The relationship between social deprivation and a frailty index of cumulative deficits in French middle-aged caregivers

Background The Institut Pasteur de Lille, in the north of France, has implemented a large, multidisciplinary health check, which aims to identify frailty in middle-aged caregivers. We aimed to construct an adapted frailty index of cumulative deficit (FI-CD) and study the associated factors, in particular socioeconomic factors. Methods The cross-sectional study included caregivers aged 45 to 65. A 34-item FI-CD including deficits adapted to a middle-aged population (related to cognition and autonomy, dietetics, physical activity, comorbidities, functional signs, lab values and paraclinical examinations) was constructed in accordance with standard procedures. It was calculated as a ratio of deficits present out of the total number of possible deficits, giving a continuous score between 0 and 1. Scores > 0.25 and > 0.4 were classified as frailty and severe frailty, respectively. Univariate and multivariate associations were studied using linear regressions. Results One hundred and seventeen caregivers were included; among them, 111 were analyzed due to missing values. The mean FI-CD was 0.22 ± 0.08. Forty (36%) individuals were classified as frailty and three (2.7%) as severe frailty. In multivariate analysis, FI-CD was significantly associated with age (beta [95% confidence interval] = 0.005 [0.002; 0.009] per 1-year increase, p = 0.005) and social deprivation (beta = 0.054 [0.007; 0.102], p = 0.025). A significant interaction was observed between and age and social deprivation (p = 0.036). The adjusted relationship between FI-CD and age was beta = 0.010 [0.002; 0.019], p = 0.017 in precarious caregivers, and beta = 0.003 [− 0.001; 0.007], p = 0.19 in non-precarious caregivers. Conclusions The study suggested that the 34-item FI-CD could have clinical utility in the management of middle-aged caregivers. Social deprivation appeared as an important factor associated with frailty, highlighting the importance of early care and social support for precarious caregivers.

The Measurements of Frailty and Their Possible Application to Spinal Conditions. A Systematic Review

Background: Frailty is associated with an increased risk of postoperative adverse events (AEs) within the surgical spine population. Multiple frailty tools have been reported in the surgical spine literature. However, the applicability of these tools remains unclear. The primary objective of this systematic review is to appraise the construct, feasibility, objectivity, and clinimetric properties of frailty tools reported in the surgical spine literature. Secondary objectives included determining the applicability and the most sensitive surgical spine population for each tool. Methods: This systematic review was registered with PROSPERO: CRD42019109045. Publications from January 1950 to December 2020 were identified by a comprehensive search of PubMed, Ovid, Embase, and Cochrane, supplemented by manual screening. Studies reporting and validating a frailty tool in the surgical spine population with a measurable outcome were included. Each tool and its respective clinimetric properties were evaluated using validated criteria and definitions. The applicability of each tool and its most sensitive surgical spine population was determined by panel consensus. Bias was assessed using the Newcastle-Ottawa Scale.Results: 47 studies were included in the final qualitative analysis. A total of 14 separate frailty tools were identified, in which nine tools assessed frailty according to the cumulative deficit definition, while four instruments utilized phenotypic or weighted frailty models. One instrument assessed frailty according to the comprehensive geriatric assessment (CGA) model. Twelve measures were validated as risk stratification tools for predicting postoperative AEs, while one tool investigated the effect of spine surgery on postoperative frailty trajectory. The modified frailty index (mFI), 5-item mFI, adult spinal deformity frailty index (ASD-FI), FRAIL Scale, and CGA had the most positive ratings for clinimetric properties assessed. Conclusions: The assessment of frailty is important in the surgical decision-making process. Cumulative deficit and weighted frailty instruments are appropriate risk stratification tools. Phenotypic tools are sensitive for capturing the relationship between spinal pathology, spine surgery, and prehabilitation on frailty trajectory. CGA instruments are appropriate screening tools for identifying health deficits susceptible to improvement and guiding optimization strategies. Studies are needed to determine whether spine surgery and prehabilitation are effective interventions to reverse frailty.

Trajectories of frailty in aging: Prospective cohort study

Background Emerging evidence suggests that there is significant variability in the progression of frailty in aging. We aimed to identify latent subpopulations of frailty trajectories, and examine their clinical and biological correlates. Methods We characterized frailty using a 41-item cumulative deficit score at baseline and annual visits up to 12 years in 681 older adults (55% women, mean age 74·6 years). Clinical risk profile and walking while talking performance as a clinical marker of trajectories were examined. Mortality risk associated with trajectories was evaluated using Cox regression adjusted for established survival predictors, and reported as hazard ratios (HR). Proteome-wide analysis was done. Findings Latent class modeling identified 4 distinct frailty trajectories: relatively stable (34·4%) as well as mild (36·1%), moderate (24·1%) and severely frail (5·4%). Four distinct classes of frailty trajectories were also shown in an independent sample of 515 older adults (60% women, 68% White, 26% Black). The stable group took a median of 31 months to accumulate one additional deficit compared to 20 months in the severely frail group. The worst trajectories were associated with modifiable risk factors such as low education, living alone, obesity, and physical inactivity as well as slower walking while talking speed. In the pooled sample, mild (HR 2·33, 95% CI 1·30–4·18), moderate (HR 2·49, 95% CI 1·33–4·66), and severely frail trajectories (HR 5·28, 95% CI 2·68–10·41) had higher mortality compared to the stable group. Proteomic analysis showed 11 proteins in lipid metabolism and growth factor pathways associated with frailty trajectories. Conclusion Frailty shows both stable and accelerated patterns in aging, which can be distinguished clinically and biologically.

Development and Validation of a Clinical Frailty Index for the World Trade Center General Responder Cohort

Objectives: To develop and validate a clinical frailty index to characterize aging among responders to the 9/11 World Trade Center (WTC) attacks. Methods: This study was conducted on health monitoring data on a sample of 6197 responders. A clinical frailty index, WTC FI-Clinical, was developed according to the cumulative deficit model of frailty. The validity of the resulting index was assessed using all-cause mortality as an endpoint. Its association with various cohort characteristics was evaluated. Results: The sample’s median age was 51 years. Thirty items were selected for inclusion in the index. It showed a strong correlation with age, as well as significant adjusted associations with mortality, 9/11 exposure severity, sex, race, pre-9/11 occupation, education, and smoking status. Discussion: The WTC FI-Clinical highlights effects of certain risk factors on aging within the 9/11 responder cohort. It will serve as a useful instrument for monitoring and tracking frailty within this cohort.

83 A Deficit Accumulation Frailty Index Predicts Mortality in Older South Africans: Findings from the HAALSI Study

Introduction Few studies have investigated frailty in older people in sub-Saharan Africa, yet such information is vital to prepare responses to rapid population ageing. We aimed to derive and test a cumulative deficit frailty index in a population of older people from rural South Africa. Methods We analysed data from the Health and Ageing in Africa: Longitudinal Studies of an INDEPTH Community (HAALSI) study, which enrolled participants aged 40 years and older nested within the Agincourt Health and Demographic Survey Site, South Africa. We created a 32-variable cumulative deficit frailty index using questionnaire (illnesses, symptoms and activities of daily living), physical performance and physiological indices, and blood test results. Each variable was dichotomised to 1 (deficit) or 0 (no deficit). The frailty index for each individual was calculated as the mean of all frailty variables. Frailty categories were defined using cut-offs from the UK electronic frailty index: 0-0.12 (non-frail), >0.12-0.24 (mild frailty), >0.24-0.36 (moderate frailty) and >0.36 (severe frailty). Cox proportional hazards models, both unadjusted and adjusted for age and sex, were fitted to test the association between frailty status and all-cause mortality. Results We analysed data from 3989 participants, mean age 61 years (SD 13); 2175 (54.5%) were female. The mean follow-up period was 17 months; 1464 (36.7%) were non-frail, 2059 (51.6%) had mild frailty, 402 (10.1%) had moderate frailty and 64 (1.6%) had severe frailty. A total of 135 (3.4%) died. Adjusted Cox models showed worse frailty category was associated with higher risk of death compared with non-frail individuals: hazard ratios 1.94 (95% CI 1.23, 3.07) for mild frailty, 3.25 (95% CI 1.86, 5.68) for moderate frailty, and 5.50 (95% CI 2.44, 12.40) for severe frailty. Conclusions Frailty measured by a cumulative deficits index is common and predicts mortality in a rural population of older South Africans.

Using elastic nets to estimate frailty burden from routinely collected national aged care data

Objectives To (1) use an elastic net (EN) algorithm to derive a frailty measure from a national aged care eligibility assessment program; (2) compare the ability of EN-based and a traditional cumulative deficit (CD) based frailty measures to predict mortality and entry into permanent residential care; (3) assess if the predictive ability can be improved by using weighted frailty measures. Materials and Methods A Cox proportional hazard model based EN algorithm was applied to the 2003–2013 cohort of 903 996 participants for selecting items to enter an EN based frailty measure. The out-of-sample predictive accuracy was measured by the area under the curve (AUC) from Cox models fitted to 80% training and validated on 20% testing samples. Results The EN approach resulted in a 178-item frailty measure including items excluded from the 44-item CD-based measure. The EN based measure was not statistically significantly different from the CD-based approach in terms of predicting mortality (AUC 0.641, 95% CI: 0.637–0.644 vs AUC 0.637, 95% CI: 0.634–0.641) and permanent care entry (AUC 0.626, 95% CI: 0.624–0.629 vs AUC 0.627, 95% CI: 0.625–0.63). However, the weighted EN based measure statistically outperforms the weighted CD measure for predicting mortality (AUC 0.774, 95% CI: 0.771–0.777 vs AUC 0.757, 95% CI: 0.754–0.760) and permanent care entry (AUC 0.676, 95% CI: 0.673–0.678 vs AUC 0.671, 95% CI: 0.668–0.674). Conclusions The weighted EN and CD-based measures demonstrated similar prediction performance. The CD-based measure items are relevant to frailty measurement and easier to interpret. We recommend using the weighted and unweighted CD-based frailty measures.

Frailty to predict unplanned hospitalization, stroke, bleeding, and death in atrial fibrillation

Aims Atrial fibrillation (AF) and frailty are common, and the prevalence is expected to rise further. We aimed to investigate the prevalence of frailty and the ability of a frailty index (FI) to predict unplanned hospitalizations, stroke, bleeding, and death in patients with AF. Methods and results Patients with known AF were enrolled in a prospective cohort study in Switzerland. Information on medical history, lifestyle factors, and clinical measurements were obtained. The primary outcome was unplanned hospitalization; secondary outcomes were all-cause mortality, bleeding, and stroke. The FI was measured using a cumulative deficit approach, constructed according to previously published criteria and divided into three groups (non-frail, pre-frail, and frail). The association between frailty and outcomes was assessed using multivariable-adjusted Cox regression models. Of the 2369 included patients, prevalence of pre-frailty and frailty was 60.7% and 10.6%, respectively. Pre-frailty and frailty were associated with a higher risk of unplanned hospitalizations [adjusted hazard ratio (aHR) 1.82, 95% confidence interval (CI) 1.49–2.22; P < 0.001; and aHR 3.59, 95% CI 2.78–4.63, P < 0.001], all-cause mortality (aHR 5.07, 95% CI 2.43–10.59; P < 0.001; and aHR 16.72, 95% CI 7.75–36.05; P < 0.001), and bleeding (aHR 1.53, 95% CI 1.11–2.13; P = 0.01; and aHR 2.46, 95% CI 1.61–3.77; P < 0.001). Frailty, but not pre-frailty, was associated with a higher risk of stroke (aHR 3.29, 95% CI 1.2–8.39; P = 0.01). Conclusion Over two-thirds of patients with AF are pre-frail or frail. These patients have a high risk for unplanned hospitalizations and other adverse events. These findings emphasize the need to carefully evaluate these patients. However, whether screening for pre-frailty and frailty and targeted prevention strategies improve outcomes needs to be shown in future studies. Clinical trial registration Clinicaltrials.gov identifier number: NCT02105844.

Mapping the river drought-indices in west Sumatra

The smallest magnitudes from a series of daily average-streamflows every month are selected to form a new series of data called a series of monthly minima from daily averagestreamflows or then just simply called the monthly minimum-streamflows. The present study uses these monthly minimum-streamflows to determine a drought index in terms of duration and deficit streamflows of successive drought in every watershed in West Sumatra Province. Both terms of drought index are determined by using the theory of runs with a 5-year average-period. So far, we successfully collect series of the daily average-streamflows for 19 watersheds with a minimum length of 20 years. The resulting indices are then mapped using the geographical information system ArcGIS. The drought indices are expressed in 4 levels of drought: normal (green), mild (blue), moderate (yellow) and severe (red). The study results show that the river or watershed with the longest droughtduration is Batang Anai, i.e. 33 months (severe level), with a cumulative deficit-streamflows of 143.26 m3/s. The river with the shortest drought-duration is Batang Siat, i.e. 11 months (mild level), with a cumulative deficit-streamflows of 44.64 m3/s. The average drought-duration for all corresponding rivers is 20 months (mild level) with a cumulative deficit-streamflows of 131.57 m3/s.

P3782Frailty to predict unplanned hospitalizations, stroke, bleeding and death in atrial fibrillation

Aim We investigated the prevalence of frailty, and the relationships between frailty and the risk of adverse clinical outcomes in patients with atrial fibrillation (AF). Methods Patients with known AF were enrolled in a nation-wide observational cohort study in Switzerland. Information on medical history, medication, lifestyle factors and clinical measurements were obtained. The primary outcome was unplanned hospitalizations, secondary outcomes were all-cause mortality, bleeding and stroke. The frailty index (FI) was measured using a cumulative deficit approach according to previously published criteria. Participants were divided into three groups (non-frail, pre-frail and frail) according to their FI at study entry. The association between frailty and clinical outcomes was assessed using multivariable adjusted Cox proportional hazard models. Results We included 2369 patients with a mean age of 73±8 years (27.3% female). The prevalence of frailty and pre-frailty was 10.6% and 60.7%, respectively. Frailty was associated with unplanned hospitalization (adjusted hazard ratio [HR] 3.59; 95% confidence interval [95% CI], 2.78–4.63; p<0.001), all-cause mortality (adjusted HR 16.72; 95% CI 7.75–36.05; p<0.001), bleeding (adjusted HR 2.46; 95% CI 1.61–3.77; p<0.001), and stroke (adjusted HR 3.29; 95% CI 1.29–8.39; p=0.01) (Figure). Similarly, pre-frailty was significantly associated with unplanned hospitalization (adjusted HR 1.82; 95% CI 1.49–2.22; p<0.001), all-cause mortality (adjusted HR 5.07; 95% CI 2.43–10.59; p<0.001) and bleeding (adjusted HR 1.53; 95% CI 1.11–2.13; p=0.01), but not with stroke. Cumulative incidence of adverse events Conclusion In our cohort, more than two thirds of AF patients were either pre-frail or frail. These patients have a high risk of unplanned hospitalizations and other adverse outcomes, indicating that frailty is a powerful tool to predict adverse clinical outcomes in AF patients. Acknowledgement/Funding Swiss National Science Foundation; Foundation for Cardiovascular Research Basel; University of Basel

EU fiscal governance and budget consolidation in Visegrád countries

Budget consolidations in Visegrád countries, which followed European financial and debt crisis, were mainly driven by external factors such as EU fiscal governance. Since the Visegrád countries have accomplished their consolidation effort, it seems topical to study their experience and assess the efficiency of consolidation measures. Involving descriptive statistical analysis, the authors posit that supranational impact on national budgets of Visegrád countries was quite efficient, as all economies concerned have accomplished a relatively sizeable fiscal consolidation. This happened largely due to the fact that the governments did not intend to lose vast amounts of funds from the EU budget. Such an option was quite feasible as a part of possible sanctions related to excessive deficit. The Czech Republic, Hungary, Poland and the Slovak Republic run different consolidations as to scale, structure and measures taken, though one could highlight some similarities. On the one hand, consolidations were to a great extent carried out through the means of indirect taxation, because they have a less distortive nature, given the structural characteristics of countries at issue. On the other hand, the governments refrained from raising direct taxes due to their distortive character. Hungary was the only country, which took some active measures in the field of corporate taxation, and subsequently suffered from drop in tax collection. The Visegrád countries did cut government expenditures, but strived to use the most effective instruments such as curbing employment in public sector. Further, there were some subsidiary factors at place that influenced consolidation pace. For example, three of four Visegrád countries are not members of a currency union, which inter alia contributed to monetizing government debt. At the same time, some measures taken by the countries, were of a quite formal nature. For instance, Hungary totally nationalized pension system in order to increase budget revenues. Nevertheless, all Visegrád countries reached deficit target without any revolutionary changes to main fiscal aggregates, which means that consolidations were at least nominally effective. However, cumulative deficit change was not fully accompanied by lowering debt and was by several times less than cumulative transfers from the EU budget. At the same time the budget consolidations in Visegrád countries could be called efficient as GDP growth rates restored, as did investors’ confidence and exports.