A frailty paradigm would be useful in primary care to identify older people at risk, but appropriate metrics at that level are lacking. We created and validated a simple instrument for frailty screening in Europeans aged ≥50. Our study is based on the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE, http://www.share-project.org), a large population-based survey conducted in 2004-2005 in twelve European countries.

Background: Recommendations for routine frailty screening in general practice are increasing as frailty prevalence grows. In England, frailty identification became a contractual requirement in 2017. However, there is little guidance on the most effective and practical interventions once frailty has been identified.Aim: To assess the comparative effectiveness and ease of implementation of frailty interventions in primary care.Design and setting: A systematic review of frailty interventions in primary care.Method: Scientific databases were searched from inception to May 2017 for randomised controlled trials or cohort studies with control groups on primary care frailty interventions. Screening methods, interventions, and outcomes were analysed in included studies. Effectiveness was scored in terms of change of frailty status or frailty indicators and ease of implementation in terms of human resources, marginal costs, and time requirements.Results: A total of 925 studies satisfied search criteria and 46 were included. There were 15 690 participants (median study size was 160 participants). Studies reflected a broad heterogeneity. There were 17 different frailty screening methods. Of the frailty interventions, 23 involved physical activity and other interventions involved health education, nutrition supplementation, home visits, hormone supplementation, and counselling. A significant improvement of frailty status was demonstrated in 71% (n= 10) of studies and of frailty indicators in 69% (n=22) of studies where measured. Interventions with both muscle strength training and protein supplementation were consistently placed highest for effectiveness and ease of implementation.Conclusion: A combination of muscle strength training and protein supplementation was the most effective intervention to delay or reverse frailty and the easiest to implement in primary care. A map of interventions was created that can be used to inform choices for managing frailty.

Background: the clinical frailty scale (CFS) was validated as a predictor of adverse outcomes in community-dwelling older people. In our hospital, the use of the CFS in emergency admissions of people aged ≥ 75 years was introduced under the Commissioning for Quality and Innovation payment framework. Aim: we retrospectively studied the association of the CFS with patient characteristics and outcomes. Design: retrospective observational study in a large tertiary university National Health Service hospital in UK. Methods: the CFS was correlated with transfer to specialist Geriatric ward, length of stay (LOS), in-patient mortality and 30-day readmission rate. Results: between 1st August 2013 and 31st July 2014, there were 11 271 emergency admission episodes of people aged ≥ 75 years (all specialties), corresponding to 7532 unique patients (first admissions); of those, 5764 had the CFS measured by the admitting team (81% of them within 72 hr of admission). After adjustment for age, gender, Charlson comorbidity index and history of dementia and/or current cognitive concern, the CFS was an independent predictor of in-patient mortality [odds ratio (OR) = 1.60, 95% confidence interval (CI): 1.48 to 1.74, P < 0.001], transfer to Geriatric ward (OR = 1.33, 95% CI: 1.24 to 1.42, P < 0.001) and LOS ≥ 10 days (OR = 1.19, 95% CI: 1.14 to 1.23, P < 0.001). The CFS was not a multivariate predictor of 30-day readmission. Conclusions: the CFS may help predict in-patient mortality and target specialist geriatric resources within the hospital. Usual hospital metrics such as mortality and LOS should take into account measurable patient complexity.

Falls are a major problem in older adults worldwide with an estimated 30% of elderly adults over 65 years of age falling each year. The direct and indirect societal costs associated with falls are enormous. A system that could provide an accurate automated assessment of falls risk prior to falling would allow timely intervention and ease the burden on overstretched healthcare systems worldwide. An objective method for assessing falls risk using body-worn kinematic sensors is reported. The gait and balance of 349 community-dwelling elderly adults was assessed using body-worn sensors while each patient performed the “timed up and go” (TUG) test. Patients were also evaluated using the Berg balance scale (BBS). Of the 44 reported parameters derived from body-worn kinematic sensors, 29 provided significant discrimination between patients with a history of falls and those without. Cross-validated estimates of retrospective falls prediction performance using logistic regression models yielded a mean sensitivity of 77.3% and a mean specificity of 75.9%. This compares favorably to the cross-validated performance of logistic regression models based on the time taken to complete the TUG test (manually timed TUG) and the Berg balance score. These models yielded mean sensitivities of 58.0% and 57.8%, respectively, and mean specificities of 64.8% and 64.2%, respectively. Results suggest that this method offers an improvement over two standard falls risk assessments (TUG and BBS) and may have potential for use in supervised assessment of falls risk as part of a longitudinal monitoring protocol.

Background: the frailty index (FI) is an approach to the operationalisation of frailty based on accumulation of deficits. It has been less studied in Europeans. Objective: to construct sex-specific FIs from a large sample of Europeans and study their associations with age and mortality. Design: longitudinal population-based survey. Setting: the Survey of Health, Ageing and Retirement in Europe (SHARE, http://share-dev.mpisoc.mpg.de/). Subjects: a total of 16,217 females and 13,688 males aged ≥50 from wave 1 (2004–05). Mortality data were collected between 2005 and 2006 (mean follow-up: 2.4 years). Methods: regression curve estimations between age and an FI constructed as per the standard procedure. Logistic regressions were used to assess the relative effects of age and the FI towards mortality. Results: in both sexes, there was a significant non-linear association between age and the FI (females: quadratic R² = 0.20, P < 0.001; males: quadratic R² = 0.14, P < 0.001). Overall, the FI was a much stronger predictor of mortality than age, even after adjusting for the latter (females: age-adjusted OR 100.5, 95% confidence interval (CI): 46.3–218.2, P < 0.001; males: age-adjusted OR 221.1, 95% CI: 106.7–458.4, P < 0.001). Conclusion: the FI had the expected properties in this large sample of Europeans.