Kenneth Rockwood

Standard laboratory tests to identify older adults at increased risk of death

BackgroundOlder adults are at an increased risk of death, but not all people of the same age have the same risk. Many methods identify frail people (that is, those at increased risk) but these often require time-consuming interactions with health care providers. We evaluated whether standard laboratory tests on their own, or added to a clinical frailty index (FI), could improve identification of older adults at increased risk of death.MethodsThis is a secondary analysis of a prospective cohort study, where community dwelling and institutionalized participants in the Canadian Study of Health and Aging who also volunteered for blood collection (nu2009=u20091,013) were followed for up to six years. A standard FI (FI-CSHA) was constructed from data obtained during the clinical evaluation and a second, novel FI was constructed from laboratory data plus systolic and diastolic blood pressure measurements (FI-LAB). A combined FI included all items from each index. Predictive validity was tested using Cox proportional hazards analysis and discriminative ability by the area under receiver operating characteristic (ROC) curves.ResultsOf 1,013 participants, 51.3% had died by six years. The mean baseline value of the FI-LAB was 0.27 (standard deviation 0.11; range 0.05 to 0.63), the FI-CSHA was 0.25 (0.11; 0.02 to 0.72), and the combined FI was 0.26 (0.09; 0.06 to 0.59). In an age- and sex-adjusted model, with each increment in the FI-LAB, the hazard ratios increased by 2.8% (95% confidence interval 1.02 to 1.04). The hazard ratios for the FI-CSHA and the combined FI were 1.02 (1.01 to 1.03) and 1.04 (1.03 to 1.05), respectively. The FI-LAB and FI-CSHA remained independently associated with death in the face of the other. The areas under the ROC curves were 0.72 for FI-LAB, 0.73 for FI-CSHA and 0.74 for the combined FI.ConclusionsAn FI based on routine laboratory data can identify older adults at increased risk of death. Additional evaluation of this approach in clinical settings is warranted.

What are frailty instruments for

Frailty is measured to understand its nature and biology, to aid diagnosis and care planning, to measure outcomes and to stratify risk. Such goals oblige two types of frailty measures - for screening and for assessment - and recognition that not all measures will serve all purposes. When the goal is broad identification of people at risk, a dichotomised approach (frailty is present or absent ) is appropriate. If, however, the degree of risk varies, strategies to test grades of frailty will be required. Frailty measures should be implemented and evaluated in relation to the goal for their use.

Aging as a Process of Deficit Accumulation: Its Utility and Origin

Individuals of the same age differ greatly with respect to their health status and life span. We have suggested that the health status of individuals can be represented by the number of health deficits that they accumulate during their life. We have suggested that this can be measured by a fitness-frailty index (or just a frailty index), which is the ratio of the deficits present in a person to the total number of deficits considered (e.g. available in a given database or experimental procedure). Further, we have proposed that the frailty index represents the biological age of the individual, and suggested an algorithm for its estimation. In investigations by many groups, the frailty index has shown reproducible properties such as: age-specific, nonlinear increase, higher values in women, strong association with mortality and other adverse outcomes, and universal limit to its increase. At the level of individual, the frailty index shows complex stochastic dynamics, reflecting both stochasticity of the environment and the ability to recover from various illnesses. Most recently, we have proposed that the origin of deficit accumulation lies in the interaction between the environment, the organism and its ability to recover. We apply a stochastic dynamics framework to illustrate that the average recovery time increases with age, mimicking the age-associated increase in deficit accumulation.

Heterogeneity of Human Aging and Its Assessment

Understanding the heterogeneity in health of older adults is a compelling question in the biology of aging. We analyzed the performance of five measures of health heterogeneity, judging them by their ability to predict mortality. Using clinical and biomarker data on 1,013 participants of the Canadian Study of Health and Aging who were followed for up to 6 years, we calculated two indices of biological age using the Klemera and Doubal method, which controversially includes using chronological age as a biomarker, and three frailty indices (FIs) that do not include chronological age: a standard clinical FI, an FI from standard laboratory blood tests and blood pressure, and their combination (FI-combined). Predictive validity was tested using Cox proportional hazards analysis and discriminative ability by the area under the receiver-operating characteristic curves. All five measures showed moderate performance that was improved by combining measures to evaluate larger numbers of items. The greatest addition in explanatory power came from the FI-combined that showed the best mortality prediction in an age-adjusted model. More extensive comparisons across different databases are required, but these results do not support including chronological age as a biomarker.

Effect Size Analyses of Souvenaid in Patients with Alzheimer’s Disease

Background: Souvenaid® (uridine monophosphate, docosahexaenoic acid, eicosapentaenoic acid, choline, phospholipids, folic acid, vitamins B12, B6, C, and E, and selenium), was developed to support the formation and function of neuronal membranes. Objective: To determine effect sizes observed in clinical trials of Souvenaid and to calculate the number needed to treat to show benefit or harm. Methods: Data from all three reported randomized controlled trials of Souvenaid in Alzheimer’s disease (AD) dementia (Souvenir I, Souvenir II, and S-Connect) and an open-label extension study were included in analyses of effect size for cognitive, functional, and behavioral outcomes. Effect size was determined by calculating Cohen’s d statistic (or Cramér’s V method for nominal data), number needed to treat and number needed to harm. Statistical calculations were performed for the intent-to-treat populations. Results: In patients with mild AD, effect sizes were 0.21 (95% confidence intervals: –0.06, 0.49) for the primary outcome in Souvenir II (neuropsychological test battery memory z-score) and 0.20 (0.10, 0.34) for the co-primary outcome of Souvenir I (Wechsler memory scale delayed recall). No effect was shown on cognition in patients with mild-to-moderate AD (S-Connect). The number needed to treat (6 and 21 for Souvenir I and II, respectively) and high number needed to harm values indicate a favorable harm:benefit ratio for Souvenaid versus control in patients with mild AD. Conclusions: The favorable safety profile and impact on outcome measures converge to corroborate the putative mode of action and demonstrate that Souvenaid can achieve clinically detectable effects in patients with early AD.

Comparison and clinical applications of the frailty phenotype and frailty index approaches

The previous chapter focused on the conceptualization and operationalization of the deficit accumulation and phenotypic approaches to the description of frailty. The purpose of this chapter is to summarize some studies that compared these most commonly used frailty definitions. We also discuss the strengths and limitations of using these two frailty assessments in clinical settings and how they might be usefully employed in future studies.

Neuropsychiatric symptom clusters targeted for treatment at earlier versus later stages of dementia.

To characterize clusters of neuropsychiatric symptoms targeted for tracking the disease course in people with dementia, in relation to stage.

What can we expect of health in old age

730 www.thelancet.com Vol 387 February 20, 2016 The longing for longevity without decrepitude is ancient. Homer tells us that to live out his days with Penelope, Odysseus rejected immortality. Later restored to family and kingdom, the gods’ further favour included being able to look forward to an unenfeebled old age. So how goes our longing now? Around the world, although life expectancy is increasing for most people, a wholly healthy old age is elusive. In The Lancet, Carol Jagger and colleagues make clear that whether we reckon the ancient longing to be realised depends on how we measure health, and on which perspective we have. The authors compared the results from two rounds of the Cognitive Function and Ageing Study, done in England in 1991 and 2011. Health expectancy was measured in three ways: self-perceived health, life without disability, and time free from cognitive impairment. In 2011, on a background of increasing life expectancy, men spent 3·8 more years (95% CI 3·5–4·1), and women spent 3·1 more years (2·7–3·4), in good or better self-perceived health than in 1991. Similarly, fewer people rated their health as fair or poor in 2011 than in 1991, although this eff ect was not signifi cant after adjustment for region, education, and deprivation. In contrast to a Swedish report of cohorts studied 30 years apart, the prevalence of disability increased. However, the pattern gives some cause for hope: men spent 1·3 more years (1·1–1·6) with mild disability, compared with 0·5 years (0·3–0·8) with moderate–severe disability; the corresponding fi gures for women were 2·5 years (2·2–2·8) with mild disability and 0·6 years (0·3–0·9) with moderate– severe disability. Although more time was spent with disability, moderate–severe disability decreased, so that the increase—and most of the additional time lived— was spent in a mildly disabled state. The least equivocal change was that less time was spent by women with cognitive impairment (0·7 years [0·2–1·3]), and more time spent without cognitive impairment (4·4 years [4·3–4·5]), in 2011 than in 1991. Achievement of longer life and reduced impairment is an important step towards the Homeric ideal. Especially for cognitive health, what future progress can be made is debated. The decline in cognitive impairment was not insubstantial (odds ratio [OR] 0·53 [95% CI 0·49–0·56]). Most of this decrease was accounted for by a decline in severe cognitive impairment (OR 0·49, [0·43–0·56]). This decrease is much larger than that returned so far on the massive investments in research on dementia biomarkers and hoped-for disease-modifying therapies. Those investments gamble that any positive results from proof-of-concept trials in younger (ie, from their 40s) and often otherwise well patients, especially from high-risk samples, will be relevant to older adults with many health defi cits, who are the most common patients with dementia. Equally, whether improving overall health—lessening health defi cits and their eff ects—would further result in reduced cognitive impairment is unknown. Jagger and colleagues suggest that the observed increase in mild disability might result from specifi c problems, notably obesity and musculoskeletal disease. Here, caution must be urged. Although understanding which illnesses contribute to disability is important, disability rates are potently related to age. As a result, the extent of overall, age-related defi cit accumulation might be as important to disability rates as which illnesses people have. Health defi cits are not just diseases, but can range from even minor laboratory abnormalities to lower than average enjoyment of life. For this reason, a broadly construed approach to improving health might pay current and future dividends. So too might a broadly What can we expect of health in old age?