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Background: The prevalence of frailty increases with age in older adults, but frailty is largely unreported for younger adults, where its associated risk is less clear. Furthermore, less is known about how frailty changes over time among younger adults. We estimated the prevalence and outcomes of frailty, in relation to accumulation of deficits, across the adult lifespan., Methods: We analyzed data for community-dwelling respondents (age 15-102 years at baseline) to the longitudinal component of the National Population Health Survey, with seven two-year cycles, beginning 1994-1995. The outcomes were death, use of health services and change in health status, measured in terms of a Frailty Index constructed from 42 self-reported health variables., Results: The sample consisted of 14,713 respondents (54.2% women). Vital status was known for more than 99% of the respondents. The prevalence of frailty increased with age, from 2.0% (95% confidence interval [CI] 1.7%-2.4%) among those younger than 30 years to 22.4% (95% CI 19.0%-25.8%) for those older than age 65, including 43.7% (95% CI 37.1%-50.8%) for those 85 and older. At all ages, the 160-month mortality rate was lower among relatively fit people than among those who were frail (e.g., 2% v. 16% at age 40; 42% v. 83% at age 75 or older). These relatively fit people tended to remain relatively fit over time. Relative to all other groups, a greater proportion of the most frail people used health services at baseline (28.3%, 95% CI 21.5%-35.5%) and at each follow-up cycle (26.7%, 95% CI 15.4%-28.0%)., Interpretation: Deficits accumulated with age across the adult spectrum. At all ages, a higher Frailty Index was associated with higher mortality and greater use of health care services. At younger ages, recovery to the relatively fittest state was common, but the chance of complete recovery declined with age.

Background: Frailty in individuals can be operationalized as the accumulation of health deficits, for which several trends have been observed in Western countries. Less is known about deficit accumulation in China, the country with the world's largest number of older adults., Methods: This study analyzed data from the Beijing Longitudinal Study of Aging, to evaluate the relationship between age and deficit accumulation in men and women and to evaluate the impact of frailty on mortality. Community dwelling people aged 55+ years at baseline (n = 3275) were followed every two to three years between 1992 and 2000, during which time 36% died. A Frailty Index was constructed using 35 deficits, drawn from a range of health problems, including symptoms, disabilities, disease, and psychological difficulties., Results: Most deficits increased the eight-year risk of death and were more lethal in men than in women, although women had a higher mean level of frailty (Frailty Index = 0.11 ± 0.10 for men, 0.14 ± 0.12 for women). The Frailty Index increased exponentially with age, with a similar rate in men and women (0.038 vs. 0.039; r > 0.949, P < 0.01). A dose-response relationship was observed as frailty increased., Conclusions: A Frailty Index employed in a Chinese sample, showed properties comparable with Western data, but deficit accumulation appeared to be more lethal than in the West.

As nonreplicative cells age, they commonly accumulate subcellular deficits that can compromise function. As people age, they too experience problems that can accumulate. As deficits (symptoms, signs, illnesses, disabilities) accumulate, people become more susceptible to adverse health outcomes, including worse health and even death. This state of increased risk of adverse health outcomes is indistinguishable from the idea of frailty, so deficit accumulation represents another way to define frailty. Counting deficits not only allows grades of frailty to be discerned but also provides insights into the complex problems of older adults. This process is potentially useful to geriatricians who need to be experts in managing complexity. A key to managing complexity is through instruments such as a comprehensive geriatric assessment, which can serve as the basis for routine clinical estimation of an individual's degree of frailty. Understanding people and their needs as deficits accumulate is an exciting challenge for clinical research on frailty and its management by geriatricians., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Background: There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use., Methods: We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools., Results: The CSHA Clinical Frailty Scale was highly correlated (r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%-30.6%) and entry into an institution (23.9%, 95% CI 8.8%-41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality)., Interpretation: Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.

Models of human mortality include a factor that summarises intrinsic differences in individual rates of ageing, commonly called frailty. Frailty also describes a clinical syndrome of apparent vulnerability. In a representative, cross-sectional, Canadian survey (n = 66,589) we calculated a frailty index as the mean accumulation of deficits and previously showed it to increase exponentially with age. Here, its density function exhibited a monotonic change in shape, being least skewed at the oldest ages. Although the shape gradually changed, the frailty index was well fitted by a gamma distribution. Of note, the variation coefficient, initially high, decreased from middle age on. Being able to quantify frailty means that health risks can be summarised at both the individual and group levels.

Several machine learning techniques (multilayer and single layer perceptron, logistic regression, least square linear separation and support vector machines) are applied to calculate the risk of death from two biomedical data sets, one from patient care records, and another from a population survey. Each dataset contained multiple sources of information: history of related symptoms and other illnesses, physical examination findings, laboratory tests, medications (patient records dataset), health attitudes, and disabilities in activities of daily living (survey dataset). Each technique showed very good mortality prediction in the acute patients data sample (AUC up to 0.89) and fair prediction accuracy for six year mortality (AUC from 0.70 to 0.76) in individuals from epidemiological database surveys. The results suggest that the nature of data is of primary importance rather than the learning technique. However, the consistently superior performance of the artificial neural network (multi-layer perceptron) indicates that nonlinear relationships (which cannot be discerned by linear separation techniques) can provide additional improvement in correctly predicting health outcomes.

This paper develops a method for appraising health status in elderly people. A frailty index was defined as the proportion of accumulated deficits (symptoms, signs, functional impairments, and laboratory abnormalities). It serves as an individual state variable, reflecting severity of illness and proximity to death. In a representative database of elderly Canadians we found that deficits accumulated at 3% per year, and show a gamma distribution, typical for systems with redundant components that can be used in case of failure of a given subsystem. Of note, the slope of the index is insensitive to the individual nature of the deficits, and serves as an important prognostic factor for life expectancy. The formula for estimating an individual's life span given the frailty index value is presented. For different patterns of cognitive impairments the average within-group index value increases with the severity of the cognitive impairment, and the relative variability of the index is significantly reduced. Finally, the statistical distribution of the frailty index sharply differs between well groups (gamma distribution) and morbid groups (normal distribution). This pattern reflects an increase in uncompensated deficits in impaired organisms, which would lead to illness of various etiologies, and ultimately to increased mortality. The accumulation of deficits is as an example of a macroscopic variable, i.e., one that reflects general properties of aging at the level of the whole organism rather than any given functional deficiency. In consequence, we propose that it may be used as a proxy measure of aging.

The lambda model of the equilibrium-point hypothesis (Feldman & Levin, 1995) is an approach to motor control which, like physics, is based on a logical system coordinating empirical data. The model has gone through an interesting period. On one hand, several nontrivial predictions of the model have been successfully verified in recent studies. In addition, the explanatory and predictive capacity of the model has been enhanced by its extension to multimuscle and multijoint systems. On the other hand, claims have recently appeared suggesting that the model should be abandoned. The present paper focuses on these claims and concludes that they are unfounded. Much of the experimental data that have been used to reject the model are actually consistent with it.