New horizons in frailty: ageing and the deficit-scaling problem.

Division of Geriatric Medicine, Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia, Canada.
Age and Ageing (Impact Factor: 3.11). 06/2013; DOI: 10.1093/ageing/aft059
Source: PubMed

ABSTRACT All the current frailty measures count deficits. They differ chiefly in which items, and how many, they consider. These differences are related: if a measure considers only a few items, to define broad risks those items need to integrate across several systems (e.g. mobility or function). If many items are included, the cumulative effect of small deficits can be considered. Even so, it is not clear just how small deficits can be. To better understand how the scale of deficit accumulation might impact frailty measurement, we consider how age-related, subcellular deficits might become macroscopically visible and so give rise to frailty. Cellular deficits occur when subcellular damage has neither been repaired nor cleared. With greater cellular deficit accumulation, detection becomes more likely. Deficit detection can be done by either subclinical (e.g. laboratory, imaging, electrodiagnostic) or clinical methods. Not all clinically evident deficits need cross a disease threshold. The extent to which cellular deficit accumulation compromises organ function can reflect not just what is happening in that organ system, but deficit accumulation in other organ systems too. In general, frailty arises in relation to the number of organ systems in which deficits accumulate. This understanding of how subcellular deficits might scale has implications for understanding frailty as a vulnerability state. Considering the cumulative effects of many small deficits appears to allow important aspects of the behaviour of systems close to failure to be observed. It also suggests the potential to detect frailty with less reliance on clinical observation than current methods employ.

1 Bookmark
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background Older 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.Methods This 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 (n¿=¿1,013) 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.Conclusions An 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.
    BMC Medicine 10/2014; 12(1):171. · 7.28 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Objectives To evaluate transitions in health status and risk of death in older adults in relation to baseline health deficits and protective factors.DesignProspective cohort study with reassessments at 5, 8, and 15 years.SettingSecondary analysis of data from the Beijing Longitudinal Study on Aging.ParticipantsUrban and rural community-dwelling people aged 55 and older at baseline (n = 3,275), followed from 1992 to 2007, during which time 51% died.MeasurementsHealth status was quantified using the deficit accumulation–based frailty index (FI), constructed from 30 intrinsic health measures. A protection index was constructed using 14 extrinsic items (e.g., exercise, education). The probabilities of health changes, including death, were evaluated using a multistate transition model.ResultsWomen had more health deficits (mean baseline FI 0.13 ± 0.11) than did men (mean baseline FI 0.11 ± 0.10). Although health declined on average (mean FIs increased), improvement and stability were common. Baseline health significantly affected health transitions and survival over various follow-up durations (odds ratio (OR) = 1.27, 95% confidence interval (CI) = 1.17–1.37 for men; OR = 1.24, 95% CI = 1.16–1.33 for women for each increment of deficits). Each protective factor reduced the risk of health decline and the risk of death in men and women by 13% to 25%.Conclusion Deficit accumulation–based transition modeling demonstrates persisting effects of baseline health status on age-related health outcomes. Some mitigation by protective factors can be demonstrated, suggesting that improving physical and social conditions might be beneficial.
    Journal of the American Geriatrics Society 04/2014; · 4.22 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Effective therapies have transformed HIV infection into a chronic disease, and new problems are arising related to aging. This article reviews the aging process, age-related deficit accumulation and frailty, and how these might be affected by chronic HIV infection.
    Current Opinion in HIV and AIDS 05/2014; · 4.39 Impact Factor


Available from
May 27, 2014