Atrial FibrillationNCT04724889
Predictors of Atrial Fibrillation in Patients Undergoing Implantable Loop Recorder Implant
An observational study of Atrial Fibrillation and Stroke, run by Cambridge University Hospitals NHS Foundation Trust at 1 site in United Kingdom.
Trial 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). Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Atrial Fibrillation, Stroke
- What is being tested?
- blood test
- How many people
- 100 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Aug 2019to 1 Oct 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients that have been referred for Implantable Loop Recorder.
Who may be able to join
- Male or Female, aged 18 years or above.
- Patients referred for ILR
- Patients without history of AF
- Able to give consent
Who cannot join
- Patients with history of AF
- Patients unable to give consent
Trial locations and contacts
1 site in 1 country.
United Kingdom1 site, 1 recruiting
- Recruiting
Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust
Cambridge, CB2 0QQ
Peter Pugh, 00441223349147, peter.pugh@addenbrookes.nhs.uk
About this study
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.
Read the 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.
- Conditions
- Atrial Fibrillation, Stroke
- Being tested
- blood test
- Medical subject headings
- Atrial Fibrillation, Stroke
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
blood testDiagnostic test
Blood test to check high sensitivity troponin. Additional blood biomarkers maybe added in light of new research
| Study group | Role | What they receive |
|---|---|---|
| Patients with underlying AF | Patients that will have AF detected by ILR will be compared with patients without AF. Receives: Diagnostic Test: blood test | |
| Patients without AF | Patients that will have AF detected by ILR will be compared with patients without AF. Receives: Diagnostic Test: blood test |
What is being measured
The primary outcome is the main question the study is designed to answer.
Medical comordbidities as potential predictors of AF in patients with and without stroke
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
Measured: 1 year
Increased height and weight as potential predictors of AF in patients with and without stroke
To determine whether increase height (in cm) and weight (in kg) are associated with AF
Measured: 1 year
Smoking history (non smoker, ex smoker, current smoker) and increased alcohol intake as potential predictors of AF in patients with and without stroke
To determine whether smoking history (non smoker vs ex smoker vs current smoker) and increased alcohol intake (>14 units/ week) are associated with AF
Measured: 1 year
Electrocardiographic variables as potential predictors of AF
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
Measured: 1 year
Holter monitor variables as potential predictors of AF
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
Measured: 1 year
Echocardiographic variables as potential predictors of AF
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
Measured: 1 year
Blood biomarkers as potential predictors of AF
To determine whether existing blood biomarkers (haemoglobin, white cells, platelets, sodium, potassium, creatinine, thyroid function, lipid profile) are associated with AF
Measured: 1 year
Secondary outcomes (1)
High sensitivity troponin as a predictor of Atrial Fibrillation in patients with and without previous stroke
To determine whether high sensitivity troponin is associated with AF
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jan 2021
- Study start1 Aug 2019
- Primary completion1 Aug 2021 (estimated)
- Study completion1 Oct 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Atrial FibrillationStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cambridge University Hospitals NHS Foundation Trust
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Peter J Pugh, Cambridge University Hospitals NHS Foundation Trust
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04724889
- Sponsor's protocol ID
- 254722
- Status last verified
- Jan 2021
- First submitted
- 6 Dec 2018
- Last updated
- 26 Jan 2021
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 26 Jan 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Predictors of Atrial Fibrillation in Patients Undergoing Implantable Loop Recorder Implant
- ClinicalTrials.gov ID
- NCT04724889
- Acronym / sponsor ID
- 254722
- Conditions
- Atrial Fibrillation, Stroke
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- Cambridge University Hospitals NHS Foundation TrustUniversity, hospital or other
- Study start
- 1 Aug 2019 (actual)
- Primary completion
- 1 Aug 2021 (estimated)
- Study completion
- 1 Oct 2021 (estimated)
- First posted
- 26 Jan 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Patients with underlying AF | – | Diagnostic Test: blood testPatients that will have AF detected by ILR will be compared with patients without AF. |
| Patients without AF | – | Diagnostic Test: blood testPatients that will have AF detected by ILR will be compared with patients without AF. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients that have been referred for Implantable Loop Recorder.
Key inclusion criteria (4 listed)
- Male or Female, aged 18 years or above.
- Patients referred for ILR
- Patients without history of AF
- Able to give consent
Key exclusion criteria (2 listed)
- Patients with history of AF
- Patients unable to give consent
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| blood testBlood test to check high sensitivity troponin. Additional blood biomarkers maybe added in light of new research | Diagnostic test | Patients with underlying AF, Patients without AF |
Primary outcome
Medical comordbidities as potential predictors of AF in patients with and without stroke
Time frame: 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
Time frame: 1 year
To determine whether increase height (in cm) and weight (in kg) are associated with AF
Smoking history (non smoker, ex smoker, current smoker) and increased alcohol intake as potential predictors of AF in patients with and without stroke
Time frame: 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
Electrocardiographic variables as potential predictors of AF
Time frame: 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
Holter monitor variables as potential predictors of AF
Time frame: 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
Echocardiographic variables as potential predictors of AF
Time frame: 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
Blood biomarkers as potential predictors of AF
Time frame: 1 year
To determine whether existing blood biomarkers (haemoglobin, white cells, platelets, sodium, potassium, creatinine, thyroid function, lipid profile) are associated with AF
1 secondary outcome
High sensitivity troponin as a predictor of Atrial Fibrillation in patients with and without previous stroke
Time frame: 1 year
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Jan 2021.
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Atrial Fibrillation (AF)
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust
Cambridge, United Kingdom
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Atrial Fibrillation and Stroke, run by Cambridge University Hospitals NHS Foundation Trust at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 26 Jan 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Medical comordbidities as potential predictors of AF in patients with and without stroke (time frame: 1 year). The study lists 7 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Jan 2021.