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ARTICLES: Atrial Fibrillation

NursE led Atrial Fibrillation Management: The NEAT Study

A Randomized Controlled Trial

Gallagher, Celine RN, PhD; Orchard, Jessica MPH; Nyfort-Hansen, Karin B Pharm, Grad Dip Ed(Health); Sanders, Prashanthan MBBS, PhD; Neubeck, Lis RN, PhD; Hendriks, Jeroen M. RN, PhD

Author Information
The Journal of Cardiovascular Nursing: 9/10 2020 - Volume 35 - Issue 5 - p 456-467
doi: 10.1097/JCN.0000000000000680
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Abstract

Atrial fibrillation (AF) has emerged as one of the greatest healthcare challenges of this century. Incidence and prevalence rates have exponentially risen over recent decades and age-adjusted mortality rates have increased approximately 2-fold for both males and females.1 Hospitalizations are known to be the main driver of the growing healthcare burden associated with AF.2 Impairment to health-related quality of life (HRQoL) in individuals with AF is considerably worse than the general population and those with other chronic cardiovascular conditions, including post–myocardial infarction or percutaneous coronary intervention.3 Indeed, the degree of impairment to HRQoL in AF is akin to that of the population with heart failure.3 A poorer quality of life has been observed in intermittent AF compared with permanent AF, perhaps because of the greater symptom burden.4 In large registry data from the United States, lower disease-specific quality of life, as assessed by the Atrial Fibrillation Effect on Quality of Life Questionnaire, in 10 132 individuals with AF was associated with a higher risk of all-cause hospitalizations (hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.2–1.84; P ≤ .001).5

Few investigators have examined the impact of education, and motivational interviewing to elicit health behavior change, on HRQoL and cardiovascular risk factor status in AF. In a cohort of individuals undertaking first-time ablation for AF, nurse-delivered education at 5 different time points, involving face-to-face contact on 2 occasions during the hospital stay and telephone calls over a 3-month period, resulted in improvements in 2 domains of the Short Form-36 (SF-36) but did not significantly impact rehospitalizations over 6 months of follow-up.6 An online educational platform for individuals undertaking cardioversion or AF ablation resulted in improved knowledge, as assessed by a validated knowledge questionnaire, which was sustained until 12 weeks post procedure.7 A pilot study, involving 19 participants with AF, examined the impact of a nurse-delivered cardiovascular risk factor management program over a 3-month period, delivered using motivational interviewing principles. This study involved participants attending 1 face-to-face session, with follow-up undertaken by telephone. This intervention did not impact body mass index (BMI), waist circumference, HRQoL, or anxiety and depression questionnaire scores but did result in improved self-reported AF symptom severity.8

Appropriate use of oral anticoagulation is an established pillar of AF management to reduce stroke risk. Despite well-established guidelines in this regard and improved use of this therapy with the introduction of the novel oral anticoagulants, use of this therapy remains suboptimal, with significant geographical heterogeneity, as is evident from numerous international registries.9,10 Electronic decision support systems have been proposed as a mechanism to improve appropriate use of therapy with oral anticoagulation.11 Although this has resulted in improved use of appropriate oral anticoagulation in some instances,12 it has had little effect on discordant treatment in other studies.13,14

Cardiovascular risk factors play a critical role in the development and progression of AF. Specifically, modifiable risk factors, including overweight and obesity, hypertension, physical inactivity, and alcohol intake, contribute to a growing disease burden.15,16 Of note, a growing body of evidence has suggested that modification of these cardiovascular risk factors, through the use of an individualized approach, has resulted in reduced subjective and objective AF burden, improved physical activity and cardiorespiratory fitness levels, and improved disease-specific quality of life.17–20 However, scant evidence exists for this approach in the context of nurse-delivered care.

Patient education and engagement are key components of the chronic care model.21 However, few studies have examined the impact of education on clinically relevant outcomes in the AF population. The aim of this study was to determine if a brief nurse-led education program, incorporating tailored advice and goal setting for management of cardiovascular risk factors using a motivational interviewing approach, facilitated by a guideline-based electronic decision support tool to ensure appropriate oral anticoagulation, can improve HRQoL and cardiovascular risk factor status in individuals with AF.

METHODS

Study Design

The NursE led ATtrial Fibrillation Management (NEAT) study was a multicenter, prospective, randomized controlled feasibility study undertaken collaboratively by the University of Sydney and the University of Adelaide. The study was registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12615000928516). Ethics approval was received from the Sydney Local Health District Human Resources Ethics Committee with reciprocal agreement from the University of Adelaide Human Research Ethics Committee (HREC/15/CRGH/57).

Participants

Eligible participants were referred for participation in the study by cardiologists at the Royal Prince Alfred Hospital and Concord Repatriation Hospital in Sydney and the Centre for Heart Rhythm Disorders at the University of Adelaide, Australia. Inclusion criteria were AF documented on electrocardiogram and 18 years or older. Both inpatients and outpatients were eligible for participation. Exclusion criteria were non–English-speaking individuals or an inability to provide informed consent. Participants were allocated to the intervention group or usual care by a computer-generated 1:1 randomization schedule. The study conformed with the Declaration of Helsinki and informed consent was obtained from all participants.

Baseline Visit and Follow-up Assessment

Baseline information was collected by nurses conducting the study at each of the sites. This baseline visit included sociodemographic and clinical data recorded in an electronic case record form. Information collected included demographic data such as age, gender, and education level. Health-related quality of life was assessed using the Short-Form 12 survey (SF-12). Cardiovascular risk factors recorded included smoking status, blood pressure measurement, alcohol consumption, waist circumference, BMI, and physical activity level. Medication adherence was assessed with the Morisky Medication Adherence Scale,22 and physical activity, using the Global Physical Activity Questionnaire.23

All participants attended a final assessment on exit from the study after 3 months of follow-up. This was undertaken by a researcher blinded to group allocation. The final assessment included completion of the SF-12, Morisky Medication Adherence Scale, the Global Physical Activity Questionnaire, and cardiovascular risk factor measurements including waist circumference, BMI, blood pressure, smoking status, and alcohol intake. A current medication list was also recorded at baseline and final visits.

Intervention

Participants in the intervention arm of this study attended 1 nurse-led educational and risk factor management session. This session was scheduled to last for approximately 1 hour but was adapted based upon perceived need. The following components were incorporated into the intervention:

  1. An electronic decision support tool designed to ensure appropriate use of OAC, based on individual stroke risk score and current AF guidelines;
  2. Clinical profiling including medication adherence and cardiovascular risk factor status; and
  3. Health counseling and goal setting.

At the baseline visit, education was provided concerning basic AF pathophysiology, causes, potential complications, treatment options, and appropriate stroke prevention therapies based on individual risk scores. This session was facilitated by written educational material (Living with Atrial Fibrillation).24

After this, and using the principles of motivational interviewing, participants were encouraged to set 3 to 4 realistic risk factor or behavioral goals in line with their priorities and motivation. This was determined after discussion with the individual, according to motivational interviewing principles, to identify their values and preferences and any barriers to achieving behavioral change.25 Goals were set by participants according to what was deemed most important to them. In line with the principles of motivational interviewing, a discussion concerning each individual's confidence in their ability to achieve change was undertaken to further assist in identifying any barriers to success.25 The nurse assisted in ensuring that these goals were realistic and achievable over the follow-up time frame and identified strategies to assist with meeting goal targets. A printed summary of each participant's goals was given to them. This also contained written information about each individual's stroke risk score and if current antithrombotic therapy was appropriate. If antithrombotic therapy was deemed inappropriate based upon stroke risk, the patient was encouraged to discuss this with their treating physicians. Follow-up consisted of telephone-only support. Each participant received 3 to 4 telephone calls over the 3-month follow-up period to monitor their progress and reassess goals if necessary. If a participant did not answer or could not take the telephone call, a total of 3 attempts were made to reach the individual. If they could not be reached after 3 attempts, this telephone call was lapsed, and individuals were moved to the next scheduled telephone call as per the study protocol. The control group attended standard follow-up with their cardiologist and/or general practitioner. The frequency of this follow-up and care provided was left to the discretion of the treating physician(s).

Goal Setting

Participants in the intervention arm set a mean of 3 goals. The most commonly set goal related to improving physical activity levels (32%). Other frequently used goals set included self-monitoring and management of blood pressure (24%), closely followed by weight loss (22%). Less commonly set goals related to self-monitoring of cardiovascular risk factors (eg, lipids, glucose monitoring) at 6% and pulse self-monitoring to facilitate recognition of AF episodes (4%).

Telephone Follow-up

Participants in the intervention arm received a mean of 3.4 ± 1.1 telephone calls over the follow-up period. Mean duration of follow-up telephone calls was 8.8 ± 4.9 minutes. The telephone calls were undertaken by the nurse delivering the intervention. The aim of the telephone calls was to review progress with goals set by participants, set new goals if required, and provide ongoing support.

Personnel

The personnel delivering the intervention were specialist cardiac nurses who had all undertaken training in motivational interviewing as part of their cardiology training.

Outcome Measures

The primary outcome measure was HRQoL as assessed by the SF-12 questionnaire. The SF-12 questionnaire is an abbreviated version of the SF-36 questionnaire with established validity and reliability in measuring HRQoL.26 Secondary outcome measures included cardiovascular risk factors such as blood pressure, BMI, self-reported smoking status, and physical activity as assessed by the Global Physical Activity Questionnaire. Blood pressure was taken via automated measurement (Omron Healthcare, Lake Forest, Illinois). This was recorded with the participant in a seated position after at least 5 minutes resting. The first blood pressure measurement was used. Height and weight were recorded in light clothing with shoes removed and using the same tape measure and scales for each individual's baseline and follow-up measurements. Medication adherence was assessed by the Morisky Medication Adherence Scale. Appropriate use of oral anticoagulation was determined according to the CHA2DS2-VASc (congestive heart failure, hypertension, age ≥75 years, diabetes, stroke/transient ischemic attack, thromboembolism, vascular disease, age 65–74 years, sex category; all score 1 point except, for age ≥75 years and previous stroke/transient ischemic attack, which score 2 points) score with scores of 2 or higher necessitating the use of oral anticoagulation unless a contraindication was present. Anticoagulation was not deemed necessary in those with a CHA2DS2-VASc score of 0 unless this was in the context of undertaking a procedure such as cardioversion or ablation for AF or atrial flutter. Any type of antithrombotic therapy in individuals with a CHA2DS2-VASc score of 1 was deemed appropriate unless anticoagulation was prescribed based on female gender as an isolated risk factor. This was in accordance with the European Society of Cardiology guidelines for AF that were current at the time of study development.27

Power Analysis

Based on the Choice of Health Options In prevention of Cardiovascular Events for people with Atrial Fibrillation study, in which patients were encouraged to set individual goals to manage their cardiovascular risk factors, and international data for HRQoL, the sample size for the study was calculated on a minimum clinically important difference of 8.1 in the SF-12 physical function domain (effect size of 0.75) and α of 0.8 and critical level of 0.05.8,28 This resulted in a minimal total sample size of 60, or 30 participants per group. Allowing for 20% loss to follow-up, 72 participants were required (36 per group).

Statistical Analyses

Primary analyses were conducted using SPSS for Windows (Version 23.0). Continuous variables are reported as mean ± standard deviation, and categorical variables, as numbers and percentages. Within-subject differences between baseline and follow-up were analyzed using Wilcoxon signed ranks tests for nonparametric variables (2-tailed P < .05 considered significant). Between-group comparisons were analyzed using Student t test, the Mann-Whitney U test (for nonnormally distributed continuous data), and the χ2 test. Data on the SF-12 were analyzed using software licensed and provided by Optum Insight.

RESULTS

A total of 72 participants were randomized with 36 participants in each group. Mean age was 63 ± 12 years and 66 ± 10 years in the intervention group and control group, respectively, and distribution of gender was similar in both groups, with 44% of participants being female. Table 1 depicts the baseline characteristics. All participants had previously been diagnosed with AF. One participant in the control group did not meet the inclusion criteria and was excluded from analysis. A total of 33 participants in each arm completed the 3-month final follow-up. The CONSORT diagram is displayed in Figure 1.

TABLE 1
TABLE 1:
Baseline Characteristics of Study Participants
FIGURE 1
FIGURE 1:
CONSORT diagram.

Health-Related Quality of Life

Significant differences were evident in baseline SF-12 scores between groups, with the control group demonstrating a lower mean physical component summary (PCS) score, physical functioning, and role physical subscale scores (Table 2). There was a significant improvement in the mental component summary score in the control group from baseline to follow-up (Table 2). No within-group differences were evident from baseline to follow-up with the PCS score. An improvement in the bodily pain subscale of the SF-12 occurred for the intervention group over time. The control group demonstrated an improvement in the general health, social function, and role emotional subscales over time. However, there were no significant differences between groups at final follow-up for the PCS score, mental component summary score, or any of the SF-12 subscales (Table 2 and Figures 2 and 3).

TABLE 2
TABLE 2:
Short Form-12 Summary and Subscale Scores at Baseline and Follow-up
FIGURE 2
FIGURE 2:
Short Form-12 survey summary component scores at final follow-up. PCS indicates physical component summary score; MCS, mental component summary score. Error bars represent interquartile range.
FIGURE 3
FIGURE 3:
Short Form-12 survey (SF-12) subscale outcomes at final follow-up. Error bars represent interquartile range.

Cardiovascular Risk Factors

Blood Pressure

At baseline, no significant differences in systolic (128 ± 21 and 130 ± 21 mm Hg for intervention and control, respectively; P = .65) or diastolic (71 ± 11 vs 73 ± 11 mm Hg for intervention and control, respectively; P = .30) blood pressure were observed. At final follow-up, there were no significant differences for systolic (125 ± 21 and 124 ± 15 mm Hg for intervention and control, respectively; P = .80) or diastolic (71 ± 11 and 73 ± 11 mm Hg for intervention and control, respectively; P = .39) blood pressure (Table 3 and Figure 4a and b).

TABLE 3
TABLE 3:
Risk Factors and Medication Adherence Measures at Baseline and Follow-up
FIGURE 4
FIGURE 4:
Systolic (a) and diastolic (b) blood pressure at final follow-up. Error bars represent standard deviation.

Body Mass Index, Waist Circumference, and Physical Activity

Body mass index did not demonstrate any significant differences between groups at baseline (30.3 ± 6.9 and 30.1 ± 5.8 kg/m2 for intervention and control, respectively; P = .87). At final follow-up, no significant differences between groups were observed for BMI (30.0 ± 6.7 and 30.2 ± 5.9 kg/m2 for intervention and control, respectively; P = .90) or waist circumference (104 ± 13 and 104 ± 16 cm for intervention and control, respectively; P = .97; Table 3 and Figure 5a and b). Physical activity levels, as assessed by the Global Physical Activity Questionnaire score, did not differ between groups at final follow-up (8.5 ± 1.1 and 8.4 ± 1.2 for intervention and control respectively; P = .60; Table 3).

FIGURE 5
FIGURE 5:
Body mass index (a) and waist circumference (b) at final follow-up. Error bars represent standard deviation.

Smoking Status

Current smoking status did not differ between groups at final follow-up (6.1% for intervention and 3.0% for control; P = 1.0; Table 3).

Oral Anticoagulation

Appropriate use of oral anticoagulation was demonstrated in 97.2% and 97.1% of participants at baseline for the intervention and control groups, respectively (P = 1.0). There were no differences evident between groups at final follow-up for appropriate oral anticoagulation use (93.9% vs 97.0% for intervention and control, respectively; P = 1.0). Medication adherence, as assessed by the Morisky Medication Adherence Scale at baseline (P = .08 for interaction) or final follow-up (P = .81 for interaction) did not differ between groups (Table 3).

DISCUSSION

Education and empowerment of individuals to achieve self-care are important elements of chronic disease management. This prospective randomized study in patients with AF demonstrates that a nurse-led education program, which allowed the patient to self-select target goals, did not significantly impact on quality of life or cardiovascular risk factor status in a cohort of individuals with AF. Furthermore, self-management, including medication adherence and physical activity levels, were not significantly improved with this intervention. These findings highlight the complexity and need for evaluation of interventions of service delivery to ensure optimal design of care models.

Several studies have examined the impact of various interventions on quality of life in populations with AF with results consistent to that observed in our intervention. In a single-center randomized controlled trial (RCT) undertaken in the Netherlands of 712 newly diagnosed AF participants, an integrated care approach in a nurse-led, cardiologist-supported clinic did not significantly impact on quality of life as assessed by the SF-36 at final follow-up.29 This occurred despite a significant reduction in the primary endpoint: a composite of cardiovascular mortality and hospitalizations.12 In both the NEAT intervention and the RCT undertaken in the Netherlands, high baseline levels of quality of life were observed and may account for the lack of observed effect. A nurse-delivered home-based intervention for individuals who had been admitted to a hospital primarily because of AF, which included education, clinical profiling, referral on to other members of the multidisciplinary team as required, and recommendations to treating physicians about gold standard care delivery according to current AF guidelines, also did not significantly impact on quality of life as assessed by the SF-12.30 An RCT that examined an exercise-based rehabilitation program for individuals who had undertaken an ablation for AF did not demonstrate any impact on quality of life, as assessed by the SF-36, in individuals at short-term follow-up despite an improvement in exercise capacity as demonstrated by peak VO2.20 Another study, examining the impact of nurse-led education in a cohort of patients undergoing AF ablation, demonstrated improvement in 2 subscales of the SF-36 questionnaire.6 However, no consistent effect across multiple domains of general HRQoL have been demonstrated by any intervention in populations with AF. Despite the well-recognized importance of patient-reported outcomes such as quality of life, inherent difficulties in choosing between general and disease-specific questionnaires have also been acknowledged in addition to the large sample sizes often required to demonstrate statistically significant differences.31 However, given that many factors can impact on HRQoL, it may be of benefit to focus on disease-specific quality of life measures, which have a greater likelihood of demonstrating change.

Numerous studies have examined the impact of cardiovascular risk factor management on outcomes in populations with AF. Several studies have used a single-center physician-led model in dedicated risk factor clinics. The first of these studies assessed the impact of a comprehensive risk factor management strategy on AF symptom burden as assessed by the AF Symptom Severity Scale in an RCT of 150 symptomatic overweight and obese individuals with AF.17 After 15 months of follow-up AF burden, symptoms and symptom severity significantly decreased in the intervention group compared with control.

In the “Routine Versus Aggressive Risk Factor Driven Upstream Rhythm Control for Prevention of Early Atrial Fibrillation in Heart Failure” (RACE 3) study, a different approach to cardiovascular risk factor management was undertaken with a combination of predefined pharmacological therapy and lifestyle measures.32 In this study of 245 individuals with persistent AF and early heart failure, the intervention consisted of 3 pharmacological therapies (mineralocorticoid receptor antagonists, statins, angiotensin converting enzyme inhibitors, or angiotensin receptor blockers) in addition to an exercise-based cardiac rehabilitation program. Furthermore, participants in the intervention arm attended a specialist nurse-led outpatient clinic at 6 weekly intervals to assist with self-management of both conditions. This intervention demonstrated a significantly enhanced likelihood of sinus rhythm, as demonstrated by Holter monitoring, after 12 months of follow-up in the intervention group compared with the control group.32 Recently, the quality of life substudy of RACE 3 demonstrated a greater improvement in the intervention arm for the physical functioning, physical role limitations, and general health subscores of the SF-36 at 1 year follow-up compared with usual care.33

In a postablation cohort, aggressive cardiovascular risk factor management has demonstrated a greater likelihood of freedom from AF in those participating in interventional studies of observational design. These studies have largely been undertaken as single-center physician-led models and have simultaneously targeted numerous cardiovascular risk factors in a dedicated clinic. The first of these studies allocated 149 individuals, who had been referred for catheter ablation for symptomatic AF, to an intervention or control arm based on their decision to participate or decline the risk factor management program.18 This intervention resulted in a greater likelihood of arrhythmia freedom in the intervention group compared with control after a mean follow-up of approximately 3.4 years (HR, 4.8; 95% CI, 2.04–11.04; P < .001).34 The effectiveness of this intervention was confirmed at longer-term follow-up of approximately 5 years, with the same risk factor management program resulting in an almost 6-fold increase in the likelihood of freedom from AF in individuals who achieved the greatest degree of weight loss (≥10%) compared with those who lost the least amount or gained weight (HR, 5.9; 95% CI, 3.4–10.3; P < .001).18

The lack of impact on cardiovascular risk factor status observed in the NEAT intervention is speculated to be in part attributable to the lack of intensity of the risk factor management program in addition to the short follow-up duration. In the NEAT intervention, there was only 1 face-to-face visit, with the remainder of the intervention delivered by telephone follow-up. This may lead to a lack of accountability for participants who were not required to maintain a lifestyle journal nor undertake any further in-clinic visits. Furthermore, there were no prespecified risk factor targets to work toward with participants instead encouraged to set their own self-defined lifestyle goals. A comprehensive approach targeting numerous risk factors simultaneously was not undertaken in this study, with individuals instead working on risk factor or behavioral goals of their choice. The Substrate Modification with Aggressive Blood Pressure Control in AF study highlighted the need for a comprehensive approach to cardiovascular risk factor management. In this study, targeting a single risk factor (blood pressure) did not significantly impact the risk of atrial arrhythmia recurrence in individuals post catheter ablation for AF.35

Several other possibilities must be considered in light of the lack of observed effect in this study. The structure of this intervention, in which education and follow-up was provided by a nurse without the support of a multidisciplinary team, may have been a contributory factor. The aim of the NEAT intervention was to improve patient outcomes through the use of a disease management program; however, recent guidelines have highlighted the need for an integrated approach to care including the “4 pillars” of comprehensive AF care (anticoagulation, rate control, rhythm control, and cardiovascular risk factor management) combined with active patient involvement, ongoing education, and structured follow-up, guided by a multidisciplinary team and the use of eHealth.36,37 Although other studies have demonstrated improved cardiovascular risk factor status with the intervention undertaken by a single physician provider, this has been in the context of support from an electrophysiologist to reinforce advice provided in this clinic.18,34 Furthermore, the impact on cardiovascular risk factor status was evident after longer-term follow-up of 3.5 and 5 years, respectively, in these studies.18,34 It is possible that the short follow-up duration in part accounted for the lack of improvement in cardiovascular risk factor status observed in the NEAT intervention.

Future Directions

This study has highlighted several areas for consideration in the design of future studies examining alternative models of care delivery in AF. Building on work undertaken to date, several factors are likely to contribute to improved patient outcomes in this population. These include provision of multidisciplinary care with the involvement of a specialized cardiologist38,39 and nurse12,39 at its core. Referral to other members of the multidisciplinary team is likely to further enhance outcomes, although the optimal team composition remains unknown and, given the heterogenous nature of the condition, is likely to require an individualized approach. Indeed, the impact of a multidisciplinary approach in AF has not been fully explored, although the RACE 3 study involved the use of a specialist nurse, physiotherapist, and dietician as required. This study did demonstrate an increased likelihood of sinus rhythm at final follow-up, although little clinically significant difference in cardiovascular risk factor status. Interventions that have demonstrated marked improvements in cardiovascular risk factor status in AF have simultaneously addressed multiple factors in a single intervention within a dedicated clinic.18,34 The impact of a clinic combining holistic AF care and risk factor management in a single intervention has not been tested to date.

Limitations

Although in this study, the impact of a brief nurse-led education and risk factor management program on outcomes in a random sample of individuals with AF was examined, several limitations exist. First, our sample represents a well-treated cohort overall at baseline, which is not generally comparable with other reported populations with AF. For example, a global anticoagulant registry in the field demonstrated the appropriate use of oral anticoagulation in 63.1% of individuals, whereas in our cohort, this occurred in 97.2% and 97.1% of individuals for the intervention and control groups, respectively.40 This represents a well-treated sample with limited opportunity for improvement and is reflective of the high level of specialist care given to most participants in this cohort.

Second, the short-term duration of follow-up in this study allows little time to significantly impact on parameters such as cardiovascular risk factors, which have only demonstrated improvement in studies with longer follow-up duration. Furthermore, although this was a generally overweight and obese cohort, blood pressure was well controlled at baseline, and therefore, the impact on risk factor outcomes is likely to be minimal, as weight management generally requires longer and more intense follow-up management. Health-related quality of life has been difficult to impact on in previous studies related to AF interventions and highlights the difficulty associated with impacting on this outcome measure. Our study also did not have a predefined script for the delivery of the baseline visit and follow-up telephone calls, which may be a contributing factor to the lack of observed effect. Although all of the nurses delivering the intervention had received training in motivational interviewing, this training was undertaken at different time points by different providers, and this may have impacted on results obtained. Finally, as this was a feasibility study, the limitation of the small sample size needs to be acknowledged and could, in part, account for the lack of impact observed, particularly in relation to cardiovascular risk factor status, as the study was not powered for this outcome.

CONCLUSIONS

A brief nurse-delivered education and risk factor management program, limited to 1 single clinic visit and telephone follow-up, did not significantly impact on HRQoL in individuals with AF after short-term follow-up. This intervention had no significant impact on cardiovascular risk factor outcomes, including blood pressure, smoking status, alcohol consumption, physical activity levels, or weight reduction. Future interventions should focus on evaluating the impact of a comprehensive approach to AF management, including intense and targeted control of cardiovascular risk factors, over a longer period, to improve outcomes in this population.

What’s New and Important

  • Chronic conditions, such as AF, require active involvement of patients in their care and ongoing education, tailored to each individual's circumstance, with the aim of improving self-management.
  • Structured follow-up, ideally with face-to-face consultations, is likely to be a key factor in assisting patients to achieve goals related to lifestyle and behavioral modification.
  • Improvements in cardiovascular risk factor profiles through lifestyle modification are likely to take longer time periods, of at least 1 to 2 years, to demonstrate enhanced patient outcomes.
  • Future studies should focus on interventions of greater intensity, longer follow-up duration, and using a multidisciplinary team, to provide further evidence of such interventions and consequently improve outcomes in the AF population.

Acknowledgments

We would like to acknowledge the support of BePatient in developing the database and electronic case record form for this study.

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Keywords:

anticoagulation; atrial fibrillation; cardiovascular risk factors; nurse led; patient education; quality of life

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