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NS-2549; No. of Pages 13 International Journal of Nursing Studies xxx (2015) xxx–xxx

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Review

Frail phenotype and mortality prediction: A systematic review and meta-analysis of prospective cohort studies Shu-Fang Chang *, Pei-Ling Lin School of Nursing, College of Nursing, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan

A R T I C L E I N F O

A B S T R A C T

Article history: Received 24 August 2014 Received in revised form 22 March 2015 Accepted 3 April 2015

Aim: This study focused on older adults living in communities, primarily to investigate the relationship between physical frailty and mortality, and secondly to examine gender and age effects on the relationship between frailty and mortality. Background: The World Health Organization indicated that frailty has become an indicator of a lack of successful aging. Systematic literature reviews have yet to focus on the association between various frailty phases and mortality. Meanwhile, few studies researched gender and age effects on the correlation between physical frailty and mortality among older adults living in communities. Design: A systematic review and meta-analysis of prospective studies. Method: Frailty was assessed according to the Cardiovascular Health Study by Fried et al., who defined a frail phenotype as exhibiting the following five properties: weight loss, exhaustion, weakness, low physical activity, and mobility impairment. We included original epidemiologic population-based studies, cohort surveys, systematic reviews, and meta-analyses. Study samples included only adults aged 65 years or older who lived in communities. We excluded studies investigating hospitalised, institutionalised older adults, and those that examined disease-specific targets. We performed a pooled analysis of mortality of frailty by employing a random-effects model. Results: A total of 35,538 older adults and 7994 deaths were included in the metaanalysis. We identified 11 population-based studies that examined the relationship between mortality and frailty status in older adults. Compared with robust older adults, older people with frailty have the highest risks of mortality, followed by older people in the pre-frail phase. Older men with frailty have a higher risk of mortality than do frail older women. No age threshold for mortality risk was observed. Conclusion: Frailty is a prevalent and critical geriatric syndrome associated with decreased survival. Through geriatric assessment of frailty, essential information pertaining to mortality among older adults can be obtained. ß 2015 Elsevier Ltd. All rights reserved.

Keywords: Frailty Geriatric assessment Mortality Systematic review Meta-analysis

* Corresponding author: Tel.: +886 2 28227101x3109. E-mail addresses: [email protected] (S.-F. Chang), [email protected] (P.-L. Lin). http://dx.doi.org/10.1016/j.ijnurstu.2015.04.005 0020-7489/ß 2015 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Chang, S.-F., Lin, P.-L., Frail phenotype and mortality prediction: A systematic review and meta-analysis of prospective cohort studies. Int. J. Nurs. Stud. (2015), http://dx.doi.org/10.1016/j.ijnurstu.2015.04.005

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S.-F. Chang, P.-L. Lin / International Journal of Nursing Studies xxx (2015) xxx–xxx

What is already known about the topic?  According to studies on the prevalence of frailty, elderly people older than 65 years old and living in communities have a frailty prevalence of 5.8–35%.  Frailty influences the quality of life, institutionalisation, and death of community-dwelling elderly people.  Previous studies have investigated only the correlation between frailty and mortality. However, explorations of the effects that various phases of frailty and sex have on mortality were neglected.

What this paper adds  Compared with robust older adults, elderly people with frailty have the highest risks of mortality, followed by elderly people in the pre-frail phase.  Elderly men with frailty have higher risk of mortality than that of frail elderly women.  Age had no effect on the relationship between frailty and mortality.  Through geriatric assessment of frailty, essential information pertaining to mortality among older adults can be obtained. 1. Introduction The World Health Organization (WHO, 2002) divided aging and aged societies into the following categories: aging society (7% of population older than 65 years), aged society (14% of population older than 65 years), and superaged society (20% of population older than 65 years). Kinsella and Velkoff (2011) reported that the proportion of older people older than 65 years has reached approximately 11% worldwide and is estimated to reach 1 billion by 2030. Geriatric syndromes refer to certain clinical symptoms, such as incontinence, pain, malnutrition and cognitive impairment that are difficult to ascribe to an individual disease diagnosis (Reuben, 1991). Frailty is a geriatric syndrome that has gained attention in recent years (Ahmed et al., 2007). Yang et al. (2015) indicated that older adults (particularly those who are frail) often present with geriatric syndromes, which may be induced by acute injuries or accompanied by functional decline. Buchner and Wagner (1992) were the earliest to define frailty, describing it as a decrease in physiologic reserve and an increase in probability of disability. In older adults living in the community, it has been estimated that 18.8–50.9% of individuals are pre-frail (Chang et al., 2014; Romero-Ortuno et al., 2010; Santos-Eggimann et al., 2009) and 5.8–35% are frail (Kulmala et al., 2014a,b; Romero-Ortuno et al., 2010). Studies have shown that frailty reduces mobility, quality of life, and cognitive function (Abellan van Kan et al., 2008; Chang et al., 2014; Napoli et al., 2014) and increases the risks of falling, hospitalisation, and death (Baldwin et al., 2014; Shamliyan et al., 2013). Frailty is an essential concept in geriatrics, involving declining functioning and well-being (Fried et al., 2009). Geriatric specialists generally attribute frailty to increased vulnerability and decreased ability to maintain homeostasis

(Markle-Reid and Browne, 2003; Shamliyan et al., 2013). In the relevant literature, the conceptual definition of frailty includes physiological, psychological, and social dimensions (de Vries et al., 2011; Kelaiditi et al., 2013) and includes nutritional state, physical activity, energy, muscle strength, disability, cognitive function, and social relations and support (Dayhoff et al., 1998; de Vries et al., 2011; Fried et al., 2004; Shamliyan et al., 2013; Wolf et al., 1996). However, evaluation methods based on multidimensional concepts are complex and are time consuming. Therefore, in 2013, six countries (including the U.S. and European countries) held a consensus meeting on physical frailty (Morley et al., 2013). During the meeting, participants indicated that physical frailty is a crucial clinical syndrome that includes reduced strength, endurance, and body function, all of which cause people to be increasingly vulnerable, dependent, and at a higher risk of death (Morley et al., 2013). Previous studies have primarily applied the five physical frailty validity indicators proposed by Fried et al. (2001) to evaluate frailty in older people. However, the metrics and cut-off point standards in some studies differ slightly. Although frailty has been demonstrated to increase the risk of death (Kulmala et al., 2014a,b), the risk of death for older adults of different sexes is still debated. Berges et al. (2009) indicated that older men have higher frailty-related mortality rates than do older women; however, Kulmala et al. (2014a,b) asserted the opposite. Therefore, examining the correlation of sex with frailty and mortality rate is necessary. In addition, frailty profoundly influences the quality of life, institutionalisation, and longevity of community-dwelling older people (Avila-Funes et al., 2009; Shamliyan et al., 2013). Previous studies have investigated only the correlation between frailty and mortality (Fried et al., 2001; Graham et al., 2009; Jacobs et al., 2011; Kulmala et al., 2014a,b; Shamliyan et al., 2013). However, few studies have investigated the correlation between the mortality of frail and prefrail older adults and the mortality of prefrail older adults and robust adults. Therefore, the correlation between the mortality of older adults in different phases of frailty requires further investigation. 1.1. Aim In this study, a systematic literature review and metaanalysis were performed. We first investigated the correlation between various phases of physical frailty and the mortality of older adults living in communities. Second, we examined gender and age effects on the relationship between physical frailty and mortality. 2. Methods 2.1. Search strategy We conducted an electronic search of the MEDLINE and CINAHL databases and the Cochrane Library, reviewing data from January 2001 to July 2014. Search term combinations were ‘‘frailty’’ OR ‘‘frail’’ and ‘‘mortality’’ OR ‘‘death rate’’ OR ‘‘die’’ OR ‘‘died’’ OR ‘‘survival’’ and

Please cite this article in press as: Chang, S.-F., Lin, P.-L., Frail phenotype and mortality prediction: A systematic review and meta-analysis of prospective cohort studies. Int. J. Nurs. Stud. (2015), http://dx.doi.org/10.1016/j.ijnurstu.2015.04.005

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NS-2549; No. of Pages 13 S.-F. Chang, P.-L. Lin / International Journal of Nursing Studies xxx (2015) xxx–xxx

‘‘older people’’ OR ‘‘older’’ OR ‘‘geriatric’’ OR ‘‘senior’’. In addition, references from reviews and selected articles were reviewed for potentially relevant citations. Only fulllength published research articles (original articles) were considered.

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survival. We adopted the adjusted relative measures if both adjusted and crude (unadjusted) estimates were provided. Any disagreement in abstracted data was resolved by a third reviewer. 2.4. Quality assessment

2.2. Inclusion and exclusion criteria Frailty was defined according to the construct previously validated by Fried et al. in the Cardiovascular Health Study (Fried et al., 2001). Fried et al. proposed the following five clinical indicators of frailty: weight loss, the unintentional weight loss of more than 10 pounds in the last year or 35% of body weight loss in prior year; exhaustion, using the CES-D Depression Scale, identified by the questions, ‘‘I felt that everything I did was an effort’’ and ‘‘I could not get going’’; physical activity, based on the short version of the Minnesota Leisure Time Activity questionnaire, with a weighted score of physical activity calculated for each gender and kilocalories expended per week determined; walk time, based on time required to walk 15 feet (adjusted for gender and standing height); and grip strength, stratified by gender and body mass index (BMI) quartiles. In CHS indicators, the lowest quartile stratified by gender was used as cut-off point for physical inactivity, strength, and walking speed. Among these five indicators, when three or more are present, the person is classified as frail; when one or two indicators is present, the person is classified as pre-frail; and when no indicators apply, the person is classified as robust. We reviewed all of the literature pertaining to the five indicators of frailty proposed by Fried et al. (2001). The methods for measuring frailty differ slightly among studies; these differing methods include variations in the calculation of weight change, walking distance, calories expended during physical activity, and grip strength. We included original epidemiologic population-based studies, cohort surveys, systematic reviews, and meta-analyses published between January 2001 and July 2014. To be eligible, studies must have reported the association between frailty phenotype and survival. Study samples included only older adults 65 years old or older who lived in communities. We excluded literature reviews, letters to the editor, book chapters, and dissertations and theses. We also excluded studies investigating hospitalised and institutionalised older adults; studies examining disease-specific targets; experimental studies with the purpose of determining frailty status and reducing mortality; and studies with follow-up periods shorter than one year, various definitions of frailty, duplicate cohorts, or a cross-sectional methodology. Original research articles were obtained using electronic searches. 2.3. Data extraction Two researchers independently evaluated the studies and abstracted the data. We abstracted frailty definitions from each study and analysed the sampling strategies; inclusion and exclusion criteria; sample size; prevalence; incidence; and adjusted relative measures of the association between frailty, pre-frailty, or robust condition and

This study has followed the PRISMA guidelines and three methods were used to analyse the quality of the literature. First, we referred to the guide published by the Agency for Healthcare Research and Quality, which assesses the quality of a study according to the risk of bias, consistency, and the precision of survival estimates (Agency for Healthcare Research and Quality, 2014). We reviewed the evidence strength of each study on frailty and mortality rates according to the guide’s instructions. Second, we examined whether each study performed confounding factor adjustment. Finally, we classified the evidence level of each study according to the Oxford classification principles (Oxford Centre for Evidence-Based Medicine, 2011) and the study design. Studies that received lower scores according to these three methods were classified into a lower level during analysis. 2.5. Statistical analysis Hazard ratios (HRs) and their 95% CIs in terms of the comparison among frailty status groups were extracted for further meta-analysis. Summary estimates of HRs were calculated with a random-effects model, which assumes that the true underlying effect varies among studies. The summary HRs obtained from subgroups of studies grouped by gender and age (using 80 years as the cut-off point) were compared using a mixed-effects model in which the subgroup levels were fixed (e.g. no another sex can be defined other than male and female; or all patients aged either more than 80 or less than 80 years old) and true effects among studies were random. The statistical heterogeneity across studies was assessed with Cochran’s Qwithin using chi-square and I2 statistics, the latter of which measure the proportion of overall variation that is attributable to between-study heterogeneity. For the I2 statistics, >50% indicates moderately heterogeneous results and >75% is considered highly heterogeneous (Higgins et al., 2003). Potential publication bias was assessed with the funnel plot and Egger’s intercept test (Egger et al., 1997). All data analyses were conducted with CMA 2.2 (Comprehensive meta-analysis). 3. Results Fig. 1 depicts the details of the literature review. Among the initial 38 studies identified, studies were excluded for the following reasons: lacked data (hazard ratio), included inpatient or nonolder populations; followed up lasting less than one year; used different definitions of frailty; used duplicate cohorts and cross-sectional method. After excluding these studies, we included 11 prospective cohort studies that were agreed upon by the two reviewers. According to the guide published by the Agency for Healthcare Research and Quality (2014), the assessment

Please cite this article in press as: Chang, S.-F., Lin, P.-L., Frail phenotype and mortality prediction: A systematic review and meta-analysis of prospective cohort studies. Int. J. Nurs. Stud. (2015), http://dx.doi.org/10.1016/j.ijnurstu.2015.04.005

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Identified from database search (N=1824) The Cochrane Library (n =2) Medline (n =629) CINAHL (n =74) PubMed (n =813) OVID (n =306)

Duplicates or did not satisfy criteria (N=1773)

Records included for review of full text (N=51)

Could not extract relative RR or HR estimates (N= 13) 1. OR (n = 11) 2. Meta (n = 2)

Retrieved for eligibility (n = 38) Excluded (n = 27): 1. Inpatient or Nonelderly population (n = 3) 2. Less than one year of the follow-up (n = 1) 3. Different definitions of frailty (n = 18) 4. Not divided into three groups (5)

Used in meta-analysis (n = 11)

Fig. 1. Flowchart for study selection.

results on the quality of 11 studies indicated that the strength of evidence regarding the frailty and mortality rate for each study was classified as high grade. Table 1 shows that each study performed confounding factor adjustment. Finally, according to the Oxford classification principles (Oxford Centre for Evidence-Based Medicine, 2011), all 11 studies were categorised as cohort studies and were therefore classified as having a 2b level of evidence in the B grade of recommendation. 3.1. Study sample Although all studies defined physical frailty according to the five indictors proposed by Fried et al. (2001), the measurement cut-off points differed slightly among studies. Among 11 studies, four studies applied cutoff

points derived from original Fried measures, and the remaining seven studies applied different cutoff points for certain indicators. Table 1 summarises the characteristics of the 11 studies. In total, these studies included 35,538 people and recorded 7994 deaths over a mean follow-up duration of 6.05 years (SD = 3.05 years). One of these studies described two distinct cohorts, the follow-up periods of which differed (Fried et al., 2001). Two studies provided data for both men and women (Berges et al., 2009; Kulmala et al., 2014a,b), two studies included only men (Cawthon et al., 2007; Ensrud et al., 2009), one study included only women (Ensrud et al., 2007), and the six studies provided data derived from the combined results from both sexes. In addition, two studies stratified the analysis by age, using 80 years as the cutoff point (Cawthon et al., 2007; Ensrud et al., 2007).

Please cite this article in press as: Chang, S.-F., Lin, P.-L., Frail phenotype and mortality prediction: A systematic review and meta-analysis of prospective cohort studies. Int. J. Nurs. Stud. (2015), http://dx.doi.org/10.1016/j.ijnurstu.2015.04.005

Population

Sample size (no. of death)

Sex

Age

Length of follow up

Subgroup

HR (95% CI) prefrail/robust

HR (95% CI) frail/robust

Adjustment

1. Avila-Funes (2008)

Three-City Study (3C)

6078 (316)

F/M

365

4 years

None

1.17 (0.90–1.54)

1.21 (0.78–1.87)

Adjusted for sex, education level, income, smoking status, alcohol use, number of chronic diseases, selfreported health, Center for Epidemiologic Studies-Depression scale score (excluding the two questions included in the frailty definition), Mini-Mental State Examination score, and baseline disability (mobility, IADL, and ADL)

2. Abizanda (2013)

FRADEA

993 (105)

F/M

>70

534  153 days

None

3.4 (1.0–12.8)

5.5 (1.5–20.2)

Adjusted for age, sex, Barthel Index, and Charlson Index

3. Berges (2009)

Hispanic Established Population for the Epidemiologic Study of the Elderly (HEPESE)

1996 (892)

F/M

365

10 years

Women Men

1.29 (1.05–1.60) 1.46 (1.17–1.83)

1.92 (1.39–2.65) 3.04 (2.16–4.28)

Adjusted for all covariates (Age, Married, Education, BMI, Smoker, Heart attack, Stroke, Hypertension, Cancer, Hip fracture, Diabetes, Grip strength, Walk time, PASE)

4. Cano (2012)

The Hispanic Established Populations for the Epidemiological Study of the Elderly

1815 (690)

F/M

367

10 years

None

1.39 (1.17–1.64)

1.97 (1.53–2.55)

Adjusted for all covariates (age, gender, education, marital status, diabetes, heart attack, stroke, cancer, hip fracture, hypertension, arthritis, Cognitive Impairment)

5. Cawthon (2007)

MrOS

5993 (669)

M

365

4.7 years

Overall Cohorty Age

Frail phenotype and mortality prediction: a systematic review and meta-analysis of prospective cohort studies.

This study focused on older adults living in communities, primarily to investigate the relationship between physical frailty and mortality, and second...
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