Abstract
Background
In older patients with atrial fibrillation (AF), physical, cognitive, and psychosocial limitations are prevalent. The prognostic value of these conditions for major bleeding is unclear.
Objective
To determine whether geriatric conditions are prospectively associated with major bleeding in older patients with AF on anticoagulation.
Design
Multicenter cohort study with 2-year follow-up from 2016 to 2020 in Massachusetts and Georgia from cardiology, electrophysiology, and primary care clinics.
Participants
Diagnosed with AF, age 65 years or older, CHA2DS2-VASc score of 2 or higher, and taking oral anticoagulant (n=1,064). A total of 6507 individuals were screened.
Main Measures
A six-component geriatric assessment of frailty, cognitive function, social support, depressive symptoms, vision, and hearing. Main outcome was major bleeding adjudicated by a physician panel.
Key Results
At baseline, participants were, on average, 75.5 years old and 49% were women. Mean CHA2DS2-VASc score was 4.5 and the mean HAS-BLED score was 3.3. During 2.0 (± 0.4) years of follow-up, 95 (8.9%) participants developed an episode of major bleeding. After adjusting for key covariates and accounting for competing risk from death, cognitive impairment (hazard ratio [HR] 1.62, 95% confidence interval [CI]: 1.02–2.56) and frailty (HR 2.77, 95% CI 1.38–5.58) were significantly associated with the development of major bleeding.
Conclusions
In older patients with AF taking anticoagulants, cognitive impairment and frailty were independently associated with major bleeding.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11606-022-07410-x.
INTRODUCTION
Atrial fibrillation (AF) is the most common cardiac arrhythmia in older individuals and is associated with an increased risk of stroke and heart failure. Advanced age is the most important risk factor for AF and >80% of adults in the USA with AF were 65 years or older in 2010.1 With the aging of the American population, the burden of AF is projected to further increase.2
Physical, cognitive, and psychosocial impairments are common in older populations with cardiovascular conditions.3 We previously reported that up to 15% of older ambulatory adults with AF were frail, 30% were depressed, and 40% were cognitively impaired.4 These impairments pose challenges in patients’ daily lives and have been associated with poor clinical outcomes in isolated reports.5 However, their prognostic value for major bleeding has not been studied in a contemporary cohort of older patients with AF. As many older patients with AF are now treated with direct oral anticoagulants (DOACs), the performance of existing bleeding risk prediction tools is modest, limiting their utility.6
In the present report, we examined the prognostic value of geriatric conditions over 2-year follow-up for physician-adjudicated clinical outcomes. We also examined how geriatric conditions could improve the current paradigm of bleeding risk stratification and inform the risks and benefits discussions of anticoagulant prescription among older patients with AF.
METHODS
Study Sample
The details of the SAGE (Systematic Assessment of Geriatric Elements) - AF study have been previously described.3,4,7 The inclusion criteria were as follows: (1) age 65 years or older; (2) ambulatory visit at one of four Central Massachusetts practices (University of Massachusetts Memorial Health Care internal medicine, cardiology, or electrophysiology, Heart Rhythm Associates of Central Massachusetts), one practice in Eastern Massachusetts (Boston University cardiology), or two practices in Central Georgia (Family Health Center and Georgia Arrhythmia Consultants); (3) AF present on an electrocardiogram or Holter monitor or noted in any clinic note or hospital record, and 4) a CHA2DS2VASC8 (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) risk score ≥ 2. Participants were not eligible if they had an absolute contraindication to oral anticoagulation, had an indication for oral anticoagulation other than AF (i.e., mechanical heart valve), could not provide informed consent, did not speak English, had a planned invasive high bleeding risk procedure, were incarcerated, or were unwilling or unable to participate in planned follow-upvisits. A total of 6,507 individuals were screened. For the present analysis, only participants taking an oral anticoagulant (n=1,064) at the time of study enrollment were included. The enrollment flow chart is shown in Supplementary Figure S1.
All participants provided informed written consent. Study protocols were approved by the Institutional Review Boards at the University of Massachusetts Medical School, Boston University, and Mercer University.
Data Abstraction and Assessment of Geriatric Conditions
Socio-demographic information, clinical data, and relevant laboratory results were abstracted from the medical record by trained staff.
At baseline (2016–2018), six geriatric conditions (frailty, cognitive dysfunction, social support, depressive symptoms, vision impairment, and hearing impairment) were assessed by validated measures. Frailty was assessed by the Cardiovascular Health Survey frailty scale.9 Each component receives one point and the scale ranges from 0 to 5 (0: not frail; 1–2: pre-frail; 3 or more: frail). Cognition was assessed by the Montreal Cognitive Assessment Battery (MoCA).10 The modified version of the Social Support Scale and the Social Network Scale11 was used to assess the social support. The depressive symptoms were assessed by the Patient Health Questionnaire -9.12 Visual and hearing impairment were self-reported as yes/no. Details of assessment of geriatric conditions are in the Supplementary material.
Outcome Assessment
Death and bleeding events during the 2-year follow-up were adjudicated from the medical records and death certificates by a committee of physicians. Bleeding events were graded according to the International Society on Thrombosis and Hemostasis scale.13 Major bleeding included fatal bleeding, symptomatic bleeding in a critical area or organ (e.g., intracranial, spinal, ocular, pericardial, articular, retroperitoneal, or intramuscular with compartment syndrome), or bleeding that resulted in a fall in hemoglobin of ≥2 g/dL, or transfusion of ≥2 units of whole blood.
Statistical Analysis
The baseline characteristics were compared according to the presence of the composite of clinically relevant bleeding events or death using analysis of variance for continuous variables and the χ2 test for categorical variables.
The primary study outcome was major bleeding. The secondary outcome was a composite of all-cause mortality, major bleeding, and stroke.
The association between the six geriatric conditions and study outcomes was examined using Cox regression in which we controlled for age, sex, race, insurance status, major bleeding history, heart failure, coronary artery disease, peripheral arterial disease, hypertension, diabetes, renal disease, liver disease, and antiplatelet use. Variables adjusted for in the model were selected based on clinical significance and statistical significance from the results shown in Table 1. Race was included in our regression model because African Americans are less likely to develop atrial fibrillation but are at higher risk of stroke once they have atrial fibrillation compared with non-African American, suggesting that outcomes of AF may differ by race.14,15
Table 1.
Baseline Characteristics by Major Bleeding During Follow-up
| Major bleeding | p-value | ||
|---|---|---|---|
| Characteristic | Yes | No | |
| (n=95) | (n=969) | ||
| Age, M (SD) | 77.1 (7.3) | 75.6 (7.0) | 0.05 |
| 65–74 years | 39 (41.1%) | 480 (49.5%) | 0.22 |
| 75–84 years | 39 (41.1%) | 362 (37.4%) | |
| 85 years or older | 17 (11.8%) | 127 (13.1%) | |
| Female | 36 (37.9%) | 489 (50.5%) | 0.02 |
| Non-Hispanic White | 75 (79.0%) | 827 (85.4%) | 0.1 |
| College graduate or above | 31 (34.1%) | 407 (42.6%) | 0.12 |
| Income | |||
| $0–$49,999 | 45 (56.3%) | 410 (50.8%) | 0.64 |
| $50,000–$99,999 | 22 (27.5%) | 255 (31.6%) | |
| $100,000 or more | 13 (16.3%) | 142 (17.6%) | |
| Commercial insurance/HMO/PPO | 15 (15.8%) | 169 (17.4%) | 0.88 |
| Medicare | 71 (74.7%) | 701 (72.3%) | |
| CHA2DS2-VASC score (M, SD) | 4.9 (1.7) | 4.5 (1.6) | 0.02 |
| HAS-BLED score (M, SD) | 3.6 (1.1) | 3.2 (1.0) | <0.01 |
| Smoking status | |||
| Never smoker | 39 (41.1%) | 469 (48.4%) | 0.05 |
| Former smoker | 50 (52.6%) | 480 (49.5%) | |
| Current smoker | 6 (6.3%) | 20 (2.1%) | |
| History of major bleeding | 29 (30.5%) | 180 (18.6%) | 0.01 |
| Intracranial hemorrhage | 0 (0%) | 12 (1.2%) | |
| Gastrointestinal bleed | 22 (23.2%) | 101 (10.4%) | |
| Bleeding requiring transfusion | 9 (9.5%) | 27 (2.8%) | |
| Medical History | |||
| Heart failure | 48 (50.5%) | 362 (37.4%) | 0.02 |
| Ischemic heart disease | 39 (41.1%) | 262 (27.0%) | 0.01 |
| Peripheral vascular disease | 21 (22.1%) | 129 (13.3%) | 0.02 |
| Hypertension | 86 (90.5%) | 881 (90.9%) | 0.9 |
| Diabetes | 36 (37.9%) | 270 (27.9%) | 0.04 |
| Hyperlipidemia | 80 (84.2%) | 769 (79.4%) | 0.26 |
| Stroke | 16 (16.8%) | 92 (9.5%) | 0.03 |
| Alcohol abuse/dependency | 25 (26.3%) | 308 (31.8%) | 0.27 |
| Anemia | 37 (39.0%) | 297 (30.7%) | 0.1 |
| Asthma/COPD | 25 (26.3%) | 243 (25.1%) | 0.79 |
| Renal disease | 39 (41.1%) | 271 (28.0%) | <0.01 |
| Implantable cardiac device | 36 (37.9%) | 330 (34.1%) | 0.45 |
| Creatinine (mg/dL) | 1.3 (0.7) | 1.1 (0.5) | <0.01 |
| Hemoglobin (g/dL) | 12.8 (2.1) | 13.1 (1.8) | 0.1 |
| Platelet (× 109 per liter) | 195.6 (61.9) | 210.4 (69.9) | 0.08 |
| Systolic blood pressure (mmHg) | 128.8 (17.6) | 131.4 (19.9) | 0.22 |
| Baseline visit heart rate (bpm) | 38 (40.0%) | 270 (27.9%) | 0.01 |
| Aspirin | 8 (8.4%) | 47 (4.9%) | 0.08 |
| Clopidogrel | 1 (1.1%) | 1 (0.1%) | |
| Direct oral anticoagulant | 35 (36.8%) | 431 (44.5%) | 0.15 |
| Warfarin | 60 (63.2%) | 538 (55.5%) | |
Data are presented as n (%) or mean (standard deviation).
Abbreviations: mmHg, millimeter of mercury; mg/dL, milligrams per deciliter; g/dL, grams per deciliter; bpm, beats per minute
Participants’ 2-year survival from major bleeding was estimated using Kaplan–Meier curves and compared using the log-rank test.
When major bleeding was examined as the outcome of interest, competing risk from death was accounted for by calculating the cause-specific hazard ratios.
Because DOACs have a lower risk of stroke and bleeding compared with warfarin,16 stratified analyses (DOAC versus warfarin) were performed. In the warfarin subgroup, time in therapeutic range was additionally controlled for as an indicator for INR stability. INR stability was assessed by time in therapeutic range. We collected up to 12 INRs in the 4 weeks prior to enrollment. It was assessed at baseline and not used as a time-varying covariate.
To further evaluate the prognostic value of frailty and cognitive impairment, the concordance statistic (C-statistic) of HAS-BLED was calculated for major bleeding and compared with those of HAS-BLED plus geriatric conditions. The Mann–Whitney test was used to compare the areas under the receiver operating characteristics curves.17 The continuous net reclassification index (NRI) was used to evaluate the predictive value of adding frailty and cognitive impairment to the HAS-BLED score to check for a possible increase in the predicted risks for outcome events and decrease in predicted risks for nonevents.
We utilized the following formula in calculation of event and nonevent NRIs. Event (major bleeding) NRI = (number of events with increased predicted risk − number of events with decreased predicted risk)/number of events. Nonevent NRI = (number of nonevents with decreased predicted risk − number of nonevents with increased predicted risk)/number of nonevents. The overall NRI is equal to the sum of the event and nonevent NRI.18
All statistical analyses were performed using SAS 9.4 (SAS Institute, Inc., Cary, NC). A two-sidedp value < 0.05 was considered to be statistically significant.
Role of the Funding source
The funding source of this project was R01HL126911 from the National Heart, Lung, and Blood Institute. The funding source had no role in the study’s design, conduct, or reporting.
RESULTS
Study Population
Between 2016 and 2018, 1,244 participants were enrolled. Of these, 1,064 individuals were taking oral anticoagulants and included in these analyses. At baseline, participants were on average 75.5 (± 7.1) years old; 49% were women. Individuals who developed major bleeding (n= 95, 8.9%) were older than those who did not. They had a higher burden of comorbidities, including a history of major bleeding, heart failure, ischemic heart disease, peripheral artery disease, diabetes, stroke, and renal disease compared with those who did not develop major bleeding. They were also more likely to report taking aspirin. Their CHA2DS2VASC and HAS-BLED scores were higher than in the individuals who did not develop major bleeding (please refer to Table 1 for details).
At baseline, physical, cognitive, and psychosocial impairments were prevalent: frailty (n= 149, 14.0%), cognitive impairment (n=449, 42.2%), social isolation (n=133, 12.5%), hearing impairment (n=386, 36.3%), visual impairment (n=370, 34.8%), and depressive symptoms (n=303, 28.5%) were all commonly occurring comorbidities.
During average follow-up of 2.0 years (standard deviation 0.4), 97 (9.1%) individuals died. Major bleeding occurred in 95 (8.9%) individuals. There were 13 (1.2%) individuals who developed stroke.
Geriatric Conditions and Major Bleeding
Among the six geriatric conditions of interest, cognitive impairment and frailty were significantly associated with major bleeding during the follow-up(Table 2).
Table 2.
Hazard Ratios of Experiencing a Major Bleeding Episode Over 2 Years by Geriatric Conditions
| Hazard ratio (95% confidence interval) | |||
|---|---|---|---|
| Unadjusted | Model 1 | ||
| Cognitive impairment | Yes | 1.97 (1.31, 2.97) | 1.62 (1.02, 2.56) |
| No | Reference | ||
| Depression | Yes | 1.32 (0.86, 2.02) | 1.26 (0.79, 2.02) |
| No | Reference | ||
| Frailty | Frail | 3.38 (1.81, 6.31) | 2.77 (1.38, 5.58) |
| Pre-frail | 1.95 (1.13, 3.36) | 1.73 (0.99, 3.04) | |
| No | Reference | ||
| Hearing impairment | Yes | 1.48 (0.98, 2.21) | 1.30 (0.83, 2.03) |
| No | Reference | ||
| Social isolation | Yes | 1.00 (0.55, 1.82) | 1.07 (0.58, 1.98) |
| No | Reference | ||
| Vision impairment | Yes | 1.10 (0.72, 1.67) | 0.97 (0.63, 1.48) |
| No | Reference | ||
Adjusted for age, sex, race, insurance, bleeding history, heart failure, coronary artery disease, peripheral arterial disease, hypertension, diabetes, chronic obstructive lung disease, renal disease liver disease, antiplatelet use.
Kaplan–Meier estimates of freedom from major bleeding, according to the presence of cognitive impairment at baseline, are shown in Figure 1. After controlling for age, sex, race, insurance, bleeding history, heart failure, coronary artery disease, peripheral arterial disease, hypertension, diabetes, chronic obstructive lung disease, renal disease, liver disease, and antiplatelet use and accounting for the competing risk from death, cognitively impaired participants had a significantly increased risk of major bleeding (hazard ratio [HR] 1.62, 95% confidence interval [CI]: 1.02–2.56) as compared with individuals who were not cognitively impaired.
Figure 1.
Kaplan–Meier estimates of freedom from major bleeding by the presence of cognitive impairment: SAGE-AF (Systematic Assessment of Geriatric Elements in Atrial Fibrillation) 2016–2020.
Kaplan–Meier estimates of freedom from major bleeding, according to frailty status at baseline, are shown in Figure 2. After controlling for several demographic and clinical variables and accounting for the competing risk from death, compared to not being frail, patients who were frail (HR 2.77, 95% CI 1.38–5.58) had a significantly increased risk for major bleeding.
Figure 2.
Kaplan–Meier estimates of freedom from major bleeding by the frailty status: SAGE-AF (Systematic Assessment of Geriatric Elements in Atrial Fibrillation), 2016–2020.
The prognostic value of cognitive impairment and frailty for major bleeding was not different significantly among individuals on warfarin or DOAC (Supplementary Figure S2).
The C-statistic of HAS-BLED predicting major bleeding was 0.59, which increased to 0.64 after the addition of frailty and cognitive impairment (p=0.006) (Supplementary Figure S3). The continuous net reclassification index (NRI) of adding frailty and cognitive impairment to HAS-BLED was 0.41 (95% confidence interval 0.21–0.62; event NRI = 0.16 and non-event NRI = 0.26) (Supplementary Table S1).
Geriatric Conditions and the Composite of Death, Major Bleeding, and Stroke
Cognitive impairment (HR 1.42, 95% CI: 1.03–1.98), frailty (HR 2.33, 95% CI: 1.39–3.91), and depression (HR 1.70, 95% CI: 1.24–2.33) were significantly associated with the composite of death, major bleeding, and stroke after controlling for age, sex, race, insurance, bleeding history, heart failure, coronary artery disease, peripheral arterial disease, hypertension, diabetes, chronic obstructive lung disease, renal disease liver disease, and antiplatelet use (Table 3).
Table 3.
Hazard Ratios of Experiencing Death, Major Bleeding, or Stroke Over 2-Year Follow-up by Geriatric Conditions
| Hazard ratio (95% confidence interval) | |||
|---|---|---|---|
| Unadjusted | Adjusted | ||
| Cognitive impairment | Yes | 1.99 (1.47, 2.68) | 1.42 (1.03, 1.98) |
| No | Reference | ||
| Depression | Yes | 1.76 (1.30, 2.38) | 1.70 (1.24, 2.33) |
| No | Reference | ||
| Frailty | Frail | 3.86 (2.41, 6.19) | 2.33 (1.39, 3.91) |
| Pre-frail | 2.23 (1.48, 3.37) | 1.67 (1.08, 2.57) | |
| No | Reference | ||
| Hearing impairment | Yes | 1.40 (1.04, 1.88) | 1.15 (0.84, 1.58) |
| No | Reference | ||
| Social isolation | Yes | 1.08 (0.70, 1.68) | 1.22 (0.78, 1.91) |
| No | Reference | ||
| Vision impairment | Yes | 1.22 (0.90, 1.65) | 1.05 (0.77, 1.44) |
| No | Reference | ||
Adjusted for age, sex, race, insurance, bleeding history, heart failure, coronary artery disease, peripheral arterial disease, hypertension, diabetes, chronic obstructive lung disease, renal disease liver disease, antiplatelet use.
DISCUSSION
In a contemporary cohort of geriatric patients with AF prescribed anticoagulation, impairments in several clinically important and easily assessable geriatric conditions were prevalent and prognostic for adverse clinical outcomes. Cognitive impairment and frailty were prospectively associated with a significantly increased risk of major bleeding over the 2-year follow-up. The associations between cognitive impairment, frailty, and major bleeding did not differ significantly between individuals on warfarin or DOAC. Furthermore, the addition of frailty and cognitive impairment to the HAS-BLED score significantly improved its prediction for major bleeding.
Anticoagulation is the cornerstone treatment modality for stroke prevention in AF management. Despite the undesired consequence of bleeding,19,20 anticoagulation is believed to provide clinical benefit even in very elderly patients with AF.21 Similar to AF, the prevalence of cognitive impairment and frailty rises with increasing age.22,23 Intuitively, these conditions should confer a higher bleeding risk in older patients with AF. In this context, our study addressed this clinically relevant question with the systematic evaluation of geriatric conditions, prospective follow-up, and rigorous outcome adjudication.
The reports on the prognostic value of various geriatric conditions in individuals with AF are limited. For example, depression has been associated with increased all-cause mortality in patients with AF who had concomitant heart failure5 and who were seen in the primary care setting.24 Frailty has been associated with an increased risk of dying and re-admission after AF ablation.25 However, findings from previous studies are limited due to the following: (1) being conducted before the DOAC era so all participants were on warfarin, not reflecting the current prescription pattern of anticoagulants;26(2) exposures of interest (frailty or cognitive impairment) were assessed by clinical documentation27 or International Classification of Diseases codes instead of validated tools,25 which could lead to under-reporting and misclassification; and (3) bleeding outcomes were not centrally adjudicated by a physician panel but relied on billing codes.26
We observed a high rate of bleeding (9% major bleeding, 26% clinically relevant non-major bleeding over 2 years), which exceeded the rates from the pivotal trials of DOAC therapy in AF. In the ARISTOTLE trial comparing apixaban to warfarin for stroke prevention in patients with AF (median age 70 years, interquartile range 63–76 years old, at least one additional risk factor for stroke, mean CHADS2 score 2.1), the annual rate of major bleeding was 2.1% in the apixaban group and 3.1% in the warfarin group.20 In the ROCKET-AF trial, rivaroxaban was compared to warfarin in patients with nonvalvular AF (median age 73 years , interquartile range 65–78 years old, mean CHADS2 score 3.5) where the rate of clinically relevant bleeding was approximately 14% annually in both treatment arms.19 The older age and higher burden of comorbidities of patients in our cohort may explain the differences observed between our studies and prior clinical trials. The observed net clinical benefit between prevention of stroke and bleeding complications may be less favorable in clinical practice as compared to those seen in clinical trials. This should be weighed in any risk/benefit discussions of anticoagulation prescription and reinforces the importance of refining bleeding risk stratification in patients with AF.
Our finding expands the prognostic value of frailty for worse clinical outcomes in older populations with conditions other than AF.28 Frailty was assessed not by biological age or count of comorbidities. Instead, the assessment centered around functional status and included weight loss, exhaustion, low physical activity, slow gait speed, and weakness. Assessment of these symptoms has not been an integral part of clinic visits for AF and our findings should encourage providers to assess them when taking care of older patients with AF.
The implications of this study are twofold. First, patients at high risk for stroke are generally considered high risk for bleeding because of the overlapping components of CHA2DS2VASC and HASBLED. Our findings suggest that the absence of frailty and cognitive impairment can give clinicians more confidence in prescribing anticoagulation to these individuals. Secondly, the use of bleeding risk scores is advocated by the management guidelines in AF care.29 Therefore, our findings call for future studies that would derive and validate risk calculators integrating assessment of cognition and frailty in older patient populations.
STUDY STRENGTHS AND LIMITATIONS
Our study has several strengths. First, we used a prospective design and evaluated the prognostic utility of geriatric conditions with brief but validated instruments amenable to administration in clinical settings. Second, participants were geographically diverse from multiple ambulatory health systems. Despite a large burden of comorbid diseases, loss to follow-up was infrequent. An experienced panel of clinician reviewers formally adjudicated mortality and categorized bleeding events from electronic health record data. We were able to account for the competing risk from death when we examined the association between geriatric conditions and the development of a major bleeding episode. However, we did not have data on the burden of AF. Very few participants developed stroke and the study was underpowered to examine the association between geriatric conditions and stroke. Given the observational nature of the present study, we cannot establish causation and residual confounding may have affected our study results.
In conclusion, among older persons with AF who are at increased risk for stroke and are anticoagulated, cognitive impairment and frailty are novel and important risk factors for major bleeding. Cognitive and physical functional status should be considered in the shared decision-making process regarding anticoagulation for patients with AF.
Supplementary information
(DOCX 345 kb)
Funding
This manuscript was supported by grant R01HL126911 from the National Heart, Lung, and Blood Institute. David McManus’s time was also supported by grants R01HL137734, R01HL137794, R01HL13660, and R01HL141434, also from the National Heart, Lung and Blood Institute.
Declarations
Conflict of Interest
DDM has received direct research or grant support from Apple Computer, Fitbit, Bristol-Myers Squibb, Boerhingher-Ingelheim, Pfizer, Samsung, Philips Healthcare, Biotronik, and Flexcon. DDM has received consultancy fees from the Heart Rhythm Society, Bristol-Myers Squibb, Pfizer, Flexcon, and Boston Biomedical Associates. DDM serves on the Steering Committee of the GUARD AF study and Advisory Committee for the Fitbit Heart Study.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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