Detection of unknown atrial fibrillation by prolonged ECG monitoring in an all-comer patient cohort and association with clinical and Holter variables

Objectives Prolonged ECG monitoring is clinically useful to detect unknown atrial fibrillation (AF) in stroke survivors. The diagnostic yield of prolonged ECG monitoring in other patient populations is less well characterised. We therefore studied the diagnostic yield of prolonged Holter ECG monitoring for AF in an unselected patient cohort referred from primary care or seen in a teaching hospital. Methods We analysed consecutive 7-day ECG recordings in unselected patients referred from different medical specialities and assessed AF detection rates by indication, age and comorbidities. Results Seven-day Holter ECGs (median monitoring 127.5 hours, IQR 116 to 152) were recorded in 476 patients (mean age 54.6 (SD 17.0) years, 55.9% female) without previously known AF, requested to evaluate palpitations (n=241), syncope (n=99), stroke or transient ischaemic attack (n=75), dizziness (n=29) or episodic chest pain (n=32). AF was newly detected in 42/476 (8.8%) patients. Oral anticoagulation was initiated in 40/42 (95.2%) patients with newly detected AF. Multivariate logistic regression, adjusted for age, sex and monitoring duration found four clinical parameters to be associated with newly detected AF: hypertension OR=2.54, (1.08 to 8.61) (adjusted OR (95% CI)), p=0.034; previous stroke or TIA OR=4.14 (1.81 to 13.01), p=0.001; left-sided valvular heart disease OR=5.07 (2.48 to 18.70), p<0.001 and palpitations OR=2.86, (1.33 to 10.44), p=0.015. Conclusions Open multispeciality access to prolonged ECG monitoring, for example, as part of integrated, cross-sector AF care, can accelerate diagnosis of AF and increase adequate use of oral anticoagulation, especially in older and symptomatic patients with comorbidities.

How might this impact on clinical practice? ► Judicious use of Holter ECG monitoring for new AF detection especially in the presence of clinical factors increasing the chances of AF detection could have significant diagnostic and therapeutic implications.

AbstrAct
Objectives Prolonged ECG monitoring is clinically useful to detect unknown atrial fibrillation (AF) in stroke survivors. The diagnostic yield of prolonged ECG monitoring in other patient populations is less well characterised. We therefore studied the diagnostic yield of prolonged Holter ECG monitoring for AF in an unselected patient cohort referred from primary care or seen in a teaching hospital.
Methods We analysed consecutive 7-day ECG recordings in unselected patients referred from different medical specialities and assessed AF detection rates by indication, age and comorbidities.

IntROduCtIOn
Atrial fibrillation (AF), a common cause of stroke and cardiovascular death, often remains undetected until a severe complication occurs, such as an ischaemic stroke. 1 2 Timely diagnosis of AF is a major clinical need with immediate therapeutic consequences in patients at high stroke risk who would benefit from oral anticoagulation. 3 4 Systematic ECG monitoring improves detection of undiagnosed paroxysmal AF in survivors of a stroke or transient ischaemic attack (TIA), detecting AF in around 4% of unselected stroke survivors using 3-day Holter monitoring 5 6 and in up to 25% of selected patients with cryptogenic stroke using implantable monitors. 3 7 Recent guidelines recommend at least 72 hours of ECG monitoring in stroke survivors to detect silent AF. 1 8 The diagnostic yield of prolonged ECG monitoring in other groups of patients at risk of AF has not been studied systematically. We therefore quantified AF detection rates of 7-day Holter ECG monitoring in an unselected cohort of consecutive patients referred for such monitoring, and identified factors that are associated with detection of unknown AF by multivariate regression.

Patients and procedures
We analysed 584 consecutive 7-day Holter ECG recordings performed in adult patients  . All analyses were subsequently reviewed by two cardiology physicians (JQ, YP). We did not find any discrepancy between the initial analysis and its review for AF detection and any Holter ECG parameter of interest. We excluded 108 patients with known AF, those <18 years of age and recordings with <110 hours analysable monitoring duration. The remaining 476 recordings constituted our primary analysis data set (figure 1). Clinical information was verified by three researchers (JQ, YP, MN) from hospital records. This analysis was approved by the clinical effectiveness department at SWBH NHS Trust as part of our ongoing quality improvement programme (QIP SG323).

definitions
The study outcome, AF, was defined as chaotic atrial arrhythmia with loss of p wave activity and irregular RR interval lasting for at least 30 s. We defined atrial or supraventricular ectopic as narrow QRS complex similar to sinus beat with different or absent p wave and <80% of prevailing RR interval. Supraventricular ectopic (SVE) runs were defined as regular or irregular runs of three or more consecutive atrial ectopics lasting for less than 30 s. Sinus pause was defined as increase in RR interval due to delay in p wave activity resulting in a pause >2 s. We categorised significant atrial ectopy as ≥50 atrial ectopics/day and significant sinus pauses as ≥10 sinus pauses/day based on cut-offs calculated through receiver operating characteristic (ROC) curve. All comorbidities were taken as previously documented through records from primary care or specialist clinics. Valvular disease was taken as moderateto-severe left (mitral or aortic) valvular disease, stenosis or regurgitation confirmed on prior echocardiography.

statistical analysis
Normality was assessed by inspecting the frequency distribution curves. For normally distributed variables we reported mean and SD, for other parameters median and IQR. Categorical variables were compared using χ 2 tests and continuous variables using independent t-test or Mann-Whitney U test as appropriate. The p values of <0.05 were considered statistically significant. The cutoffs for continuous variables were calculated through the Youden's index (maximum sensitivity and minimum 1-specificity) obtained from the receiver operating characteristics (ROC) curve. The univariate relationship to the outcome was quantified using logistic regression. A multivariate logistic regression model through enter method was fitted using a combination of various clinical variables which includes hypertension, left-sided moderate/ severe valvular disease, previous cerebrovascular accident and palpitations which were chosen due to their clinical relevance. The derived model was adjusted for sex, age and duration of recording. The model was internally validated using bootstrapping to produce an optimismadjusted model. We assessed the bootstrapped model's performance by quantifying the C-statistic (equivalent to area under the ROC curve). All the statistical analyses were performed using SPSS V.24 (IBM).

Results
Clinical characteristics of the patient population and AF detection Mean age of the study population was 56 years, 56% were female, and 40% were older than 60 years (  2). The AF group had more comorbidities such as hypertension, coronary artery disease, history of stroke or transient ischaemic attack, moderate-to-severe left-sided valvular disease and palpitations. There was no difference seen for diabetes and hypercholesterolaemia.

Other relevant findings
Other medically relevant findings were second degree atrioventricular (AV) block (10/474, 2.1%), third degree AV block (2/474, 0.4%) and non-sustained ventricular tachycardia (12/474, 2.5%). These were all detected in patients who underwent monitoring for dizziness. Artefact burden in the final cohort was 3.3% (SD 3.5)     figure 4. The model was adjusted for age, sex and duration of recording.
The area under the curve (C statistic) for our multivariate model was 0.91 (95% CI 0.87 to 0.95) with individual C-statistics for each variable mentioned in figure 5, table 3.

dIsCussIOn
We found that 7-day ECG monitoring detected unknown AF in 9% of an unselected cohort presenting with various symptoms. Almost all patients were initiated on oral anticoagulation following AF detection. The AF detection rates of 9.3% in stroke survivors is comparable to AF rates in IDEAS (4.3%, 72 hours monitoring, 5 FIND-AF (12.5%, 10 days monitoring) 9 and FIND-AF randomised (14%). 6 The data supports the wider use of systematic ECG monitoring to allow early initiation of therapy for AF, particularly stroke prevention, for example, as part of an integrated approach to AF care. External validation of our findings is desirable.
Factors associated with newly detected AF Patients with AF were older (table 1, figures 2 and 4) than those without AF, similar to other reports 10 11 and consistent with the known finding that older age is associated with prevalent AF. 12 13 We found that each decade increase in age increased the odds of detecting AF by 10.8. In addition, previous history of stroke and left-sided valvular heart disease was associated with silent AF in univariate analysis which is comparable to prior reports. 14 15 In our study palpitations were the symptom that was most frequently associated with underlying AF (figure 4). Our analysis supports some prior reports associating palpitations with AF 16 while others found a more ephemeral nature of presenting symptoms. 17 As expected, longer monitoring duration increased AF detection. 18 In addition, excessive supraventricular ectopic activity was associated with unknown AF (table 2, figure 4), comparable to prior analyses. [19][20][21] Sinus node disease, identified by sinus pauses, 22 has been linked to underlying AF. 23 24 Although, sinus pauses were not part of our multivariate model, but there is evidence to suggest that it could be associated with unknown AF, confirming findings from one prior study. 25 We suggest further ECG monitoring, beyond 7 days, to look for AF in clinically high risk patients as identified by our multivariate model, especially, if they have evidence of significant atrial ectopy or sinus pauses on prior monitoring.
Open access eCG monitoring -an alternative approach to increase detection of unknown AF? Current guidelines recommend pulse palpation followed by an ECG in patients with an irregular pulse in populations >65 years to detect AF. 1 8 Pulse palpation can be replaced by a blood pressure machine. 26 27 Systematic prolonged ECG monitoring is recommended in stroke survivors. In addition, community-based ECG screening programmes using patient-operated devices are able to identify patients with silent AF, especially when elderly populations are screened, for example, those aged 75 years or more. [28][29][30] Such population-based screening programmes require a specific infrastructure that is currently confined to a research environment or not available at all. Our study suggests that open access to prolonged ECG monitoring has a high diagnostic yield in patients with various symptoms, opening up an alternative approach to increase the detection of unknown AF. Open access to ECG monitoring has the advantage of using existing health infrastructure, but is limited to populations with symptoms.
limitations Our findings will need validation in other, external patient cohorts. Although the number of patients in our study was reasonable for a busy teaching hospital however more patients are required for further studies especially to assess Holter ECG variables with incident AF. The number of patients also had an effect on the relatively wide CIs for the calculated ORs. AF group had longer duration of monitoring that could introduce bias. To rectify this we adjusted our multivariate variable for duration of recording. Moreover, older patient usually have higher incidence of comorbidities which may be one reason why the multivariate model strongly predicted AF.

COnClusIOn
Seven-day Holter ECG monitoring detects unknown AF in around 9% of patients with various symptoms in an open access, 'all-comer' setting, suggesting that this is a useful diagnostic approach to enhance detection of unknown AF. Risk factor analysis for paroxysmal AF and systematic evaluations of treatment and outcomes after AF screening are needed to define populations for screening silent AF. Comparable AF detection rates between cardiology and primary care also supports provision of ECG monitoring using open-access services across various healthcare sectors.