Automated interpretations of single-lead electrocardiograms predict incident atrial fibrillation: The VITAL-AF Trial.

BACKGROUND: Single-lead electrocardiograms (1L ECG) are increasingly used for atrial fibrillation (AF) detection. Automated 1L ECG interpretation may possess prognostic value for future AF among cases where screening does not result in a short-term AF diagnosis. OBJECTIVE: Investigate the association between automated 1L ECG interpretation and incident AF. METHODS: VITAL-AF was a randomized controlled trial investigating the effectiveness of screening for AF using 1L ECGs. For the present study, participants were divided into four groups based on automated classification of 1L ECGs. Patients with prevalent AF were excluded. Associations between groups and incident AF were assessed using Cox proportional hazards models adjusted for risk factors. The start of follow-up was defined as 60 days after the latest 1L ECG (as some individuals had numerous screening 1L ECGs). RESULTS: The study sample included: Never screened (n=16,306), Normal (n=10,914), Other (n=2,675), Possible AF (n=561). Possible AF had the highest AF incidence (5.91 per 100 person-years, 95% Confidence Interval [CI] 4.24-8.23). Possible AF was associated with greater hazard of incident AF compared to Normal (adjusted Hazard Ratio (2.48, 95% CI 1.66-3.71). Other was associated with greater hazard of incident AF when compared to Normal (1.41, 95% CI 1.04-1.90). CONCLUSIONS: In patients undergoing AF screening with 1L ECGs without prevalent AF or AF within 60 days of screening, presumptive positive and indeterminate 1L ECG interpretations were associated with future AF. Abnormal 1L ECGs may identify individuals at higher risk for future AF.

Development and Validation of an Intracranial Hemorrhage Risk Score in Older Adults with Atrial Fibrillation Treated with Oral Anticoagulant.

Background: High risk of intracranial hemorrhage (ICH) is a leading reason for withholding anticoagulation in patients with atrial fibrillation (AF). We aimed to develop a claims-based ICH risk prediction model in older adults with AF initiating oral anticoagulation (OAC). Methods: We used US Medicare claims data to identify new users of OAC aged ≥65 years with AF in 2010-2017. We used regularized Cox regression to select predictors of ICH. We compared our AF ICH risk score with the HAS-BLED bleed risk and Homer fall risk scores by area under the receiver operating characteristic curve (AUC) and assessed net reclassification improvement (NRI) when predicting 1-year risk of ICH. Results: Our study cohort comprised 840,020 patients (mean [SD] age 77.5 [7.4] years and female 52.2%) split geographically into training (3963 ICH events [0.6%] in 629,804 patients) and validation (1397 ICH events [0.7%] in 210,216 patients) sets. Our AF ICH risk score, including 50 predictors, had superior AUCs of 0.653 and 0.650 in the training and validation sets than the HAS-BLED score of 0.580 and 0.567 (p<0.001) and the Homer score of 0.624 and 0.623 (p<0.001). In the validation set, our AF ICH risk score reclassified 57.8%, 42.5%, and 43.9% of low, intermediate, and high-risk patients, respectively, by HAS-BLED score (NRI: 15.3%, p<0.001). Similarly, it reclassified 0.0, 44.1, and 19.4% of low, intermediate, and high-risk patients, respectively, by the Homer score (NRI: 21.9%, p<0.001). Conclusion: Our novel claims-based ICH risk prediction model outperformed the standard HAS-BLED score and can inform OAC prescribing decisions.

Patient Characteristics Associated With Using Transcatheter Left Atrial Appendage Occlusion Versus Oral Anticoagulants for Atrial Fibrillation.

BACKGROUND: Transcatheter left atrial appendage occlusion (LAAO) is an alternative to oral anticoagulants (OACs) for stroke prevention in patients with atrial fibrillation, but the predictors of LAAO use in routine care are unclear. We aimed to assess the utilization trends of LAAO and compare the change in characteristics of LAAO users versus OACs since its marketing. METHODS: Using the US Medicare claims database (March 15, 2015, to December 31, 2020), we identified patients with atrial fibrillation, ≥65 years, and CHA2DS2-VASc score ≥2 (men) or ≥3 (women), with either first implantation of an LAAO device or initiation of OACs, including apixaban, dabigatran, rivaroxaban, edoxaban, or warfarin. Patient characteristics, measured 365 days before the first LAAO or OAC use date, were compared using logistic regression. RESULTS: There were 30 058 LAAO recipients (mean age, 77.74 years; female, 42.1%) and 792 600 OAC initiators (mean age, 78.48; female, 53.3%). In 2020, patients had higher odds of initiating LAAO use than in 2015 (0.52 versus 9.32%; adjusted odds ratio [aOR], 13.64 [95% CI, 12.56-14.81]). Old age (ie, >85 versus 65-75 years; aOR, 0.84 [95% CI, 0.80-0.88]), female sex (aOR, 0.74 [95% CI, 0.71-0.76]), Black race (aOR, 0.63 [95% CI, 0.58-0.68]) versus White race, and Medicaid eligibility (aOR, 0.61 [95% CI, 0.58-0.64]) were associated with lower odds of receiving LAAO. Among clinical characteristics, frailty, cancer, fractures, and venous thromboembolism were associated with lower odds of LAAO use, while history of intracranial and extracranial bleeding, coagulopathy, and falls were associated with higher odds of receiving LAAO. CONCLUSIONS: Among patients with atrial fibrillation receiving stroke-preventive therapy, LAAO use increased rapidly from 2015 to 2020 and was positively associated with the risk factors for OAC complications but negatively associated with old age, advanced frailty, and cancer. Black race and female sex were associated with a lower likelihood of receiving LAAO.

Estimating Vitamin K Antagonist Anticoagulation Benefit in People With Atrial Fibrillation Accounting for Competing Risks: Evidence From 12 Randomized Trials.

BACKGROUND: Patients with atrial fibrillation have a high mortality rate that is only partially attributable to vascular outcomes. The competing risk of death may affect the expected anticoagulant benefit. We determined if competing risks materially affect the guideline-endorsed estimate of anticoagulant benefit. METHODS: We conducted a secondary analysis of 12 randomized controlled trials that randomized patients with atrial fibrillation to vitamin K antagonists (VKAs) or either placebo or antiplatelets. For each participant, we estimated the absolute risk reduction (ARR) of VKAs to prevent stroke or systemic embolism using 2 methods-first using a guideline-endorsed model (CHA2DS2-VASc) and then again using a competing risk model that uses the same inputs as CHA2DS2-VASc but accounts for the competing risk of death and allows for nonlinear growth in benefit. We compared the absolute and relative differences in estimated benefit and whether the differences varied by life expectancy. RESULTS: A total of 7933 participants (median age, 73 years, 36% women) had a median life expectancy of 8 years (interquartile range, 6-12), determined by comorbidity-adjusted life tables and 43% were randomized to VKAs. The CHA2DS2-VASc model estimated a larger ARR than the competing risk model (median ARR at 3 years, 6.9% [interquartile range, 4.7%-10.0%] versus 5.2% [interquartile range, 3.5%-7.4%]; P<0.001). ARR differences varied by life expectancies: for those with life expectancies in the highest decile, 3-year ARR difference (CHA2DS2-VASc model - competing risk model 3-year risk) was -1.3% (95% CI, -1.3% to -1.2%); for those with life expectancies in the lowest decile, 3-year ARR difference was 4.7% (95% CI, 4.5%-5.0%). CONCLUSIONS: VKA anticoagulants were exceptionally effective at reducing stroke risk. However, VKA benefits were misestimated with CHA2DS2-VASc, which does not account for the competing risk of death nor decelerating treatment benefit over time. Overestimation was most pronounced when life expectancy was low and when the benefit was estimated over a multiyear horizon.

Predicting post-stroke cognitive impairment using electronic health record data.

BACKGROUND: Secondary prevention interventions to reduce post-stroke cognitive impairment (PSCI) can be aided by the early identification of high-risk individuals who would benefit from risk factor modification. AIMS: To develop and evaluate a predictive model to identify patients at increased risk of PSCI over 5 years using data easily accessible from electronic health records. METHODS: Cohort study that included primary care patients from two academic medical centers. Patients were aged 45 years or older, without prior stroke or prevalent cognitive impairment, with primary care visits and an incident ischemic stroke between 2003 and 2016 (development/internal validation cohort) or 2010 and 2022 (external validation cohort). Predictors of PSCI were ascertained from the electronic health record. The outcome was incident dementia/cognitive impairment within 5 years and beginning 3 months following stroke, ascertained using International Classification of Diseases, Ninth/Tenth Revision (ICD-9/10) codes. For model variable selection, we considered potential predictors of PSCI and constructed 400 bootstrap samples with two-thirds of the model derivation sample. We ran 10-fold cross-validated Cox proportional hazards models using a least absolute shrinkage and selection operator (LASSO) penalty. Variables selected in >25% of samples were included. RESULTS: The analysis included 332 incident diagnoses of PSCI in the development cohort (n = 3741), and 161 and 128 incident diagnoses in the internal (n = 1925) and external (n = 2237) validation cohorts, respectively. The C-statistic for predicting PSCI was 0.731 (95% confidence interval (CI): 0.694-0.768) in the internal validation cohort, and 0.724 (95% CI: 0.681-0.766) in the external validation cohort. A risk score based on the beta coefficients of predictors from the development cohort stratified patients into low (0-7 points), intermediate (8-11 points), and high (12-23 points) risk groups. The hazard ratios (HRs) for incident PSCI were significantly different by risk categories in internal (high, HR: 6.2, 95% CI: 4.1-9.3; Intermediate, HR: 2.7, 95% CI: 1.8-4.1) and external (high, HR: 6.1, 95% CI: 3.9-9.6; Intermediate, HR: 2.8, 95% CI: 1.9-4.3) validation cohorts. CONCLUSION: Five-year risk of PSCI can be accurately predicted using routinely collected data. Model output can be used to risk stratify and identify individuals at increased risk for PSCI for preventive efforts. DATA ACCESS STATEMENT: Mass General Brigham data contain protected health information and cannot be shared publicly. The data processing scripts used to perform analyses will be made available to interested researchers upon reasonable request to the corresponding author.

Brain MRI microbleeds and risk of intracranial hemorrhage in atrial fibrillation patients: A Swedish case-control study.

OBJECTIVES: Our goal was to quantify the independent association of brain microbleeds with future intracranial hemorrhage (ICrH). Microbleed findings on brain magnetic resonance imaging (MRI) may identify distinctive risk factors for ICrH which could inform the anticoagulant therapy decision for atrial fibrillation (AF) patients. Our study design includes patients with MRIs for numerous reasons, not limited to evaluation of stroke. MATERIALS AND METHODS: The source population was all patients with AF from a nationwide Swedish health care register. Case patients had an ICrH between 2006 and 2013 and ≥1 brain MRI for an unrelated condition before the ICrH. Each case was matched to four controls who had a brain MRI without a subsequent ICrH. The MRIs were re-reviewed by neuroradiologists. Associations between MRI findings and subsequent ICrH were assessed using logistic regression, adjusting for comorbidities and antithrombotic medications. RESULTS: A total of 78 cases and 312 matched controls were identified; 29 cases and 79 controls had MRI sequences suitable for analysis of microbleeds. Patients with ≥10 microbleeds had a markedly increased risk of ICrH (adjusted odds ratio 14.56; 95 % confidence interval: 2.86-74.16, p < 0.001). All patients with ≥10 microbleeds had microbleeds in the lobar region and ≥10 lobar microbleeds was associated with intracerebral hemorrhages, univariable OR 8.54 (2.01-36.33), p = 0.004. CONCLUSIONS: Leveraging a nationwide database with brain imaging obtained prior to ICrH, we identified a strong association between ≥10 microbleeds on brain MRI and subsequent ICrH among AF patients. Lobar brain regions were involved whenever there were ≥10 microbleeds. Brain MRIs may help optimize the anticoagulation decision in selected AF patients.

Predicting post-stroke cognitive impairment using electronic health record data.

Importance: Secondary prevention interventions to reduce post-stroke cognitive impairment (PSCI) can be aided by the early identification of high-risk individuals who would benefit from risk factor modification. Objective: To develop and evaluate a predictive model to identify patients at increased risk of PSCI over 5 years using data easily accessible from electronic health records. Design: Cohort study with patients enrolled between 2003-2016 with follow-up through 2022. Setting: Primary care practices affiliated with two academic medical centers. Participants: Individuals 45 years or older, without prior stroke or prevalent cognitive impairment, with primary care visits and an incident ischemic stroke between 2003-2016 (development/internal validation cohort) or 2010-2022 (external validation cohort). Exposures: Predictors of PSCI were ascertained from the electronic health record. Main Outcome: The outcome was incident dementia/cognitive impairment within 5 years and beginning 3 months following stroke, ascertained using ICD-9/10 codes. For model variable selection, we considered potential predictors of PSCI and constructed 400 bootstrap samples with two-thirds of the model derivation sample. We ran 10-fold cross-validated Cox proportional hazards models using a least absolute shrinkage and selection operator (LASSO) penalty. Variables selected in >25% of samples were included. Results: The analysis included 332 incident diagnoses of PSCI in the development cohort (n=3,741), and 161 and 128 incident diagnoses in the internal (n=1,925) and external (n=2,237) validation cohorts. The c-statistic for predicting PSCI was 0.731 (95% CI: 0.694-0.768) in the internal validation cohort, and 0.724 (95% CI: 0.681-0.766) in the external validation cohort. A risk score based on the beta coefficients of predictors from the development cohort stratified patients into low (0-7 points), intermediate (8-11 points), and high (12-35 points) risk groups. The hazard ratios for incident PSCI were significantly different by risk categories in internal (High, HR: 6.2, 95% CI 4.1-9.3; Intermediate, HR 2.7, 95% CI: 1.8-4.1) and external (High, HR: 6.1, 95% CI: 3.9-9.6; Intermediate, HR 2.8, 95% CI: 1.9-4.3) validation cohorts. Conclusions and Relevance: Five-year risk of PSCI can be accurately predicted using routinely collected data. Model output can be used to risk stratify and identify individuals at increased risk for PSCI for preventive efforts.

Characteristics and Attitudes of Wearable Device Users and Nonusers in a Large Health Care System.

BACKGROUND: Consumer wearable devices with health and wellness features are increasingly common and may enhance disease detection and management. Yet studies informing relationships between wearable device use, attitudes toward device data, and comprehensive clinical profiles are lacking. METHODS AND RESULTS: WATCH-IT (Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology) studied adults receiving longitudinal primary or ambulatory cardiovascular care in the Mass General Brigham health care system from January 2010 to July 2021. Participants completed a 20-question electronic survey about perceptions and use of consumer wearable devices, with responses linked to electronic health records. Multivariable logistic regression was used to identify factors associated with device use. Among 214 992 individuals receiving longitudinal primary or cardiovascular care with an active electronic portal, 11 121 responded (5.2%). Most respondents (55.8%) currently used a wearable device, and most nonusers (95.3%) would use a wearable if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, most believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR], 0.80 per 10-year increase [95% CI, 0.77-0.82]), male sex (OR, 0.87 [95% CI, 0.80-0.95]), and heart failure (OR, 0.75 [95% CI, 0.63-0.89]) were associated with lower odds of wearable device use, whereas higher median income (OR, 1.08 per 1-quartile increase [95% CI, 1.04-1.12]) and care in a cardiovascular medicine clinic (OR, 1.17 [95% CI, 1.05-1.30]) were associated with greater odds of device use. CONCLUSIONS: Among patients in primary and cardiovascular medicine clinics, consumer wearable device use is common, and most users perceive value in wearable health data.

Frailty, Home Time, and Health Care Costs in Older Adults With Atrial Fibrillation Receiving Oral Anticoagulants.

Importance: There are no data on patient-centered outcomes and health care costs by frailty in patients with atrial fibrillation (AF) taking oral anticoagulants (OACs). Objective: To compare home time, clinical events, and health care costs associated with OACs by frailty levels in older adults with AF. Design, Setting, and Participants: This community-based cohort study assessed Medicare fee-for-service beneficiaries 65 years or older with AF from January 1, 2013, to December 31, 2019. Data analysis was performed from January to December 2022. Exposures: Apixaban, rivaroxaban, and warfarin use were measured from prescription claims. Frailty was measured using a validated claims-based frailty index. Main outcomes and measures: Outcome measures were (1) home time (days alive out of the hospital and skilled nursing facility) loss greater than 14 days; (2) a composite end point of ischemic stroke, systemic embolism, major bleeding, or death; and (3) total cost per member per year after propensity score overlap weighting. Results: The weighted population comprised 136 551 beneficiaries, including 45 950 taking apixaban (mean [SD] age, 77.6 [7.3] years; 51.3% female), 45 320 taking rivaroxaban (mean [SD] age, 77.6 [7.3] years; 51.9% female), and 45 281 taking warfarin (mean [SD] age, 77.6 [7.3] years; 52.0% female). Compared with apixaban, rivaroxaban was associated with increased risk of home time lost greater than 14 days (risk difference per 100 persons, 1.8 [95% CI, 1.5-2.1]), composite end point (rate difference per 1000 person-years, 21.3 [95% CI, 16.4-26.2]), and total cost (mean difference, $890 [95% CI, $652-$1127]), with greater differences among the beneficiaries with frailty. Use of warfarin relative to apixaban was associated with increased home time lost (risk difference per 100 persons, 3.2 [95% CI, 2.9-3.5]) and composite end point (rate difference per 1000 person-years, 29.4 [95% CI, 24.5-34.3]), with greater differences among the beneficiaries with frailty. Compared with apixaban, warfarin was associated with lower total cost (mean difference, -$1166 [95% CI, -$1396 to -$937]) but higher cost when excluding OAC cost (mean difference, $1409 [95% CI, $1177 to $1642]) regardless of frailty levels. Conclusions and Relevance: In older adults with AF, apixaban was associated with increased home time and lower rates of clinical events than rivaroxaban and warfarin, especially for those with frailty. Apixaban was associated with lower total cost compared with rivaroxaban but higher cost compared with warfarin due to higher OAC cost. These findings suggest that apixaban may be preferred for older adults with AF, particularly those with frailty.

A Lifestyle Modification Program for Secondary Prevention of Atrial Fibrillation: A Pilot Study.

Background: Lifestyle modification programs, such as cardiac rehabilitation, may reduce atrial fibrillation (AF) burden and improve quality of life (QOL), but remain unproven. The objective of this pilot study was to assess feasibility, acceptability, and preliminary effectiveness of an exercise and nutrition-based cardiac rehabilitation-like program for AF patients. Methods: We enrolled overweight adults aged ≥ 30 years with symptomatic AF in a 12-week cardiac lifestyle group program, including 6 virtual and 6 in-person visits. All visits included discussion and education about nutrition, exercise, and behavior modification. In-person visits included supervised aerobic exercise and strength training. Outcomes at baseline and 12 weeks included feasibility of participation, acceptability, change in weight and BMI, and changes in survey-based AF burden, symptoms, and QOL. Results: From 84 invitees, 11 (13.1%) were enrolled (mean age 64; baseline BMI 38 kg/m2); 9 (82%) completed the program. Patients attended an average of 9.7 (81%) visits (Range: 6-11). Mean weight loss was 9.1 pounds (Range: 0-16); mean BMI decrease was 1.4 kg/m2 (Range: 0-2.6). Patients found the program helpful overall: all reported making diet and exercise changes during the program. Compared to baseline, patients reported decreased AF burden (12.9 vs. 11.7, p = 0.03) and symptom (10.1 vs. 5.6, p = 0.003) scores at the conclusion of the program. Patients also reported increased QOL overall (68.9 vs. 86.4, p = 0.001). Conclusions: Participation in a cardiac rehab-like program was feasible and acceptable for overweight patients with symptomatic AF. Results suggest preliminary effectiveness of the program for reducing AF burden and symptoms and increasing QOL.

Characteristics and Attitudes of Wearable Device Users and Non-Users in a Large Healthcare System.

Introduction: Consumer wearable devices with health and wellness features are increasingly common and may enhance prevention and management of cardiovascular disease. However, the characteristics and attitudes of wearable device users versus non-users are poorly understood. Methods: Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology (WATCH-IT) was a prospective study of adults aged ≥18 years receiving longitudinal primary or ambulatory cardiovascular care at one of eleven hospitals within the Mass General Brigham multi-institutional healthcare system between January 2010-July 2021. We invited patients, including wearable users and non-users, to participate via an electronic patient portal. Participants were asked to complete a 20-question survey regarding perceptions and use of consumer wearable devices. Responses were linked to electronic health record data. Multivariable logistic regression was used to identify factors associated with device use. Results: Among 280,834 individuals receiving longitudinal primary or cardiovascular care, 65,842 did not have an active electronic portal or opted out of research contact. Of the 214,992 individuals sent a survey link, 11,121 responded (5.2%), comprising the WATCH-IT patient sample. Most respondents (55.8%) reported current use of a wearable device, and most non-users (95.3%) reported they would use a wearable device if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, the majority believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR] 0.80 per 10-year increase, 95% CI 0.77-0.82), male sex (0.87, 95% CI 0.80-0.95), and heart failure (0.75, 95% CI 0.63-0.89) were associated with lower odds of wearable device use, whereas higher median zip code income (1.08 per 1-quartile increase, 95% CI 1.04-1.12) and care in a cardiovascular medicine clinic (1.17, 95% CI 1.05-1.30) were associated with greater odds of device use. Nearly all respondents (98%) stated they would share device data with researchers studying health outcomes. Conclusions: Within an electronically assembled cohort of patients in primary and cardiovascular medicine clinics with linkage to detailed health records, wearable device use is common. Most users perceive value in wearable data. Our platform may enable future study of the relationships between wearable technology and resource utilization, clinical outcomes, and health disparities.

Development and Validation of the DOAC Score: A Novel Bleeding Risk Prediction Tool for Patients With Atrial Fibrillation on Direct-Acting Oral Anticoagulants.

BACKGROUND: Current clinical decision tools for assessing bleeding risk in individuals with atrial fibrillation (AF) have limited performance and were developed for individuals treated with warfarin. This study develops and validates a clinical risk score to personalize estimates of bleeding risk for individuals with atrial fibrillation taking direct-acting oral anticoagulants (DOACs). METHODS: Among individuals taking dabigatran 150 mg twice per day from 44 countries and 951 centers in this secondary analysis of the RE-LY trial (Randomized Evaluation of Long-Term Anticoagulation Therapy), a risk score was developed to determine the comparative risk for bleeding on the basis of covariates derived in a Cox proportional hazards model. The risk prediction model was internally validated with bootstrapping. The model was then further developed in the GARFIELD-AF registry (Global Anticoagulant Registry in the Field-Atrial Fibrillation), with individuals taking dabigatran, edoxaban, rivaroxaban, and apixaban. To determine generalizability in external cohorts and among individuals on different DOACs, the risk prediction model was validated in the COMBINE-AF (A Collaboration Between Multiple Institutions to Better Investigate Non-Vitamin K Antagonist Oral Anticoagulant Use in Atrial Fibrillation) pooled clinical trial cohort and the Quebec Régie de l'Assurance Maladie du Québec and Med-Echo Administrative Databases (RAMQ) administrative database. The primary outcome was major bleeding. The risk score, termed the DOAC Score, was compared with the HAS-BLED score. RESULTS: Of the 5684 patients in RE-LY, 386 (6.8%) experienced a major bleeding event, within a median follow-up of 1.74 years. The prediction model had an optimism-corrected C statistic of 0.73 after internal validation with bootstrapping and was well-calibrated based on visual inspection of calibration plots (goodness-of-fit P=0.57). The DOAC Score assigned points for age, creatinine clearance/glomerular filtration rate, underweight status, stroke/transient ischemic attack/embolism history, diabetes, hypertension, antiplatelet use, nonsteroidal anti-inflammatory use, liver disease, and bleeding history, with each additional point scored associated with a 48.7% (95% CI, 38.9%-59.3%; P<0.001) increase in major bleeding in RE-LY. The score had superior performance to the HAS-BLED score in RE-LY (C statistic, 0.73 versus 0.60; P for difference <0.001) and among 12 296 individuals in GARFIELD-AF (C statistic, 0.71 versus 0.66; P for difference = 0.025). The DOAC Score had stronger predictive performance than the HAS-BLED score in both validation cohorts, including 25 586 individuals in COMBINE-AF (C statistic, 0.67 versus 0.63; P for difference <0.001) and 11 945 individuals in RAMQ (C statistic, 0.65 versus 0.58; P for difference <0.001). CONCLUSIONS: In individuals with atrial fibrillation potentially eligible for DOAC therapy, the DOAC Score can help stratify patients on the basis of expected bleeding risk.

Predictors of intracranial hemorrhage in patients with atrial fibrillation treated with oral anticoagulants: Insights from the GARFIELD-AF and ORBIT-AF registries.

BACKGROUND: An unmet need exists to reliably predict the risk of intracranial hemorrhage (ICH) in patients with atrial fibrillation (AF) treated with oral anticoagulants (OACs). HYPOTHESIS: An externally validated model improves ICH risk stratification. METHODS: Independent factors associated with ICH were identified by Cox proportional hazard modeling, using pooled data from the GARFIELD-AF (Global Anticoagulant Registry in the FIELD-Atrial Fibrillation) and ORBIT-AF (Outcomes Registry for Better Informed Treatment of Atrial Fibrillation) registries. A predictive model was developed and validated by bootstrap sampling and by independent data from the Danish National Patient Register. RESULTS: In the combined training data set, 284 of 53 878 anticoagulated patients had ICH over a 2-year period (0.31 per 100 person-years; 95% confidence interval [CI]: 0.28-0.35). Independent predictors of ICH included: older age, prior stroke or transient ischemic attack, concomitant antiplatelet (AP) use, and moderate-to-severe chronic kidney disease (CKD). Vitamin K antagonists (VKAs) were associated with a significantly higher risk of ICH compared with non-VKA oral anticoagulants (NOACs) (adjusted hazard ratio: 1.61; 95% CI: 1.25-2.08; p = .0002). The ability of the model to discriminate individuals in the training set with and without ICH was fair (optimism-corrected C-statistic: 0.68; 95% CI: 0.65-0.71) and outperformed three previously published methods. Calibration between predicted and observed ICH probabilities was good in both training and validation data sets. CONCLUSIONS: Age, prior ischemic events, concomitant AP therapy, and CKD were important risk factors for ICH in anticoagulated AF patients. Moreover, ICH was more frequent in patients receiving VKA compared to NOAC. The new validated model is a step toward mitigating this potentially lethal complication.

Effect of clinic-based single-lead electrocardiogram rhythm assessment on oral anticoagulation prescriptions in patients with previously diagnosed atrial fibrillation.

Background: Despite benefits of oral anticoagulation (OAC), many individuals with diagnosed atrial fibrillation (AF) do not receive OAC. Objective: The purpose of this study was to assess whether cardiac rhythm assessment for AF impacted use of OAC in patients with previously diagnosed AF. Methods: VITAL-AF was a cluster randomized controlled trial conducted in 16 primary care practices assessing the efficacy of AF rhythm assessment with single-lead electrocardiogram in routine care. Patients 65 years and older were offered rhythm assessment at visits. In this secondary analysis, we evaluated rhythm assessment uptake and compared initiation and discontinuation of OAC in patients with previously diagnosed AF from intervention and control arms over 1 year. Results: The study included 4593 patients with previously diagnosed AF (2250 intervention; 2343 control). In the intervention arm, 2022 (89.9%) completed rhythm assessment (median 2 visits with rhythm assessment) and 40.1% had ≥1 "Possible AF" result. Initiation of OAC was similar in the intervention (17.7%) and control (19.1%) arms but was influenced by the rhythm assessment result: higher with a "Possible AF" (26.1%; adjusted odds ratio [aOR] 1.62; 95% confidence interval [CI] 1.04-2.51), and lower with a "Normal" result (9.9%; aOR 0.45; 95% CI 0.29-0.71) compared to control. OAC discontinuation was similar in the intervention (6.3%) and control (7.2%) arms, with lower discontinuation with a "Possible AF" result (3.8%; aOR 0.51; 95% CI 0.32-0.81). Conclusions: Including patients with previously diagnosed AF in a point-of-care rhythm assessment strategy did not increase overall OAC use compared to the control arm. However, the rhythm assessment result influenced both initiation and discontinuation of OAC.

Accuracy and variability of cardiologist interpretation of single lead electrocardiograms for atrial fibrillation: The VITAL-AF trial.

BACKGROUND: Screening for atrial fibrillation (AF) using consumer-based devices capable of producing a single lead electrocardiogram (1L ECG) is increasing. There are limited data on the accuracy of physician interpretation of these tracings. The goal of this study is to assess the sensitivity, specificity, confidence, and variability of cardiologist interpretation of point-of-care 1L ECGs. METHODS: Fifteen cardiologists reviewed point-of-care handheld 1L ECGs collected from patients aged 65 years or older enrolled in the VITAL-AF clinical trial [NCT035115057] who underwent cardiac rhythm assessments with a 1L ECG using an AliveCor KardiaMobile device. Random sampling of 1L ECGs for cardiologist review was stratified by the AliveCor algorithm interpretation. A 12L ECG performed on the same day for clinical purposes was used as the gold standard. Cardiologists each reviewed a common sample of 200 1L ECG tracings and completed a survey associated with each tracing. Cardiologists were blinded to both the AliveCor algorithm and same day 12L ECG interpretation. For each tracing, study cardiologists were asked to assess the rhythm (sinus rhythm, AF, unclassifiable), report their assessment of the quality of the tracing, and rate their confidence in rhythm interpretation. The outcomes included the sensitivity, specificity, variability, and confidence in physician interpretation. Variables associated with each measure were identified using multivariable regression. RESULTS: The average sensitivity for AF was 77.4% (range 50%-90.6%, standard deviation [SD]=11.4%) and the average specificity was 73.0% (range 41.3%-94.6%, SD = 15.4%). The mean variability was 30.8% (range 0%-76.2%, SD = 23.2%). The average reviewer confidence of 1L ECG rhythm assessment was 3.6 out of 5 (range 2.5-4.2, SD = 0.6). Patient and tracing factors associated with sensitivity, specificity, variability, and confidence were identified and included age, body mass index, and presence of artifact. CONCLUSION: Cardiologist interpretation of point-of-care handheld 1L ECGs has modest diagnostic sensitivity and specificity with substantial variability for AF classification despite high confidence. Variability in cardiologist interpretation of 1L ECGs highlights the importance of confirmatory testing for diagnosing AF.

Screening for undiagnosed atrial fibrillation using a single-lead electrocardiogram at primary care visits: patient uptake and practitioner perspectives from the VITAL-AF trial.

BACKGROUND: Screening for atrial fibrillation (AF) is appealing because AF is common, when undiagnosed may increase stroke risk, and stroke is preventable with anticoagulants. This study assessed patient and primary care practitioner (PCP) acceptability of screening for AF using a 30-s single-lead electrocardiogram (SL-ECG) during outpatient visits. METHODS: Secondary analyses of a cluster randomized trial. All patients ≥ 65 years old without prevalent AF seen during a 1-year period and their PCPs. Screening using a SL-ECG was performed by medical assistants during check-in at 8 intervention sites among verbally consenting patients. PCPs were notified of "possible AF" results; management was left to their discretion. Control practices continued with usual care. Following the trial, PCPs were surveyed about AF screening. Outcomes included screening uptake and results, and PCP preferences for screening. RESULTS: Fifteen thousand three hundred ninety three patients were seen in intervention practices (mean age 73.9 years old, 59.7% female). Screening occurred at 78% of 38,502 individual encounters, and 91% of patients completed ≥ 1 screening. The positive predictive value of a "Possible AF" result (4.7% of SL-ECG tracings) at an encounter prior to a new AF diagnosis was 9.5%. Same-day 12-lead ECGs were slightly more frequent among intervention (7.0%) than control (6.2%) encounters (p = 0.07). Among the 208 PCPs completing a survey (73.6%; 78.9% intervention, 67.7% control), most favored screening for AF (87.2% vs. 83.6%, respectively), though SL-ECG screening was favored by intervention PCPs (86%) while control PCPs favored pulse palpation (65%). Both groups were less certain if AF screening should be done outside of office visits with patch monitors (47% unsure) or consumer devices (54% unsure). CONCLUSIONS: Though the benefits and harms of screening for AF remain uncertain, most older patients underwent screening and PCPs were able to manage SL-ECG results, supporting the feasibility of routine primary care screening. PCPs exposed to a SL-ECG device preferred it over pulse palpation. PCPs were largely uncertain about AF screening done outside of practice visits. TRIAL REGISTRATION: ClinicalTrials.gov NCT03515057. Registered May 3, 2018.

Can Treatment Support Mitigate Nicotine Metabolism-Based Disparities in Smoking Abstinence? Secondary Analysis of the Helping HAND 4 Trial.

INTRODUCTION: The nicotine metabolite ratio (NMR), a biomarker of CYP2A6-mediated nicotine metabolism, predicts the efficacy of nicotine replacement therapy (NRT), with fast metabolizers benefiting less than slow metabolizers. Whether treatment support to optimize NRT use (henceforth "treatment support") modifies this pharmacogenetic relationship is unknown. METHODS: Hospitalized adult daily smokers were assigned to one of two post-discharge smoking cessation interventions offering NRT and counseling: (1) Transitional Tobacco Care Management, which delivered enhanced treatment support via free combination NRT at discharge and automated counseling, and (2) a quitline-based approach representing usual care (UC). The primary outcome was biochemically verified 7-day point prevalence abstinence 6 months after discharge. Secondary outcomes were the use of NRT and counseling during the 3-month intervention period. Logistic regression models tested for interactions between NMR and intervention, controlling for sex, race, alcohol use, and BMI. RESULTS: Participants (N = 321) were classified as slow (n = 80) or fast (n = 241) metabolizers relative to the first quartile of NMR (0.012-0.219 vs. 0.221-3.455, respectively). Under UC, fast (vs. slow) metabolizers had lower odds of abstinence at 6 months (aOR 0.35, 95% CI 0.13-0.95) and similar odds of NRT and counseling use. Compared to UC, enhanced treatment support increased abstinence (aOR 2.13, 95% CI 0.98-4.64) and use of combination NRT (aOR 4.62, 95% CI 2.57-8.31) in fast metabolizers, while reducing abstinence in slow metabolizers (aOR 0.21, 95% CI 0.05-0.87; NMR-by-intervention interaction p = .004). CONCLUSIONS: Treatment support increased abstinence and optimal use of NRT among fast nicotine metabolizers, thereby mitigating the gap in abstinence between fast and slow metabolizers. IMPLICATIONS: In this secondary analysis of two smoking cessation interventions for recently hospitalized smokers, fast nicotine metabolizers quit at lower rates than slow metabolizers, but providing fast metabolizers with enhanced treatment support doubled the odds of quitting in this group and mitigated the disparity in abstinence between fast and slow metabolizers. If validated, these findings could lead to personalized approaches to smoking cessation treatment that improve outcomes by targeting treatment support to those who need it most.

Association of Kidney Function With Risk of Adverse Effects of Therapies for Atrial Fibrillation.

Introduction: Atrial fibrillation (AF) is common in chronic kidney disease (CKD) and is treated with rate control medications, antiarrhythmic medications, as well as anticoagulation and procedures, each of which have associated risks. We aimed to evaluate the association of CKD status with the risks of adverse effects after initiation of AF therapies. Methods: This was a cohort study of community-based adults who newly initiated rate control medications, antiarrhythmic medications, warfarin, direct oral anticoagulants (DOACs) or received AF procedures in the 1 year after diagnosis of AF. Baseline estimated glomerular filtration rate (eGFR) was calculated using outpatient serum creatinine measures. Adverse effects within 1 year related to each AF therapy or within 1 month of an AF procedure were ascertained from vital sign databases, electrocardiograms (ECGs), and administrative codes. Fine-Gray hazard models were used to study the association of eGFR categories with risk of adverse effects for each AF therapy. Results: Among 115,564 patients with incident AF, lower eGFR (vs. eGFR ≥60 ml/min per 1.73 m2) was significantly associated with higher adjusted risk of adverse effects after initiation of rate control therapies (most commonly hypotension and bradycardia) as follows: eGFR 45-59 (hazard ratio [HR] 1.14, 95% confidence interval [CI] 1.07-1.22), 30-44 (HR 1.15, 95% CI 1.06-1.25), and 15-29 (HR 1.29, 95% CI: 1.12-1.47) ml/min per 1.73 m2. Lower eGFR was associated with higher adjusted risk of adverse effects (most commonly prolonged QRS and QTc intervals) after initiation of an antiarrhythmic medication (vs. eGFR >60 ml/min per 1.73 m2) as follows: eGFR 45-59 (HR 1.12, 95% CI 1.01-1.23) and eGFR<15 (HR 1.43, 95% CI 1.01-2.01) ml/min per 1.73 m2. Conclusion: There was a graded association between lower eGFR and risk of major bleeding with warfarin use, with the greatest risk among those with eGFR <15 ml/min per 1.73 m2 (HR of 2.93, 95% CI 1.99-4.30). There was no association of eGFR with major bleeding in patients receiving DOACs. Rates of adverse effects within 1 month of an AF procedure were low among patients with (n = 18) and without (n = 41) CKD and was underpowered for further analyses. In conclusion, lower eGFR was associated with significantly higher risks of adverse effects after initiation of commonly used therapies to treat AF. These data may help inform the complex therapeutic decisions in patients with CKD and AF.