HLC 1820 No. of Pages 7
Heart, Lung and Circulation (2015) xx, 1–7 1443-9506/04/$36.00 http://dx.doi.org/10.1016/j.hlc.2015.03.001
ORIGINAL ARTICLE
Utility of CMR Markers of Myocardial Injury in Predicting LV Functional Recovery: Results from PROTECTION AMI CMR sub-study Suchi Grover a,b,c*, Gregory Bell d, Michael Lincoff e, Lucas Jeorg a, Per Lav Madsen a, Saling Huang d, Sean Leow a,c, Gemma Figtree f, Adhiraj Chakrabarty a,c, Darryl P. Leong a,g, Richard J. Woodman h, Joseph B. Selvanayagam a,b,c a
Flinders University, Adelaide, SA, Australia Cardiology Department, Flinders Medical Centre, Adelaide, SA Austrlaia c Cardiac Imaging Research Centre, South Australian Health and Medical Research Institute, Adelaide, SA, Australia d KAI Pharmaceuticals Inc, San Francisco, CAL, USA e Cleveland Clinic, Coordinating Center for Clinical Research (C5 Research), Cleveland, OH, USA f Cardiology Department, Royal North Shore Hospital, Sydney, NSW, Australia g Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada h Flinders Centre for Epidemiology and Biostatistics, Flinders University, Adelaide, SA, Australia b
Received 12 January 2015; received in revised form 2 March 2015; accepted 5 March 2015; online published-ahead-of-print xxx
Background
Adverse left ventricular (LV) remodelling following acute ST-segment elevation myocardial infarction (STEMI) has prognostic importance. We aimed to predict 90-day left ventricular (LV) function following acute STEMI using variables from clinical presentation, biomarkers, and cardiovascular magnetic resonance imaging (CMR).
Methods
Consecutive patients undergoing primary percutaneous coronary intervention for anterior STEMI as part of the Selective Inhibition of Delta-protein Kinase C for the Reduction of Infarct Size in Acute Myocardial Infarction (PROTECTION-AMI) trial were enrolled into the CMR sub-study at selected sites. CMR was performed at baseline (days 3 to 5) and 90 days and used to evaluate infarct size, myocardial salvage index, infarct heterogeneity, microvascular obstruction and global LV function. Biochemical markers including creatinine kinase area under the curve (CK AUC), peak CK, peak CK-myocardial band (CK-MB) and AUC, and troponin I were collected at specific time-points.
Results
Ninety-six patients were enrolled in the CMR sub study and 85 completed the 90-day follow-up, across 24 centres worldwide. LV ejection fraction (EF) was 56% (46-63%) at baseline and 60% (49-67%) at 90 days (p2 standard deviation (SD) greater than that of remote myocardium by semiautomatic software detection on T2 W images and quantified as a percentage of total
Please cite this article in press as: Grover S, et al. Utility of CMR Markers of Myocardial Injury in Predicting LV Functional Recovery: Results from PROTECTION AMI CMR sub-study. Heart, Lung and Circulation (2015), http://dx.doi.org/10.1016/ j.hlc.2015.03.001
HLC 1820 No. of Pages 7
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Utility of CMR Markers of Myocardial Injury in Predicting LV Functional Recovery
myocardium on matched slices [4]. Using LGE images, hyperenhanced pixels were defined as those with image intensities >5SD above the mean of image intensities in a remote myocardial region in the same image. A further region of infarct was quantified with image intensity as >2SD greater than remote myocardium. This was defined as the infarct at periphery with 5SD infarct size used to quantify the core infarct region. Infarct heterogeneity was defined as the region of difference between the periphery infarct (2SD infarct size) and the core infarct (5SD infarct size)[10]. Microvascular obstruction was visualised using LGE images and quantified by manual planimetry of hypoenhanced region surrounded by LGE in each short axis slice [11]. Myocardial Salvage was calculated as the difference between reversible myocardial injury (using T2W images to identify oedematous myocardium) and irreversible
myocardial injury (as defined by 5SD infarct size on LGE images) and calculated as a percentage [4].
Biochemical Parameters Cardiac enzymes (troponin, CK, CK-MB) and N-terminal Btype natriuretic peptide (NT-pro-BNP) were collected at prespecified timepoints and sent to a central laboratory for processing. Curve fitting was performed by a central laboratory (according to accepted methodologies to generate CK area under the curve (AUC) and estimated peak, CK-MB AUC and peak, and cardiac troponin I estimated peak and AUC [12].
Statistical Analysis Data for continuous variables are presented as medians (interquartile, IQ range), and categorical variables are
Table 1 Baseline characteristics. Variable
Overall trial
Sub-study cohort
P-value
Anterior cohort N
997
96
Demographic Age, years
6112
6312
0.12
Male sex, %
80
77
0.5
160, 16 110, 11
8, 8 7, 7
0.05 0.03
Clinical, (n,%) Prior coronary artery disease Prior MI Prior PCI
110, 11
4, 4
0.03
Prior congestive heart failure
10, 1
0, 0
1.0
History of Stroke
40, 4
2, 2
0.09
History of PVD
30, 3
1, 1
0.57
Diabetes –type I
10, 1
1, 1
0.17
Diabetes – type II
160, 16
8, 8
0.05
Hypertension Hypercholesterolaemia
459, 46 329, 33
40, 42 22, 23
0.45 0.05
Current Smokers
419, 42
37, 39
0.59
Time from symptom onset to PCI, mins
191 (143, 261)
170 (111,226)
ST segment AUC, mV/min
6830 (4898,9599)
5807 (4397,8380)
Systolic BP (mmHg)
13622
12919
< 0.01
Diastolic BP (mmHg)
8114
7610
< 0.01
BMI (kg/m2) Killip class, (n,%)
27 (24,30)
27 (24,30)
1
907, 91
88, 92
2
70, 7
8, 8
3
10, 1
0, 0
4
0, 0
0, 0
Presentation
0.82
Adverse Events Death (n,%)
30, 3
3, 3
1.0
Congestive Heart failure (n, %) Arrhythmia (n, %)
90, 9 25, 3
8, 8 1, 1
1.0 0.7
Cardiogenic Shock (n, %)
30, 3
1, 1
0.5
Values are expressed as meansd or median (IQR). MI – myocardial infarction; PCI – percutaneous coronary intervention; PVD – peripheral vascular disease; BP – blood pressure; BMI – body mass index.
Please cite this article in press as: Grover S, et al. Utility of CMR Markers of Myocardial Injury in Predicting LV Functional Recovery: Results from PROTECTION AMI CMR sub-study. Heart, Lung and Circulation (2015), http://dx.doi.org/10.1016/ j.hlc.2015.03.001
HLC 1820 No. of Pages 7
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S. Grover et al.
in the CMR sub-study were similar in age, gender, Killip class, co-morbidities and time to treatment (Table 1).
presented as frequencies and percentages. Wilcoxon rank sum tests were used to evaluate differences in continuous variables between the entire study cohort (n=997) and those patients selected for the sub-study (n=96). Chi-squared tests of independence were used to test for associations between groups for categorical variables. We evaluated the relationship between LVEF and baseline markers of myocardial damage (CMR derived infarct size, myocardial salvage, microvascular obstruction and infarct heterogeneity; and biochemical markers including troponin I, CK, CK-MB using both univariate correlational analysis and multivariate linear regression). We checked all variables for normality and log-transformed variables when necessary. All model residuals were also assessed for normality. We compared models using Akaike’s and Schwarz’s Bayesian information criteria (AIC and BIC respectively) and chose the model with the largest AIC and BIC. All statistical tests were two-sided, and a p-value
Heart, Lung and Circulation (2015) xx, 1–7 1443-9506/04/$36.00 http://dx.doi.org/10.1016/j.hlc.2015.03.001
ORIGINAL ARTICLE
Utility of CMR Markers of Myocardial Injury in Predicting LV Functional Recovery: Results from PROTECTION AMI CMR sub-study Suchi Grover a,b,c*, Gregory Bell d, Michael Lincoff e, Lucas Jeorg a, Per Lav Madsen a, Saling Huang d, Sean Leow a,c, Gemma Figtree f, Adhiraj Chakrabarty a,c, Darryl P. Leong a,g, Richard J. Woodman h, Joseph B. Selvanayagam a,b,c a
Flinders University, Adelaide, SA, Australia Cardiology Department, Flinders Medical Centre, Adelaide, SA Austrlaia c Cardiac Imaging Research Centre, South Australian Health and Medical Research Institute, Adelaide, SA, Australia d KAI Pharmaceuticals Inc, San Francisco, CAL, USA e Cleveland Clinic, Coordinating Center for Clinical Research (C5 Research), Cleveland, OH, USA f Cardiology Department, Royal North Shore Hospital, Sydney, NSW, Australia g Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada h Flinders Centre for Epidemiology and Biostatistics, Flinders University, Adelaide, SA, Australia b
Received 12 January 2015; received in revised form 2 March 2015; accepted 5 March 2015; online published-ahead-of-print xxx
Background
Adverse left ventricular (LV) remodelling following acute ST-segment elevation myocardial infarction (STEMI) has prognostic importance. We aimed to predict 90-day left ventricular (LV) function following acute STEMI using variables from clinical presentation, biomarkers, and cardiovascular magnetic resonance imaging (CMR).
Methods
Consecutive patients undergoing primary percutaneous coronary intervention for anterior STEMI as part of the Selective Inhibition of Delta-protein Kinase C for the Reduction of Infarct Size in Acute Myocardial Infarction (PROTECTION-AMI) trial were enrolled into the CMR sub-study at selected sites. CMR was performed at baseline (days 3 to 5) and 90 days and used to evaluate infarct size, myocardial salvage index, infarct heterogeneity, microvascular obstruction and global LV function. Biochemical markers including creatinine kinase area under the curve (CK AUC), peak CK, peak CK-myocardial band (CK-MB) and AUC, and troponin I were collected at specific time-points.
Results
Ninety-six patients were enrolled in the CMR sub study and 85 completed the 90-day follow-up, across 24 centres worldwide. LV ejection fraction (EF) was 56% (46-63%) at baseline and 60% (49-67%) at 90 days (p2 standard deviation (SD) greater than that of remote myocardium by semiautomatic software detection on T2 W images and quantified as a percentage of total
Please cite this article in press as: Grover S, et al. Utility of CMR Markers of Myocardial Injury in Predicting LV Functional Recovery: Results from PROTECTION AMI CMR sub-study. Heart, Lung and Circulation (2015), http://dx.doi.org/10.1016/ j.hlc.2015.03.001
HLC 1820 No. of Pages 7
3
Utility of CMR Markers of Myocardial Injury in Predicting LV Functional Recovery
myocardium on matched slices [4]. Using LGE images, hyperenhanced pixels were defined as those with image intensities >5SD above the mean of image intensities in a remote myocardial region in the same image. A further region of infarct was quantified with image intensity as >2SD greater than remote myocardium. This was defined as the infarct at periphery with 5SD infarct size used to quantify the core infarct region. Infarct heterogeneity was defined as the region of difference between the periphery infarct (2SD infarct size) and the core infarct (5SD infarct size)[10]. Microvascular obstruction was visualised using LGE images and quantified by manual planimetry of hypoenhanced region surrounded by LGE in each short axis slice [11]. Myocardial Salvage was calculated as the difference between reversible myocardial injury (using T2W images to identify oedematous myocardium) and irreversible
myocardial injury (as defined by 5SD infarct size on LGE images) and calculated as a percentage [4].
Biochemical Parameters Cardiac enzymes (troponin, CK, CK-MB) and N-terminal Btype natriuretic peptide (NT-pro-BNP) were collected at prespecified timepoints and sent to a central laboratory for processing. Curve fitting was performed by a central laboratory (according to accepted methodologies to generate CK area under the curve (AUC) and estimated peak, CK-MB AUC and peak, and cardiac troponin I estimated peak and AUC [12].
Statistical Analysis Data for continuous variables are presented as medians (interquartile, IQ range), and categorical variables are
Table 1 Baseline characteristics. Variable
Overall trial
Sub-study cohort
P-value
Anterior cohort N
997
96
Demographic Age, years
6112
6312
0.12
Male sex, %
80
77
0.5
160, 16 110, 11
8, 8 7, 7
0.05 0.03
Clinical, (n,%) Prior coronary artery disease Prior MI Prior PCI
110, 11
4, 4
0.03
Prior congestive heart failure
10, 1
0, 0
1.0
History of Stroke
40, 4
2, 2
0.09
History of PVD
30, 3
1, 1
0.57
Diabetes –type I
10, 1
1, 1
0.17
Diabetes – type II
160, 16
8, 8
0.05
Hypertension Hypercholesterolaemia
459, 46 329, 33
40, 42 22, 23
0.45 0.05
Current Smokers
419, 42
37, 39
0.59
Time from symptom onset to PCI, mins
191 (143, 261)
170 (111,226)
ST segment AUC, mV/min
6830 (4898,9599)
5807 (4397,8380)
Systolic BP (mmHg)
13622
12919
< 0.01
Diastolic BP (mmHg)
8114
7610
< 0.01
BMI (kg/m2) Killip class, (n,%)
27 (24,30)
27 (24,30)
1
907, 91
88, 92
2
70, 7
8, 8
3
10, 1
0, 0
4
0, 0
0, 0
Presentation
0.82
Adverse Events Death (n,%)
30, 3
3, 3
1.0
Congestive Heart failure (n, %) Arrhythmia (n, %)
90, 9 25, 3
8, 8 1, 1
1.0 0.7
Cardiogenic Shock (n, %)
30, 3
1, 1
0.5
Values are expressed as meansd or median (IQR). MI – myocardial infarction; PCI – percutaneous coronary intervention; PVD – peripheral vascular disease; BP – blood pressure; BMI – body mass index.
Please cite this article in press as: Grover S, et al. Utility of CMR Markers of Myocardial Injury in Predicting LV Functional Recovery: Results from PROTECTION AMI CMR sub-study. Heart, Lung and Circulation (2015), http://dx.doi.org/10.1016/ j.hlc.2015.03.001
HLC 1820 No. of Pages 7
4
S. Grover et al.
in the CMR sub-study were similar in age, gender, Killip class, co-morbidities and time to treatment (Table 1).
presented as frequencies and percentages. Wilcoxon rank sum tests were used to evaluate differences in continuous variables between the entire study cohort (n=997) and those patients selected for the sub-study (n=96). Chi-squared tests of independence were used to test for associations between groups for categorical variables. We evaluated the relationship between LVEF and baseline markers of myocardial damage (CMR derived infarct size, myocardial salvage, microvascular obstruction and infarct heterogeneity; and biochemical markers including troponin I, CK, CK-MB using both univariate correlational analysis and multivariate linear regression). We checked all variables for normality and log-transformed variables when necessary. All model residuals were also assessed for normality. We compared models using Akaike’s and Schwarz’s Bayesian information criteria (AIC and BIC respectively) and chose the model with the largest AIC and BIC. All statistical tests were two-sided, and a p-value
