Fadi Nahab MD Associate Professor of Neurology and Pediatrics

Emory University Medical Director, Stroke Program

Emory University Hospital, Emory University Hospital Midtown

Update on Cryptogenic Stroke Evaluation and Treatment

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Disclosures

• Consultant: Imedex, Medtronic, Expert witness

• Speaker’s bureau: Medtronic

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Objectives

• Be familiar with the risk of recurrent cryptogenic stroke and potential causes

• Recognize that biomarkers may help to identify causes of cryptogenic stroke

• Consider unrecognized paroxysmal atrial fibrillation as an important contributor to cryptogenic stroke and the benefits of prolonged cardiac monitoring

• Understand the risks and potential benefits of various treatment strategies, including ongoing studies

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Cryptogenic Stroke: Causes

Bang OY et al. Stroke. 2014;45:1186-1194.

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Cryptogenic Stroke: Causes

• Cardiac etiologies: – Paroxysmal AFib, SBE (culture negative), papillary fibroelastoma

• Subtle arterial dissections • CNS vasculitis • Hypercoagulable state in setting of cancer • Metabolic disorders: Hyper-homocysteine, Fabry’s disease • Plaque in aortic arch • HIV, CNS infection • Drug abuse • Genetic etiologies (CADASIL, MELAS, etc.)

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Definitions of Cryptogenic Stroke

1. Adams HP et al. Stroke. 1993;24:35-41; 2. Causative Classification System for Ischemic Stroke (CCS). Available at:

https://ccs.mgh.harvard.edu/ccs_intro.php. Accessed April 15, 2015; 3. Hart RG et al. Lancet Neurol. 2014;13:429-438; 4. Amarenco

P et al. Cerebrovasc Dis. 2013;36:1-5.

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Cardiac Testing

Manning WJ. Available at:

http://www.uptodate.com/contents/echocardiography-in-detection-of-

cardiac-and-aortic-sources-of-systemic-embolism.

Accessed December 15, 2015.

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TTE vs TEE

17

39

0

20

40

60

80

100

Identified onBoth TTE and

TEE

Identified onTEE Only

Potential Cardioembolic Source Identified

de Bruijn SF et al. Stroke. 2006;37:2531-2534.

Patients

(%

)

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MRV Pelvis & Cryptogenic Stroke

• N=46 – 18-60 yrs

– Ischemic stroke <72 hrs

– Deficit >3 hours

• MRV pelvis time of flight (TOF, PC)

• Low interrater agreement, K=0.23

Stroke 2004;35:46-50

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CE-MRV Pelvis & Cryptogenic Stroke

• Contrast-enhanced Pelvic MRV

• Excellent interrater agreement, K=1.0

Stroke 2014;45:2324-2329

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Cryptogenic Stroke & D-dimer

• Case-control study (n=140) – D-dimer obtained >10

days from stroke

– Mean D-dimer levels were significantly higher in the UCA vs CSA group

• UCA 615 vs CSE 139, p<0.001

CSA=Definite stroke association; UCA=Unidentified/cancer-associated stroke

Stroke 2012;43:3029-3034.

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Cryptogenic Stroke & D-dimer

• 348 consecutive cryptogenic stroke patients

• 71 (20%) with active cancer at time of stroke

• D-dimer obtained within 24 hours of admission

• Mean D-dimer level was significantly higher in cancer-associated stroke patients vs those without cancer (p<0.001)

PLoS One 2012;7:e44959

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Atrial Fibrillation Burden and Short-Term Risk of

Stroke: Case-Crossover Analysis of Continuously

Recorded Heart Rhythm From Cardiac Electronic

Implanted Devices • 187 acute ischemic stroke patients

with CIEDs monitored for at least 4 months prior to index event.

• 28 patients had ≥5.5 hours of AF burden within 30 days prior to stroke.

• AF burden of >5.5 hr increased the

risk for ischemic stroke 4-5 fold.

• The risk for stroke was transient and reduced rapidly after 10d post AF event.

Turakhia, Circ Arrhythm Electrophysiol; 2015

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Cardiac Monitoring Strategies

1. Vasamreddy CR et al. J Cardiovasc Electrophysiol. 2006;17:134-139; 2. Gladstone DJ et al. N Engl J Med. 2014;370:2467-2477; 3. Rosenberg MA et al. Pacing Clin Electrophysiol.

2013;36:328-333; 4. Kamel H et al. Stroke. 2013;44:528-530. 5. Shinbane JS et al. Heart Rhythm Society 2013 34th Annual Scientific Sessions, Volume 10, Issue 5S, 2013.

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Studies of Outpatient Monitoring in Cryptogenic Stroke Patients

Glotzer TV, Ziegler PD. Heart Rhythm. 2015;12:234-241.

Kasshout O, et al. J Stroke Cerebrovasc 2015 (in review)

Emory (2015) 132 30 seconds MCOT 30 days 13%

Three-year longevity for long-term monitoring2

MR Conditional at 1.5 and the only ICM

at 3.0 Tesla with no post-insertion

waiting required‡

Proven AF algorithm accurately detects AF

in 98.5% of patients1

Reveal LINQ ™ ICM The Smallest ICM to Provide Continuous and Wireless Data Collection and

Trending

† Reveal LINQ ICM has been demonstrated to pose no known hazards in a specified MR environment with specified conditions of use. Please see Reveal LINQ

ICM clinician manual or MRI Technical Manual for more details.

1. Hindricks G, Pokushalov E, Urban L, et al. Performance of a new leadless implantable cardiac monitor in detecting and quantifying atrial fibrillation: Results of

the XPECT Trial. Circ Arrhythm Electrophysiol. April 2010;3(2):141-147.

2. See the Reveal LINQ ICM clinician manual for usage parameters

Reveal LINQ ICM is 1/3

the width of an AAA battery

No wires or leads

CRYSTAL AF

CRYSTAL AF: Study Design and End Points

End Point

Primary • Time to first detection of AF at 6 months of follow-up

Secondary • Time to first detection of AF at 12 months • Recurrent stroke or TIA • Change in use of oral anticoagulant drugs

Sanna T et al. N Engl J Med. 2014;370:2478-2486.

• Randomized, controlled clinical trial with 441 patients

• Compared continuous, long-term monitoring with Reveal ICM vs.

conventional follow-up

• Assessment at scheduled and unscheduled visits

• ECG monitoring performed at the discretion of the site investigator

CRYSTAL AF: Patients

• Age ≥40 years

• Diagnosis of stroke or TIA occurring within previous 90 days

• Stroke was classified as cryptogenic after extensive testing: – 12-lead ECG

– ≥24 hours of ECG monitoring

– TEE

– Screening for thrombophilic states (in patients <55 years of age)

– Magnetic resonance angiography, computerized tomography angiography, or catheter angiography of head and neck

– Ultrasonography of cervical arteries or transcranial Doppler ultrasonography of intracranial arteries allowed in place of MRA or CTA for patients aged ≥55 years

Patients were only categorized with cryptogenic stroke after extensive diagnostic testing

Sanna T et al. N Engl J Med. 2014;370:2478-2486.

CRYSTAL AF: Study Population

Sanna T et al. N Engl J Med. 2014;370:2478-2486.

447 patients were enrolled

6 were excluded • 4 did not meet eligibility criteria

• 2 withdrew consent

441 underwent randomization

221 were assigned to ICM • 208 had ICM inserted

• 13 did not have ICM inserted

220 were assigned to control • 220 received standard of care

12 crossed over to control

12 exited the study • 3 died

• 1 was lost to follow-up

• 5 withdrew

• 3 were withdrawn by investigator

6 crossed over to ICM

13 exited the study • 2 died

• 1 was lost to follow-up

• 7 withdrew

• 3 were withdrawn by investigator

221 were included in intention-to-treat analysis 220 were included in intention-to-treat analysis

CRYSTAL AF: AFib at 6 months

Sanna T et al. N Engl J Med. 2014;370:2478-2486.

CRYSTAL AF: AFib at 12 months

Sanna T et al. N Engl J Med. 2014;370:2478-2486.

12 Month Endpoints

ICM Control

Median Time from Randomization to AF Detection

84 days

52.5 days

Patients found to have AF 29 4

% Asymptomatic Episodes 79% 50%

Oral Anticoagulation Usage, overall 14.7% 6.0%

OAC use in AF patients 96.6% 100%

Tests required to find AF Automatic AF detection

121 ECGs 32 24-hour Holters 1 Event Recorder

Complications 5 (2.4%) ICMs removed due to insertion site infection or pocket erosion

None

CRYSTAL AF: Detection of AF at 36 Months

Sanna T et al. N Engl J Med. 2014;370:2478-2486.

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Predictors for Atrial Fibrillation Detection after

Cryptogenic Stroke:

Results from CRYSTAL AF

Assessed whether these parameters

predicted ICM detected AF:

• Age, sex, race

• Body Mass Index,

• Type and severity of index event

• CHADS2 score

• PR-interval

• Diabetes, hypertension

• Congestive heart failure

• Patent foramen ovale

• Premature atrial contractions

Increasing age and a prolonged PR-

interval were independently

associated with AF, but the

predictive ability was only moderate.

Thijs et al. Neurology 2015 (in press)

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MRI FLAIR Lesions & PAF

• Cortical lesions (vs other) were significantly associated with detection of PAF:

– OR 5.5 (95% CI: 1.4 - 20.9)

MRI Lesion 30-day PAF

Cortical lesion 21.2 %

High subcortical 4.1%

None 5.9%

P-value: 0.01

Kasshout O, et al. J Stroke Cerebrovasc 2015 (under review)

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Echocardiography Variables & PAF Variable Area under the

Curve (AUC) Value Sensitivity Specificity

LA Diameter .67 (48-87) 3.75 83% 52%

A .49 (.25-.74) 82.5 67% 49%

a’ septal .93 (.80-.99) 8.5 99% 85%

a’ lateral .52 (.29-.76) 13.5 71% 32%

LAVI .7 (.52-.88) 31.5 83% 68%

LAVI/A .61 (.37-.86) 0.33 83% 45%

LAVI/a’(lateral) .67 (.45-.9) 2.3 83% 59%

LAVI/a’(septal) .98 (.92-.99) 4.6 99% 96% LA=Left atrium; a’=Tissue Doppler velocity; A=Late diastolic Doppler velocity ; LAVI=Left atrial volume index

Kasshout O, et al. J Stroke Cerebrovasc 2015 (under review)

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Real World Experience

Methods: • Inclusion Criteria: Received ICM after CS as

defined by physician, follow-up censored at 182 days of monitoring

• Data transmitted via CareLink Remote Monitoring

• AF episodes (≥2 minutes) were adjudicated • AF detection rates were computed using

Kaplan Meier survival estimates Results: • 1247 patients included, 53% male, mean age

of 65 years • 1521 AF episodes detected in 147 patients,

yield of 12.2% at 6 months • Median time to detection: 58 [IQR 11-101]

Days • Median duration of longest AF episode: 3.4

[IQR 0.4-11.8] hours

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Emory Experience • A random sampling of ILR tracings identified as atrial fibrillation by

the Medtronic algorithm was adjudicated by a board certified electrophysiologist for accuracy.

• Among 166 rhythm strips identified as atrial fibrillation by the Medtronic algorithm in 52 consecutive patients:

– 140 (84%) were incorrectly identified as atrial fibrillation

• 57% as premature atrial complexes(PACs) • 22% as T wave over-sensing, • 10% due to noise • 5.0% due to premature ventricular complexes (PVCs) • 2.9% due to under-sensing • 2.9% due to sinus arrhythmia.

• Of the 38 (73%) patients with cryptogenic stroke, 4 (11%) were identified as having true atrial fibrillation over 413 patient-months of monitoring – Mean time to atrial fibrillation detection was 93 days after ILR.

International Stroke Conference 2016

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(ESUS)

Lancet Neurol 2014;13:429-438.

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ESUS Studies

Anticipated completion: 1November 2017 (n=6000), 2January 2018 (n=7060)

1. ClinicalTrials.gov. NCT02239120. Accessed Dec 15, 2015

2. ClinicalTrials.gov. NCT02313909. Accessed Dec 15, 2015.

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Risks of ESUS Treatment Paradigm

• Assumption #1 – A significant % of these strokes are due to either:

• 1. AFib • 2. Another mechanism that is responsive to anticoagulation

therapy

• Assumption #2 – Treatment with an anticoagulant will be safe for these

other causes

• Assumption #3 – Enough patients will survive long enough to show overall

benefit

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Cryptogenic Stroke: Recurrent Stroke Risk

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Age +PFO 2-yr stroke or death rate

-PFO 2-yr stroke or death rate

P-value

<55 yrs 2.0% 9.3% 0.15

55-64 yrs 10.0% 13.9% 0.70

≥65 yrs 37.9% 14.5% 0.01

Stroke 2004;35:2145-2149.

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Cryptogenic Stroke Treatment Options

• Preferred therapy = single antiplatelet agent unless: – Heart rhythm monitoring shows atrial fibrillation

• Anticoagulation

– TTE with large left atrium and no prior valvular disease • Cardiac monitor; consider aspirin/clopidogrel vs anticoagulation

– D-dimer >1000 beyond 10 days from stroke onset • Routine cancer screening; consider whole body imaging. Consider anticoagulation if

cancer identified.

– PFO • Monitor cardiac rhythm; consider leg ultrasound, contrast-enhanced MRV pelvis if D-

dimer elevated. Single antiplatelet therapy. No clear benefit from PFO closure.

– Migraine w/ aura • Headache prophylaxis for frequent HA

– Recurrent stroke on antiplatelet agent • Assess medication adherence, drug-drug interactions (e.g. NSAID use) and opportunity

to optimize risk factors before considering anticoagulation

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Diet & Stroke

• REGARDS Study – Southern Diet (added fats, fried food, eggs, organ and

processed meats, and sugar-sweetened beverages) • 56% higher risk of acute CHD (comparing highest vs lowest

quartile); p=0.003

– Participants eating ≥2 weekly servings of fried fish (vs <1 serving/month)

• 63% higher hazard of ischemic stroke or MI

• Adjusted for socio-demographic variables, health behaviors, and cardiovascular disease risk factors.

Shikany JM, et al. Circulation 2015;132:804-814. Nahab F, et al. AJCN 2015 (under review)

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Summary

• The risk of recurrent cryptogenic stroke depends on the underlying (and unknown) cause

• Biomarkers may be important predictors of cancer-related cryptogenic stroke

• Unrecognized paroxysmal atrial fibrillation is a significant contributor to cryptogenic stroke and prolonged cardiac monitoring is important; age and left atrial parameters on echocardiography may refine those at highest risk.

• The success of any therapy will likely depend on the treated population and the efficacy and safety of the chosen treatment