Aucun titre de diapositive · Collagen production and secretion AF AF . Potential elements of a...
Transcript of Aucun titre de diapositive · Collagen production and secretion AF AF . Potential elements of a...
Stanley Nattel, MD
Montreal Heart Institute
Atrial Cardiomyopathy:
is it an evolving clinical reality?
Stanley Nattel, MD
Montreal Heart Institute
Atrial Cardiomyopathy:
is it an evolving clinical reality?
YES!
Review of main aspects of atrial cardiomyopathy
Significance for stroke risk:
— Risk prediction
— Therapeutic decision making
New pathophysiological concepts
Outline
Review of main aspects of atrial cardiomyopathy
Significance for stroke risk:
— Risk prediction
— Therapeutic decision making
New pathophysiological concepts
Outline
Consensus document 2016
Published simultaneously in Europace, Heart Rhythm and Journal of Arrhythmia
Cardiac disease Risk factors
Systemic conditions Gene variants
Autonomic imbalance
Fibroblasts
Basic mechanisms leading to atrial
cardiomyopathy
AF
Angiotensin-dependent Angiotensin-independent
Cardiac disease Risk factors
Systemic conditions Gene variants
Autonomic imbalance
AF
Ion channel abnormities
Ca2+ handling abnormities
Fibrosis
Myofibroblasts
Collagen production
and secretion
AF
AF
Potential elements of a clinically relevant classification
of atrial cardiomyopathies
Atrial electrical dysfunction, AF
Atrial mechanical dysfunction
Procoagulant state
Atrial fibrosis
ATRIAL CARDIOMYOPATHY
Gene variants Risk factors Ventricular dysfunction Infiltrative disorders
Drug toxicity Valvular heart disease Endocrine abnormalities
1) Causal factors
c) LGE-MRI (fibrosis)
b) ECG indices
(PR; AF rate, amplitude)
a) Echo indices (LA size, contractility)
d) Biomarkers (VWF, coagulation markers)
Cardiac dysfunction
Stroke
Impaired QOL Testing for validity:
Quantifiable outcomes
2) Objective+
quantifiable
classification
measures
Therapeutic decision making
Review of main aspects of atrial cardiomyopathy
Significance for stroke risk:
— Risk prediction
— Therapeutic decision making
New pathophysiological concepts
Outline
Atrial Cardiomyopathy-
Useful concept or just another term to be forgotten?
To be of value, the term should add something to our practical
understanding and clinical management of AF cases: Evidence of value?
We predict stroke risk and decide on
anticoagulation not based on AF
characteristics, but based on factors
associated with atrial cardiomyopathy.
What is new in this area since my
last presentation here in 2017?
A LOT!
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2016
Looked at wide range of clinical and biomarker
factors as predictors of stroke in ARISTOTLE
database ( 14,701 pts) and validated the
predictors in STABILITY database (1,400 pts).
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2016
Looked at wide range of clinical and biomarker
factors as predictors of stroke in ARISTOTLE
database ( 14,701 pts) and validated the
predictors in STABILITY database (1,400 pts).
Factors included CHA2DS2-VaSc criteria, other
clinical features and a variety of biomarkers.
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2016
Looked at wide range of clinical and biomarker
factors as predictors of stroke in ARISTOTLE
database ( 14,701 pts) and validated the
predictors in STABILITY database (1,400 pts).
Factors included CHA2DS2-VaSc criteria, other
clinical features and a variety of biomarkers.
Two biomarkers proved quite significant, both
potentially cardiomyopathic indicators: NT-
proBNP and Troponin.
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2018
Each risk factor is assigned points based on
value.
Points are totaled up for each factors.
Total number of points predicts stroke risk.
For example take 64 y.o. man.
With no prior stroke/TIA, an NT-BNP of 1480
and TnT of 4.2.
Risk points would be 0 (no stroke/TIA)
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2018
Each risk factor is assigned points based on
value.
Points are totaled up for each factors.
Total number of points predicts stroke risk.
For example take 64 y.o. man.
With no prior stroke/TIA, an NT-BNP of 1480
and TnT of 4.2.
Risk points would be 0 (no stroke/TIA) + 1.2
(age 64)
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2018
Each risk factor is assigned points based on
value.
Points are totaled up for each factors.
Total number of points predicts stroke risk.
For example take 64 y.o. man.
With no prior stroke/TIA, an NT-BNP of 1480
and TnI of 4.2.
Risk points would be 0 (no stroke/TIA) + 1.2
(age 64) +1.4 (Troponin I of 4.2)
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2018
Each risk factor is assigned points based on
value.
Points are totaled up for each factors.
Total number of points predicts stroke risk.
For example take 64 y.o. man.
With no prior stroke/TIA, an NT-BNP of 1480
and TnI of 4.2.
Risk points would be 0 (no stroke/TIA) +
1.25 (age 64) +1.5 (Troponin I of 4.2) + 7.5
(NT-BNP of 1480)
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2016
Each risk factor is assigned points based on
value.
Points are totaled up for each factors.
Total number of points predicts stroke risk.
For example take 64 y.o. man.
With no prior stroke/TIA, an NT-BNP of 1480
and TnI of 4.2.
Risk points would be 0 (no stroke/TIA) +
1.25 (age 64) +1.5 (Troponin I of 4.2) + 7.5
(NT-BNP of 1480)=10.25 total risk points
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2016
Each risk factor is assigned points based on
value.
Points are totaled up for each factors.
Total number of points predicts stroke risk.
For example take 64 y.o. man.
With no prior stroke/TIA, an NT-BNP of 1480
and TnI of 4.2.
Risk points would be 0 (no stroke/TIA) +
1.25 (age 64) +1.5 (Troponin I of 4.2) + 7.5
(NT-BNP of 1480)=10.25 10.25 total risk
points
This gives a 1-year stroke/systemic
embolism risk of just over 1% and a 3-year
risk of 2.5%
Note that in this calculation, troponin and especially NT-BNP
have great weight, more than age and prior stroke/TIA
Stroke Risk Determination in AF patients: The ABC
(Age, Biomarkers, Clinical History) Score
Hijazi Z et al, EHJ 2016
Thus, with only 2 clinical (age, prior stroke/TIA) and 2 biomarker criteria,
ABC score is at least as predictive as CHA2DS2-VaSC
The biomarkers used (proNT-BNP and troponin) are atrial cardiomyopathic indices
The biomarkers have very strong weight in the model, supporting the importance of
atrial cardiomyopathy in stroke risk
Review of main aspects of atrial cardiomyopathy
Significance for stroke risk:
— Risk prediction
— Therapeutic decision making
New pathophysiological concepts
Outline
Atrial Cardiomyopathy- Stroke Risk Time of stroke
AF episodes
Martin DT et al, EHJ 2015
No clear relationship between timing of AF and stroke
6 months pre-stroke
No AF episodes pre-stroke
Could AF-associated stroke risk be a function of associated
atrial cardiomyopathy and not AF itself?
Atrial Cardiomyopathy and Stroke Prevention: ARCADIA Trial
Int J Stroke 2019
This study should tell us whether atrial cardiomyopathy can be a
significant factor in stroke even in patients with sinus rhythm
Review of main aspects of atrial cardiomyopathy
Significance for stroke risk:
— Risk prediction
— Therapeutic decision making
New pathophysiological concepts
Outline
AF risk in CAD patients:
Biomarker evidence of inflammatory signaling
Nortamo S et al, Int J Cardiol 2017
In ARTEMIS, a prospective Japanese study of 1946 CAD patients, 143 (8.4%) developed new-onset AF .
The authors performed multivariate analysis to define AF predictors among clinical and biomarker indices.
Significant predictors were age (p=.004), weight (p=.045), LAD (p=.001), asthma/COPD meds (p=0.001), lack of
cholesterol meds (p=.008), soluble ST2 (sST2) blood level (p=.006) and CRP
CRP is a well-known inflammatory marker
sST2 binds to the anti-inflammatory interleukin IL-33 and reduces its anti-
inflammatory action; sST2 promotes inflammation and apoptosis
Thus, biomarkers support the idea of an inflammatory atrial cardiomyopathy
as a precursor to AF
Role of cardiomyocyte inflammatory signaling in
AF pathophysiology
Yao C et al, Circulation 2018
The NLRP3 inflammasome is a well known inflammatory protein signaling complex in macrophages
NLRP3 acts via a downstream protein ASC to release active caspase-1, which releases the
inflammatory mediator IL-1β from pro-IL-1β.
This study looked at CARDIOMYOCYTE NLRP3 changes in AF patients and animal models
The NLRP3 inflammasome is activated in
atrial cardiomyocytes from subjects with
clinical and experimental AF
CM-specific overexpression of NLRP3 in
mice causes spontaneous and inducible AF
CM NLRP3 O/E mice
Role of cardiomyocyte inflammatory signaling in
AF pathophysiology
Yao C et al, Circulation 2018
NLRP3 cardiomyocyte overexpression
causes atrial structural remodeling
NLRP3 activation causes chronic cardiomyocyte
inflammatory signaling in AF patients that may
be central to AF pathophysiology
Conclusions
Atrial cardiomyopathy is an evolving concept
Conclusions
Atrial cardiomyopathy is an evolving concept
There is evidence that consideration of atrial cardiomyopathy may add value to risk estimation
Conclusions
Atrial cardiomyopathy is an evolving concept
There is evidence that consideration of atrial cardiomyopathy may add value to risk estimation
Atrial inflammatory signaling may play an important role in leading to atrial cardiomyopathy and AF
Conclusions
Atrial cardiomyopathy is an evolving concept
There is evidence that consideration of atrial cardiomyopathy may add value to patient management
Atrial inflammatory signaling may play an important role in leading to atrial cardiomyopathy and AF
Consideration of the concept of atrial cardiomyopathy may lead to improved risk prediction, therapeutic guidance, pathophysiological understanding and therapeutic innovation
Thank you!..Grazie!