relative importance are in Table 2. The higher relative importance the more it influenced the model’s outcome, however ranking does not imply the direction of influence. All importance values add up to a total of 1. Our machine learning models were able to predict who is likely to be discharged with GEDI assessment with good accuracy and thus select a cohort appropriate for GEDI care. Future implementation of this machine learning model into the electronic health record may assist in the identification of older adults who should be prioritized for GEDI care.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Cardiometabolic diseases, frailty, and healthcare utilization and expenditure in community-dwelling Chinese older adults

This study investigated associations between cardiometabolic diseases, frailty, and healthcare utilization and expenditure among Chinese older adults. The participants were 5204 community-dwelling adults aged at least 60 years from the China Health and Retirement Longitudinal Study. Five cardiometabolic diseases were assessed including hypertension, dyslipidemia, diabetes, cardiac diseases and stroke. Frailty status was based on five criteria: slowness, weakness, exhaustion, inactivity, and shrinking. Participants were deemed frailty if they met at least three criteria. As the number of cardiometabolic diseases increased, so did the prevalence of frailty, and the proportion of healthcare utilization, including outpatient visit and inpatient visit. Moreover, the total healthcare expenditure and the odds of catastrophic health expenditure were increased with the number of cardiometabolic disorders. After adjusting for covariates, cardiometabolic diseases were positively associated with higher odds of frailty, incurring outpatient and inpatient visit. And individuals with 2 or more cardiometabolic diseases had a higher odds of catastrophic health expenditure than persons with non-cardiometabolic disease. Participants who were frailty were more likely to report higher odds of healthcare utilization. These findings suggest that both cardiometabolic diseases and frailty assessment may improve identification of older adults likely to require costly, extensive healthcare.

Validation of the detection of elder abuse through emergency care technicians (DETECT) screening tool: a study protocol

IntroductionElder mistreatment (EM) is a high prevalence threat to the health and well-being of older adults in the USA. Medics are well-positioned to help with identification of older adults at...

Risk factors for delirium among older adults in the emergency department: a systematic review protocol

IntroductionDelirium is commonly missed in older adults presenting to the emergency department (ED). Although current recommendations for active screening of delirium in the ED, this might not be feasible or...

Development of a fall-risk assessment profile for community-dwelling older adults by using the National Health Interview Survey in Taiwan

BackgroundFalls represent a global health issue among older adults and cause a considerable burden on medical systems. In this study, a fall-risk assessment profile was developed for community-dwelling older adults.MethodThe data of survey participants aged > 65 years were obtained from three rounds (2005, 2009, and 2013) of the National Health Interview Survey in Taiwan. In total, 8356 older participants were included in this study. Logistic regression analyses were used to determine potential predictors associated with falls. The regression coefficients of the predictors in the final model were translated into scores (by multiplying by 5) and then summed to obtain a total risk-score for falls. A receiver operating characteristic (ROC) curve was used to evaluate the discriminative performance of the risk assessment profile.ResultSelf-reported falls within 1 year accounted for 19.1% of the total falls. The predictors that were included in the risk profile according to the logistic regression analysis results were as follows: female sex (adjusted odds ratio = 1.57; risk-score = 2), living alone (adjusted odds ratio = 1.56; risk-score = 2), urinary incontinence (adjusted odds ratio = 1.36; risk-score = 2), perceived unhealthiness (adjusted odds ratio = 1.32; risk-score = 1), perceived pain (adjusted odds ratio = 1.51; risk-score = 2), hospital admission in the past year (adjusted odds ratio = 2.42; risk-score = 4), low activity of daily living (ADL) scores (adjusted odds ratio = 1.29; risk-score = 1), and low mobility function scores (adjusted odds ratio = 1.68; risk-score = 3). At a total risk-score cutoff point of 6 (range 0–17), the model predicted falls with a sensitivity and specificity of 75.16 and 52.75%, respectively (area under the ROC curve = 0.70).ConclusionThe fall-risk assessment profile comprising eight predictors—female sex, living alone, incontinence, perceived unhealthiness, perceived pain, hospital admission in the past year, low ADL scores, and low mobility function scores—may serve as an assessment tool for identification of older adults with a high risk of falling, and assessment results can be used to facilitate community-based intervention.

Factors Associated With a Higher Risk of Undiagnosed Prediabetes in a Community-Dwelling Medicare Population.

OBJECTIVE: To identify characteristics in an ambulatory Medicare population that are significantly more likely to be associated with a high risk of undiagnosed prediabetes.<br/> DESIGN: Cross-sectional study.<br/> SETTING: Fourteen health clinics targeting Medicare beneficiaries were held throughout northern and central California during the fall of 2017.<br/> PATIENTS, PARTICIPANTS: Noninstitutionalized Medicare beneficiaries receiving medication therapy management services without self-reported diabetes.<br/> INTERVENTIONS: Beneficiaries were screened for their risk of type 2 diabetes mellitus (T2DM) through the use of the American Diabetes Association (ADA) risk assessment (score of ≥ 5 indicates increased risk of developing type 2 diabetes) by pharmacy students. For this study, patients with a score of ≥ 5 were considered to be at high risk for undiagnosed prediabetes.<br/> MAIN OUTCOME MEASURE(S): Characteristics significantly more likely to be identified in patients at high risk for undiagnosed prediabetes.<br/> RESULTS: A total of 683 Medicare beneficiaries without self-reported diabetes completed the ADA risk assessment, with 457 (66.9%) receiving a score of 5 or more. In those, the presence of hyperlipidemia, hypertension, obesity, coronary heart disease, and use of aspirin were all characteristics researchers identified as significantly more likely to be found in this group. In contrast, those of Asian race or who took dietary supplements were significantly less likely to score 5 or higher in the questionnaire.<br/> CONCLUSION: Identification of older adults at higher risk for undiagnosed prediabetes through the use of appropriate screening tools allows for targeted preventive interventions, potentially lowering risk of developing T2DM for selected patients.

Digital assessment of falls risk, frailty, and mobility impairment using wearable sensors

Falls are among the most frequent and costly population health issues, costing $50bn each year in the US. In current clinical practice, falls (and associated fall risk) are often self-reported after the “first fall”, delaying primary prevention of falls and development of targeted fall prevention interventions. Current methods for assessing falls risk can be subjective, inaccurate, have low inter-rater reliability, and do not address factors contributing to falls (poor balance, gait speed, transfers, turning). 8521 participants (72.7 ± 12.0 years, 5392 female) from six countries were assessed using a digital falls risk assessment protocol. Data consisted of wearable sensor data captured during the Timed Up and Go (TUG) test along with self-reported questionnaire data on falls risk factors, applied to previously trained and validated classifier models. We found that 25.8% of patients reported a fall in the previous 12 months, of the 74.6% of participants that had not reported a fall, 21.5% were found to have a high predicted risk of falls. Overall 26.2% of patients were predicted to be at high risk of falls. 29.8% of participants were found to have slow walking speed, while 19.8% had high gait variability and 17.5% had problems with transfers. We report an observational study of results obtained from a novel digital fall risk assessment protocol. This protocol is intended to support the early identification of older adults at risk of falls and inform the creation of appropriate personalized interventions to prevent falls. A population-based approach to management of falls using objective measures of falls risk and mobility impairment, may help reduce unnecessary outpatient and emergency department utilization by improving risk prediction and stratification, driving more patients towards clinical and community-based falls prevention activities.

SCREENING FOR LOW SHORT PHYSICAL PERFORMANCE BATTERY SCORES: CAN GRIP STRENGTH AND SINGLE CHAIR STAND BE USEFUL?

The clinical value of low Short Physical Performance Battery (SPPB) scores for identification of older adults at-disability-risk who may benefit from structured intervention is well-established. Feasibility concerns – e.g., time, space constraints – are factors that often preclude SPPB implementation in clinical settings. We assessed whether grip strength (GS) and/or single chair stand (SCS), simple and highly feasible tests, could be useful for clinical identification of older adults with poor SPPB performance. Cross-sectional study using most recent data (Round 7) from the National Health and Aging Trends Study, which enrolled a large U.S. representative sample of Medicare beneficiaries 65 years and older (baseline round: 2011; yearly follow-ups). Nursing home residents were excluded. Sample size was 4,612. Outcome: poor SPPB performance (score <8). Low GS: <20 Kg (women) or <30 Kg (men), and able to do a SCS without use of arm (yes/no) were predictors. Logistic regression, areas under the curves (AUC), and accuracy statistics were computed. AUC for low GS was 0.66, and SCS inability was 0.68; when both tests were considered together, AUC increased significantly: 0.76. Among those SCS-unable (n=752), 95.6% had SPPB<8. A two-stage screening approach; i.e., detection of SCS inability first, followed by low GS in those SCS-able resulted in a net-sensitivity of 75.3%, and net-specificity of 83.5%. Sequential screening with SCS and GS testing might offer a case finding screening approach appealing to busy clinical settings from feasibility, accuracy, and/or efficiency perspectives for identification of older adults with low SPPB who may benefit from established interventions.

Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study.

This study evaluated the predictive ability of 11 obesity- and lipid-related parameters, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body roundness index (BRI), “A” body-shape index (ABSI), conicity index (C), visceral adiposity index (VAI), triglyceride-to-glucose fasting index (TyG), triglyceride-to-glucose fasting related to BMI (TyG-BMI), triglyceride-to-glucose fasting related to WC (TyG-WC), and triglyceride-to-glucose fasting related to WtHR (TyG-WtHR), to identify patients from an elderly Colombian population with a high risk of prediabetes according to the 2016 American Diabetes Association criteria. The data were obtained from the 2015 Colombian Health and Wellbeing and Aging Survey. A total of 3307 elderly Colombian individuals (aged over 60 years) were included. Anthropometric data, fasting plasma glucose, blood lipid profiles, family history, and health-related behaviors were assessed, and prediabetes was defined as a fasting plasma glucose of 100 to 125 mg/dL. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for each anthropometric indicator, using the prediabetes classification to identify their sensitivity and specificity, and these indicated that the prevalence of prediabetes was 25.3% in this population. After adjusting for potential confounding factors, the TyG index was strongly associated with the odds of having prediabetes in both sexes, and multivariate logistic regression analysis showed that the ORs for prediabetes increased across quartiles (p < 0.001). The TyG index was best able to identify prediabetes in either sex (AUC and optimal cut-off = 0.700 and 8.72, and 0.695 and 8.92 for men and women, respectively), suggesting that compared to the other parameters, the TyG index has the best discriminative power to predict prediabetes in the whole population. Thus, we propose the TyG index be used as a complementary marker for assessing prediabetes in older adults.

Accuracy of clinical-functional tools to identify risk of falls among community-dwelling older adults

Abstract Introduction: The identification of older adults who present greater chances of falling is the first step in the prevention of falls. Clinical instruments have been shown to be able to differentiate fallers from non-fallers, but their predictive validity remains controversial. Objective: To investigate the accuracy of the Short Physical Performance Battery (SPPB) and Quick Screen Clinical Fall Risk Assessment (QuickScreen) instruments to identify risk of falls in community-dwelling older adults. Method: This is a prospective methodological study with 81 older adults (≥ 60 years), assessed at baseline by SPPB and QuickScreen and monitored after one year to identify the occurrence of falls. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the ROC curve (AUC) were calculated. Results: 28.4% of the sample reported falls. QuickScreen presented 52.2% sensitivity, 74.1% specificity, 44.4% PPV, 79.6% NPV and 0.656 AUC. The AUC for SPPB was not significant (p = 0.087). Conclusion: QuickScreen presented poor accuracy when predicting falls and SPPB was unable to identify community-dwelling older adults at risk of falls. The QuickScreen instrument stood out for its high potential to identify true negatives.

Identification of older adults with frailty in the Emergency Department using a frailty index: results from a multinational study.

frailty is a central concept in geriatric medicine, yet its utility in the Emergency Department (ED) is not well understood nor well utilised. Our objectives were to develop an ED frailty index (FI-ED), using the Rockwood cumulative deficits model and to evaluate its association with adverse outcomes. this was a large multinational prospective cohort study using data from the interRAI Multinational Emergency Department Study. The FI-ED was developed from the Canadian cohort and validated in the multinational cohort. All patients aged ≥75 years presenting to an ED were included. The FI-ED was created using 24 variables included in the interRAI ED-Contact Assessment tool. there were 2,153 participants in the Canadian cohort and 1,750 in the multinational cohort. The distribution of the FI-ED was similar to previous frailty indices. The mean FI-ED was 0.26 (Canadian cohort) and 0.32 (multinational cohort) and the 99th percentile was 0.71 and 0.81, respectively. In the Canadian cohort, a 0.1 unit increase in the FI-ED was significantly associated with admission (odds ratio (OR) = 1.43 [95% CI: 1.34-1.52]); death at 28 days (OR = 1.55 [1.38-1.73]); prolonged hospital stay (OR = 1.37 [1.22-1.54]); discharge to long-term care (OR = 1.30 [1.16-1.47]); and need for Comprehensive geriatric Assessment (OR = 1.51 [1.41-1.60]). The multinational cohort showed similar associations. the FI-ED conformed to characteristics previously reported. A FI, developed and validated from a brief geriatric assessment tool could be used to identify ED patients at higher risk of adverse events.

The "Surprise Question" Asked of Emergency Physicians May Predict 12-Month Mortality among Older Emergency Department Patients.

Identification of older adults with serious illness (life expectancy less than one year) who may benefit from serious illness conversations or other palliative care interventions in the emergency department (ED) is difficult. To assess the performance of the "surprise question (SQ)" asked of emergency physicians to predict 12-month mortality. We asked attending emergency physician "Would you be surprised whether this patient died in the next 12 months?" regarding patients ≥65 years old that they had cared for that shift. We prospectively obtained death records from Massachusetts Department of Health Vital Records. An urban, university-affiliated ED. Twelve-month mortality. We approached 38 physicians to answer the SQ, and 86% participated. The mean age of our cohort was 76 years, 51% were male, and 45% had at least one serious illness. Out of 207 patients, the physicians stated that they "would not be surprised" if the patient died in the next 12 months for 102 of the patients (49%); 44 of the 207 patients (21%) died within 12 months. The SQ demonstrated sensitivity of 77%, specificity of 56%, positive predictive value of 32%, and negative predictive value of 90%. When combined with other predictors, the model sorted the patient who lived from the patient who died correctly 72% of the time (c-statistic = 0.72). Use of the SQ by emergency physicians may predict 12-month mortality in older ED patients and may help emergency physicians identify older adults in need of palliative care interventions.