Frailty predictors and outcomes among older patients with cardiovascular disease: Data from Fragicor

Archives of Gerontology and Geriatrics 61 (2015) 1–7

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Frailty predictors and outcomes among older patients with cardiovascular disease: Data from Fragicor ˆ ngela T. Paes d, Esther Tinoco a, Alberto Frisoli Jr.a,b,*, Sheila Jean McNeill Ingham b,c, A a a a Andrea Greco , Norma Zanata , Vitor Pintarelli , Izo Elber a, Jairo Borges a, Antonio Carlos Camargo Carvalho b a

Cardiogeriatric Unit, Cardiology Division, Federal University of Sa˜o Paulo, Sa˜o Paulo, Brazil Cardiology Division, Federal University of Sa˜o Paulo, Sa˜o Paulo, Brazil c Physical Medicine and Rehabilitation, Federal University of Sa˜o Paulo, Sa˜o Paulo, Brazil d Statistics Department, Federal University of Sa˜o Paulo, Sa˜o Paulo, Brazil b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 7 June 2014 Received in revised form 6 March 2015 Accepted 6 March 2015 Available online 14 March 2015

The aim of this study was to evaluate predictive factors for frailty among older outpatient adults with cardiovascular disease (CVD) and to assess the predictive value of frailty in regard to mortality, disability and hospitalization at 1-year follow-up. A prospective cohort study was carried out with subjects over 65 years of age from an outpatient Cardiology clinic, with at least one CVD. At baseline, we classified frailty as proposed by Fried, i.e.; unintentional weight loss (10 lbs in the past year), self-reported exhaustion, weakness (measured by grip strength), slow walking speed, and low physical activity. A frail person was defined by the presence of three or more criteria, prefrail by one or two and robust by the absence of them. Disability, previous hospitalizations, falls, morphometric and socio-demographic variables were collected; as well as the presence of CVD and hemodynamic parameters (HP): systolic (SPB) and diastolic blood pressure (DBP), heart rate (HR) and ejection fraction (EF). At 1-year follow-up, the outcomes assessed were: disability, number of hospitalizations and death. 172 subjects were included in this study with a mean age of 77 years old. The prevalence of frail was 39.8%, prefrail 51.5% and robust was 8.7%. Among the CVD and HP evaluated, myocardial infarction (MI), presence of three or more CVDs, lower SPB and DBP were significant and independent factors associated with the frailty phenotype. At 1-year follow up, frailty was an independent predictor for disability (Odds Ratio (OR): 3.94 (1.59–9.75); p = 0.003) and it increased death probability by three times if compared to the robust group. In conclusion, older outpatients with CVD have a higher probability to be frail than older adults who do not have a CVD. Low SPB and DBP must always be taken into consideration due to their high association with frailty. It is also important to diagnose frailty in this population due to the high association with mortality and disability. ß 2015 Elsevier Ireland Ltd. All rights reserved.

Keywords: Fragility Cardiovascular disease Disability Mortality

1. Introduction Frailty is a very heterogeneous clinical syndrome characterized by a diversity of signs and symptoms; it is associated with a decreased reserve or disturbances in the systemic reactions to stress (Fried et al., 2001) and it promotes a greater susceptibility to

* Corresponding author at: Rua Pedro de Toledo, 1010, Sao Paulo, SP 04039-002, Brazil. Tel.: +55 11 5084 6041; fax: +55 11 5575 5710. E-mail address: [email protected] (A. Frisoli Jr.). http://dx.doi.org/10.1016/j.archger.2015.03.001 0167-4943/ß 2015 Elsevier Ireland Ltd. All rights reserved.

disability, falls, hip fractures, hospitalization and death (Bilotta et al., 2010; De Lepeleire, Iliffe, Mann, & Degryse, 2009; Fried et al., 2001; Gill, Gahbauer, Han, & Allore, 2010; Rockwood & Mitnitski, 2007). Prior studies have demonstrated that frailty status in older people increases the mortality rate by six (18%) when compared to robust (3%) older people after a 7-year follow up period (Fried, Ferrucci, Darer, Williamson, & Anderson, 2004; Fried et al., 2001). Prevalence of frailty among elderly adluts from the community varies significantly according to the continent, age and ethnic groups. In subjects aged 65 years or more it ranges from 7 to 12% in the U.S. (Fried et al., 2001), increasing to 21–48% in Latin American

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and Caribbean countries, while, intermediate numbers are seen in some European countries (Alvarado, Zunzunegui, Beland, & Bamvita, 2008; Santos-Eggimann, Cuenoud, Spagnoli, & Junod, 2009). CVDs, very prevalent in the older population, have emerged as a strong risk factor for frailty (Afilalo, Karunananthan, Eisenberg, Alexander, & Bergman, 2009). Recent cross sectional studies, evaluating older people from the community, have demonstrated an association between CVD and frailty (Bandeen-Roche et al., 2006; Chin, Dekker, Feskens, Schouten, & Kromhout, 1999; Di Napoli, Papa, & V, 2002; Klein, Klein, Knudtson, & Lee, 2005; Newman et al., 2001; Woods et al., 2005). Also, in prospective cohort studies CVDs were associated with incidental frailty (Bandeen-Roche et al., 2006; Chin et al., 1999; Klein et al., 2005; Newman et al., 2001; Woods et al., 2005). Specific CVDs (coronary artery disease, stroke and hypertension (HTN)) among older women who were not frail at baseline, were each predictive of incident frailty over a 3-year follow-up. In addition to this, subclinical cardiovascular alterations detected by noninvasive testing (echocardiographic left ventricular hypertrophy, regional wall motion abnormalities, electrocardiographic abnormalities, systolic HTN, carotid intima-media thickness, magnetic resonance imaging evidence of stroke, and ankle arm index <0.8), were each associated with frailty and mortality (Newman et al., 2001). One of the reasons for this association may be explained by common biologic pathways that CVD and frailty share: inflammation, higher levels of factor VIII, D-dimer, C-reactive protein and thrombosis (Di Napoli et al., 2002; Mora, Rifai, Buring, & Ridker, 2006; Smith et al., 2005; Tzoulaki et al., 2007). However, the prevalence of frailty and its consequences among outpatients with CVD is still unknown. This knowledge could be important to shed light on the association between frailty and CVDs, and if this association could alter the rates of mortality, hospitalization, falls and disability. To the best of our knowledge no studies have yet evaluated the prevalence of frailty (Cardiovascular Health Study frailty criteria) in an older outpatient population with CVD. The aim of our study was to evaluate the association between CVD and HP with frailty among an older outpatient population and to assess the predictive value of frailty in regards to mortality, disability and hospitalization at a 1-year follow-up. We hypothesized that patients with more CVDs, and worse HP, individually or in an interaction fashion, will be associated with frailty. Secondly, we believe, that the presence of frailty will predict a higher risk for death, incidental hospitalization and disability among elderly patients with CVD.

A total of 204 individuals were assessed in a Cardiology outpatient clinic and 32 were excluded. One hundred seventy two patients were then included at baseline and 69 subjects were lost to follow-up (Fig. 1). 2.3. Baseline evaluation At baseline, morphometric and socio-demographic variables were evaluated: marital status, personal income, level of education (illiterate, lower than or more than 9 years of education) and number of medications used. CVDs evaluated were: diastolic or systolic heart failure (HF), peripheral artery disease (PAD), atrial fibrillation (AFib), previous MI (>3 months), Angina pectoris (AP), HTN and CVD3+ that was defined as the presence of three or more CVDs. All diagnoses were made according to the American Heart Association (AHA) Guidelines of Diagnosis (American College of Cardiology et al., 2013; Jessup et al., 2009; Wenger, 2012) with exception of PAD that was diagnosed by duplex ultrasound of lower limbs or ABI results described in the medical charts. Hemodynamic parameters evaluated were: SBP and DBP, HR and EF categorized by quartiles. Cognitive status by mini mental state examination (Folstein et al., 1975); presence of comorbidities (chronic obstructive pulmonary disease (COPD), diabetes mellitus, dyslipidemia, non dialitic kidney failure, osteoarthritis and osteoporosis) and previous hospitalization were also assessed. Alcohol intake was classified as high (more than 2 drinks a day), moderate (1 or 2 drinks a day), low (less than 1 drink a day) and no intake. Smoking was considered positive if it was current or if stopped less than 4 years prior to the interview. Disability was assessed by the number of tasks performed in activities of daily living (ADL) and instrumental activities of daily living (IADL); the cut point for disability was 5 for ADL and 25 for IADL (Abou-Raya & Abou-Raya, 2009; Katz, Downs, Cash, & Grotz, 1970; Katz, Ford, Moskowitz, Jackson, & Jaffe, 1963; Lawton & Brody, 1969). Weight, height and body mass index (BMI), arterial blood pressure (measured 3 times in the supine position) and HR (measured 3 times in the supine position) were also evaluated.

204 outpatients were invited to participate in the study

2. Methods Exclusion criteria (n = 32) Moderate or severe dementia Chronic infectious disease Parkinson’s disease Cancer in last 5 years

2.1. Design, setting and participants Fragicor (FRAgilidade em idosos com doenc¸as CardiOvasculaRes/Frailty in an older population with CVD) is a prospective cohort study that aimed at evaluating frailty status and its outcomes in an older population with cardiovascular disease. The Ethical Review Board at our Institution approved this study and informed written consent was obtained from all participants.

172 Included in the study

2.2. Inclusion and exclusion criteria Inclusion criteria were: adults from a Cardiology outpatient clinic with at least one CVD, age over 65 years old, both genders and all ethnic groups. We considered, as exclusion criteria, the majority of clinical conditions or diseases that could confound any frailty criteria or physical activity, as follows: unstable medical conditions, any form of cancer in the last five years, chronic renal failure in need of dialysis, chronic liver disease, Parkinson’s disease, severe infectious disease requiring hospitalization in the last month, moderate or severe dementia classified by the MMSE (mini-mental state examination) (Folstein, Folstein, & McHugh, 1975; Fried et al., 2001).

Lost to follow-up (n = 69) Did not want to continue Could not be contacted Was not able to answer the questions by phone

103 completed the one year follow-up or died Fig. 1. Study flowchart.

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Frailty phenotype was determined by Fried’s criteria (Fried et al., 2001). Frailty was diagnosed by the presence of 3 or more, of the following criteria: Unintentional weight loss of 10 pounds in the prior year or, at follow-up, loss of 5% of body weight in the prior year (by direct weight measurement); Weakness: If the strongest of the three measures of grip strength of the dominant hand was lower than the cut off; Exhaustion: Identified by two questions from the CES–D scale ‘‘ (a) I felt that everything I did was an effort; (b) I could not get going. The question is asked ‘‘How often in the last week did you feel this way?’’ 0 = rarely or none of the time (1 day), 1 = some or a little of the time (1–2 days), 2 = a moderate amount of the time (3– 4 days), or 3 = most of the time. Subjects answering ‘‘2’’ or ‘‘3’’ to either of these questions are categorized as frail by the exhaustion criterion." (Orme, Reis, & Herz, 1986); Low walking speed: if the walking velocity, based on the time to walk 15 feet, was lower than the cut off; Low physical activity: If physical activities, based on the short version of the Minnesota Leisure Time Activity questionnaire (Lustosa et al., 2011; Taylor et al., 1978) were lower than the cut off. Prefrail was diagnosed when 1 or 2 criteria were present and robust when no criterion was present. We considered the same cut off values for all frailty criteria described by Fried (Fried et al., 2001). 2.4. One-year follow-up At one-year follow-up, subjects, caregivers or relatives were contacted for a structured interview, by phone, by an investigator blinded to the baseline data. If the subject or his/her caregiver was not reached by the first phone call, a maximum of four calls, with a one-week interval, was allowed. Adverse outcomes evaluated after one year were: incidental disability, hospitalization and death. Mortality was evaluated by phone call and confirmed by fax or e-mail of the death certificates. Two certificates were not received. Incidental disability was diagnosed in patients that: (i) were not disabled at baseline but at the one year follow-up presented with a score of ADL <5 and or IADL <25 (Abou-Raya & Abou-Raya, 2009; Katz et al., 1970; Katz et al., 1963; Lawton & Brody, 1969) or (ii) by the loss of one or more tasks of ADL and/or IADL among patients with disability diagnosed at baseline (Fried et al., 2001). Hospitalization was considered positive for any hospital stay over 24 h. This information was self-reported and obtained by the phone calls described above. Only the number of hospital commitments was considered. 2.5. Statistical analysis Qualitative variables are expressed as absolute and relative frequencies. Quantitative data are summarized as means, medians, standard deviations (SD), minimum and maximum values. To

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compare the three groups (robust, prefrail and frail) the chi-square test for qualitative variables and analysis of variance (ANOVA) for quantitative variables were used. Logistic regression analyses were performed to evaluate the association among variables with frailty status at base line and to predict the influence of frailty on the outcomes. These methods were also used to analyze the relationships between other variables. In the case of two quantitative variables, scatter diagrams and correlation coefficients were used. SAS version 9.0 (SAS Institute, Cary, NC, USA) was used for all statistical analysis. Significance was set at p < 0.05. 3. Results 3.1. Baseline characteristics At baseline, 172 subjects were included, with a mean age of 77 years old. Main characteristics are shown in Tables 1 and 2. Of these, 37.8% were frail, 51.2% were prefrail and 11% robust. Frail individuals were significantly older, had lower MMSE scores, and took more medications than the others groups. The frail group also had significantly more subjects with CVD3+, disability, illiteracy and previous MI compared to prefrail and robust groups. Among HP, the lowest quartiles of systolic (LqSBP < 120 mmHg) and diastolic (LqDBP < 70 mmHg) blood pressures were significantly and independently associated with frailty; moreover, there was not an interaction between LqSBP and LqDBP. In addition to this, frail subjects reported a higher number of hospitalization episodes in the previous year (nearly five episodes more; p = 0.001) (Table 2). In unadjusted and adjusted regression analyses for frailty, continuous significant variables were: age, MMSE (1 point), years of education (1 year), number of medications (1 med), previous hospitalizations (1 event). Significant categorical variables were previous MI and illiteracy (Table 3). In an unadjusted regression analysis previous MI, previous hospitalization and illiteracy were the higher predictors of frailty followed by age, lower scores in MMSE, less years of education and number of medications in use. After adjusting for the significant variables (age, education and female gender), cognitive decline, previous hospitalization and MI remained significant and independent predictors for frailty at baseline among older outpatients with CVD (Table 3). 3.2. Frailty criteria Among the frailty criteria evaluated, low energy (52.9%), low walking speed (49.4%) and weakness (58.1%) were significantly more prevalent than weight loss (20.3%) and exhaustion (22.7%) in the total group (n = 172). In the frail group, low energy occurred more frequently (90.8%), followed by weakness (89.2%) low

Table 1 Characteristics of the groups at baseline (continuous variables: average  SD).

Age (years) Family income Personal income MMSE EF (%) # Medications # Hospitalizations in the previaous year BMI (kg/m2) SBP (mmHg) DBP (mmHg) HR (bpm) # Falls in last 12 months

Total (n = 172)

Frail (n = 65)

Prefrail (n = 88)

Robust (n = 19)

p

77.13  5.86 3.09  1.69 1.62  1.13 23.48  5.0 50.18  16.47 5.64  2.48 0.53  0.84 26.29  5.22 138.80  24.9 80.76  12.57 71.58  16.27 1.37  3.62

78.77  5.82 3.03  1.84 1.43  0.96 21.92  5.24 48.32  17.06 6.31  2.26 0.85  1.05 26.33  5.89 135.77  30.14 77.97  14.15 71.87  17.78 2.52  5.9

76.07  4.50 3.15  1.62 1.73  1.23 24.54  4.68 51.04  15.52 5.28  2.62 0.36  0.58 26.49  4.99 139.88  21.48 82.53  10.89 70.98  15.57 0.71  1.69

76.47  4.50 2.93  1.52 1.77  1.10 23.95  4.73 53.80  19.11 4.94  2.10 0.13  0.34 25.10  3.26 144.22  18.81 82.22  11.66 73.47  14.57 1.8  1.69

0.016 0.853 0.245 0.005 0.572 0.018 0.001 0.622 0.087 0.388 0.837 0.168

SD = standard deviation; MMSE = mini mental status exam; EF = ejection fraction; BMI = Body mass index; SBP = Systolic blood pressure; DBP: Diastolic blood pressure; HR = Heart Rate; bpm = beats per minute. One income is equivalent to US$ 300.00/month. P value refers to the difference between the three groups (frail, prefrail and robust). Bold values mean that they are statistical significant.

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Table 2 Characteristics of the groups at baseline (categorical variables: %).

Female Caucasian Illiterate <9 years of education 9 years of education Widowed Disability ADL disability IADL disability Hypertension Previous MI Angina CHF Atrial fibrillation EF < 45% Previous Stroke Dyslipidemia PAD Kidney failure COPD Osteoarthritis Osteoporosis Previous history of Cancer Diabetes Dementia CVD 3+ Falls Previous hospitalization

3.3. One-year follow-up

Total (n = 172)

Frail (n = 65)

Prefrail (n = 88)

Robust (n = 19)

p

62.2 55.3 18.2 75.9 5.9 43.5 42.9 18 42.9 84.2 24.0 21.1 68.4 19.4 39.8 12.3 43.3 15.8 14.0 14.6 29.4 20 11.1 33.3 40.4 34.9 35.3 41.8

67.7 60.3 27.7 67.7 4.6 50 64.1 30.8 64.9 81.5 32.3 18.5 78.5 18.6 43.9 10.8 43.1 16.9 18.5 13.8 29.7 23.4 13.8 40.0 50.8 46.9 38.1 55.4

56.8 56.3 14.0 79.0 7.0 39.1 34.5 11.4 34.5 82.8 20.7 21.8 58.6 23.1 36.2 11.5 41.4 12.6 12.6 17.2 28.7 18.4 11.1 29.9 33.3 29.1 29.3 37.1

68.4 31.3 5.3 89.4 5.3 42.1 10.5 5.3 10.5 100 10.5 26.3 78.9 5.6 40.0 21.1 52.6 5.3 5.3 5.3 31.6 15.8 0 26.3 36.8 21.1 66.7 12.5

0.328 0.560 0.027 0.222 0.114 0.022 <0.001 0.114 <0.001 0.148 0.018 0.713 0.018 0.228 0.798 0.498 0.682 0.303 0.303 0.409 1.00 0.680 0.236 0.323 0.091 0.030 0.229 0.005

ADL = activities of daily living; IADL = instrumental activities of daily living; MI = Myocardial infarction; History of cancer: considered cured prior to 5 years of the beginning of the study. CHF = Congestive heart failure; EF = ejection fraction; PAD = peripheral artery disease; COPD = chronic obstructive pulmonary disease; CVD 3+: cardiovascular diseases comorbidities (three or more of Hypertension, CHF, atrial fibrillation, angina and MI). P value refers to the difference between the three groups (frail, prefrail and robust). Bold values mean that they are statistical significant.

walking speed (86.2%), exhaustion (47.7%), and weigh loss (32.3%). In an unadjusted logistic regression analysis, with frailty at baseline as the outcome, low energy presented an OR of 23.04 (9.0– 58.78), weakness 12.82 (5.34–30.76), low walking speed 16.73 (7.31–38.10), exhaustion 11.28 (4.73–26.91) and weight loss 3.17(1.40–68.1). Even after adjusting for age, education, MI, previous hospitalizations and medications, all frailty criteria remained significant predictors for frailty.

At one-year follow up, 8.7% of the population died, 40% presented with a loss in ADL or IADL scores, 30.4% reported at least one fall and 27.2% had one or more hospitalization episodes. The number of falls and hospitalization were higher in the frail group, but this was not significant (Table 4). Of the group that reported deterioration in their physical function, 36.1% presented a new diagnosis of disability and 63.9%, a worsening disability. The frail group had twice as many subjects with a decline in their disability status when compared to the prefrail group and four times as many when compared to the robust group (p = 0.006; Table 4). Almost 15% (n = 6) of the subjects with a disability at baseline died during follow up, and this could have underestimated the prevalence of subjects with a worse disability at 1 year. Subjects that lost one or more tasks in ADL or IADL were significantly older, had a lower level of education, were taking more medications, had less income and lower MMSE scores at baseline. Presence of frailty increased death probability by three times when compared to the robust group and almost 1.5 times when compared to the prefrail group. In unadjusted and adjusted regression analyses, frailty at baseline presented a positive association with disability, death and hospitalization; however, association with death and hospitalization did not reach statistical significance (Table 5). No frailty criteria presented a significant association, individually or in an interaction fashion, with death at one year. 4. Discussion This study evaluated the prevalence of frailty and adverse outcomes among community-dwelling older adults with CVD. We have described a high prevalence of frailty together with a low prevalence of robust subjects. This result is contrary to the one found by Moreira in community dwelling older adults over 65 years of age in Rio de Janeiro, Brazil (Moreira & Lourenc¸o, 2013). A few reasons could explain this: (I) Personal and family income were very low in the frail, prefrail and robust groups. This portrays a very poor population with a low probability of access to a balanced diet and adequate health care. Previous studies have documented the association of poverty and food intake, as well as the increase in frailty prevalence and health problems (Huisman et al., 2004; Macuco et al., 2012; Miller et al., 1996). In a recent US survey, frail (OR 4.7;

Table 3 Univariate and multivariate regression analyses (adjusted for age, education and female gender) for frailty at baseline. Multivariate

Univariate

LqDBP (<70 mmHg) LqSBP (<120 mmHg) SBP and DBP Disability Hospitalizations CVD3+ Previous MI Medication Age (years) MMSE <9 years of education 9 years of education

OR

CI (95%)

p

OR

CI (95%)

p

21.50 10.20 9.50 4.12 2.63 2.42 2.41 1.20 1.08 0.90 0.39 0.2

3.88–118.93 1.87–55.38 2.00–45.05 2.13–7.95 1.29–5.35 1.26–4.62 1.41–4.12 1.05–1.37 1.02–1.14 0.85–0.96 0.18–0.88 0.06–0.84

<0.001 0.007 0.005 <0.001 0.008 0.007 0.001 0.007 0.005 0.002 0.023 0.026

11.47 2.66

1.91–68.77 1.05–6.70

0.008 0.038

2.37 2.24 2.98 3.01

0.99–5.67 1.04–4.80 1.06–8.35 1.09–8.34

0.053 0.039 0.038 0.033

0.92

0.84–1.00

0.059

OR = odds ratio; CI = confidence interval; LqSBP = Lowest quartile systolic blood pressure; LqDBP = Lowest quartile diastolic blood pressure; MMSE = mini-mental state examination; hospitalization (number of hospitalizations in last year); CVD 3+: cardiovascular diseases comorbidities (three or more of Hypertension, CHF, atrial fibrillation, angina and MI); MI = Myocardial infarction. Bold values mean that they are statistical significant.

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Table 4 Prevalence of death, disability, hospitalization and falls at one-year follow-up among the frail, prefrail and robust groups.

Death (n = 9) Worsening physical function (n = 36) Hospitalization (n = 25) Falls (n = 28)

Total % (n = 103)

Frail % n = 41)

Prefrail % (n = 53)

Robust % n = 9)

p

8.7 34.9 24.3 27.2

14.6 60.6 35.3 32.4

3.8 30 21.6 31.4

11.1 14.3 28.6 14.3

0.125 0.006 0.410 0.655

P value refers to the difference between the three groups (frail, prefrail and robust). Bold values mean that they are statistical significant.

95% CI: 1.7–12.7) and prefrail (OR 2.1; 95% CI: 0.8–5.8) people were more likely to report being food deprived than robust people (Smit, Winters-Stone, Loprinzi, Tang, & Crespo, 2013). (II) A low level of education is an important risk factor for negligent self-care and poor health and, consequently, an increased risk for frailty. We could observe this in our population, as nearly 30% of the frail group was illiterate. Poverty is usually associated with reduced years of education, and this, in turn, is associated with decreased medication use and decreased use of clinical preventive services and increased rates of comorbidities (Huisman et al., 2004; Zarulli, Marinacci, Costa, & Caselli, 2013). (III) Dementia and disability were both very common in our population, and they are associated with mortality, low quality of life and other bad outcomes that may lead to a failure to prosper or to a loss of the capacity to react to injuries. Dementia and disability share predisposing factors, like atherosclerosis and high levels of inflammatory cytokines, which may also participate in the etiology of frailty. Recently, Gray et al., in a prospective population-based cohort of 6.6 years with 2619 older people, demonstrated that frailty was associated with a higher risk of developing non-Alzheimer dementia (OR 2.57; 95% CI: 1.08–6.11), but not for all-cause dementia (OR 1.20; 95% CI: 0.85–1.69) or for Alzheimer Disease (OR 1.08; 95% CI: 0.74–1.57) (Gray et al., 2013). We did not differentiate between the different types of dementia; however, the higher prevalence of CVD suggests a higher risk of atherosclerosis raising the probability of non-AD dementia. (IV) Sarcopenia and cachexia: Sarcopenia has recently been defined as a syndrome of muscle loss in addition to low walking speeds (equal to or less than 1 m/s or to a distance of less than 400 m walked in a 6 min walk test) (Morley et al., 2011). Cachexia is conceptualized as loss of more than 5% of body weight over 12 months, or less, in the presence of a chronic illness such as CHF, chronic obstructive pulmonary disease, kidney failure, cancer with anemia, inflammation or low levels of serum albumin (Evans et al., 2008). Both syndromes are frequent in the older population, especially in the very old (Evans et al., 2008). They may have some overlap and may be present in the same subject at the same time, especially, among older people with HF and other CVD. The definition criteria for both syndromes are similar to certain frailty criteria that were found in our subjects, such as

weakness in 89.2%, low walking speed in 86.2% and weight loss in 32.3%. Progressive mobility restriction and loss of muscle mass and body weight are very frequent in older people with HF. This could suggest that the prevalence of sarcopenia and cachexia must be high enough to increase the incidence of frailty in this population. To the best of our knowledge, this is the first time that low SPB and DBP have been shown to be independent factors associated with frailty. Previously, low blood pressure (systolic or diastolic) has been associated with mortality and disability. A recent longitudinal study with 1466 older adults observed that low DBP (70 mmHg) was associated with an increased all-cause mortality risk. This relation was particularly strong in subjects with frailty risk factors: age (>80 years), lower levels of both physical and cognitive functioning (Post Hospers, Smulders, Maier, Deeg, & Muller, 2014). Earlier, a longitudinal study with twelve thousand older adults demonstrated that low DBP for men between 64 and 85 years old and older than 85 years was inversely associated with mortality. Similar results were described with low SPB for men older than 85 years old (Satish, Freeman, Ray, & Goodwin, 2001). Low blood pressure may be the result of a neurodegenerative disease process causing impaired blood pressure auto regulation or behavioral changes, such as dietary changes and weight loss (Feldstein, 2012). Low blood pressure may cause a dysfunctional vascular system, may compromise perfusion of vital organs, including the brain, with subsequent decline in cognitive and physical functioning (Iadecola & Davisson, 2008; Strandgaard & Paulson, 1994). Recent findings from the National Health and Nutrition Examination Survey analysis showed that the association between low systemic BP and cognitive decline (Odden, Peralta, Haan, & Covinsky, 2012) was most pronounced in those who were physically frail (Sabayan et al., 2012). Frailty may be associated with the consequences of multiple systems deterioration and dysfunction of the cardiovascular system auto regulation, represented by the low systemic blood pressure. Additionally, the elevated rate of cardiovascular comorbidities (3 or more) in the frail group, suggests that they are more likely to have arterial diseases with inflammation, coagulation disorders and lower rates of peripheral oxygenation (Crucet et al., 2013; Parathath et al., 2011). The high frequency of HF in our sample (80%) may corroborate these findings. HF is a very important predictor of hospitalization, health deterioration and death. In a

Table 5 Adjusted and unadjusted logistic regression analyses for frailty at baseline in regard to disability/worsening disability, death and hospitalization after one year (comparing to robust group). Adjusted#

Disability/worsening disability Hospitalization Death

Unadjusted

OR

CI (95%)

p

OR

CI (95%)

p

3.94 1.88 3.37

1.59–9.75 0.74–4.81 0.79–14.33

0.003 0.18 0.10

3.05 2.56 2.94

1.14–3.18 0.59–11.04 0.64–13.41

0.03 0.20 0.16

Bold values mean that they are statistical significant. # Significant variables: age, education and female gender.

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prospective cohort, from Canada, individuals with newly diagnosed HF presented a median survival of 2.4 years, with a 1-year mortality of 33.1% (Morse et al., 2008; Novack et al., 2010). In the USA, mortality rates, following a hospital admission for patients with a primary diagnosis of HF, were 8.5% at 30 days and 28.7% at 1 year (Novack et al., 2010). The association between frailty and older patients with HF and other CVDs has been described but it is not well understood. One of the reasons for this is that frailty criteria vary among studies, making comparisons difficult. Depending on the criteria used, the prevalence of frailty ranges from 25 to 50% (Alvarado et al., 2008; Fried et al., 2004; Fried et al., 2001; Santos-Eggimann et al., 2009). In a study with 622 older patients, with an average EF of 30%, frailty’s prevalence was 39.9% (defined by a Barthel index (basic ADL) < 90; OARS scale (IADL) < 10 in women and < 6 in men; Pfeiffer mental status questionnaire (Pfeiffer, 1975) > 3  1 adjusted for education and a positive modified Geriatric Depression Scale (D‘Ath, Katona, Mullan, Evans, & Katona, 1994). At one-year follow-up, there was a 9.5% mortality rate and a significant association between frailty and mortality (Lupon et al., 2008). Yet another study found that 30% of HF patients, attending a HF clinic, were frail (n = 83; mean age: 70 years) in contrast to none in the age- and sex-matched control group without HF (n = 54; mean age: 70 years) (Abou-Raya & Abou-Raya, 2009).

lack of consistent studies in an outpatient population with CVD may make the interpretation of the value of frailty in predicting catastrophic outcomes challenging. Systematic and prospective studies are still necessary to corroborate our findings. 4.2. Limitations This study had an important loss to follow-up (40%) and also a small sample size (172) and this could have biased our results. Also, additional follow-up time points (6 months) and a longer follow-up period (two years) could help shed more light on the association between the presence of frailty and cardiovascular disease. In spite of this, our results are similar to previous large clinical trials (Woods et al., 2005) that found that frail women, at baseline, were more likely to be older, have lower family income and have a lower level of education. Another important limitation was that the outcomes were self-reported and not adjudicated (except for cause of death). At baseline, we depended on subjects’ recollection of events and this could lead to a memory bias. Lastly, the initial ADLs and IADLs questionnaires were completed in person while the follow-up ones were concluded by phone and this, again, could lead to bias as response to in person questionnaires can differ from over the phone responses.

4.1. Frailty and mortality

5. Conclusion

In our population, the frail group presented with a mortality rate three times higher than the one described by Fried for the CHS dwelling community population after one year (Fried et al., 2001). Previous reports have demonstrated that frailty increases mortality rate in older patients with CVD from the community, but not as high as the rate observed in our study after 1 year. In the Beaver Dam Eye Study (Klein et al., 2005), frailty was associated with a 56% increase in all-cause mortality after 4.5 years (adjusted hazard ratio (HR) 1.56; CI: 1.27–1.92) among community dwelling elders with frailty and CVD. Other longitudinal studies, with older adults from the community, using different frailty criteria, have demonstrated the synergistic effect between frailty and CVD in regard to mortality, with a HR range from 1.62 to 6.03 (Cacciatore et al., 2005; Lupon et al., 2008; Rich, 2005). Our results could be explained by the high age of our population, the very low income and educational levels, the elevated rates of CVDs, disability and dementia. These features are consistently associated with frailty and mortality, and probably, interact as synergist syndromes increasing the mortality rates. In spite of the fact that the frail group had a higher number of hospitalizations during the one-year follow-up this was not significant; nonetheless, previous hospitalization (before baseline assessment) was very high and an independent predictor of frailty. One reason that could explain why recurrent hospitalization was a strong risk factor for frailty might be the elevated number of CVDs and other non-CVD comorbidities. Another possible explanation is the immunologic deficiency found in the frail population with consequent higher infection rates and elevated levels of several inflammatory cytokines (interleukin 6, C-reactive protein, tumor necrosis factor-a, and CXC chemokine ligand-10) (Collerton et al., 2012; Hubbard, O‘Mahony, Savva, Calver, & Woodhouse, 2009; Leng, Xue, Tian, Walston, & Fried, 2007; Qu et al., 2009a; Qu, Yang, Walston, Fedarko, & Leng, 2009b). These inflammatory cytokines may decrease ventricular function and increase the rate of systemic infections with consequent HF decompensation, more hospitalizations and lower resilience. The diagnosis of frailty in this population may help in the identification of older patients with a higher probability of incidental disability and mortality; consequently, it may be an important risk factor to be considered in treatment decisions, like cardiovascular surgeries. The diversity of frailty criteria and the

Older outpatients with CVD have a higher probability to be frail than older adults who do not have a CVD. Low SPB and DBP must always be taken into consideration due to their high association with frailty. It is also important to diagnose frailty in this population due to the high association with mortality and disability. Implications: It is very important to evaluate frailty in an older outpatient population with prevalent cardiovascular disease, because it could be an important aspect in a decision making situation, such as surgeries and even hospice care enrollment. Blood pressure must be carefully monitored to avoid unwanted and unexpected value reductions; however, further studies are necessary to clarify if the normalization of the blood pressure levels and optimized prevention of the CVDs will improve the incidence of frailty and, if the progression to a prefrail or robust status could result in improved mortality and disability rates. Funding The authors received no funding for this project. Conflict of interest statement The authors have no conflict of interest to disclose. References Abou-Raya, S., & Abou-Raya, A. (2009). Osteoporosis and congestive heart failure (CHF) in the elderly patient: Double disease burden. Archives of Gerontology and Geriatrics, 49, 250–254. Afilalo, J., Karunananthan, S., Eisenberg, M. J., Alexander, K. P., & Bergman, H. (2009). Role of frailty in patients with cardiovascular disease. The American Journal of Cardiology, 103, 1616–1621. Alvarado, B. E., Zunzunegui, M. V., Beland, F., & Bamvita, J. M. (2008). Life course social and health conditions linked to frailty in Latin American older men and women. Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 63, 1399–1406. American College of Cardiology, American Heart Association, European Heart Rhythm Association, Wann, L. S., Curtis, A. B., Ellenbogen, K. A., Estes, N. A., Ezekowitz, M. D., et al. (2013). Management of patients with atrial fibrillation (compilation of 2006 ACCF/AHA/ESC and 2011 ACCF/AHA/HRS recommendations): A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation, 127, 1916–1926. Bandeen-Roche, K., Xue, Q. L., Ferrucci, L., Walston, J., Guralnik, J. M., Chaves, P., et al. (2006). Phenotype of frailty: Characterization in the women’s health and aging

A. Frisoli Jr. et al. / Archives of Gerontology and Geriatrics 61 (2015) 1–7 studies. Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 61, 262–266. Bilotta, C., Bowling, A., Case, A., Nicolini, P., Mauri, S., Castelli, M., et al. (2010). Dimensions and correlates of quality of life according to frailty status: A crosssectional study on community-dwelling older adults referred to an outpatient geriatric service in Italy. Health and Quality of Life Outcomes, 8, 56. Cacciatore, F., Abete, P., Mazzella, F., Viati, L., Della Morte, D., D‘Ambrosio, D., et al. (2005). Frailty predicts long-term mortality in elderly subjects with chronic heart failure. European Journal of Clinical Investigation, 35, 723–730. Chin, A. P. M. J., Dekker, J. M., Feskens, E. J., Schouten, E. G., & Kromhout, D. (1999). How to select a frail elderly population? A comparison of three working definitions. Journal of Clinical Epidemiology, 52, 1015–1021. Collerton, J., Martin-Ruiz, C., Davies, K., Hilkens, C. M., Isaacs, J., Kolenda, C., et al. (2012). Frailty and the role of inflammation, immunosenescence and cellular ageing in the very old: Cross-sectional findings from the Newcastle 85+ Study. Mechanisms of Ageing and Development, 133, 456–466. Crucet, M., Wust, S. J., Spielmann, P., Luscher, T. F., Wenger, R. H., & Matter, C. M. (2013). Hypoxia enhances lipid uptake in macrophages: Role of the scavenger receptors Lox1, SRA, and CD36. Atherosclerosis, 229, 110–117. D‘Ath, P., Katona, P., Mullan, E., Evans, S., & Katona, C. (1994). Screening, detection and management of depression in elderly primary care attenders, I: The acceptability and performance of the 15 item Geriatric Depression Scale (GDS15) and the development of short versions. Family Practice, 11, 260–266. De Lepeleire, J., Iliffe, S., Mann, E., & Degryse, J. M. (2009). Frailty: An emerging concept for general practice. The British Journal of General Practice: The Journal of the Royal College of General Practitioners, 59, e177–e182. Di Napoli, M., Papa, F., & Villa Pini Stroke Data Bank Investigators (2002). Inflammation, hemostatic markers, and antithrombotic agents in relation to long-term risk of new cardiovascular events in first-ever ischemic stroke patients. Stroke: A Journal of Cerebral Circulation, 33, 1763–1771. Evans, W. J., Morley, J. E., Argiles, J., Bales, C., Baracos, V., Guttridge, D., et al. (2008). Cachexia: A new definition. Clinical Nutrition, 27, 793–799. Feldstein, C. A. (2012). Association between chronic blood pressure changes and development of Alzheimer’s disease. Journal of Alzheimer’s Disease: JAD, 32, 753–763. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. Fried, L. P., Ferrucci, L., Darer, J., Williamson, J. D., & Anderson, G. (2004). Untangling the concepts of disability, frailty, and comorbidity: Implications for improved targeting and care. Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 59, 255–263. Fried, L. P., Tangen, C. M., Walston, J., Newman, A. B., Hirsch, C., Gottdiener, J., et al. (2001). Frailty in older adults: Evidence for a phenotype. Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 56, M146–M156. Gill, T. M., Gahbauer, E. A., Han, L., & Allore, H. G. (2010). Trajectories of disability in the last year of life. The New England Journal of Medicine, 362, 1173–1180. Gray, S. L., Anderson, M. L., Hubbard, R. A., Lacroix, A., Crane, P. K., McCormick, W., et al. (2013). Frailty and incident dementia. Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 68, 1083–1090. Hubbard, R. E., O‘Mahony, M. S., Savva, G. M., Calver, B. L., & Woodhouse, K. W. (2009). Inflammation and frailty measures in older people. Journal of Cellular and Molecular Medicine, 13, 3103–3109. Huisman, M., Kunst, A. E., Andersen, O., Bopp, M., Borgan, J. K., Borrell, C., et al. (2004). Socioeconomic inequalities in mortality among elderly people in 11 European populations. Journal of Epidemiology and Community Health, 58, 468–475. Iadecola, C., & Davisson, R. L. (2008). Hypertension and cerebrovascular dysfunction. Cell Metabolism, 7, 476–484. Jessup, M., Abraham, W. T., Casey, D. E., Feldman, A. M., Francis, G. S., Ganiats, T. G., et al. (2009). 2009 focused update: ACCF/AHA Guidelines for the Diagnosis and Management of Heart Failure in Adults: A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines: Developed in collaboration with the International Society for Heart and Lung Transplantation. Circulation, 119, 1977–2016. Katz, S., Downs, T. D., Cash, H. R., & Grotz, R. C. (1970). Progress in development of the index of ADL. The Gerontologist, 10, 20–30. Katz, S., Ford, A. B., Moskowitz, R. W., Jackson, B. A., & Jaffe, M. W. (1963). Studies of illness in the aged, the index of ADL: A standardized measure of biological and psychosocial function. JAMA: The Journal of the American Medical Association, 185, 914–919. Klein, B. E., Klein, R., Knudtson, M. D., & Lee, K. E. (2005). Frailty, morbidity and survival. Archives of Gerontology and Geriatrics, 41, 141–149. Lawton, M. P., & Brody, E. M. (1969). Assessment of older people: Self-maintaining and instrumental activities of daily living. The Gerontologist, 9, 179–186. Leng, S. X., Xue, Q. L., Tian, J., Walston, J. D., & Fried, L. P. (2007). Inflammation and frailty in older women. Journal of the American Geriatrics Society, 55, 864–871. Lupon, J., Gonzalez, B., Santaeugenia, S., Altimir, S., Urrutia, A., Mas, D., et al. (2008). Prognostic implication of frailty and depressive symptoms in an outpatient population with heart failure. Revista espanola de cardiologia, 61, 835–842. Lustosa, L. P., Pereira, D. S., Dias, R. C., Britto, R. R., Parentoni, A. N., & Pereira, L. S. M. (2011). Translation and cultural adaptation of the Minnesota Leisure Time Activities Questionnaire in community-dwelling older people. Geriatria & Gerontologia, 5, 57–65. Macuco, C. R., Batistoni, S. S., Lopes, A., Cachioni, M., da Silva Falcao, D. V., Neri, A. L., et al. (2012). Mini-Mental State Examination performance in frail, pre-frail, and non-frail community dwelling older adults in Ermelino Matarazzo, Sao Paulo, Brazil. International Psychogeriatrics/IPA, 24, 1725–1731.

7

Miller, D. K., Carter, M. E., Miller, J. P., Fornoff, J. E., Bentley, J. A., Boyd, S. D., et al. (1996). Inner-city older blacks have high levels of functional disability. Journal of the American Geriatrics Society, 44, 1166–1173. Mora, S., Rifai, N., Buring, J. E., & Ridker, P. M. (2006). Additive value of immunoassaymeasured fibrinogen and high-sensitivity C-reactive protein levels for predicting incident cardiovascular events. Circulation, 114, 381–387. Moreira, V. G., & Lourenc¸o, R. A. (2013). Prevalence and factors associated with frailty in an older population from the city of Rio de Janeiro, Brazil: The FIBRA-RJ Study. Clinics (Sa˜o Paulo), 68, 979–985. Morley, J. E., Abbatecola, A. M., Argiles, J. M., Baracos, V., Bauer, J., Bhasin, S., et al. (2011). Sarcopenia with limited mobility: An international consensus. Journal of the American Medical Directors Association, 12, 403–409. Morse, L., Teng, Y. D., Pham, L., Newton, K., Yu, D., Liao, W. L., et al. (2008). Spinal cord injury causes rapid osteoclastic resorption and growth plate abnormalities in growing rats (SCI-induced bone loss in growing rats). Osteoporosis International, 19, 645–652. Newman, A. B., Gottdiener, J. S., McBurnie, M. A., Hirsch, C. H., Kop, W. J., Tracy, R., et al. Cardiovascular Health Study Research Group. (2001). Associations of subclinical cardiovascular disease with frailty. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 56, M158–M166. Novack, V., Pencina, M., Zahger, D., Fuchs, L., Nevzorov, R., Jotkowitz, A., et al. (2010). Routine laboratory results and thirty day and one-year mortality risk following hospitalization with acute decompensated heart failure. PLoS ONE, 5, e12184. Odden, M. C., Peralta, C. A., Haan, M. N., & Covinsky, K. E. (2012). Rethinking the association of high blood pressure with mortality in elderly adults: The impact of frailty. Archives of Internal Medicine, 172, 1162–1168. Orme, J. G., Reis, J., & Herz, E. J. (1986). Factorial and discriminant validity of the Center for Epidemiological Studies Depression (CES-D) scale. Journal of Clinical Psychology, 42, 28–33. Parathath, S., Mick, S. L., Feig, J. E., Joaquin, V., Grauer, L., Habiel, D. M., et al. (2011). Hypoxia is present in murine atherosclerotic plaques and has multiple adverse effects on macrophage lipid metabolism. Circulation Research, 109, 1141–1152. Pfeiffer, E. (1975). A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. Journal of the American Geriatrics Society, 23, 433–441. Post Hospers, G., Smulders, Y. M., Maier, A. B., Deeg, D. J., & Muller, M. (2014). Relation between blood pressure and mortality risk in an older population: Role of chronological and biological age. Journal of Internal Medicine. Qu, T., Walston, J. D., Yang, H., Fedarko, N. S., Xue, Q. L., Beamer, B. A., et al. (2009). Upregulated ex vivo expression of stress-responsive inflammatory pathway genes by LPS-challenged CD14(+) monocytes in frail older adults. Mechanisms of Ageing and Development, 130, 161–166. Qu, T., Yang, H., Walston, J. D., Fedarko, N. S., & Leng, S. X. (2009). Upregulated monocytic expression of CXC chemokine ligand 10 (CXCL-10) and its relationship with serum interleukin-6 levels in the syndrome of frailty. Cytokine, 46, 319–324. Rich, M. W. (2005). Heart failure in the oldest patients: The impact of comorbid conditions. The American Journal of Geriatric Cardiology, 14, 134–141. Rockwood, K., & Mitnitski, A. (2007). Frailty in relation to the accumulation of deficits. Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 62, 722–727. Sabayan, B., Oleksik, A. M., Maier, A. B., van Buchem, M. A., Poortvliet, R. K., de Ruijter, W., et al. (2012). High blood pressure and resilience to physical and cognitive decline in the oldest old: The Leiden 85-plus Study. Journal of the American Geriatrics Society, 60, 2014–2019. Santos-Eggimann, B., Cuenoud, P., Spagnoli, J., & Junod, J. (2009). Prevalence of frailty in middle-aged and older community-dwelling Europeans living in 10 countries. Journals of Gerontology: Series A: Biological Sciences and Medical Sciences, 64, 675–681. Satish, S., Freeman, D. H., Jr., Ray, L., & Goodwin, J. S. (2001). The relationship between blood pressure and mortality in the oldest old. Journal of the American Geriatrics Society, 49, 367–374. Smit, E., Winters-Stone, K. M., Loprinzi, P. D., Tang, A. M., & Crespo, C. J. (2013). Lower nutritional status and higher food insufficiency in frail older US adults. The British Journal of Nutrition, 110, 172–178. Smith, A., Patterson, C., Yarnell, J., Rumley, A., Ben-Shlomo, Y., & Lowe, G. (2005). Which hemostatic markers add to the predictive value of conventional risk factors for coronary heart disease and ischemic stroke? The Caerphilly Study. Circulation, 112, 3080–3087. Strandgaard, S., & Paulson, O. B. (1994). Cerebrovascular consequences of hypertension. Lancet, 344, 519–521. Taylor, H. L., Jacobs, D. R., Jr., Schucker, B., Knudsen, J., Leon, A. S., & Debacker, G. (1978). A questionnaire for the assessment of leisure time physical activities. Journal of Chronic Diseases, 31, 741–755. Tzoulaki, I., Murray, G. D., Lee, A. J., Rumley, A., Lowe, G. D., & Fowkes, F. G. (2007). Relative value of inflammatory, hemostatic, and rheological factors for incident myocardial infarction and stroke: The Edinburgh Artery Study. Circulation, 115, 2119–2127. Wenger, N. K. (2012). 2011 ACCF/AHA focused update of the guidelines for the management of patients with Unstable Angina/Non-ST-Elevation Myocardial Infarction (updating the 2007 Guideline): Highlights for the clinician. Clinical Cardiology, 35, 3–8. Woods, N. F., LaCroix, A. Z., Gray, S. L., Aragaki, A., Cochrane, B. B., Brunner, R. L., et al. (2005). Frailty: Emergence and consequences in women aged 65 and older in the Women’s Health Initiative Observational Study. Journal of the American Geriatrics Society, 53, 1321–1330. Zarulli, V., Marinacci, C., Costa, G., & Caselli, G. (2013). Mortality by education level at late-adult ages in Turin: A survival analysis using frailty models with period and cohort approaches. BMJ Open, 3.