Clinical trial NCT06542770: Atrial Anomalies Predict Silent Atrial Fibrillation Detected by Implantable Cardiac Monitor in Cryptogenic Stroke
Official title: Subtle Ultrasound Atrial Anomalies Predicts the Early Diagnosis of Silent Atrial Fibrillation Detected by Implantable Cardiac Monitor in Patients With Cryptogenic Stroke. A Randomized Trial
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Paroxysmal Atrial Fibrillation
Cardiac Rhythm Disorder
Left Atrial Dilatation
Cryptogenic Stroke
Keywords: Atrial strain. Implantable cardiac monitor
Lead sponsor: Parc de Salut Mar
Sponsor class: OTHER
First posted: 2024-08-07
Enrollment: 100
Sex: ALL
Minimum age (years): 50
Maximum age (years): 89
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Randomized prospective parallel study
Primary purpose: DIAGNOSTIC

Brief summary: Cryptogenic stroke (CS) causes about 30% of admissions to a stroke unit. Silent paroxysmal atrial fibrillation (PAF) is believed to be the underlying cause of a significant proportion of patients. The use of implantable cardiac monitors (ICM) early after the CS has demonstrated benefits in the diagnostic yield, but the indication for ICM in the current guidelines remains unclear. Atrial contraction strain (ACS) evaluated by cardiac ultrasound could be of help to select the patients more prone to suffer from silent PAF.

The purpose of this investigation is to conduct a randomized prospective unicentric study to evaluate the usefulness of ICM for early detection of silent PAF episodes in patients with CS. Clinical and ultrasound predictors of PAF occurrence (ACS) will be studied in order to define patients needing a closer follow-up.

Detailed description: Introduction

Cryptogenic stroke (CS) is a stroke in which etiology cannot be determined after a comprehensive evaluation and it is the cause of about 30% of admissions to a stroke unit. In these cases single antiplatelet therapy is recommended as a long term treatment. However, silent paroxysmal atrial fibrillation (PAF) is believed to be the underlying cause of a significant proportion of episodes, and it´s recognition merits urgency since carries to oral anticoagulation (OAC) and antiplatelet therapy cessation. According to guidelines, in order to detect PAF we need to monitor the patient´s ECG for at least 48h, although the longer the monitoring is, the better the diagnostic yield.

Previous research showed controversial results regarding the use of implantable cardiac monitors (ICM) in such patients when the ICM had been implanted late after the CS. On the other hand, studies with an early implant demonstrated a clear benefit in the diagnostic yield. To date, the strategy to search actively for PAF in patients with CS is still not well established, and even when internal loop recorders (ILR) are our best option to recognize paroxysmal arrhythmic events, guidelines are not clear about the cases in which they might be indicated. Some markers, such as age, cardiovascular risk factors, blood biomarkers or cardiac ultrasound characteristics have been related to a higher silent PAF detection. Recent data points at the use of left atrium atrial strain (LAS) to select the patients more prone to suffer from silent PAF.

It remains to be defined the usefulness of ILR implanted early after the CS in order to diagnose the presence of silent PAF, and the roll or ACS in such patients in order to predict those being at higher risk.

Methods

This is a randomized prospective unicentric study to evaluate the usefulness of ICM for early detection of silent PAF episodes in patients with CS. During the first 48 hours from admission, patients were randomized to receive standard care (Control Group) or early ICM implantation (Study Group) before discharge. A special effort will be made to search for the clinical and ultrasound atrial predictors of PAF occurrence in order to better define what patients need a closer follow-up.

Ultrasound evaluation

The following ultrasound atrial features will be studied to separate patients into two categories:

1. LA dilatation: indexed volumen \>32 ml/m2
2. PALS (Peak atrial longitudinal strain) \<21%
3. PACS ( Peak atrial contraction strain ) \<13%
4. Atrial ejection fraction \<55%

Patients will be considered as having a "normal" LA if none of the above mentioned characteristics is accomplished, in opposition to patients who accomplish at least one characteristic described above, which will be considered as "atrial cardiomyopathy" patients.

Patients will be immediately treated with antiplatelet treatment. OAC will be started if PAF is detected during admission. Whilst in the Stroke Unit, all patients will be continuously ECG-monitored for at least 48 h and will undergo a cardiac transthoracic echocardiogram with complete evaluation of strain parameters.

Demographic factors, vascular risk factors and comorbidities will be collected. Work-up during admission will include, at least, a complete neurological examination, 12-lead ECG, brain computed tomography (CT), blood test and neurovascular imaging (magnetic resonance angiography, angioCT and/or two-dimensional ultrasound of supra-aortic trunks and intracranial territory).

The diagnosis of CS will be revisited in all patients 3 months after the index episode, and those found to have any potential cause other than PAF will be additionally excluded. The study follows national and international principles (Declaration of Helsinki), and it was approved by the local ethics committee. All patients are required to sign the specific informed consent.

Strategies for PAF detection Since the prevalence of AF is higher in patients having LA anomalies, we will divide the total group into two categories before randomization, depending on the presence or absence of: LA dilatation, and/or impaired ACS. Then we will randomize all patients to Control Group or Study Group.

Control group: after discharge from the Stroke Unit, patients in the control group will be studied with daily ECGs whilst admitted at the hospital. Outpatient serial ECGs will be performed at the time of each visit at the Neurology Clinic 3, 6 and 12 months after the stroke, and every 6 months thereafter. Additional ECGs will be performed if patients had symptoms potentially related to PAF. Furthermore all patients will undergo a 72h-Holter-monitoring scheduled 1 month after discharge.

Study group: patients in the active study group will undergo an ICM implant 3-4 days after the stroke and prior to discharge. All devices (Abbott Jot) will be implanted subcutaneously under local anaesthesia in the left chest region and programmed with an specific algorithm for AF detection set at 30 seconds for detection. All patients will be included in remote monitoring system (Merlin), which will be programmed to send alerts in case of registering episodes qualifying for AF detection, and a monthly routine registration. All ICM recordings will be reviewed by a specialized cardiologist. Patients will be seen at the arrhythmia and the neurology outpatient clinics at 3, 6 and 12 months after the stroke, and every 6 months thereafter.

End-points and follow-up Primary clinical outcome: detection of AF at follow-up, which is defined by the presence of a confirmatory 12-leads ECG, or a registration lasting more than 30 seconds in, either the 72h-Holter-Monitoring, or in the ICM recording. In case of AF detection OAC will be initiated immediately.

Secondary clinical outcomes: ultrasounds predictors for AF occurrence: LA indexed volumen, maximum systolic global longitudinal strain (PALs), atrial contraction strain (PACs), atrial ejection fraction.

We also will search for stroke recurrences, defined as new neurological events recorded after hospital discharge and validated by a vascular neurologist.

Statistical analysis Results are reported as mean (SD), median (p25-p75) or frequency (%). Comparisons between groups were performed with the Student t test or chi-squared analysis. The association between clinical variables and the study end-points was evaluated using survival analysis methodology (Cox regression models). The Kaplan-Meier method was used to estimate the cumulative probability of PAF detection and stroke recurrence in both groups, and comparisons were made by the log-rank test. Significance was set at P \< 0.05.

Eligibility criteria: Inclusion Criteria:

* Acute ischemic stroke or transient ischemic attack (TIA) from January 2022 to July 2023
* Age between 50 and 89 years;
* Undetermined origin at hospital admission according to the SSS-TOAST criteria (2):

  1. Absence of major structural heart disease by cardiac ultrasound (normal global and segmental left ventricle contraction, absence of valvular/rheumatic disease, absence of intracardiac shunts)
  2. Absence of AF during 48h ECG-monitoring
  3. Absence of major anomalies in the supra-aortic trunks ultrasound.

Exclusion Criteria:

1. Patients with a history of hemorrhagic stroke;
2. Presence with prior atrial fibrillation or atrial flutter;
3. Permanent contraindication or indication for OAC for other reasons;
4. Recent (\<1 month) major surgery or cardiac events;
5. Presence of severe cardiac abnormalities;
6. Patients with life expectancy \<1 year or severe stroke (modified Rankin Scale \> 4).

Primary outcomes:
measure: Detection atrial fibrilation at follow-up
timeFrame: Up to 2 years follow-up (ICM and standard care practice)
Secondary outcomes:
measure: LA indexed volume
timeFrame: Before Day 3 since the Criptogenic Stroke
measure: Maximum Systolic Global Longitudinal Strain (PALs)
timeFrame: Before Day 3 since the Criptogenic Stroke
measure: Atrial Contraction Strain (PACs)
timeFrame: Before Day 3 since the Criptogenic Stroke
measure: Atrial Ejection Fraction
timeFrame: Before Day 3 since the Criptogenic Stroke
measure: stroke recurrences
timeFrame: Up to 2 years follow-up (ICM and standard care practice)
Other outcomes:
Locations:
city: Barcelona
country: Spain
facility: Hospital del Mar
Study officials:
affiliation: Hospital del Mar
name: Ermengol Valles Gras, PhD
role: PRINCIPAL_INVESTIGATOR
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