Abstract
Background.
Oral anticoagulation (OAC) is challenging in older Non-Valvular Atrial Fibrillation (NVAF) patients who are often frail and have cognitive impairment (CI). We examine the characteristics of older NVAF patients associated with higher odds of physical and cognitive impairments. We also examined if these high-risk patients have different OAC prescribing patterns and their satisfaction with treatment, as it may impact optimal management of their NVAF.
Methods.
The SAGE-AF cohort (2016-2018) patients had NVAF, were ≥65 years, and eligible for the receipt of OAC. Measures included frailty (Fried Frailty scale), CI (Montreal Cognitive Assessment Battery), OAC prescribing and type (DOAC, VKA), depressive symptoms (PHQ9), bleeding, stroke risk and treatment benefit (Anti-Clot Treatment scale).
Results.
Patients (n=1244) were 49% female, aged 76 (SD: 7) years. 14% were frail and 42% had CI. Frailty and CI co-occurred in 9%. Odds of having both impairments versus none were higher with depression (OR=4.62, 95%CI: 2.59,8.26), older age (OR=1.56, 95%CI = 1.29,1.88), lower education (OR=3.81, 95%CI = 2.13,6.81), race/ethnicity other than non-Hispanic white (OR=7.94, 95%CI = 4.34,14.55), bleeding risk (OR=1.43, 95%CI = 1,12,1.81), and stroke risk (OR=1.35, 95%CI = 1.13,1.62). OAC prescribing was not associated with CI and frailty status. Among patients taking OACs (85%), those with both impairments were more likely to take DOAC than VKA (OR=1.69, 95%CI = 1.01, 2.80). Having both impairments (OR=1.87, 95%CI = 1.08,3.27) or CI (OR: 1.56, 95%CI = 1.09,2.24) was associated with higher odds of reporting lower treatment benefit.
Conclusion.
In a large cohort of older NVAF patients half were frail or cognitively impaired and 9% had both impairments. We highlight characteristics of patients who may benefit from cognitive and physical function screenings in order to maximize treatment and enhance prognosis. Finally, the co-occurrence of impairment was associated with low perceived benefit of treatment which may impede optimal management.
Keywords: non-valvular atrial fibrillation, frailty, cognitive impairment, Oral anticoagulation, burden of treatment, benefit of treatment
INTRODUCTION
Atrial fibrillation (AF), the most common cardiac arrhythmia, is associated with an increased risk for stroke, especially in older adults.1-3 In addition to increasing stroke risk, AF is responsible for serious complications including decreased quality of life, frequent hospitalization, and an increased risk of dying.4-6 Oral anticoagulation (OAC) treatment is the cornerstone of stroke prevention in patients with Non-Valvular Atrial Fibrillation (NVAF). 7-9 However, OAC is often not prescribed in eligible older patients due to a variety of reasons.10 This is especially true for patients with geriatric impairments, such as physical frailty and cognitive impairment (CI), that may increase the risk of medication non-adherence and complications including falls.10-13
Older patients with AF are four times more likely to be frail and twice as likely to have cognitive impairment than older patients without AF.14-16 Some studies suggest that older patients with AF who are frail or cognitively impaired are less likely to be prescribed an OAC than their non-impaired peers placing these patients at greater risk for stroke.10, 11, 17-19 However, these studies often had an upper age limit of 80 years and had methodological limitations, including the use of data from medical records to determine cognitive or frailty status, potentially leading to underestimation of the prevalence of frailty and CI or their influence on OAC prescribing. 10, 12, 13 Moreover, data on the use of direct oral anticoagulant versus vitamin K antagonist medication in older patients who are frail and cognitively impaired, using validated and comprehensive assessments, are sparse. 10, 19, 20 Even less is known about how often frailty and cognitive impairment co-occur in patients with NVAF and whether these particularly high-risk patients have different OAC prescribing patterns and, among those prescribed, the type of OAC. 10
Another factor in OAC treatment that is increasingly important to AF providers, patients, and their families is satisfaction with treatment, so much so that measures of treatment satisfaction are increasingly included as important patient-related outcomes in clinical trials. 21 Treatment satisfaction, which includes the perceived burden and benefit that a patient attributes to their treatment, has been associated with better treatment adherence among older patients with AF. 22, 23 Patient satisfaction of AF treatment is therefore central in achieving the target therapeutic goal for treatment.
Using data from the Systematic Assessment of Geriatric Elements in Atrial Fibrillation (SAGE-AF) Study we describe the separate and combined prevalence of frailty and cognitive impairment in a cohort of older adults with NVAF and examine characteristics associated with higher odds of impairment. Among these high-risk patients, we also examine whether OAC treatment patterns vary according to cognitive and frailty status; and (3) examine whether patient reported burden and benefits of OAC treatment vary by cognitive and frailty status.
METHODS
Study design and population
The ongoing SAGE-AF cohort enrolled a total of 1244 older patients between 2016 and 2018 from 5 practice sites in Massachusetts and 2 in Central Georgia. 24 Eligibility criteria included age ≥65 years, NVAF (if the arrhythmia was present on an electrocardiogram or Holter monitor or if it was noted in any clinic note or hospital record), had a CHA2DS2-VASc ≥2 and no contraindications to the receipt of OAC. Participants were not eligible for enrollment if they had an indication for OAC other than NVAF (i.e., mechanical heart valve requiring OAC), had a medical record diagnosis of dementia, did not speak English, had a planned invasive high bleeding risk procedure, were in prison, or if they were unwilling or unable to participate in planned one- and two-year follow-up visits. In addition, if our trained staff were concerned about a patient’s ability to provide informed consent, a standardized Capacity for Informed Consent Instrument that combines capacity assessment questions with interviewer observation was used to determine ability to provide consent. 25
All study participants received an invitation to participate one week before their scheduled clinic visit. All SAGE-AF participants have given informed written consent. Study protocols were approved by the University of Massachusetts Medical School, Boston University, and Mercer University Institutional Review Boards.
Data collection
All SAGE-AF study participants had a medical history obtained and a physical examination performed in the context of their routine care, typically on the day of study enrollment. All participants underwent a 60-minute interviewer-administered, computer-assisted interview with standardized measures, including assessments of mood, frailty, cognition, social support, and other patient-reported measures.
Study Outcomes and Predictor Variables
Frailty was assessed using the Fried Frailty scale 26, a biological model of frailty based on five components: weight loss/shrinking; exhaustion; low physical activity (assessed using the Minnesota Leisure Time Activity questionnaire27; slow gait speed (assessed using a 15-foot timed walk); and weakness (assessed using grip strength). Each element receives a single point and the frailty index ranges from 0-5. Patients were rated as frail if 3 or more criteria were present. 26
Cognitive impairment (CI) was assessed using the Montreal Cognitive Assessment Battery (MoCA), scored 0-30 with higher scores representing better cognitive performance. 28 A cut-point of 23 was used to classify CI. 29 MoCA correlates well (.89) with the widely used Mini Mental State Exam (MMSE), but outperforms the MMSE in the detection of mild CI (sensitivity .90 vs. .18). 28-31 MoCA is the recommended screening test for CI in patients with CVD by the NINDS and the Canadian Stroke Institute and has 4 versions available to reduce practice effects. 32, 33
OAC medication prescribing (yes/no) and the type of OAC medication (vitamin-K antagonist [VKA] vs or direct oral anticoagulants [DOAC]) were abstracted from patients’ medical records and confirmed with patients during the baseline interview. Participants completed the Anti-Clot Treatment Scale (ACTS), a validated 15-item survey designed to assess OAC satisfaction. 34, 35 Treatment burden was measured on a 12-item scale, with scores ranging from 12 to 60, with higher scores indicating lower perceived burden. Treatment benefit is measured with 3 items, with scores ranging from 3 to 15, with higher scores indicating greater perceived benefit.
Demographic, clinical, treatment, and laboratory characteristics were abstracted from the medical record including participants’ age and sex, smoking status, type of NVAF, and comorbidities relevant to stroke and bleeding risk (AMI, diabetes type II, hyperlipidemia, stroke, anemia, asthma). CHA2DS2VASC (congestive heart failure; hypertension; aged ≥75 y [doubled]; diabetes mellitus; prior stroke, transient ischemic attack, or thromboembolism [doubled]; vascular disease; age 65-74; female sex) and HAS-BLED scores were calculated. Participants self-reported education, marital status, living situation, race and ethnicity during the interview.
In addition to the in-person assessment of cognitive function and frailty, other geriatric elements were measured and included visual and auditory impairment (self-reported), social isolation, social support, depression, anxiety, and occurrence of falls in the past 6 months. Social support was measured using the 5-item modified version of the Social Support Scale and the 6-item Social Network scale to assess the breadth and depth of social support.36 A cut-point of <12 was used to define social isolation. 37, 38 Depression was measured using the Patient Health Questionnaire. 39 The PHQ-9 incorporates the 9 criteria on which DSM-IV depressive disorders are based. Using a cut-point of ≥10 (range = 0-27), the PHQ-9 has high sensitivity (0.88) and specificity (0.88) for major depression in CVD patients. 40, 41 Anxiety was assessed using the Generalized Anxiety Disorder-7 42 scale. A cut-point of 5 was used to indicate the presence of these psychosocial disorders on both scales.
Statistical Analysis
Patients were categorized into four groups according to cognitive function and frailty: cognitively impaired only, frail only, both impairments, and neither impairment.
Sociodemographic and clinical characteristics of patients in each group were reported using descriptive statistics (percentages and means ± standard deviation) and between group differences were compared using analysis of variance for continuous variables and the chi-square test for categorical variables.
Multinomial logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals for frailty, CI, or both impairments in relation to no impairment. We included geriatric elements as factors in the models in addition to factors that differed significantly between the cognitive function and frailty groups at p< 0.05. We controlled for the CHA2DS2VASC score in all models and thus did not control for factors that contributed to that score. The only exception was age because the CHA2DS2VASC score only accounts for ages 65-74 (1 point) and ≥75 (2 points), thus not accounting for the influence across the age spectrum.
Logistic regression was used to examine whether the prescribing of OACs, type of OAC, high perceived burden, and low benefit differed in the four CI and frailty groups. For these models, high burden was defined as being in the bottom quartile of the ACTS Burden sub-scale while low benefit was defined as being in the top quartile of the ACTS Benefit sub-scale. For each regression analysis, three models were computed. The first model was unadjusted for other potential covariates, the second was adjusted for the CHA2DS2VASC score and age and the third model was adjusted for other geriatric elements and factors that differed significantly between the cognitive function and frailty groups at a p value of < 0.05. Statistical analyses were performed using SAS 9.4 (SAS Institute, Inc., Cary, NC).
RESULTS
Patient characteristics and prevalence of frailty and cognitive impairment
Among the 1244 SAGE-AF participants with NVAF the average age was 76 years (Standard Deviation [SD] = 7), 49% were women and 86% were non-Hispanic white. The mean of the MoCA was 23.55 and the median was 24.0. Scores ranged from 6-30 with less than 5% of the scores under 15. Fourteen percent of the cohort were frail and 42% had cognitive impairment. Five percent (n=64, 5.1%) of the sample had frailty only, 33.8% (n=420) had CI only, and 8.7% (n=108) had both frailty and CI (Table 1). The overlap of cognitive impairment and frailty at more severe levels of cognitive impairment (lower MoCA cutpoints) are presented in Table S1.
Table 1.
No impairment |
Frailty only | CI only | Frailty and CI |
P-value | |
---|---|---|---|---|---|
N=652 (52.4%) |
N=64 (5.1) | N=420 (33.8) |
N=108 (8.7) | ||
Sociodemographic | |||||
Age, mean years (SD) | 73.8 (6.3) | 75.8 (7.1) | 77.5 (7.4) | 78.2 (7.6) | <.0001 |
Female | 311 (47.7) | 44 (68.8) | 185 (44.0) | 67 (62.0) | <.0001 |
Non-Hispanic white | 616 (94.5) | 61 (95.3) | 324 (77.1) | 68 (63.0) | <.0001 |
Education a | |||||
College Graduate | 350 (54.0) | 23 (36.5) | 135 (33.3) | 19 (18.5) | <.0001 |
Marital Statusb, married | 401 (62.0) | 29 (45.3) | 217 (53.2) | 47 (44.8) | 0.0003 |
Living Situationc, alone | 177 (27.4) | 21 (32.8) | 117 (28.6) | 35 (33.3) | 0.53 |
Clinical | |||||
Type of AF | |||||
Paroxysmal | 388 (59.5) | 40 (62.5) | 255 (60.7) | 58 (53.7) | 0.66 |
Persistent | 158 (24.2) | 13 (20.3) | 104 (24.8) | 34 (31.5) | |
Permanent | 36 (5.5) | 3 (4.7) | 28 (6.7) | 6 (5.6) | |
CHA2DS2VASC, mean (SD) | 4.01 (1.50) | 5.31 (1.68) | 4.65 (1.59) | 5.57 (1.49) | <.0001 |
HAS-BLED, mean (SD) | 3.08 (1.02) | 3.38 (0.92) | 3.34 (1.12) | 3.73 (1.12) | <.0001 |
MoCA, mean (SD) | 26.33 (1.70) | 26.20 (1.72) | 20.02 (3.02) | 18.96 (4.26) | <.0001 |
Medical History | |||||
AMI | 109 (16.7) | 28 (43.8) | 78 (18.6) | 27 (25.0) | <.0001 |
Diabetes type II | 145 (22.4) | 26 (40.6) | 122 (29.1) | 53 (49.1) | <.0001 |
Hyperlipidemia | 521 (79.9) | 54 (84.4) | 336 (80.0) | 85 (78.7) | 0.82 |
Stroke | 49 (7.5) | 8 (12.5) | 44 (10.5) | 21 (19.4) | 0.0011 |
Asthma/COPD | 146 (22.4) | 24 (37.5) | 106 (25.2) | 40 (37.0) | 0.0013 |
Smoking Status | |||||
Former smoker | 325 (49.9) | 32 (50.0) | 205 (48.8) | 53 (49.1) | 0.99 |
Current smoker | 19 (2.9) | 1 (1.6) | 12 (2.9) | 3 (2.8) | |
Other geriatric impairment | |||||
Vision impairment | 188 (28.8) | 31 (48.4) | 154 (36.7) | 55 (50.9) | <.0001 |
Hearing impairment | 209 (32.1) | 17 (26.6) | 179 (42.6) | 46 (42.6) | 0.0007 |
Social Isolation | 67 (10.3) | 9 (14.1) | 66 (15.7) | 14 (13.0) | 0.07 |
Depression | 132 (20.3) | 45 (70.3) | 108 (25.7) | 68 (63.0) | <.0001 |
Anxiety | 126 (19.3) | 24 (37.5) | 92 (21.9) | 49 (45.4) | <.0001 |
Fall in the past 6 months | 119 (18.2) | 25 (39.1) | 94 (22.4) | 32 (29.6) | 0.0002 |
Note.
N=1220
N=1224
N=1225
SD: Standard Deviation.
More than one half of the cohort had paroxysmal atrial fibrillation and the mean CHA2DS2VASC and HAS-BLED scores were 4 (SD = 1.5) and 3 (SD = 1), respectively. With regards to the geriatric elements, one third of patients had vision or hearing impairment, 13% were socially isolated, 28% had elevated symptoms of depression, 24% had elevated symptoms of anxiety, and 22% reported the occurrence of falls in the past 6 months.
Characteristics associated with presence of frailty and cognitive impairment
Social isolation was associated with higher likelihood of having cognitive impairment alone (OR = 1.66, 95% CI = 1.10, 2.50) compared to having no impairments (Table 2). Patients who were depressed were more likely to have frailty (OR = 10.16, 95% CI = 5.17, 19.96) and both frailty and cognitive impairment (OR = 4.62, 95% CI = 2.59, 8.26), but were not more likely to have cognitive impairment alone. Patients reporting a fall in the last 6 months were more likely to be frail (OR = 2.11, 95% CI = 1.15, 3.87) than to have no impairments. Every 5 year increment in age increased the likelihood of being cognitively impaired (OR = 1.48, 95% CI = 1.32, 1.66) and both frail and cognitively impaired (OR = 1.56, 95% CI = 1.29, 1.88). Patients with less than a college education were twice as likely to be cognitively impaired (OR = 2.03, 95% CI = 1.52, 2.70) and four times as likely to be both frail and cognitively impaired (OR = 3.81, 95% CI = 2.13, 6.81) than to have no impairment. Patients of races/ethnicities other than non-Hispanic white had 5 times the odds of CI only (OR = 5.26, 95% CI = 3.43, 8.07) and 8 times the odds of having both impairments (OR = 7.94, 95% CI = 4.34, 14.55) than to have no impairments. Higher bleeding risk score (HAS-BLED) was associated with higher likelihood of CI (OR=1.19, 95% CI = 1.04, 1.37) and of being both frail and cognitively impaired (OR = 1.43, 95% CI = 1.12, 1.81). Finally, higher CHA2DS2VASC score was associated with higher likelihood of being frail (OR = 1.32, 95% CI = 1.06, 1.64) and of being both frail and cognitively impaired (OR = 1.35, 95% CI = 1.13, 1.62), while a medical history of AMI was associated with higher likelihood of being frail (Table 2).
Table 2.
Frailty only | CI only | Frailty and CI | |
---|---|---|---|
N=419 (33.7) | N=64 (5.1) | N=108 (8.7) | |
Other geriatric impairment | |||
Vision impairment | 1.42 (0.79, 2.58) | 1.07 (0.79, 1.45) | 1.17 (0.71, 1.93) |
Hearing impairment | 0.44 (0.23, 0.84) | 1.32 (0.99, 1.76) | 0.96 (0.58, 1.60) |
Social isolation | 1.30 (0.56, 3.04) | 1.66 (1.10, 2.50) | 1.01 (0.47, 2.17) |
Elevated symptoms of depression | 10.16(5.17, 19.96) | 1.11 (0.76, 1.62) | 4.62 (2.59, 8.26) |
Elevated symptoms of anxiety | 0.69 (0.35, 1.34) | 1.19 (0.81, 1.75) | 1.68 (0.94, 3.00) |
Any fall in the past 6 months | 2.11 (1.15, 3.87) | 0.99 (0.71, 1.40) | 1.14 (0.66, 1.98) |
Demographic characteristics | |||
Age (5 year increments) | 1.20 (0.97, 1.50) | 1.48 (1.32, 1.66) | 1.56 (1.29, 1.88) |
Less than college graduate | 1.33 (0.73, 2.43) | 2.03 (1.52, 2.70) | 3.81 (2.13, 6.81) |
Non-Hispanic white | 0.75 (0.26, 2.15) | 5.26 (3.43, 8.07) | 7.94 (4.34, 14.55) |
Not married | 1.30 (0.72, 2.34) | 0.93 (0.70, 1.25) | 0.96 (0.58, 1.58) |
Clinical characteristics | |||
CHA2DS2VASC | 1.32 (1.06, 1.64) | 1.07 (0.96, 1.19) | 1.35 (1.13, 1.62) |
HAS-BLED | 0.99 (0.75, 1.32) | 1.19 (1.04, 1.37) | 1.43 (1.12, 1.81) |
AMI | 2.79 (1.46, 5.35) | 0.90 (0.61, 1.31) | 0.88 (0.48, 1.62) |
Asthma/COPD | 1.51 (0.83, 2.77) | 0.99 (0.72, 1.37) | 1.33 (0.80, 2.24) |
Referent group is those who are not impaired (n=653).
OAC Treatment
Overall, about 85% of study participants were taking an OAC and OAC prescribing did not differ according to cognitive or frailty status (Table 3). Participants with both impairments were nearly two times more likely to be prescribed a DOAC compared with VKA in the adjusted models (OR = 1.71, 95% CI = 1.02, 2.88; Table 3). We also examined OAC prescribing and type in a subsample restricted to those with paroxysmal AF (N=741). Overall, the direction of results in this subgroup analysis are similar to those from the full cohort model although fail to reach statistical significance due to the reduced sample size. (Table S2)
Table 3.
Odds ratio (95% confidence interval) | ||||
---|---|---|---|---|
Unadjusted | Model 1 | Model 2 | ||
On OAC n (%) |
Odds of not receiving OAC treatment (N=1244) | |||
No impairment | 561 (85.9) | referent | referent | referent |
Frailty | 54 (84.4) | 1.14 (0.56, 2.32) | 1.55 (0.75, 3.22) | 1.51 (0.70, 3.27) |
CI | 354 (84.5) | 1.15 (0.82, 1.62) | 1.34 (0.94, 1.91) | 1.39 (0.94, 2.05) |
Both frailty and CI | 95 (88.-) | 0.84 (0.45, 1.56) | 1.23 (0.64, 2.35) | 1.35 (0.66, 2.77) |
On DOAC n (%) |
Odds of receiving a DOAC among those on OAC (n=1064) | |||
No impairment | 256 (45.6) | referent | referent | referent |
Frailty | 21 (38.9) | 0.76 (0.43, 1.34) | 0.92 (0.51, 1.64) | 0.89 (0.49, 1.67) |
CI | 138 (39.-) | 0.76 (0.58, 0.99) | 0.84 (0.63, 1.10) | 0.91 (0.67, 1.23) |
Both frailty and CI | 51 (53.7) | 1.38 (0.89, 2.14) | 1.73 (1.10, 2.73) | 1.71 (1.02, 2.88) |
Note. OAC: Oral anticoagulation; DOAC: Direct-Acting Oral Anticoagulants
Model 1 is adjusted for CHA2DS2VASC score, Model 2 is adjusted for Model 1 + age, education, race, marital status, has-bled score, AMI, asthma/COPD, vision impairment, hearing impairment, social support, depression, anxiety, fall in the past 6 months.
Perceived Burden and Benefit of Treatment
One third of patients with frailty or with both impairments reported high burden, whereas this was true for only 23% of patients with CI or no impairment (Table 4). Participant-reported treatment burden did not differ in our four cognition and frailty comparison groups (Table 4). Compared to participants without any impairment, those with CI alone were 50% more likely to report low benefit of treatment (OR: 1.57; 95%CI: 1.10, 2.24), while patients who were both cognitively impaired and frail were two times more likely to report low benefit (OR: 1.97; 95%CI: 1.12, 3.47).
Table 4.
Burden and Benefit results |
Odds ratio (95% confidence interval) | ||||
---|---|---|---|---|---|
Unadjusted | Model 1 | Model 2 | |||
Burden mean score (SD) |
High burden n (%) |
Odds of reporting high burden | |||
No impairment | 16.6 (5.2) | 132 (23.5) | referent | referent | referent |
Frailty | 18.1 (5.6) | 19 (35.2) | 1.77 (0.98, 3.19) | 1.74 (0.95, 3.18) | 1.05 (0.54, 2.08) |
CI | 16.5 (6.4) | 80 (22.6) | 0.95 (0.69, 1.30) | 0.94 (0.68, 1.30) | 0.87 (0.60, 1.26) |
Both frailty and CI | 17.9 (6.5) | 31 (32.6) | 1.50 (0.93, 2.41) | 1.47 (0.90, 2.42) | 0.76 (0.42, 1.37) |
Benefit mean score (SD) |
Low benefit n (%) |
Odds of reporting low benefit | |||
No impairment | 11.3 (3.5) | 98 (17.5) | referent | referent | referent |
Frailty | 10.2 (3.4) | 15 (27.8) | 1.67 (0.89, 3.20) | 1.63 (0.85, 3.16) | 1.22 (0.59, 2.50) |
CI | 10.4 (4.3) | 100 (28.3) | 1.88 (1.37, 2.59) | 1.86 (1.35, 2.57) | 1.57 (1.10, 2.24) |
Both frailty and CI | 9.6 (3.6) | 34 (35.8) | 2.67 (1.66, 4.28) | 2.59 (1.58, 4.25) | 1.97 (1.12, 3.47) |
Note. SD: Standard Deviation,
High burden was defined as being the bottom quartile of the Anti-clot Treatment Burden Scale while low benefit was defined as being the Top quartile of the Anti-clot Treatment Benefit Scale.
Model 1 is adjusted for CHA2DS2VASC score, Model 2 is adjusted for Model 1 + age, education, race, marital status, has-bled score, AMI, asthma/COPD, vision impairment, hearing impairment, social support, depression, anxiety, fall in the past 6 months
DISCUSSION
In a large cohort of older patients with NVAF, approximately one half were frail or cognitively impaired and 9% were both frail and cognitively impaired. Depression, older age, lower education, being non-White, and higher bleeding and stroke risk scores were associated with being both frail and cognitively impaired. Among patients taking an OAC, participants with CI alone were less likely to be prescribed a DOAC, while participants who were frail and cognitively impaired were more likely to be prescribed a DOAC than a VKA. Participants who were cognitively impaired and those who were both cognitively impaired and frail were significantly more likely to report low benefits associated with AF treatment.
The proportion of patients with both frailty and cognitive impairment observed in this cohort was higher than observed in a previous study. Less than one percent of patients in the ORBIT-AF registry were classified as being both frail and cognitively impaired. 19 Assessments of frailty and cognition differed between the ORBIT-AF and the SAGE-AF cohorts, however. The ORBIT-AF cohort used the American Geriatric Society’s Geriatric Evaluation and Management Tool to assess frailty and cognitive impairment was assessed by medical record review. In the SAGE-AF study, frailty was assessed using the Cardiovascular Health Survey frailty scale and cognitive impairment was objectively assessed using the Montreal Cognitive Assessment Battery. The ORBIT-AF registry included patients aged 18 years and older, while our cohort included only older patients. The proportion of frail patients in our cohort was similar to that reported in the ORBIT-AF cohort, but we observed a markedly higher proportion of cognitively impaired patients than was observed in the ORBIT-AF study. The proportion of cognitively impaired patients might have been underestimated in the ORBIT-AF study since no formal neurocognitive testing of patients was performed.
Few studies have examined factors associated with the presence of frailty and cognitive impairment in older patients with NVAF. Our results are consistent with previous findings that older age, lower education and heavier medical history are associated with either frailty or cognitive impairment in patients with AF. 15, 19 In addition to these predictors, we identified social isolation, depression, and reporting falls in the past 6 months as strong predictors of physical or cognitive impairments. Also, we observed that non-white participants were five times as likely to be cognitively impaired and were eight times as likely to be both frail and cognitively impaired than white participants. These results are consistent with previous studies in which older patients of races/ethnicities other than non-Hispanic white were at increased risk of cognitive impairment. 43 Several hypotheses have been proposed to explain racial disparities in the risk of cognitive impairment. The etiology and severity of cognitive impairment may differ, and differences may exist between these groups in the prevalence of chronic conditions, environmental, and sociodemographic factors.44, 45 These findings merit further investigation in the AF population since non-Caucasians are at increased risk for OAC related complications when compared to Caucasians. 46, 47
Contrary to previous studies of frailty and OAC prescribing in patients with AF, we found that OAC prescribing did not differ according to patient’s cognitive or frailty status suggesting that prescribers are following current guidelines that underscore the benefit of anticoagulation treatment even in frail older adults. 8 However, we found that patients with both frailty and cognitive impairment were more often treated with DOACs than VKA and that those who were cognitively impaired were more likely to be treated with VKA. Current guidelines, released after collection of these data, highlight the benefits of using DOACs. 8 It has been previously reported that the relative safety of DOACs compared to VKA is maintained among older adults with NVAF who also may be frail or cognitively impaired. 20, 48
In the SAGE-AF cohort, patients with CI alone or with both frailty and CI were more likely to report low treatment benefit. They also had socio-demographic characteristics that may challenge the optimal management of AF, such as low social support, living alone with low levels of education. These characteristics can increase the challenges of maintaining therapeutic targets and may lower satisfaction with AF treatment. 49-52 Previous studies have highlighted that higher treatment satisfaction may translate into improved treatment adherence, which is critical for the long-term prevention of stroke among AF patients. 53, 54 It has also been shown that reduced burden of treatment will translate to greater patient adherence to their treatment plans and a positive effect on clinical outcomes. 55 Therefore, satisfaction with the AF treatment is closely related to adherence of treatment and better chances of achieving the therapeutic goal. 54, 56 Future studies could examine role of type of OAC in perceived treatment burden and benefit among patients in relation to frailty and CI status.
We observed that a large proportion of older patients with AF also present with cognitive and/or physical impairment. These results emphasize that addressing only AF symptoms and stroke prevention without managing other comorbidities is unlikely to result in long-term successful management of AF. Therefore, a holistic management of AF that considers the frailty and CI status of older patients with AF is key to maximizing the success of AF management and to improving clinical outcomes. Integrated care pathways have been shown to reduce poor clinical outcomes among patients with AF and other conditions 57, 58. Our results identify key patient characteristics associated with cognitive and physical impairment and who would benefit from a more holistic management of their AF. With increasing interest in smart technology, a holistic care approach could incorporate App-based management to allow for remote care. 58
This study has several strengths. Frailty and cognitive function were measured using validated tools via standardized in-person interviews, and we studied a large contemporary cohort of patients with documented NVAF. Several limitations of this study need to be considered in the interpretation of our study findings. Patients with diagnosed dementia were excluded, thereby limiting the generalizability of the results for this patient population. In addition, there is the potential for differential misclassification in cognitively impaired participants so results should be interpreted with caution. However, while cognitive impairment may impact a participant’s ability to self-report some factors such as medication adherence, food diaries, etc, previous research shows that even with moderate cognitive impairment patients are able to accurately report medical conditions and respond to questionnaires about how they feel, including depression and anxiety. 59-61 We could not assess causal/temporal relationships between the impairments under study and OAC prescribing or satisfaction with AF treatment because of the cross-sectional nature of this analysis.
CONCLUSION
In a large cohort of older adults with NVAF, the co-occurrence of cognitive impairment and frailty is common and is associated with low perceived benefit of treatment which may impede optimal NVAF management. We observed that half of patients were frail or cognitively impaired and 9% had both impairments. Social isolation, depression, falls in the past 6 months, older age, lower level of education, race/ethnicity, and clinical risk scores were associated with a higher risk of having both impairments, suggesting that patients with these characteristics may benefit from cognitive and physical function screenings in order to maximize treatment planning and enhance the long-term prognosis of these patients.
Supplementary Material
ACKNOWLEDGEMENTS
Acknowledgments
Financial Disclosure: This manuscript was supported by grant R01HL126911 from the National Heart, Lung, and Blood Institute. DDM’s time was also supported by grants R01HL137734, R01HL137794, R01HL13660, R01HL141434 and U54HL143541from the National Heart, Lung and Blood Institute. The work was supported via a postdoctoral fellowship grant for TM from the Fonds de Recherche du Québec – Santé.
Sponsor’s Role:
The sponsor had no role in all aspects of the study or in the preparation of the manuscript.
Footnotes
Conflict of Interest: DDM has received research support from Apple Computer, Fitbit, Bristol-Myers Squibb, Boehringher-Ingelheim, Pfizer, Samsung, Philips Healthcare, Biotronik, and has received consultancy fees from Bristol-Myers Squibb, Pfizer, Flexcon, Boston Biomedical Associates, and Rose Consulting. The authors have no conflicts of interest to declare.
REFERENCES
- 1.Go AS, Hylek EM, Phillips KA, et al. Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the AnTicoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study. Jama. 2001;285(18):2370–2375. [DOI] [PubMed] [Google Scholar]
- 2.Chugh SS, Havmoeller R, Narayanan K, et al. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study. Circulation. 2014;129(8):837–847. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Colilla S, Crow A, Petkun W, Singer DE, Simon T, Liu X. Estimates of current and future incidence and prevalence of atrial fibrillation in the U.S. adult population. The American journal of cardiology. October 15 2013;112(8):1142–7. doi: 10.1016/j.amjcard.2013.05.063 [DOI] [PubMed] [Google Scholar]
- 4.Benjamin EJ, Wolf PA, D'Agostino RB, Silbershatz H, Kannel WB, Levy D. Impact of atrial fibrillation on the risk of death: the Framingham Heart Study. Circulation. September 8 1998;98(10):946–52. doi: 10.1161/01.cir.98.10.946 [DOI] [PubMed] [Google Scholar]
- 5.Wang TJ, Larson MG, Levy D, et al. Temporal relations of atrial fibrillation and congestive heart failure and their joint influence on mortality: the Framingham Heart Study. Circulation. June 17 2003;107(23):2920–5. doi: 10.1161/01.Cir.0000072767.89944.6e [DOI] [PubMed] [Google Scholar]
- 6.Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study. Stroke. August 1991;22(8):983–8. [DOI] [PubMed] [Google Scholar]
- 7.January CT, Wann LS, Alpert JS, et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the Heart Rhythm Society. Journal of the American College of Cardiology. 2014;64(21):e1–e76. [DOI] [PubMed] [Google Scholar]
- 8.January CT, Wann LS, Calkins H, et al. 2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the american college of Cardiology/American heart association task force on clinical practice guidelines and the heart rhythm society. Journal of the American College of Cardiology. 2019:25873. [DOI] [PubMed] [Google Scholar]
- 9.Andrade JG, Verma A, Mitchell LB, et al. 2018 focused update of the Canadian Cardiovascular Society guidelines for the management of atrial fibrillation. Canadian Journal of Cardiology. 2018;34(11):1371–1392. [DOI] [PubMed] [Google Scholar]
- 10.Oqab Z, Pournazari P, Sheldon RS. What is the Impact of Frailty on Prescription of Anticoagulation in Elderly Patients with Atrial Fibrillation? A Systematic Review and Meta-Analysis. Journal of atrial fibrillation. April 2018;10(6):1870. doi: 10.4022/jafib.1870 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Papakonstantinou PE, Asimakopoulou NI, Papadakis JA, et al. Frailty Status Affects the Decision for Long-Term Anticoagulation Therapy in Elderly Patients with Atrial Fibrillation. Drugs & aging. 2018;35(10):897–905. [DOI] [PubMed] [Google Scholar]
- 12.Lefebvre MC, St-Onge M, Glazer-Cavanagh M, et al. The Effect of Bleeding Risk and Frailty Status on Anticoagulation Patterns in Octogenarians With Atrial Fibrillation: The FRAIL-AF Study. The Canadian journal of cardiology. February 2016;32(2):169–76. doi: 10.1016/j.cjca.2015.05.012 [DOI] [PubMed] [Google Scholar]
- 13.Perera V, Bajorek BV, Matthews S, Hilmer SN. The impact of frailty on the utilisation of antithrombotic therapy in older patients with atrial fibrillation. Age and ageing. March 2009;38(2):156–62. doi: 10.1093/ageing/afn293 [DOI] [PubMed] [Google Scholar]
- 14.Feng L, Nyunt MS, Gao Q, et al. Physical Frailty, Cognitive Impairment, and the Risk of Neurocognitive Disorder in the Singapore Longitudinal Ageing Studies. The journals of gerontology Series A, Biological sciences and medical sciences. March 1 2017;72(3):369–375. doi: 10.1093/gerona/glw050 [DOI] [PubMed] [Google Scholar]
- 15.Polidoro A, Stefanelli F, Ciacciarelli M, Pacelli A, Di Sanzo D, Alessandri C. Frailty in patients affected by atrial fibrillation. Archives of gerontology and geriatrics. Nov-Dec 2013;57(3):325–7. doi: 10.1016/j.archger.2013.04.014 [DOI] [PubMed] [Google Scholar]
- 16.Diener H-C, Hart RG, Koudstaal PJ, Lane DA, Lip GY. Atrial fibrillation and cognitive function: JACC review topic of the week. Journal of the American College of Cardiology. 2019;73(5):612–619. [DOI] [PubMed] [Google Scholar]
- 17.Kakkar AK, Mueller I, Bassand J-P, et al. Risk profiles and antithrombotic treatment of patients newly diagnosed with atrial fibrillation at risk of stroke: perspectives from the international, observational, prospective GARFIELD registry. PloS one. 2013;8(5):e63479. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Baczek VL, Chen WT, Kluger J, Coleman CI. Predictors of warfarin use in atrial fibrillation in the United States: a systematic review and meta-analysis. BMC family practice. 2012;13(1):5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Madhavan M, Holmes DN, Piccini JP, et al. Association of Frailty and Cognitive Impairment with benefits of Oral anticoagulation in patients with atrial fibrillation. American heart journal. 2019; [DOI] [PubMed] [Google Scholar]
- 20.Martinez BK, Sood NA, Bunz TJ, Coleman CI. Effectiveness and safety of apixaban, dabigatran, and rivaroxaban versus warfarin in frail patients with nonvalvular atrial fibrillation. Journal of the American Heart Association. 2018;7(8):e008643. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Afzal SK, Hasan SS, Babar ZU. A Systematic Review of Patient Reported Outcomes Associated with the Use of Direct-acting Oral Anticoagulants. British journal of clinical pharmacology. May 11 2019;doi: 10.1111/bcp.13985 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Balkhi B, Al-Rasheedi M, Elbur AI, Alghamadi A. Association between satisfaction with and adherence to warfarin therapy on the control of international normalized ratio: A hospital-based study in Saudi Arabia. Saudi pharmaceutical journal. 2018;26(1):145–149. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Eltayeb TYM, Mohamed MS, Elbur AI, Elsayed ASA. Satisfaction with and adherence to warfarin treatment: A cross-sectional study among Sudanese patients. Journal of the Saudi Heart Association. 2017;29(3):169–175. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Saczynski J, Saket Sanghai, Catarina Kiefe, et al. Geriatric elements and oral anticoagulant prescribing in older atrial fibrillation patients: SAGE-AF. Journal of the American Geriatrics Society. In press; [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Schmitt EM, Marcantonio ER, Alsop DC, et al. Novel risk markers and long-term outcomes of delirium: the successful aging after elective surgery (SAGES) study design and methods. 2012;13(9):818. e1–818. e10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2001;56(3):M146–M157. [DOI] [PubMed] [Google Scholar]
- 27.Pereira MA, FitzerGerald SJ, Gregg EW, et al. A collection of Physical Activity Questionnaires for health-related research. Medicine and science in sports and exercise. June 1997;29(6 Suppl):S1–205. [PubMed] [Google Scholar]
- 28.Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society. 2005;53(4):695–699. [DOI] [PubMed] [Google Scholar]
- 29.Saczynski JS, Inouye SK, Guess J, et al. The Montreal Cognitive Assessment: Creating a Crosswalk with the Mini-Mental State Examination. Journal of the American Geriatrics Society. November 2015;63(11):2370–4. doi: 10.1111/jgs.13710 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. November 1975;12(3):189–98. doi: 10.1016/0022-3956(75)90026-6 [DOI] [PubMed] [Google Scholar]
- 31.McLennan SN, Mathias JL, Brennan LC, Stewart S. Validity of the Montreal Cognitive Assessment (MoCA) as a Screening Test for Mild Cognitive Impairment (MCI) in a Cardiovascular Population. Journal of Geriatric Psychiatry and Neurology. 2011/March/01 2010;24(1):33–38. doi: 10.1177/0891988710390813 [DOI] [PubMed] [Google Scholar]
- 32.Hachinski V, Iadecola C, Petersen RC, et al. National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards. Stroke. September 2006;37(9):2220–41. doi: 10.1161/01.Str.0000237236.88823.47 [DOI] [PubMed] [Google Scholar]
- 33.Pendlebury ST, Welch SJ, Cuthbertson FC, Mariz J, Mehta Z, Rothwell PM. Telephone assessment of cognition after transient ischemic attack and stroke: modified telephone interview of cognitive status and telephone Montreal Cognitive Assessment versus face-to-face Montreal Cognitive Assessment and neuropsychological battery. Stroke. January 2013;44(1):227–9. doi: 10.1161/strokeaha.112.673384 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Hanon O, Chaussade E, Gueranger P, Gruson E, Bonan S, Gay A. Patient-reported treatment satisfaction with rivaroxaban for stroke prevention in atrial fibrillation. A French observational study, the SAFARI Study. PloS one. 2016;11(12):e0166218. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Cano SJ, Lamping DL, Bamber L, Smith S. The Anti-Clot Treatment Scale (ACTS) in clinical trials: cross-cultural validation in venous thromboembolism patients. Health and quality of life outcomes. 2012;10(1):120. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Moser A, Stuck AE, Silliman RA, Ganz PA, Clough-Gorr KM. The eight-item modified Medical Outcomes Study Social Support Survey: psychometric evaluation showed excellent performance. Journal of clinical epidemiology. 2012;65(10):1107–1116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Sherbourne CD, Stewart AL. The MOS social support survey. Social science & medicine. 1991;32(6):705–714. [DOI] [PubMed] [Google Scholar]
- 38.Lubben J, Blozik E, Gillmann G, et al. Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. The Gerontologist. 2006;46(4):503–513. [DOI] [PubMed] [Google Scholar]
- 39.Spitzer RL, Kroenke K, Williams JB, Group PHQPCS. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Jama. 1999;282(18):1737–1744. [DOI] [PubMed] [Google Scholar]
- 40.Gilbody S, Richards D, Brealey S, Hewitt C. Screening for depression in medical settings with the Patient Health Questionnaire (PHQ): a diagnostic meta-analysis. Journal of general internal medicine. November 2007;22(11):1596–602. doi: 10.1007/s11606-007-0333-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Stafford L, Berk M, Jackson HJ. Validity of the Hospital Anxiety and Depression Scale and Patient Health Questionnaire-9 to screen for depression in patients with coronary artery disease. Gen Hosp Psychiatry. Sep-Oct 2007;29(5):417–24. doi: 10.1016/j.genhosppsych.2007.06.005 [DOI] [PubMed] [Google Scholar]
- 42.Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of internal medicine. 2006;166(10):1092–1097. [DOI] [PubMed] [Google Scholar]
- 43.Lopez OL, Jagust WJ, Dulberg C, et al. Risk Factors for Mild Cognitive Impairment in the Cardiovascular Health Study Cognition Study: Part 2. JAMA Neurology. 2003;60(10):1394–1399. doi: 10.1001/archneur.60.10.1394 [DOI] [PubMed] [Google Scholar]
- 44.Mayeda ER, Glymour MM, Quesenberry CP, Whitmer RA. Inequalities in dementia incidence between six racial and ethnic groups over 14 years. Alzheimers Dement. 2016;12(3):216–224. doi: 10.1016/j.jalz.2015.12.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Froehlich TE, Bogardus ST Jr., Inouye SK. Dementia and race: are there differences between African Americans and Caucasians? Journal of the American Geriatrics Society. April 2001;49(4):477–84. doi: 10.1046/j.1532-5415.2001.49096.x [DOI] [PubMed] [Google Scholar]
- 46.Shen AY, Yao JF, Brar SS, Jorgensen MB, Chen W. Racial/ethnic differences in the risk of intracranial hemorrhage among patients with atrial fibrillation. J Am Coll Cardiol. July 24 2007;50(4):309–15. doi: 10.1016/j.jacc.2007.01.098 [DOI] [PubMed] [Google Scholar]
- 47.Turagam MK, Velagapudi P, Visotcky A, Szabo A, Kocheril AG. African Americans have the highest risk of in-hospital mortality with atrial fibrillation related hospitalizations among all racial/ethnic groups: a nationwide analysis. International journal of cardiology. June 28 2012;158(1):165–6. doi: 10.1016/j.ijcard.2012.04.090 [DOI] [PubMed] [Google Scholar]
- 48.Karamichalakis N, Georgopoulos S, Vlachos K, et al. Efficacy and safety of novel anticoagulants in the elderly. Journal of geriatric cardiology: JGC. 2016;13(8):718. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Schauer DP, Moomaw CJ, Wess M, Webb T, Eckman MH. Psychosocial risk factors for adverse outcomes in patients with nonvalvular atrial fibrillation receiving warfarin. Journal of general internal medicine. December 2005;20(12):1114–9. doi: 10.1111/j.1525-1497.2005.0242.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Cruess DG, Localio AR, Platt AB, et al. Patient attitudinal and behavioral factors associated with warfarin non-adherence at outpatient anticoagulation clinics. International journal of behavioral medicine. March 2010;17(1):33–42. doi: 10.1007/s12529-009-9052-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Johnston JA, Cluxton RJ Jr., Heaton PC, Guo JJ, Moomaw CJ, Eckman MH. Predictors of Warfarin Use Among Ohio Medicaid Patients With New-Onset Nonvalvular Atrial Fibrillation. JAMA Internal Medicine. 2003;163(14):1705–1710. doi: 10.1001/archinte.163.14.1705 [DOI] [PubMed] [Google Scholar]
- 52.Orensky IA, Holdford DA. Predictors of noncompliance with warfarin therapy in an outpatient anticoagulation clinic. Pharmacotherapy. December 2005;25(12):1801–8. doi: 10.1592/phco.2005.25.12.1801 [DOI] [PubMed] [Google Scholar]
- 53.Koretsune Y, Kumagai K, Uchiyama S, et al. Patient-reported treatment satisfaction with rivaroxaban in Japanese non-valvular atrial fibrillation patients: an observational study. Current medical research and opinion. 2018;34(12):2157–2164. [DOI] [PubMed] [Google Scholar]
- 54.Wang Y, Kong MC, Lee LH, Ng HJ, Ko Y. Knowledge, satisfaction, and concerns regarding warfarin therapy and their association with warfarin adherence and anticoagulation control. Thrombosis research. 2014;133(4):550–554. [DOI] [PubMed] [Google Scholar]
- 55.Okumura Y, Yokoyama K, Matsumoto N, et al. Patient Satisfaction with Direct Oral Anticoagulants and Warfarin. International heart journal. 2018:17–649. [DOI] [PubMed] [Google Scholar]
- 56.Ruiz MA, González-Porras JR, Aranguren JL, et al. Development and validation of a new questionnaire measuring treatment satisfaction in patients with non-valvular atrial fibrillation: SAFUCA®. Quality of Life Research. 2017;26(3):767–778. [DOI] [PubMed] [Google Scholar]
- 57.Proietti M, Romiti GF, Olshansky B, Lane DA, Lip GYJJotAHA. Comprehensive Management With the ABC (Atrial Fibrillation Better Care) Pathway in Clinically Complex Patients With Atrial Fibrillation: A Post Hoc Ancillary Analysis From the AFFIRM Trial. 2020;9(10):e014932. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Guo Y, Lane DA, Wang L, et al. Mobile Health Technology to Improve Care for Patients With Atrial Fibrillation. J Am Coll Cardiol. April 7 2020;75(13):1523–1534. doi: 10.1016/j.jacc.2020.01.052 [DOI] [PubMed] [Google Scholar]
- 59.Bradford A, Brenes GA, Robinson RA, et al. Concordance of self- and proxy-rated worry and anxiety symptoms in older adults with dementia. J Anxiety Disord. January 2013;27(1):125–30. doi: 10.1016/j.janxdis.2012.11.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.McGivney SA, Mulvihill M, Taylor B. Validating the GDS depression screen in the nursing home. Journal of the American Geriatrics Society. May 1994;42(5):490–2. doi: 10.1111/j.1532-5415.1994.tb04969.x [DOI] [PubMed] [Google Scholar]
- 61.Snow AL, Kunik ME, Molinari VA, et al. Accuracy of self-reported depression in persons with dementia. Journal of the American Geriatrics Society. March 2005;53(3):389–96. doi: 10.1111/j.1532-5415.2005.53154.x [DOI] [PubMed] [Google Scholar]
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