0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Investigation |

Transitions Between Frailty States Among Community-Living Older Persons FREE

Thomas M. Gill, MD; Evelyne A. Gahbauer, MD, MPH; Heather G. Allore, PhD; Ling Han, MD, MSc
[+] Author Affiliations

Author Affiliations: Department of Internal Medicine, Yale University School of Medicine, New Haven, Conn.


Arch Intern Med. 2006;166(4):418-423. doi:10.1001/archinte.166.4.418.
Text Size: A A A
Published online

Background:  Little is known about the natural course of frailty. We performed a prospective study to determine the transition rates between frailty states and to evaluate the effect of the preceding frailty state on subsequent frailty transitions.

Methods:  We studied 754 community-living persons, aged 70 years or older, who were nondisabled in 4 essential activities of daily living. Frailty, assessed every 18 months for 54 months, was defined on the basis of weight loss, exhaustion, low physical activity, muscle weakness, and slow walking speed. Participants were classified as frail if they met 3 or more of these criteria, as prefrail if they met 1 or 2 of the criteria, and as nonfrail if they met none of the criteria.

Results:  Of the 754 participants, 434 (57.6%) had at least 1 transition between any 2 of the 3 frailty states during 54 months. The rates were 36.8%, 21.5%, and 9.2% for 1, 2, and 3 transitions, respectively. During the 18-month intervals, transitions to states of greater frailty were more common (rates up to 43.3%) than transitions to states of lesser frailty (rates up to 23.0%), and the probability of transitioning from being frail to nonfrail was very low (rates, 0%-0.9%), even during an extended period. The likelihood of transitioning between frailty states was highly dependent on one's preceding frailty state.

Conclusions:  Frailty among older persons is a dynamic process, characterized by frequent transitions between frailty states over time. Our findings suggest ample opportunity for the prevention and remediation of frailty.

Figures in this Article

Frailty is increasingly recognized as a geriatric syndrome, distinct from disability and comorbidity, that results from a multisystem reduction in reserve capacity, confers high risk for an array of adverse outcomes, and is potentially amenable to prevention and remediation.1 An important impediment to the development of frailty-specific interventions has been an incomplete understanding of the epidemiology of frailty. Until recently, research on frailty has been slowed by the absence of a standardized and valid operational definition. In a seminal report, Fried et al2 proposed that frailty be defined on the basis of the following 5 features: unintentional weight loss, exhaustion, low physical activity, muscle weakness, and slow walking speed, with the presence of 3 or more of these features denoting frailty, 1 or 2 denoting prefrailty, and none denoting no frailty. This 3-level definition for frailty had strong concurrent validity, as evidenced by expected associations with age, chronic conditions, cognitive function, and depressive symptoms, and was independently predictive of several relevant outcomes, including incident falls, hospitalization, worsening disability, and death.2

To date, little is known about the likelihood of transitions between these different frailty states over time. In the Cardiovascular Health Study,2 the 4-year incidence of frailty was 7.2% among participants who were initially nonfrail. In the Hispanic Established Populations for Epidemiological Studies of the Elderly,3 the cumulative incidence of frailty among nonfrail participants was 3.6% at 2 years, 6.6% at 5 years, and 7.9% at 7 years. Neither study reported transition rates between nonfrail and prefrail states or evaluated how often frail older persons transition to less frail states. We have recently demonstrated that disability, a key frailty-related outcome, is a reversible, and often recurrent, event.46 On the basis of these findings, we postulated that frailty may also be a dynamic process, as illustrated in Figure 1. To improve our understanding of frailty among older persons, we set out in the current study to determine the transition rates between frailty states over time and to evaluate the effect of the preceding frailty state on subsequent frailty transitions.

Place holder to copy figure label and caption
Figure 1.

Multistate model depicting possible transitions between frailty states and death.

Graphic Jump Location
STUDY POPULATION

Participants were members of the Precipitating Events Project, a longitudinal study of 754 community-living persons, aged 70 years or older, who were nondisabled (ie, required no personal assistance) at baseline in 4 essential activities of daily living: bathing, dressing, walking inside the house, and transferring from a chair.7 Exclusion criteria included significant cognitive impairment with no available proxy,8 inability to speak English, diagnosis of a terminal illness with a life expectancy of less than 12 months, and a plan to move out of the New Haven, Conn, area during the next 12 months.

The cohort was assembled between March 23, 1998, and October 26, 1999. Eligibility was determined during a screening telephone interview and was confirmed during an in-home assessment. Participants were enrolled in a 4:2:1 ratio for low, intermediate, and high risk of disability, using a model developed and validated in an earlier study.9 Participants were classified as low risk if they scored 10 seconds or less on the rapid gait test (ie, walk back and forth over a 10-ft [3-m] course as quickly as possible); as intermediate risk if they scored greater than 10 seconds on rapid gait, scored 24 or better on the Folstein Mini-Mental State Examination,10 and were younger than 85 years; and as high risk if they scored greater than 10 seconds on rapid gait and if they either scored less than 24 on the Mini-Mental State Examination or were aged 85 years or older. A complete description of our stratified sampling technique is provided elsewhere.7 Only 4.6% of the 2753 health plan members who were alive and could be contacted refused to complete the screening telephone interview, and 75.2% of the eligible members agreed to participate in the project. Persons who refused to participate did not differ significantly from those who were enrolled for age or sex. The study protocol was approved by the Yale Human Investigation Committee, New Haven; all participants provided oral informed consent.

DATA COLLECTION

Comprehensive home-based assessments were completed by trained nurse researchers at baseline and at 18, 36, and 54 months. Data were collected on demographic characteristics; cognitive status10; 13 self-reported, physician-diagnosed chronic conditions7; and frailty as described in the next section. Deaths were ascertained by review of the local obituaries and/or from an informant. Two hundred twelve participants (28.1%) died after a median follow-up of 40 months, and 30 (4.0%) dropped out of the study after a median follow-up of 22 months.

ASSESSMENT OF FRAILTY

Data from the comprehensive assessments were used to define each of the 5 criteria for frailty: weight loss, exhaustion, low physical activity, muscle weakness, and slow walking speed. Because the instruments were not identical, our operational definitions differed modestly from those previously described by Fried et al2 for use in the Cardiovascular Health Study. The specific modifications are described in Table 1. Comparable modifications have been successfully implemented in the Women's Health and Aging Studies.11

Table Graphic Jump LocationTable 1. Specific Modifications to the Frailty Criteria

In the current study, the weight loss criterion was met if the participant answered “Yes” when asked, “In the past year, have you lost more than 10 pounds?” The exhaustion criterion was met if the participant answered “Much or most of the time” when asked, “How often in the last week did you feel this way” to either of the following 2 statements from the Center for Epidemiologic Studies Depression Scale12 : “I felt that everything I did was an effort” and “I could not get going.” The physical activity criterion was met for men who scored less than 64 and women who scored less than 52 on the Physical Activity Scale for the Elderly.13,14 These sex-specific cutoff points denote the worse quintile of scores among the first 356 enrolled participants, who had been selected randomly from our source population of health plan members.7 The Physical Activity Scale for the Elderly, which assesses several occupational, household, and leisure activities during a 1-week period, has been shown to be both valid and reliable.13,15,16 The muscle weakness criterion was met when grip strength, assessed as the average of 3 readings by a handheld dynamometer (Chatillon 100; Ametek Inc, Largo, Fla), was less than or equal to the sex- and body mass index–specific cutoff points provided by Fried et al.2 Finally, the slow walking speed criterion was met if the participant scored more than 10 seconds on the rapid gait test, as previously described. This cutoff point delineated a threshold response (at the worst quartile) between rapid gait scores and the development of disability in an earlier population-based cohort of older persons.17,18

Participants were classified as frail if they met 3 or more of the aforementioned criteria, as prefrail if they met 1 or 2 of the criteria, and as nonfrail if they met none of the criteria. Among a subgroup of 24 participants who were examined independently within a 3-day period by different nurse researchers, we found that the reliability of our frailty assessment was substantial,19 with a weighted κ = 0.78. For participants who had significant cognitive impairment, information on weight loss and physical activity was obtained from a proxy informant, as previously described.8

STATISTICAL ANALYSIS

We calculated descriptive statistics for participants who completed the comprehensive assessments at baseline and at 18, 36, and 54 months. Next, we evaluated the predictive validity for each of the modified frailty criteria by the Kaplan-Meier method, with survival over 72 months as the outcome,20 and calculated unadjusted hazard ratios by the Cox proportional hazards method.21

We determined the number and rate of all participants who had at least 1 transition between any 2 of the 3 frailty states during the 54-month follow-up period. We then determined the numbers who had 1, 2, and 3 transitions and calculated the corresponding rates, including only participants who had complete frailty data for the corresponding number of transitions.

Next, we calculated rates for each of the transitions depicted in Figure 1 between baseline and 18 months, 18 and 36 months, and 36 and 54 months, respectively, including participants who had data on frailty or death at each of the 2 time points defining the relevant follow-up interval. Using data from the first 356 randomly selected and enrolled participants, we repeated these analyses to ensure that the overall results were not dependent on our stratified sampling strategy.

To determine the effect of the preceding frailty state, we stratified the results for 18 to 36 months by the baseline frailty state and those for 36 to 54 months by the frailty state at 18 months, using data from all available participants. We formally tested the independent effect of the preceding frailty state by using a cumulative logit model,22 with frailty (3 levels) at baseline and 18 months, respectively, as independent variables and frailty (3 levels) at 36 months as the dependent variable. These results were confirmed in a separate model that included frailty at 18 and 36 months, respectively, as independent variables and frailty at 54 months as the dependent variable (results available on request).

All statistical tests were 2 tailed, and P<.05 was considered to indicate statistical significance. All analyses were performed with SAS version 9.1 (SAS Institute Inc, Cary, NC).

The characteristics of the study participants at each time point are provided in Table 2. At baseline, most participants were female, were non-Hispanic white, and did not live alone. On average, participants had a high school education and 2 chronic conditions. Only a few had significant cognitive impairment. About half of the participants met the criterion for prefrailty, while comparable proportions were classified as nonfrail and frail. Over time, as the cohort aged, the proportion of participants who were frail increased, while the proportions who were nonfrail or prefrail decreased. As shown in Figure 2, each of the frailty criteria was strongly associated with the probability of survival.

Place holder to copy figure label and caption
Figure 2.

Kaplan-Meier curves for survival over 72 months according to each of the 5 modified frailty criteria at baseline. Unadjusted hazard ratios (HRs) were calculated by the Cox proportional hazards method.

Graphic Jump Location
Table Graphic Jump LocationTable 2. Characteristics of Study Participants*

Among the 754 participants, 434 (57.6%) had at least 1 transition between any 2 of the 3 frailty states during the 54-month follow-up period. The corresponding results for 1, 2, and 3 transitions, including only participants who had complete frailty data as described in the “Methods” section, were 252 (36.8%), 133 (21.5%), and 49 (9.2%), respectively. Table 3 provides the transition rates between the 3 frailty states and death for each of the 18-month follow-up intervals. While transitions were observed between each of the states, most participants remained in their current frailty state for each of the follow-up intervals. For participants who were nonfrail or prefrail, the transition rates did not change appreciably over time. For participants who were frail, the probability of transitioning to the prefrail state decreased over time, while the probability of dying increased. With only 2 exceptions, participants who were frail did not transition to the nonfrail state. Similarly, few participants transitioned from being nonfrail to frail during a single follow-up interval. When an expanded follow-up interval of 36 to 54 months was considered, no additional participant transitioned from being frail to nonfrail. Finally, depending on the follow-up interval, the likelihood of dying was approximately 3 to 5 times greater among participants who were frail than among those who were either nonfrail or prefrail. When these analyses were restricted to the first 356 enrolled participants, the results did not differ substantively (available on request).

Table Graphic Jump LocationTable 3. Numbers and Rates of Transitions According to Follow-up Interval*

The transition rates between frailty states over 18 months differed according to the participants' preceding frailty state. This finding is illustrated in Table 4, which shows the transition rates from the prefrail state at 18 months to each of the 4 possible states at 36 months according to the participants' baseline state. While the overall transition rate from prefrail at 18 months to nonfrail at 36 months was 16.5%, the transition rates were 31.8%, 14.8%, and 0% for participants who were nonfrail, prefrail, and frail, respectively, at baseline. In the cumulative logit model, frailty state at baseline and 18 months were each independently associated with frailty state at 36 months (P<.001), confirming the stratified results in Table 4.

Table Graphic Jump LocationTable 4. Numbers and Rates of Transitions From Prefrail State at 18 Months to Subsequent State at 36 Months According to Baseline State*

In this prospective cohort study, we found that frailty among older persons is a dynamic process, characterized by frequent transitions between frailty states over time. Transitions to states of greater frailty were more common than transitions to states of lesser frailty, and the probability of transitioning from being frail to nonfrail was very low, even over an extended period. Importantly, the likelihood of transitioning between frailty states was highly dependent on one's preceding frailty state.

In 2003, the Institute of Medicine identified frailty as 1 of 20 priority areas, selected from several hundred potential candidates, in need for improvement in health care quality.23 To achieve this objective, clinicians and policymakers will require an enhanced understanding of the epidemiology of frailty, including its natural course. Our results provide strong evidence to support a model of frailty that involves frequent transitions over time. These transitions occur most commonly between adjacent frailty states, suggesting a gradual progression in, or resolution of, the underlying etiologic disorder(s). In future studies, we plan to evaluate the risk factors and precipitants for the onset and progression of frailty and to identify the factors that may facilitate transitions to less frail states. Together, the results of the current and future research will help to inform the development of preventive and restorative interventions for frailty24 and, ultimately, to enhance the quality of care for older persons who are frail or at risk for frailty.1

Our assessment of frailty included modified versions of the 5 criteria that were initially operationalized by Fried et al2 using data from the Cardiovascular Health Study. While these modifications may have modestly affected our point estimates of frailty, they should have had little effect on the transition rates, which reflect changes in frailty over time. Each of our modified criteria was strongly associated with survival, providing evidence of their validity. The high reliability of our assessment suggests that most of the observed transitions represent true changes in frailty status rather than measurement error. However, some investigators25 have cautioned that it would be premature to accept the Fried et al definition of frailty as the reference standard, despite evidence supporting its validity, given the clinical complexity of frailty and the omission of potentially important features such as cognitive impairment, depressive symptoms, and poor balance (among others).26

Our stratified sampling strategy yielded a study population with a much higher prevalence of frailty and a much lower prevalence of nonfrailty relative to the study populations in the Cardiovascular Health Study2 and Women's Health and Aging Studies.11 Nevertheless, because comparable transition rates were observed among the first 356 enrolled participants, who had been randomly sampled,7 our estimates should accurately reflect those of our source population of health plan members. Whether our findings can be generalized more widely, however, may reasonably be questioned. As previously noted,27 the demographic characteristics of our source population closely mirror those of persons aged 70 years or older in New Haven County, which, in turn, are comparable with those in the United States as a whole, with the exception of race (New Haven County has a larger proportion of non-Hispanic whites in this age group than the United States, 91% vs 84%).28 The high participation rate, completeness of data collection, and low rate of attrition for reasons other than death all enhance the generalizability of our findings29 and, at least partially, offset the absence of a population-based sample.

While our study population included an increasing proportion of participants over time with significant cognitive impairment, we have previously demonstrated the validity of our proxy assessments for disability in activities of daily living.8 Because physicians are notoriously poor at identifying common geriatric problems30,31 and at using this information effectively when it is available,32,33 it is unlikely that our findings were appreciably affected by the provision of frailty-specific preventive or restorative interventions, which were not ascertained as part of the study.

Despite assessing frailty every 18 months, it is possible that we missed transitions that occurred during shorter intervals. We have previously demonstrated that older persons transition frequently between states of disability and independence.4,6 While frailty and disability are distinct geriatric syndromes,1 transitions in frailty and disability are likely related. In future studies, we plan to elucidate the temporal, and potentially reciprocal, relationships between these transitions. Because the likelihood of a subsequent state is dependent not only on the current state, but also on the previous state, for disability34 and, as demonstrated in the current study, for frailty, analytic strategies that assume a memoryless process, such as standard first-order Markov chain models, will not be valid.

To complement the exciting cross-sectional research that is exploring the biological underpinnings of frailty,3538 longitudinal studies are needed to more completely elucidate the epidemiology of frailty, including its natural course, risk factors, precipitants, and interrelationships over time with disability and comorbidity. By demonstrating that frailty, like disability, is a dynamic process, the results of the current study suggest ample opportunity for prevention and remediation and set the stage for a series of subsequent epidemiologic studies that will ultimately inform the development and evaluation of interventions designed to prevent frailty among at-risk individuals and to reduce vulnerability among those who are frail.26

Correspondence: Thomas M. Gill, MD, Yale University School of Medicine, Dorothy Adler Geriatric Assessment Center, 20 York St, New Haven, CT 06504 (gill@ynhh.org).

Accepted for Publication: September 14, 2005.

Financial Disclosure: None.

Funding/Support: This study was funded by grants R37AG17560 and R01AG022993 from the National Institute on Aging, Bethesda, Md; Robert Wood Johnson Foundation, Princeton, NJ; Paul Beeson Physician Faculty Scholar in Aging Research Program; and Patrick and Catherine Weldon Donaghue Medical Research Foundation, West Hartford, Conn. The study was conducted at the Yale Claude D. Pepper Older Americans Independence Center (supported by grant P30AG21342 from the National Institute on Aging, Bethesda, Md). Dr Gill is the recipient of K24AG021507, a Midcareer Investigator Award in Patient-Oriented Research from the National Institute on Aging.

Fried  LPFerrucci  LDarer  J  et al.  Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. J Gerontol A Biol Sci Med Sci 2004;59255- 263
Link to Article
Fried  LPTangen  CMWalston  J  et al.  Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56AM146- M156
Link to Article
Ostir  GVOttenbacher  KJMarkides  KS Onset of frailty in older adults and the protective role of positive affect. Psychol Aging 2004;19402- 408
PubMed Link to Article
Gill  TMKurland  B The burden and patterns of disability in activities of daily living among community-living older persons. J Gerontol A Biol Sci Med Sci 2003;5870- 75
Link to Article
Hardy  SEGill  TM Recovery from disability among community-dwelling older persons. JAMA 2004;2911596- 1602
PubMed Link to Article
Hardy  SEDubin  JAHolford  TRGill  TM Transitions between states of disability and independence among older persons. Am J Epidemiol 2005;161575- 584
PubMed Link to Article
Gill  TMDesai  MMGahbauer  EA  et al.  Restricted activity among community-living older persons: incidence, precipitants, and health care utilization. Ann Intern Med 2001;135313- 321
PubMed Link to Article
Gill  TMHardy  SEWilliams  CS Underestimation of disability among community-living older persons. J Am Geriatr Soc 2002;501492- 1497
PubMed Link to Article
Gill  TMWilliams  CSTinetti  ME The combined effects of baseline vulnerability and acute hospital events on the development of functional dependence among community-living older persons. J Gerontol A Biol Sci Med Sci 1999;54AM377- M383
Link to Article
Folstein  MFFolstein  SEMcHugh  PR “Mini-Mental State”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12189- 198
PubMed Link to Article
Blaum  CSQian  XLMichelon  E  et al.  The association between obesity and the frailty syndrome in older women: the Women's Health and Aging Studies. J Am Geriatr Soc 2005;53927- 934
PubMed Link to Article
Kohout  FJBerkman  LFEvans  DACornoni-Huntley  J Two shorter forms of the CES-D Depression Symptoms Index. J Aging Health 1993;5179- 193
PubMed Link to Article
Washburn  RASmith  KWJette  AMJanney  CA The Physical Activity Scale for the Elderly (PASE): development and evaluation. J Clin Epidemiol 1993;46153- 162
PubMed Link to Article
Pereira  MAFitzerGerald  SJGregg  EW  et al.  A collection of Physical Activity Questionnaires for health-related research. Med Sci Sports Exerc 1997;29 ((6, suppl)) S1- S205
Link to Article
Schuit  AJSchouten  EGWesterterp  KRSaris  WH Validity of the Physical Activity Scale for the Elderly (PASE): according to energy expenditure assessed by the doubly labeled water method. J Clin Epidemiol 1997;50541- 546
PubMed Link to Article
Washburn  RAMcAuley  EKatula  J  et al.  The Physical Activity Scale for the Elderly (PASE): evidence for validity. J Clin Epidemiol 1999;52643- 651
PubMed Link to Article
Gill  TMWilliams  CSTinetti  ME Assessing risk for the onset of functional dependence among older adults: the role of physical performance. J Am Geriatr Soc 1995;43603- 609
PubMed
Gill  TMRichardson  EDTinetti  ME Evaluating the risk of dependence in activities of daily living among community-living older adults with mild to moderate cognitive impairment. J Gerontol A Biol Sci Med Sci 1995;50AM235- M241
Link to Article
Landis  JRKoch  GG The measurement of observer agreement for categorical data. Biometrics 1977;33159- 174
PubMed Link to Article
Kaplan  ELMeier  PM Nonparametric estimation from incomplete observations. J Am Stat Soc 1958;53457- 481
Link to Article
Cox  DR Regression models and life tables. J R Stat Soc Ser A 1972;34187- 220
McCullagh  PNelder  JAeds Generalized Linear Models. 2nd ed. London, England Chapman & Hall1989;
Adams  KCorrigan  JMeds Priority Areas for National Action: Transforming Health Care Quality.  Washington, DC National Academies Press2003;
Gill  TMBaker  DIGottschalk  M  et al.  A program to prevent functional decline in physically frail, elderly persons who live at home. N Engl J Med 2002;3471068- 1074
PubMed Link to Article
Rockwood  K Frailty and its definition: a worthy challenge. J Am Geriatr Soc 2005;531069- 1070
PubMed Link to Article
Ferrucci  LGuralnik  JMStudenski  S  et al.  Designing randomized, controlled trials aimed at preventing or delaying functional decline and disability in frail, older persons: a consensus report. J Am Geriatr Soc 2004;52625- 634
PubMed Link to Article
Gill  TMAllore  HGHolford  TRGuo  Z Hospitalization, restricted activity, and the development of disability among older persons. JAMA 2004;2922115- 2124
PubMed Link to Article
American FactFinder, US Census Bureau. http://factfinder.census.gov. Accessed May 29, 2003
Szklo  M Population-based cohort studies. Epidemiol Rev 1998;2081- 90
PubMed Link to Article
Calkins  DRRubenstein  LVCleary  PD  et al.  Failure of physicians to recognize functional disability in ambulatory patients. Ann Intern Med 1991;114451- 454
PubMed Link to Article
Tinetti  MEFried  T The end of the disease era. Am J Med 2004;116179- 185
PubMed Link to Article
Calkins  DRRubenstein  LVCleary  PD  et al.  Functional disability screening of ambulatory patients: a randomized controlled trial in a hospital-based group practice. J Gen Intern Med 1994;9590- 592
PubMed Link to Article
Moore  AASiu  APartridge  JM  et al.  A randomized trial of office-based screening for common problems in older persons. Am J Med 1997;102371- 378
PubMed Link to Article
Gill  TMKurland  BF Prognostic effect of prior disability episodes among nondisabled community-living older persons. Am J Epidemiol 2003;1581090- 1096
PubMed Link to Article
Newman  ABGottdiener  JSMcBurnie  MA  et al.  Associations of subclinical cardiovascular disease with frailty. J Gerontol A Biol Sci Med Sci 2001;56AM158- M166
Link to Article
Walston  JMcBurnie  MANewman  A  et al.  Frailty and activation of the inflammation and coagulation systems with and without clinical comorbidities: results from the Cardiovascular Health Study. Arch Intern Med 2002;1622333- 2341
PubMed Link to Article
Schmaltz  HNFried  LPXue  QL  et al.  Chronic cytomegalovirus infection and inflammation are associated with prevalent frailty in community-dwelling older women. J Am Geriatr Soc 2005;53747- 754
PubMed Link to Article
Wilson  JF Frailty—and its dangerous effects—might be preventable. Ann Intern Med 2004;141489- 492
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.

Multistate model depicting possible transitions between frailty states and death.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Kaplan-Meier curves for survival over 72 months according to each of the 5 modified frailty criteria at baseline. Unadjusted hazard ratios (HRs) were calculated by the Cox proportional hazards method.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Specific Modifications to the Frailty Criteria
Table Graphic Jump LocationTable 2. Characteristics of Study Participants*
Table Graphic Jump LocationTable 3. Numbers and Rates of Transitions According to Follow-up Interval*
Table Graphic Jump LocationTable 4. Numbers and Rates of Transitions From Prefrail State at 18 Months to Subsequent State at 36 Months According to Baseline State*

References

Fried  LPFerrucci  LDarer  J  et al.  Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. J Gerontol A Biol Sci Med Sci 2004;59255- 263
Link to Article
Fried  LPTangen  CMWalston  J  et al.  Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56AM146- M156
Link to Article
Ostir  GVOttenbacher  KJMarkides  KS Onset of frailty in older adults and the protective role of positive affect. Psychol Aging 2004;19402- 408
PubMed Link to Article
Gill  TMKurland  B The burden and patterns of disability in activities of daily living among community-living older persons. J Gerontol A Biol Sci Med Sci 2003;5870- 75
Link to Article
Hardy  SEGill  TM Recovery from disability among community-dwelling older persons. JAMA 2004;2911596- 1602
PubMed Link to Article
Hardy  SEDubin  JAHolford  TRGill  TM Transitions between states of disability and independence among older persons. Am J Epidemiol 2005;161575- 584
PubMed Link to Article
Gill  TMDesai  MMGahbauer  EA  et al.  Restricted activity among community-living older persons: incidence, precipitants, and health care utilization. Ann Intern Med 2001;135313- 321
PubMed Link to Article
Gill  TMHardy  SEWilliams  CS Underestimation of disability among community-living older persons. J Am Geriatr Soc 2002;501492- 1497
PubMed Link to Article
Gill  TMWilliams  CSTinetti  ME The combined effects of baseline vulnerability and acute hospital events on the development of functional dependence among community-living older persons. J Gerontol A Biol Sci Med Sci 1999;54AM377- M383
Link to Article
Folstein  MFFolstein  SEMcHugh  PR “Mini-Mental State”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12189- 198
PubMed Link to Article
Blaum  CSQian  XLMichelon  E  et al.  The association between obesity and the frailty syndrome in older women: the Women's Health and Aging Studies. J Am Geriatr Soc 2005;53927- 934
PubMed Link to Article
Kohout  FJBerkman  LFEvans  DACornoni-Huntley  J Two shorter forms of the CES-D Depression Symptoms Index. J Aging Health 1993;5179- 193
PubMed Link to Article
Washburn  RASmith  KWJette  AMJanney  CA The Physical Activity Scale for the Elderly (PASE): development and evaluation. J Clin Epidemiol 1993;46153- 162
PubMed Link to Article
Pereira  MAFitzerGerald  SJGregg  EW  et al.  A collection of Physical Activity Questionnaires for health-related research. Med Sci Sports Exerc 1997;29 ((6, suppl)) S1- S205
Link to Article
Schuit  AJSchouten  EGWesterterp  KRSaris  WH Validity of the Physical Activity Scale for the Elderly (PASE): according to energy expenditure assessed by the doubly labeled water method. J Clin Epidemiol 1997;50541- 546
PubMed Link to Article
Washburn  RAMcAuley  EKatula  J  et al.  The Physical Activity Scale for the Elderly (PASE): evidence for validity. J Clin Epidemiol 1999;52643- 651
PubMed Link to Article
Gill  TMWilliams  CSTinetti  ME Assessing risk for the onset of functional dependence among older adults: the role of physical performance. J Am Geriatr Soc 1995;43603- 609
PubMed
Gill  TMRichardson  EDTinetti  ME Evaluating the risk of dependence in activities of daily living among community-living older adults with mild to moderate cognitive impairment. J Gerontol A Biol Sci Med Sci 1995;50AM235- M241
Link to Article
Landis  JRKoch  GG The measurement of observer agreement for categorical data. Biometrics 1977;33159- 174
PubMed Link to Article
Kaplan  ELMeier  PM Nonparametric estimation from incomplete observations. J Am Stat Soc 1958;53457- 481
Link to Article
Cox  DR Regression models and life tables. J R Stat Soc Ser A 1972;34187- 220
McCullagh  PNelder  JAeds Generalized Linear Models. 2nd ed. London, England Chapman & Hall1989;
Adams  KCorrigan  JMeds Priority Areas for National Action: Transforming Health Care Quality.  Washington, DC National Academies Press2003;
Gill  TMBaker  DIGottschalk  M  et al.  A program to prevent functional decline in physically frail, elderly persons who live at home. N Engl J Med 2002;3471068- 1074
PubMed Link to Article
Rockwood  K Frailty and its definition: a worthy challenge. J Am Geriatr Soc 2005;531069- 1070
PubMed Link to Article
Ferrucci  LGuralnik  JMStudenski  S  et al.  Designing randomized, controlled trials aimed at preventing or delaying functional decline and disability in frail, older persons: a consensus report. J Am Geriatr Soc 2004;52625- 634
PubMed Link to Article
Gill  TMAllore  HGHolford  TRGuo  Z Hospitalization, restricted activity, and the development of disability among older persons. JAMA 2004;2922115- 2124
PubMed Link to Article
American FactFinder, US Census Bureau. http://factfinder.census.gov. Accessed May 29, 2003
Szklo  M Population-based cohort studies. Epidemiol Rev 1998;2081- 90
PubMed Link to Article
Calkins  DRRubenstein  LVCleary  PD  et al.  Failure of physicians to recognize functional disability in ambulatory patients. Ann Intern Med 1991;114451- 454
PubMed Link to Article
Tinetti  MEFried  T The end of the disease era. Am J Med 2004;116179- 185
PubMed Link to Article
Calkins  DRRubenstein  LVCleary  PD  et al.  Functional disability screening of ambulatory patients: a randomized controlled trial in a hospital-based group practice. J Gen Intern Med 1994;9590- 592
PubMed Link to Article
Moore  AASiu  APartridge  JM  et al.  A randomized trial of office-based screening for common problems in older persons. Am J Med 1997;102371- 378
PubMed Link to Article
Gill  TMKurland  BF Prognostic effect of prior disability episodes among nondisabled community-living older persons. Am J Epidemiol 2003;1581090- 1096
PubMed Link to Article
Newman  ABGottdiener  JSMcBurnie  MA  et al.  Associations of subclinical cardiovascular disease with frailty. J Gerontol A Biol Sci Med Sci 2001;56AM158- M166
Link to Article
Walston  JMcBurnie  MANewman  A  et al.  Frailty and activation of the inflammation and coagulation systems with and without clinical comorbidities: results from the Cardiovascular Health Study. Arch Intern Med 2002;1622333- 2341
PubMed Link to Article
Schmaltz  HNFried  LPXue  QL  et al.  Chronic cytomegalovirus infection and inflammation are associated with prevalent frailty in community-dwelling older women. J Am Geriatr Soc 2005;53747- 754
PubMed Link to Article
Wilson  JF Frailty—and its dangerous effects—might be preventable. Ann Intern Med 2004;141489- 492
PubMed Link to Article

Correspondence

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles