Roppolo et al., 2015 (30) | Italy | Quantitative design: cross-sectional study | 267 community-dwelling elderly people | The Cardiovascular Health Study index and the Tilburg Frailty Indicator | Different instruments capture different frail individuals. |
Malmstrom et al., 2015 (31) | USA | Quantitative design: longitudinal cohort study | 998 Afro-Americans, 49 to 65 years old | How well the International Academy of Nutrition and Aging (FRAIL) frailty scale predicts future disability compared to the Study of Osteoporotic Fractures (SOF) frailty scale, the phenotype-based Cardiovascular Health Study (CHS) frailty scale, and the comprehensive Frailty Index (FI) | Combined use of instruments proves to be the best for predicting disability and mortality. |
Romero-Ortuno et al., 2010 (26) | Ireland | Quantitative design: cross-sectional survey | 17.304 women and 13.811 men over 50 included in the Survey of Health, Aging and Retirement in Europe (SHARE) | The authors created and validated a simple frailty screening instrument. | The SHARE Frailty Instrument has sufficient construct and predictive validity. |
Romero-Ortuno and Soraghan, 2014 (27) | Ireland | Quantitative design: longitudinal population- based study | 4.001 women and 3.057 men 75 or older from the Survey of Health, Aging and Retirement in Europe (SHARE) | The mortality prediction of the SHARE-FI75+ was compared with that of previous frailty scales in SHARE (SHARE-FI, 70-item index, phenotype, FRAIL). | The SHARE-FI75+ could help identify frailty in primary care. |
Jotheeswaran et al., 2016 (32) | India | Quantitative design: cross-sectional survey, group-based observational study, measurement instrument validation | 150 frail and/or care- dependent elderly people in the primary care setting | Three primary care physicians administered EASY-Care comprehensive geriatric assessment. | Robust measurement properties. |
Uchmanowicz et al., 2014 (33) | Poland | Quantitative design: cross-sectional survey, measurement instrument validation | 100 Polish patients 42 men and 58 women | The aim was to adopt and test the validity of the Polish version of the TFI | The TFI is a valid and reproducible instrument for assessing frailty among the Polish population. |
van Kempen et al., 2013 (34) | Netherlands | Quantitative design: observational pilot study, cross-sectional survey | seven academic GP practices in and around Nijmegen, the Netherlands; a total of 151 patients were included | The aim was to describe the development of the Easycare-TOS. | The instrument meets the efficiency, flexibility, and acceptability requirements for use in primary care. |
Morris et al., 2016 (28) | US | Quantitative design: cross-sectional survey, measurement instrument development, and evaluation | 464.788 people served by home care agencies | The aim was to present the development and evaluation of the interRAI HC Frailty Scale. | The instrument is based on a strong conceptual foundation. |
van Kempen, et al., 2015 (23) | Netherlands | Quantitative design: cross-sectional, explorative observational study | six family practices and one geriatric department; 587 patients 70 or older registered in these practices | The aim was to compare the frailty assessments provided by family physicians and geriatricians. | Geriatricians assess patients as frail more often than family physicians. |
Morley et al., 2013 (22) | US | Qualitative design: the Delphi method | delegates of six major international, European, and US societies, and seven other frailty specialists | The aim was to reach consensus on frailty. | A report was produced based on the consensus. |
Castell et al., 2013 (35) | Spain | Quantitative design: cross-sectional study | 1.327 people older than 65 | The aim was to estimate frailty based on the walking speed of the elderly urban population and apply the findings to primary care. | Detection of a walking speed below 0.8 m/s is a simple approach to diagnosing frailty in primary care. |
Eyigor et al., 2015 (36) | US | Quantitative design: cross-sectional multicentre study | 1.126 people over 65 from 13 centres | The Fried frailty criteria, the Mini Nutritional Assessment, the Centre for Epidemiological Studies Depression (CES-D) scale, the Charlson Comorbidity Index | Age, female gender, low education level, being a housewife, living with the family, being sedentary, presence of an additional disease, using four or more drugs/day, avoiding going outside, at least one visit to any emergency department within the past year, hospitalization within the past year, non-functional ambulation, and malnutrition increase the risk of frailty. |
Drubbel et al., 2013 (37) | Netherlands | Quantitative design: cross-sectional observational study | 1.580 patients 60 or older from a Dutch primary care centre | Whether a Frailty Index (FI), based on ICPC- coded primary care data, and the Groningen Frailty Indicator (GFI) questionnaire identify the same older people as frail. | The FI and the GFI moderately overlap in identifying frailty. Authors suggest an initial FI screening in routine healthcare data, followed by a GFI questionnaire for patients at high risk as the preferred two-step frailty screening process in primary care. |
Silva et al., 2016 (38) | Brazil | Quantitative design: cross-sectional observational study | 345 elderly people | Self-perceived health, anamnesis, Lawton and Brody’s Scale, Katz Index, Geriatric Depression Scale, Timed Up and Go Test, and Study of Osteoporotic Fracture Index | Risk of falls, frailty, functional performance on the Instrumental Activities of Daily Living, insomnia, and familial support are related to self-perceived health. |
Bertoli et al., 2017 (39) | Italy | Quantitative design: cross-sectional observational study | 112 elderly subjects: 62 were hospitalised following hip fracture and 50 control subjects were outpatients | Thyroid stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) were measured to evaluate the prevalence of thyroid hormone modifications in elderly frail subjects and its relationship with frailty. | Measuring FT3 can be a useful laboratory parameter. |
Theou et al., 2015 (40) | Ireland | Quantitative design: longitudinal study | 4.961 elderly Irish residents | Whether frailty assessment differs when constructing frailty indices using solely self- reported or test-based health measures. | Self-reported and test-based measures should be combined when trying to identify levels of frailty. |
van Kempen et al., 2015 (24) | Netherlands | Quantitative design: longitudinal primary care registry-based cohort study | 4.961 elderly Irish residents a 587 patients of four GP practices in the Netherlands | The aim was to determine the predictive value of EASY-Care TOS for negative health outcomes within the year from assessment. | GPs can predict negative health outcomes in their older populations efficiently and almost as accurately as specialists in this area. |
Bruyère et al., 2017 (25) | Belgium, EU survey | Quantitative design: international online cross-sectional survey | 388 clinicians from 44 countries, mostly doctors (93%), with geriatrics as their primary field of practice (83%). | How practitioners measure the geriatric syndrome of frailty in their daily routine. | 52.8% always assess frailty in their daily practice and 64.9% of them diagnose frailty using more than one instrument. |
Metzelthin et al., 2010 (41) | Netherlands | Quantitative design: cross-sectional survey | 687 community-dwelling elderly people 70 or older. | The Groningen Frailty Indicator (GFI), the Tilburg Frailty Indicator (TFI), the Sherbrooke Postal Questionnaire (SPQ), and the Groningen Activity Restriction Scale (GARS) | The GFI and the TFI showed high internal consistency and construct validity in contrast to the SPQ. It is not yet possible to conclude whether the GFI or the TFI should be preferred. The SPQ seems less appropriate for postal screening of frailty. |
Lee et al., 2017 (42) | Canada | Quantitative design: retrospective chart review | Complete frailty screening data were available for 383 patients75 and older. | The aim was to examine the accuracy of individual Fried frailty phenotype measures in identifying the Fried frailty phenotype in primary care. | The use of gait speed or grip strength alone was found to be sensitive and specific as a proxy for the Fried frailty phenotype, but the use of both measures together was found to be accurate, precise, specific, and more sensitive than other possible combinations. Assessing both measures is feasible within primary care. |
Campitelli et al., 2016 (29) | Canada | Quantitative design: retrospective cohort study | resident Assessment Instrument (RAI) data for all long-stay home care clients (66 or older) in Ontario, Canada (n=234.552) | The aim was to examine two versions of a frailty index (a full and a modified FI), and the CHESS scale, and compare their baseline characteristics and their predictive accuracy. | The different approaches to detecting vulnerability resulted in different estimates of frailty prevalence. The gains in predictive accuracy were often modest with the exception of the full FI. |
Vergara et al., 2016 (43) | Spain | Quantitative design: prospective multicentre cohort study | 900 individuals 70 or older | The Tilburg Frailty Indicator (TFI), the Gérontopôle Frailty Screening Tool (GFST), and the KoS model together with two biomarker levels (SOX2 and p16INK4a) for adverse events related to frailty. | Great potential for direct application in primary care. |