Cumulative Deficits Better Characterize Susceptibility to Death in Elderly People than Phenotypic Frailty: Lessons from the Cardiovascular Health Study

Abstract

OBJECTIVES:To compare how well frailty measures based on a phenotypic frailty approach proposed in the Cardiovascular Health Study (CHS) and a cumulative deficits approach predict mortality. DESIGN: Cohort study.Corresponding Author: A. Kulminski Center for Population Health and Aging, Duke University Trent Hall, Room 002, Box 90408, Durham, NC 27708. Fax: (919) 684-3861 E-mail: E-mail: Alexander.Kulminski@duke.edu. Alternate Corresponding Author: A. Yashin E-mail: E-mail: aiy@duke.edu. Author contributions: Drs. Kulminski and Yashin are responsible for study design, the accuracy of the analyses, and interpretation of the results. Drs. Kulminski, Ukraintseva, Kulminskaya, Arbeev, and Yashin take responsibility for the data integrity, and drafting the manuscript. Drs. Ukraintseva and Kulminskaya participated in elaboration of the phenotypic frailty and cumulative deficits indices. Dr. Kulminski was responsible for statistical analyses.Financial Disclosure: The research reported in this paper was supported by the grants 1R01 AG028259, 1R01-AG-027019 and 5P01-AG-008761 from the National Institute on Aging (NIA). Conflict of Interest MEASUREMENTS:A phenotypic frailty index (PFI) was defined in the same way as proposed in the CHS: assessing weight loss, exhaustion, low physical activity, slowness, and poor grip strength. A cumulative deficit index (DI) was defined based on 48 elderly deficits (signs, symptoms, impairments, diseases) included in the index, with equal weights. RESULTS:Of the 1,073 frailest individuals with the lowest survival, the PFI, categorized as proposed in the CHS into robust, prefrail, and frail categories, underestimated the risk of death for 720 persons, whereas the DI categorized into the same three frailty categories underestimated the mortality risk for 134 persons. The higher power of the DI for discriminating frail individuals in their susceptibility to death also followed from comparison of quasi-instantaneous values of both indices. The three-level DI identified 219 individuals as frail of 361 individuals identified as frail according to the three-level PFI. CONCLUSIONS:The DI can more precisely evaluate chances of death because it assesses a broader spectrum of disorders than the PFI. Both indices appear to be frailty related. Integration of both approaches is highly promising for increasing the precision of discrimination of the risk of death and especially for identification of the most vulnerable elderly people.

The association between frailty, the metabolic syndrome, and mortality over the lifespan

“…Other studies have shown that the value of the FI lies in predicting adverse outcomes even when the index is composed of factors not traditionally thought to be related to the outcome . Traditional modeling finds importance in risk when people share the same deficits, but a body of work suggests that at some point, sharing the same number of deficits can be as important as the nature of the deficits that are shared (Rockwood and Mitnitski 2007;Kulminski et al 2008a). The frailty index approach allows that insight to be formalized.…”

Assessing Balance and Mobility to Track Illness and Recovery in Older Inpatients

“…33 Indeed, the risk of adverse outcomes is defined more precisely by deficit indices than by phenotypic definitions of frailty. 34 The FI-CGA has been validated as a predictor of adverse outcomes for older people. 15 This cohort of hospitalised older adults was very frail, evidenced by the mean value of the FI-CGA being 0.42.…”

Cluster analysis to identify elderly people's profiles: a healthcare strategy based on frailty characteristics

“…12,38 The analysis therefore included variables described in connection with senility and frailty (age, cognitive abilities assessed on the MMSE scale, presence of depressive symptoms measured on the GDS scale, ADL and IADL functional statuses, number of comorbidities and number of drugs used regularly) to define significant profiles. [9][10][11]22,23,39 The results revealed that there were clusters made up of only four individuals, a number that was too small to allow inferences to be made correctly. Clusters 2, 3 and 4 were considered to present greater significance, since the number of elderly individuals in these clusters was higher.…”

“…2 Since functional losses tend to become more accentuated with advancing age, the number of people in older age groups in which there is a greater prevalence of functional decline and a greater demand for care is expected to increase. 7,[9][10][11] Based on this information, healthcare for the geriatric population must be planned using data that allow risks, possible actions and estimates of costs to be evaluated concisely and objectively. 8 Ideally, these instruments need to be both easy to apply and suitable for assessing the vulnerabilities of this population, such as their functional and cognitive disabilities, the prevalence of chronic degenerative diseases and the need for pharmacotherapeutic support.…”