Predictors of Atrial Fibrillation in Patients Undergoing Implantable Loop Recorder Implant
- Conditions
- Atrial FibrillationStroke
- Interventions
- Diagnostic Test: blood test
- Registration Number
- NCT04724889
- Brief Summary
Implantable Loop Recorders (ILR) are small devices the size of a memory stick, which are implanted to investigate stroke, palpitations and fainting episodes. They monitor the heart constantly and detect abnormalities such as slow or fast heart beats and an irregular heartbeat called Atrial Fibrillation (AF). Stroke is a life threatening condition and no cause is identified for over 30% of strokes. AF is a predominant risk factor for stroke. About 30% of patients with stroke are found to have AF when they are monitored with an ILR. Unfortunately not every patient with a stroke can have an ILR; one of the prohibiting factors is cost. Therefore, there is an urgent unmet clinical need to rationalise the use of ILRs and prioritise their implantation in those patients that have most to gain and therefore achieving cost-effectiveness and improving patient care.
In order to achieve the above, identifying parameters that can predict the presence of underlying AF is very important. Studies have shown that special factors including patient's other medical problems, family history, factors on paper recording of the electrical activity of the heart, heart monitors and ultrasound scan of the heart can be useful in predicting AF. Also certain blood molecules have been investigated as potential predictors of AF.
The aim of this study is to look at all the above factors and combine them in order to determine whether these factors can predict the presence of AF. Identify predictors of AF will allow doctors to identify patients at different risk of having AF and use the ILR in all possible patients that might need it.
- Detailed Description
Implantable Loop Recorders (ILR) are small devices the size of a memory stick, which are implanted under the surface of the skin to investigate stroke, dizziness, fainting and palpitations. They are designed to monitor the heart constantly and detect any abnormalities such as slow or fast heart beats and an irregular heartbeat called Atrial Fibrillation (AF).
Stroke is a life threatening condition placing a heavy burden on health care services. Currently there is no cause identified for over one third of strokes. AF is a predominant risk factor for stroke and about 30% of patients with stroke are found to have AF when they are monitored with an ILR.
There are different methods that can be used to screen for AF including electrocardiogram (trace of the heart) and heart monitors of different duration ranging from one to 30 days. Medical studies have shown that using an ILR is the best way to monitor the heart and identify the presence of underlying AF. Unfortunately, not every patient with a stroke can have an ILR.
The risk of stroke associated with AF can be variable depending on patient's characteristics. The risk is estimated using a scoring system and strong blood thinning medication is recommended in all high risk patients (score \>1). All patients with a prior stroke who are found to have AF will score at least 2 on the scoring system and blood thinning medication would be imperative to reduce the risk of a subsequent stroke by around 65%.
However, documenting AF is required to initiate blood thinning therapy after a stroke and therefore all patients with stroke should be screened for the presence or absence of AF. Whilst permanent AF is simple to identify, intermittent AF is considerably more difficult, especially if the patients have no symptoms relating to it.
Although the usefulness of an ILR in the context of stroke is not disputed, ILRs are not routinely used for AF monitoring in stroke survivors in all centers. One of the prohibiting factors is cost. Therefore, there is an urgent unmet clinical need to rationalise the use of ILRs and prioritise their implantation in those patients that have most to gain and therefore achieving cost-effectiveness and most importantly improving patient care.
In order to achieve the above, identifying parameters that can predict the presence of underlying AF could be very useful. Several studies have been conducted to try and identify predictors of AF. They have shown that certain parameters such as patient's comorbidities, family history, variables on electrocardiogram, heart monitors and ultrasound scan of the heart can be useful in predicting AF. In addition certain blood biomarkers have been investigated as potential predictors of AF.
The aim of this study is to look at patient's comorbidities, family history, demographic parameters, parameters from electrocardiogram, heart monitor and ultrasound scan of the heart, as well as blood biomarkers and combine them in order to determine whether these factors can predict the presence of AF.
Identifying predictors of AF will allow doctors to identify patients at high risk of developing AF, manage them better and use the ILR in all possible patients that might need it.
Investigators are planning to recruit 100 patients that have been referred for an ILR and investigate all the above parameters in order to identify the ones that can predict the presence of underlying AF. Investigators are planning to review patients medical records and also ask study participants to go through a questionnaire about, demographic parameters, medical problems, family history, smoking and alcohol consumption. In addition electrocardiogram, Holter monitor and ultrasound scan of the heart will be analysed for specific variables.
Electocardiographic variables:PR and QRS duration, P wave duration, P wave dispersion, QTc duration, PW terminal force, QRS and p wave axis Holter monitor variables: number and percentage of atrial and ventricular ectopics, minimum, maximum and mean heart rate, heart rate variability and apnoea, hypopnea index Ultrasound scan of the heart variables: left ventricular volume and dimensions, left ventricular function assessed by ejection fraction and strain, left atrial volume, dimensions and function (assessed using left atrial strain, emptying fraction and expansion index), right ventricular size and function, right atrial area, presence of patent foramen ovale and presence of significant valve stenosis or regurgitation (moderate or severe).
Existing blood parameters (heamoglobin, white cells, platelets, sodium, potassium, creatinine, thyroid function, lipid profile) will be recorded. In addition, blood samples will be collected and analysed for high sensitivity troponin. Additional blood biomarkers maybe be added in light of new research.
Study participants will be followed up for 1 year to check for presence of AF. ILR traces will be reviewed in order to identify these patients that have underlying AF of any duration, \> 30 seconds, \> 6 minutes and \> 24 hours.
All the above mentioned variables will be compared between these patients that have underlying AF and the ones that don't. The ones that are identified as predictors will be combined in order to predict risk of having underlying AF.
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 100
- Male or Female, aged 18 years or above.
- Patients referred for ILR
- Patients without history of AF
- Able to give consent
- Patients with history of AF
- Patients unable to give consent
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Patients with underlying AF blood test Patients that will have AF detected by ILR will be compared with patients without AF. Patients without AF blood test Patients that will have AF detected by ILR will be compared with patients without AF.
- Primary Outcome Measures
Name Time Method Smoking history (non smoker, ex smoker, current smoker) and increased alcohol intake as potential predictors of AF in patients with and without stroke 1 year To determine whether smoking history (non smoker vs ex smoker vs current smoker) and increased alcohol intake (\>14 units/ week) are associated with AF
Holter monitor variables as potential predictors of AF 1 year To determine whether number and percentage of atrial and ventricular ectopics, minimum, maximum and mean heart rate, heart rate variability and apnoea, hypopnea index are associated with AF
Medical comordbidities as potential predictors of AF in patients with and without stroke 1 year To determine whether medical conditions (such as hypertension, heart failure, asthma, cancer, sarcoidosis, hypothyroidism, hyperthyroidism, liver disease, kidney disease, ischaemic heart disease, pulmonary embolism, chronic obstructive pulmonary disease) are associated with AF in patients with and without stroke
Increased height and weight as potential predictors of AF in patients with and without stroke 1 year To determine whether increase height (in cm) and weight (in kg) are associated with AF
Electrocardiographic variables as potential predictors of AF 1 year To determine whether PR and QRS duration, P wave duration, P wave dispersion, QTc duration, PW terminal force, QRS and p wave axis are associated with AF
Blood biomarkers as potential predictors of AF 1 year To determine whether existing blood biomarkers (haemoglobin, white cells, platelets, sodium, potassium, creatinine, thyroid function, lipid profile) are associated with AF
Echocardiographic variables as potential predictors of AF 1 year To determine whether increased left ventricular volume and dimensions, reduced left ventricular function assessed by ejection fraction and strain, increased left atrial volume and dimensions and reduced function (assessed using left atrial strain, emptying fraction and expansion index), increased right ventricular size and reduced function, increased right atrial area, presence of patent foramen ovale and presence of significant valve stenosis or regurgitation (moderate or severe) are associated with AF
- Secondary Outcome Measures
Name Time Method High sensitivity troponin as a predictor of Atrial Fibrillation in patients with and without previous stroke 1 year To determine whether high sensitivity troponin is associated with AF
Trial Locations
- Locations (1)
Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust
🇬🇧Cambridge, United Kingdom