Validation of the Korean Version of the Clinical Frailty Scale-Adjusted Korean Triage and Acuity Scale for Older Patients in the Emergency Department.

Background and Objectives: The Clinical Frailty Scale (CFS), used to screen for prehospital frailty in patients aged >65 years, is simple, time-efficient, and has been validated in emergency departments (EDs). In this study, we analyzed whether the Korean Triage and Acuity Scale (KTAS) classification by level in older patients determined to have frailty based on the Korean version of the CFS increases the triage performance of the current KTAS. Materials and Methods: The primary outcome was 30-day in-hospital mortality, and secondary outcomes were hospital and intensive care unit (ICU) admissions. This study retrospectively analyzed prospectively collected data from three ED centers. Patients with a CFS score ranging from five (mildly frail) to nine (terminally ill) were categorized into the frailty group. We upgraded the KTAS classification of the frailty group by one level of urgency and defined this as the CFS-KTAS. Results: The cutoff values for predicting admission were three and two for the KTAS and CFS-KTAS, respectively. A significant difference was observed in the area under the receiver operating characteristic (AUROC) curve between the KTAS and CFS-KTAS. To predict ICU admission, the cutoff score was two for both scales. A significant difference was observed in the AUROC curve between the KTAS and CFS-KTAS. For predicting in-hospital mortality, the cutoff score was two for both scales. A significant difference was observed in the AUROC curve between the KTAS and CFS-KTAS. Conclusions: This study showed that the CFS-adjusted KTAS has a more useful prognostic value than the KTAS alone for predicting hospital outcomes in older patients.

Beyond the revised cardiac risk index: Validation of the hospital frailty risk score in non-cardiac surgery.

Frailty is an established risk factor for adverse outcomes following non-cardiac surgery. The Hospital Frailty Risk Score (HFRS) is a recently described frailty assessment tool that harnesses administrative data and is composed of 109 International Classification of Disease variables. We aimed to examine the incremental prognostic utility of the HFRS in a generalizable surgical population. Using linked administrative databases, a retrospective cohort of patients admitted for non-cardiac surgery between October 1st, 2008 and September 30th, 2019 in Alberta, Canada was created. Our primary outcome was a composite of death, myocardial infarction or cardiac arrest at 30-days. Multivariable logistic regression was undertaken to assess the impact of HFRS on outcomes after adjusting for age, sex, components of the Charlson Comorbidity Index (CCI), Revised Cardiac Risk Index (RCRI) and peri-operative biomarkers. The final cohort consisted of 712,808 non-cardiac surgeries, of which 55·1% were female and the average age was 53·4 +/- 22·4 years. Using the HFRS, 86.3% were considered low risk, 10·7% were considered intermediate risk and 3·1% were considered high risk for frailty. Intermediate and high HFRS scores were associated with increased risk of the primary outcome with an adjusted odds ratio of 1·61 (95% CI 1·50-1.74) and 1·55 (95% CI 1·38-1·73). Intermediate and high HFRS were also associated with increased adjusted odds of prolonged hospital stay, in-hospital mortality, and 1-year mortality. The HFRS is a minimally onerous frailty assessment tool that can complement perioperative risk stratification in identifying patients at high risk of short- and long-term adverse events.

Frailty and Quality of Life After Cochlear Implantation in Older Adults.

OBJECTIVE: To examine the relationship among frailty index, hearing measures, and hearing-related quality of life (QOL) in older recipients of cochlear implants. STUDY DESIGN: Cross-sectional survey. SETTING: Academic medical center. METHODS: Adults aged ≥65 years at the time of receiving cochlear implants between July 13, 2000, and April 3, 2019, were asked to complete a questionnaire on hearing-related QOL. Chart review was performed to identify patients' characteristics. Correlations were calculated between frailty index and audiologic outcome measures as well as between speech recognition scores and QOL scores. Linear regression models were developed to examine the impact of clinical characteristics, frailty index, and hearing measures on hearing-related QOL. RESULTS: Data for 143 respondents were included. The mean age was 80.7 years (SD, 7.1), with a mean 27.8 years of hearing loss (SD, 17.4) before implantation. The mean frailty index was 11.1 (SD, 10.6), indicating that patients had 1 or 2 of the measured comorbidities on average. No correlation was found between lower frailty index (better health) and hearing scores, including pure tone averages (PTAs) and speech recognition scores. Lower frailty index and larger improvement in PTA after cochlear implantation predicted better QOL scores on univariate analysis (respectively, P = .002, ß = -0.42 [95% CI, -0.68 to -0.16]; P = .008, ß = -0.15 [95% CI, -0.26 to -0.04]) and multivariate analysis (P = .047, ß = -0.28 [95% CI, -0.55 to -0.01]; P = .006, ß = -0.16 [95% CI, -0.28 to -0.05]). No speech recognition scores correlated with QOL after cochlear implantation. CONCLUSIONS: Frailty index does not correlate with hearing scores after cochlear implantation in older adults. Lower frailty index and more improvement in PTA predict better QOL scores after cochlear implantation in older adults.

Life expectancy estimates based on comorbidities and frailty to inform preventive care.

BACKGROUND: Long-term prognostication is important to inform preventive care in older adults. Existing prediction indices incorporate age and comorbidities. Frailty is another important factor in prognostication. In this project, we aimed at developing life expectancy estimates that incorporate both comorbidities and frailty. METHODS: In this retrospective cohort study, we used data from a 5% sample of Medicare beneficiaries with and without history of cancer from Surveillance, Epidemiology, and End Results (SEER) cancer registry areas. We included adults aged 66-95 years who were continuously enrolled in fee-for-service Medicare for ≥1 year from 1998 to 2014. Participants were followed for survival until 12/31/2015, death, or disenrollment. Comorbidity (none, low/medium, high) and frailty categories (low, high) were defined using established methods for claims. We estimated 5- and 10-year survival probabilities and median life expectancies by age, sex, comorbidities, and frailty. RESULTS: The study included 479,646 individuals (4,128,316 person-years), of whom most were women (58.7%). Frailty scores varied widely among participants in the same comorbidity category. In Cox models, both comorbidities and frailty were independent predictors of mortality. Individuals with high comorbidities (HR, 3.24; 95% CI, 3.20-3.28) and low/medium comorbidities (HR, 1.36; 95% CI, 1.34-1.39) had higher risks of death than those with no comorbidities. Compared to low frailty, high frailty was associated with higher risk of death (HR, 1.55; 95% CI, 1.52-1.58). Frailty affected life expectancy estimates in ways relevant to preventive care (i.e., distinguishing <10-year versus >10-year life expectancy) in multiple subgroups. CONCLUSION: Incorporating both comorbidities and frailty may be important in estimating long-term life expectancies of older adults. Our life expectancy tables can aid clinicians' prognostication and inform simulation models and population health management.

The feasibility and reliability of frailty assessment tools applicable in acute in-hospital trauma patients: A systematic review.

BACKGROUND: Assessing frailty in patients with an acute trauma can be challenging. To provide trustworthy results, tools should be feasible and reliable. This systematic review evaluated existing evidence on the feasibility and reliability of frailty assessment tools applied in acute in-hospital trauma patients. METHODS: A systematic search was conducted in relevant databases until February 2020. Studies evaluating the feasibility and/or reliability of a multidimensional frailty assessment tool used to identify frail trauma patients were identified. The feasibility and reliability results and the risk of bias of included studies were assessed. This study was conducted and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and registered in Prospective Register of Systematic Reviews (ID: CRD42020175003). RESULTS: Nineteen studies evaluating 12 frailty assessment tools were included. The risk of bias of the included studies was fair to good. The most frequently evaluated tool was the Clinical Frailty Scale (CFS) (n = 5). All studies evaluated feasibility in terms of the percentage of patients for whom frailty could be assessed; feasibility was high (median, 97%; range, 49-100%). Other feasibility aspects, including time needed for completion, tool availability and costs, availability of instructions, and necessity of training for users, were hardly reported. Reliability was only assessed in three studies, all evaluating the CFS. The interrater reliability varied between 42% and >90% agreement, with a Krippendorff α of 0.27 to 0.41. CONCLUSION: Feasibility of most instruments was generally high. Other aspects were hardly reported. Reliability was only evaluated for the CFS with results varying from poor to good. The reliability of frailty assessment tools for acute trauma patients needs further critical evaluation to conclude whether assessment leads to trustworthy results that are useful in clinical practice. LEVEL OF EVIDENCE: Systematic review, Level II.

Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patients ≥ 80 years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84 years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (p < 0.001). The relationship between the CFS score and mortality was nonlinear (p < 0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2).

Updating and Validating the U.S. Veterans Affairs Frailty Index: Transitioning From ICD-9 to ICD-10.

BACKGROUND: The Veterans Affairs Frailty Index (VA-FI) is an electronic frailty index developed to measure frailty using administrative claims and electronic health records data in Veterans. An update to ICD-10 coding is needed to enable contemporary measurement of frailty. METHOD: International Classification of Diseases, ninth revision (ICD-9) codes from the original VA-FI were mapped to ICD-10 first using the Centers for Medicaid and Medicare Services (CMS) General Equivalence Mappings. The resulting ICD-10 codes were reviewed by 2 geriatricians. Using a national cohort of Veterans aged 65 years and older, the prevalence of deficits contributing to the VA-FI and associations between the VA-FI and mortality over years 2012-2018 were examined. RESULTS: The updated VA-FI-10 includes 6422 codes representing 31 health deficits. Annual cohorts defined on October 1 of each year included 2 266 191 to 2 428 115 Veterans, for which the mean age was 76 years, 97%-98% were male, 78%-79% were White, and the mean VA-FI was 0.20-0.22. The VA-FI-10 deficits showed stability before and after the transition to ICD-10 in 2015, and maintained strong associations with mortality. Patients classified as frail (VA-FI > 0.2) consistently had a hazard of death more than 2 times higher than nonfrail patients (VA-FI ≤ 0.1). Distributions of frailty and associations with mortality varied with and without linkage to CMS data and with different assessment periods for capturing deficits. CONCLUSIONS: The updated VA-FI-10 maintains content validity, stability, and predictive validity for mortality in a contemporary cohort of Veterans aged 65 years and older, and may be applied to ICD-9 and ICD-10 claims data to measure frailty.

Does the Clinical Frailty Scale at Triage Predict Outcomes From Emergency Care for Older People?

STUDY OBJECTIVE: We determine whether the Clinical Frailty Scale applied at emergency department (ED) triage is associated with important service- and patient-related outcomes. METHODS: We undertook a single-center, retrospective cohort study examining hospital-related outcomes and their associations with frailty scores assessed at ED triage. Participants were aged 65 years or older, registered on their first ED presentation during the study period at a single, centralized ED in the United Kingdom. Baseline data included age, sex, Clinical Frailty Scale score, National Early Warning Score-2 and the Charlson Comorbidity Index score; outcomes included length of stay, readmissions (any future admissions), and mortality (inhospital or out of hospital) up to 2 years after ED presentation. Survival analysis methods (standard and competing risks) were applied to assess associations between ED triage frailty scores and outcomes. Unadjusted incidence curves and adjusted hazard ratios are presented. RESULTS: A total of 52,562 individuals representing 138,328 ED attendances were included; participants' mean age was 78.0 years, and 55% were women. Initial admission rates generally increased with frailty. Mean length of stay after 30- or 180-day follow-up was relatively low; all Clinical Frailty Scale categories included patients who experienced zero days' length of stay (ie, ambulatory care) and patients with relatively high numbers of inhospital days. Overall, 46% of study participants were readmitted by the 2-year follow-up. Readmissions increased with Clinical Frailty Scale score up until a score of 6 and then attenuated. Mortality rates increased with increasing frailty; the adjusted hazard ratio was 3.6 for Clinical Frailty Scale score 7 to 8 compared with score 1 to 3. CONCLUSION: Frailty assessed at ED triage (with the Clinical Frailty Scale) is associated with adverse outcomes in older people. Its use in ED triage might aid immediate clinical decisionmaking and service configuration.

The 5-Factor Modified Frailty Index in the Geriatric Surgical Population.

BACKGROUND: The modified frailty index (mFI-11) is a National Surgical Quality Improvement Program (NSQIP)-based 11-factor index that has been proven to adequately reflect frailty and predict mortality and morbidity. In the past years, certain NSQIP variables have been removed from the database; as of 2015, only 5 out of the original 11 factors remain. While the predictive power and usefulness of this 5-factor index (mFI-5) has been proven in previous work, it has yet to be studied in the geriatrics population. The goal of our study was to compare the mFI-5 to the mFI-11 in terms of value and predictive ability for mortality, postoperative infection, and unplanned 30-day readmission for patients aged 65 years and older. METHODS: Spearman's Rho was calculated to compare the value, and unadjusted and adjusted logistic regressions were created for three outcomes in nine surgical subspecialties. Correlation coefficients were above .86 across all surgical specialties except for cardiac surgery. Adjusted and unadjusted models showed similar C-statistics for mFI-5 and 11. RESULTS: Overall predictive values of geriatric mFI-5 and mFI-11 were lower than those for the general population but still had effective predictive value for mortality and post-operative complications (C-Stat ≥ .7) and weak predictive value for 30-day readmission. CONCLUSIONS: The mFI-5 is an equally effective predictor as the mFI-11 in all subspecialties and an effective predictor of mortality and postoperative complication in the geriatric population. This index has credibility for future use to study frailty within NSQIP, within other databases, and for clinical assessment and use.

Clinical Utility of the Risk Analysis Index as a Prospective Frailty Screening Tool within a Multi-practice, Multi-hospital Integrated Healthcare System.

OBJECTIVE: The goal of this project was to first address barriers to implementation of the Risk Analysis Index (RAI) within a large, multi-hospital, integrated healthcare delivery system, and to subsequently demonstrate its utility for identifying at-risk surgical patients. BACKGROUND: Prior studies demonstrate the validity of the RAI for evaluating preoperative frailty, but they have not demonstrated the feasibility of its implementation within routine clinical practice. METHODS: Implementation of the RAI as a frailty screening instrument began as a quality improvement initiative at the University of Pittsburgh Medical Center in July 2016. RAI scores were collected within a REDCap survey instrument integrated into the outpatient electronic health record and then linked to information from additional clinical datasets. NSQIP-eligible procedures were queried within 90 days following the RAI, and the association between RAI and postoperative mortality was evaluated using logistic regression and Cox proportional hazards models. Secondary outcomes such as inpatient length of stay and readmissions were also assessed. RESULTS: RAI assessments were completed on 36,261 unique patients presenting to surgical clinics across five hospitals from July 1 to December 31, 2016, and 8,172 of these underwent NSQIP-eligible surgical procedures. The mean RAI score was 23.6 (SD 11.2), the overall 30-day and 180-day mortality after surgery was 0.7% and 2.6%, respectively, and the median time required to collect the RAI was 33 [IQR 23-53] seconds. Overall clinic compliance with the recommendation for RAI assessment increased from 58% in the first month of the study period to 84% in the sixth and final month. RAI score was significantly associated with risk of death (HR=1.099 [95% C.I.: 1.091 - 1.106], p < 0.001). At an RAI cutoff of ≥37, the positive predictive values for 30- and 90-day readmission were 14.8% and 26.2%, respectively, and negative predictive values were 91.6% and 86.4%, respectively. CONCLUSIONS: The RAI frailty screening tool can be efficiently implemented within multi-specialty, multi-hospital healthcare systems. In the context of our findings and given the value of the RAI in predicting adverse postoperative outcomes, health systems should consider implementing frailty screening within surgical clinics.

Frailty subtypes and recovery in older survivors of acute respiratory failure: a pilot study.

BACKGROUND: Identifying subtypes of acute respiratory failure survivors may facilitate patient selection for post-intensive care unit (ICU) follow-up clinics and trials. METHODS: We conducted a single-centre prospective cohort study of 185 acute respiratory failure survivors, aged ≥ 65 years. We applied latent class modelling to identify frailty subtypes using frailty phenotype and cognitive impairment measurements made during the week before hospital discharge. We used Fine-Gray competing risks survival regression to test associations between frailty subtypes and recovery, defined as returning to a basic Activities of Daily Living disability count less than or equal to the pre-hospitalisation count within 6 months. We characterised subtypes by pre-ICU frailty (Clinical Frailty Scale score ≥ 5), the post-ICU frailty phenotype, and serum inflammatory cytokines, hormones and exosome proteomics during the week before hospital discharge. RESULTS: We identified five frailty subtypes. The recovery rate decreased 49% across each subtype independent of age, sex, pre-existing disability, comorbidity and Acute Physiology and Chronic Health Evaluation II score (recovery rate ratio: 0.51, 95% CI 0.41 to 0.63). Post-ICU frailty phenotype prevalence increased across subtypes, but pre-ICU frailty prevalence did not. In the subtype with the slowest recovery, all had cognitive impairment. The three subtypes with the slowest recovery had higher interleukin-6 levels (p=0.03) and a higher prevalence of ≥ 2 deficiencies in insulin growth factor-1, dehydroepiandrostersone-sulfate, or free-testosterone (p=0.02). Exosome proteomics revealed impaired innate immunity in subtypes with slower recovery. CONCLUSIONS: Frailty subtypes varied by prehospitalisation frailty and cognitive impairment at hospital discharge. Subtypes with the slowest recovery were similarly characterised by greater systemic inflammation and more anabolic hormone deficiencies at hospital discharge.

Beyond the Health Deficit Count: Examining Deficit Patterns in a Deficit-Accumulation Frailty Index.

BACKGROUND/OBJECTIVES: Exploring deficit patterns among frail people may reveal subgroups of different prognostic importance. DESIGN: Analysis of National Health and Aging Trends Study. SETTING: Community. PARTICIPANTS: Community dwelling older adults with mild to moderate frailty (deficit-accumulation frailty index (FI) of 0.25-0.40) (n = 1821). MEASUREMENTS: Latent class analysis identified distinct clinical subgroups based on comorbidity (range: 0-10), National Health and Aging Trends Study dementia classification, and short physical performance battery (SPPB) (range: 0-12). Survival analyses compared 5-year mortality by subgroups. RESULTS: Three latent classes existed: Class 1 (n = 831, mean FI = 0.30) had 2.7% probable dementia, high comorbidities (mean = 3.6), and low physical impairment (SPPB mean = 9.9); Class 2 (n = 734, mean FI = 0.32) had 6.9% probable dementia, low comorbidities (mean = 2.8), and moderate physical impairment (SPPB mean = 6.2); Class 3 (n = 256, mean FI = 0.34) had 20.7% probable dementia, low comorbidities (mean = 2.4), and high physical impairment (SPPB mean = 2.0). Compared to Class 1, Classes 2 and 3 experienced higher 5-year mortality (C2: 1.28 (95% confidence intervals (CI) = 1.00-1.62); C3: 1.87 (95% CI = 1.29-2.73)). CONCLUSION: Deficit patterns among the mild-to-moderately frail provide additional prognostic information and highlight opportunities for preventive interventions.

Variability in Hourly Activity Levels: Statistical Noise or Insight Into Older Adult Frailty?

BACKGROUND: Frailty is associated with lower mean activity; however, hourly activity is highly variable among older individuals. We aimed to relate frailty to hourly activity variance beyond frailty's association with mean activity. METHOD: Using the 2010-2011 National Social Life, Health and Aging Project wrist accelerometry data (n = 647), we employed a mixed-effects location scale model to simultaneously determine whether an adapted phenotypic frailty scale (0-4) was associated with the log10-mean hourly counts per minute (cpm) and between-and within-subject hourly activity variability, adjusting for demographics, health characteristics, season, day-of-week, and time-of-day. We tested the significance of a Frailty × Time-of-day interaction and whether adjusting for sleep time altered relationships. RESULTS: Each additional frailty point was associated with a 7.6% (10-0.0343, ß = -0.0343; 95% CI: -0.05, -0.02) lower mean hourly cpm in the morning, mid-day, and late afternoon but not evening. Each frailty point was also associated with a 24.5% (e0.219, ß = 0.219; 95% CI: 0.09, 0.34) greater between-subject hourly activity variance across the day; a 7% (e0.07, ß = 0.07; 95% CI: 0.01¸ 0.13), 6% (e0.06, ß = 0.06; 95% CI: 0, 0.12), and 10% (e0.091, ß = 0.091; 95% CI: 0.03, 0.15) greater within-subject hourly activity variance in the morning, mid-day, and late afternoon, respectively; and a 6% (e-0.06, ß = -0.06; 95% CI: -0.12, -0.003) lower within-subject hourly activity variance in the evening. Adjusting for sleep time did not alter results. CONCLUSIONS: Frail adults have more variable hourly activity levels than robust adults, a potential novel marker of vulnerability. These findings suggest a need for more precise activity assessment in older adults.

Frailty Changes Predict Mortality in 4 Longitudinal Studies of Aging.

BACKGROUND: Baseline frailty index (FI) values have been shown to predict mortality among older adults, but little is known about the effects of changes in FI on mortality. METHODS: In a coordinated approach, we analyzed data from 4 population-based cohorts: the Health and Retirement Study (HRS), the Survey of Health, Ageing and Retirement in Europe (SHARE), the English Longitudinal Survey of Ageing (ELSA), and the Longitudinal Aging Study Amsterdam (LASA), comprising a total of 24 961 respondents (65+), 95 897 observations, up to 9 repeated FI assessments, and up to 23 years of mortality follow-up. The effect of time-varying FI on mortality was modeled with joint regression models for longitudinal and time-to-event data. RESULTS: Differences (of 0.01) in current FI levels (hazard ratio [HR] = 1.04, 95% credible interval [CI] = 1.03-1.05) and baseline FI levels (HR = 1.03, 95% CI = 1.03-1.05) were consistently associated with mortality across studies. Importantly, individuals with steeper FI growth also had a higher mortality risk: An increase in annual FI growth by 0.01 was associated with an increased mortality risk of HR = 1.56 (95% CI = 1.49-1.63) in HRS, HR = 1.24 (95% CI = 1.13-1.35) in SHARE, HR = 1.40 (95% CI = 1.25-1.52) in ELSA, and HR = 1.71 (95% CI = 1.46-2.01) in LASA. CONCLUSIONS: FI changes predicted mortality independently of baseline FI differences. Repeated assessment of frailty and individual's frailty trajectory could provide a means to anticipate further health deterioration and mortality and could thus support clinical decision making.

5-Item Modified Frailty Index Predicts Outcomes After Below-Knee Amputation in the Vascular Quality Initiative Amputation Registry.

Patient frailty indices are increasingly being utilized to anticipate post-operative complications. This study explores whether a 5-factor modified frailty index (mFI-5) is associated with outcomes following below-knee amputation (BKA). All BKAs in the vascular quality initiative (VQI) amputation registry from 2012-2017 were reviewed. Preoperative frailty status was determined with the mFI-5 which assigns one point each for history of diabetes, chronic obstructive pulmonary disease or active pneumonia, congestive heart failure, hypertension, and nonindependent functional status. Outcomes included 30-day mortality, unplanned return to odds ratio (OR), post-op myocardial infarction (MI), post-op SSI, all-cause complication, revision to higher level amputation, disposition status, and prosthetic use. 2040 BKAs were performed. Logistic regression showed an increasing mFI-5 score that was associated with higher risk of combined complications (OR 1.22, confidence interval [CI] 1.07-1.38, P < .05), 30-day mortality (OR 1.60, CI 1.19-2.16, P < .05), post-op MI (OR 1.79, CI 1.30-2.45, P < .05), and failure of long-term prosthetic use (OR 1.17, CI 1.03-1.32, P < .05). In the VQI, every one-point increase in mFI-5 is associated with an increased risk of 22% for combined complications, 60% for 30-day mortality, nearly 80% for post-op MI, and 17% for failure of prosthetic use in BKA patients. The mFI-5 frailty index should be incorporated into preoperative planning and risk stratification.

Pearls and Pitfalls in the Crashing Geriatric Patient.

The geriatric population is growing and is the largest utilizer of emergency and critical care services; the emergency clinician should be comfortable in the management of the acutely ill geriatric patient. There are important physiologic changes in geriatric patients, which alters their clinical presentation and management. Age alone should not determine the prognosis for elderly patients. Premorbid functional status, frailty, and severity of illness should be considered carefully for the geriatric population. Emergency clinicians should have honest conversations about goals of care based not only a patient's clinical presentation but also the patient's values.

Plasma vascular adhesion protein-1 levels correlate positively with frailty severity in older adults.

Geriatric frailty is associated with increased mortality and links to increased inflammatory activity. Vascular adhesion protein-1 (VAP-1) is important in inflammatory process. This study investigates the relationship between plasma VAP-1 level and frailty in older adults.The cross-sectional study recruited community dwelling older adults from a hospital-based comprehensive geriatric assessment program. The demographic data, Fried Frailty Index, metabolic and inflammatory parameters were assessed.A total of 151 participants (76 women, 50.3%) were included in the analysis, and the age (mean ±â€Š standard deviation) was 77.1 ±â€Š6.1 years. The mean plasma VAP-1 level (ng/mL) was significantly different (P = .029) among different frailty groups (346.3 ±â€Š86.5 in the robust older adults, 371.6 ±â€Š107.9 in the pre-frail older adults, and 416.6 ±â€Š141.1 in the frail older adults). Multivariate ordered logistic regression analysis also demonstrated that plasma VAP-1 levels were positively associated with frailty severity (P = .039). Analysis of the frailty components with plasma VAP-1 levels showed that the elderly who had "exhaustion" (P = .016) or "weakness" (P = .025) tended to have higher plasma VAP-1 levels.The data support that VAP-1 might represent a potential plasma biomarker of frailty.

Clinical Frailty Scale in Predicting Postoperative Outcomes in Older Patients Undergoing Curative Surgery for Urologic Malignancies: A Prospective Observational Cohort Study.

OBJECTIVE: To examine the utility of the Clinical Frailty Scale (CFS) in predicting outcomes in older adults with urologic malignancies undergoing curative surgeries. METHODS: This prospective observational cohort study was conducted in a university-based tertiary medical center. Patients aged 75 years or older who were scheduled to undergo curative surgery for a urologic malignancy from January 2017 to December 2017 were recruited. Patients were grouped according to the CFS scores. The primary postoperative outcome measures were a major complication within 30 days and a decline in the activities of daily living (ADL) within 30 days and 90 days. Multivariable analyses and the area under the receiver operating characteristic curve were performed to investigate the association between the CFS and postoperative outcomes. RESULTS: A total of 82 patients, 50% women, were enrolled with mean age 81.6 years. The CFS was significantly associated with postoperative outcomes in a dose-response relationship. When compared with those with a CFS <5, patients with CFS scores ≥5 had a 10.3-times higher risk for a major complication, 8.5-times and 21.4-times higher risk for a decline in ADL within 30 days and 90 days. The area under the receiver operating characteristic curves for the CFS to predict a major complication, the 30-day decline in ADL and the 90-day decline in ADL were 0.60, 0.73, and 0.79. CONCLUSION: A higher CFS score predicted a higher risk of poor outcomes in this population. It is recommended that patients with higher CFS scores, especially above 5, are needed to receive further multidisciplinary perioperative care.

Prehabilitation of the Thoracic Surgery Patient.

Outcomes after thoracic surgery are better predicted by preoperative evaluation of patients' physiologic reserve (also known as personal biologic age rather than chronologic age), using validated assessment tools in multidisciplinary collaboration with geriatricians. Targetable risk factors should be identified, and methods should be utilized to minimize these risks. Prehabilitation has been validated as a tool to increase functional and nutritional status of patients undergoing surgery in other specialties and improve outcomes. Although research is still limited in thoracic surgery, early results are promising.