Previous studies have shown that patients with normal vasodilator myocardial perfusion imaging (MPI) findings remain at a greater risk of future cardiac events than patients with normal exercise MPI findings. The aim was to assess improvement in risk classification provided by the heart rate response (HRR) in patients with normal vasodilator MPI findings when added to traditional risk stratification. We retrospectively studied 2,000 patients with normal regadenoson or adenosine MPI findings. Risk stratification was performed using Adult Treatment Panel III framework. Patients were stratified by HRR (percentage of increase from baseline) into tertiles specific to each vasodilator. All-cause mortality and cardiac death/nonfatal myocardial infarction (MI) ≤2 years from the index MPI were recorded. During follow-up, 11.8% patients died and 2.7% patients experienced cardiac death/nonfatal MI in the adenosine and regadenoson groups, respectively. The patients who died had a greater Framingham risk score (12 ± 4 vs 11 ± 4, p = 0.009) and lower HRR (22 ± 16 vs 32 ± 21, p <0.0001). In an adjusted Cox model, the lowest tertile HRR was associated with an increased risk of mortality (hazard ratio 2.1) and cardiac death/nonfatal MI (hazard ratio 2.9; p <0.01). Patients in the highest HRR tertile, irrespective of the Adult Treatment Panel III category, were at low risk. When added to the Adult Treatment Panel III categories, the HRR resulted in net reclassification improvement in mortality of 18% and cardiac death/nonfatal MI of 22%. In conclusion, a blunted HRR to vasodilator stress was independently associated with an increased risk of cardiac events and overall mortality in patients with normal vasodilator MPI findings. The HRR correctly reclassified a substantial proportion of these patients in addition to the traditional risk classification models and identified patients with normal vasodilator MPI findings, who had a truly low risk of events.
Traditional risk factors such as age, gender, blood pressure, smoking history, cholesterol, and diabetes mellitus have been shown to predict coronary heart disease risk and death in a number of studies. Global risk algorithms, such as the Framingham risk score, or its modification in the third report of the National Cholesterol Education Program’s Expert Panel on the Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel [ATP] III), encapsulate these risk factors to estimate the 10-year coronary heart disease event risk. Myocardial perfusion imaging (MPI) using adenosine or regadenoson is an established method for detecting coronary heart disease and for risk stratification of patients with exercise limitations. Compared to patients undergoing exercise testing, those referred for vasodilator-based MPI have a greater pretest probability of coronary heart disease and, therefore, have a slightly greater risk of cardiac death and myocardial infarction (MI) despite normal MPI findings (1% to 2%/year for vasodilator stress vs <1% for exercise). Furthermore, the prognostic value of functional status provided by the exercise portion of the test is not available. The best method for risk stratification in this population is not well established. We have recently shown that the heart rate response (HRR) to adenosine and regadenoson is an independent predictor of outcome, provides incremental prognostic information to clinical and imaging variables, and helps in better risk stratification. The present study examined whether the addition of HRR to adenosine or regadenoson to traditional risk stratification in patients with normal MPI findings improves risk stratification.
Methods
The study population included 2,000 patients who underwent vasodilator MPI at the University of Alabama at Birmingham: 1,000 consecutive patients with normal adenosine MPI findings and another 1,000 consecutive patients with normal regadenoson MPI findings (after our center switched completely from using adenosine to using regadenoson). For the purposes of the present retrospective study, normal MPI findings were defined as a normal perfusion pattern and normal left ventricular ejection fraction (LVEF) ≥50%. A total of 3,000 patients undergoing MPI were screened, patients with abnormal MPI findings (n = 617) or LVEF <50% (n = 383) were excluded. Using this database, we have previously shown that patients with normal regadenoson MPI findings experienced outcomes similar to those with normal adenosine MPI findings.
Patients selected for the present study underwent either adenosine or regadenoson MPI. Both agents were delivered using peripheral intravenous access. Adenosine was administered as a continuous infusion (140 μg/kg/min for 6 minutes), and regadenoson was administered as a single bolus of 0.4 mg, followed by a saline flush. Technetium-99m-sestamibi determined by the patient’s weight was injected at 3 minutes into the infusion of adenosine and 10 to 20 seconds after the saline flush following regadenoson administration, as previously described. All the studies were done in the absence of accompanying exercise. The heart rate and blood pressure were measured at baseline and every 2 minutes until the completion of the study. Medications (including β blockers) and caffeinated beverages were withheld on the morning of the stress portion of the study.
Gated single photon emission computed tomography images were acquired 1 hour after tracer injection using a dual-head detector gamma camera with a 20% energy window centered on the 140-keV gamma peak. Cameras were operated in an elliptical 180° acquisition orbit with 32 projections and 30 to 40 seconds per projection. Gating was done with 8 to 16 frames per RR cycle. Images were processed using filtered back projection. All MPI studies were interpreted visually, aided by automated quantitative analysis, by readers who were unaware of subsequent events and without attenuation or scatter correction. At rest images were obtained whenever uncertainty was present in the interpretation of the stress images, as previously described. The LVEF and end-diastolic and end-systolic volumes were measured from the stress gated images using the method previously described by Germano et al.
The variables abstracted from the patients’ medical records included patient demographics (age, gender, race); co-morbidities, including hypertension, hyperlipidemia, diabetes mellitus, stroke, previous MI, previous cardiovascular interventions, such as percutaneous coronary intervention or coronary artery bypass grafting; history of tobacco use; medication usage at MPI, and laboratory results (serum creatinine and lipid panel).
The estimated glomerular filtration rate was calculated according to the Modification of Diet in Renal Disease study formula. Patients were considered to have chronic kidney disease if their estimated glomerular filtration rate was 15 to 60 ml/min/1.73 m 2 . Patients were considered to have end-stage renal disease if their estimated glomerular filtration rate was <15 mL/min/1.73 m 2 or if they were taking renal replacement therapy.
The HRR was calculated as the maximum percentage of change from baseline, as previously described. For each of the stress agents, patients were divided into 3 groups according to the HRR tertiles. The HRR tertiles for adenosine were defined as <16%, 16% to 32%, and >32%. The corresponding tertiles for regadenoson were <21%, 21% to 37%, and >37%.
The primary outcome of interest was defined as all-cause mortality and was determined using the Social Security Death Index (assessed on July 31, 2011). The secondary outcome was a composite of cardiac death and nonfatal MI (as documented by the appropriate combination of symptoms, electrocardiographic findings, and enzyme changes). Cardiac death was defined as death from fatal arrhythmia, MI, or heart failure and was determined by reviewing the electronic medical records and death certificates. All events were censored at 2 years after the index MPI study. The interval to an event was defined as the duration from the baseline MPI study to death, cardiac death/nonfatal MI, or the end of 2 years of follow-up.
All statistical analyses were performed using the Statistical Package for Social Sciences, version 18, for Windows (SPSS, Chicago, Illinois). Student’s t test and the Mann-Whitney U test were used to compare continuous variables and the chi-square test or Fischer’s exact test to compare categorical variables, as appropriate. The Framingham risk score for the 10-year risk of hard coronary heart disease events were calculated using age, gender, total cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, active treatment of hypertension, and smoking status. Patients were then stratified into risk groups according to the calculated Framingham risk score (low, <10%; intermediate, 10% to 20%; and high, >20%). Patients with pre-existing diabetes mellitus or vascular disease at baseline were assigned to the high-risk group, irrespective of calculated Framingham risk score according to ATP III. Patients were additionally substratified within ATP III categories according to the HRR tertile. Cox proportional hazards models were then used to calculate the hazard ratios and corresponding 95% confidence intervals for the primary and secondary end points in relation to HRR tertiles. The variables entered in the model were age, gender, ATP III category, and LVEF. Variables with co-linearity were entered into the model 1 at a time. Stepwise forward selection was used to create the final model.
The incremental effect of adding HRR to the ATP III categorization for predicting outcomes was evaluated using the net reclassification improvement. After risk categorization according to the ATP III guidelines, patients in the lowest HRR tertile (i.e., blunted HRR) were reclassified up 1 risk category, to a maximum of high risk. Patients in the middle HRR tertile were not reclassified. Finally, patients in the highest HRR tertile were reclassified down 1 risk category, to a minimum of low risk. The goal was to determine whether reclassification would assign patients who developed events to a higher risk category and those who did not to a lower risk category. The statistical significance of the net reclassification improvement was assessed, as described by Pencina et al.
The institutional review board for human research at the University of Alabama at Birmingham approved the present study.
Results
The baseline characteristics ( Table 1 ), medication use ( Table 2 ), hemodynamic parameters ( Table 3 ), and laboratory results ( Table 4 ) of the patients are presented grouped by stress agent. The cohort consisted of 2,000 patients with a mean age of 59 ± 12 years and an LVEF of 67 ± 10%; 45% were men, 64% were white, 37% had diabetes mellitus, 24% had a history of cardiovascular disease, 26% end-stage renal disease, and 18% were active smokers.
| Characteristic | Alive (n = 1,764) | Dead (n = 236) |
|---|---|---|
| Age (yrs) | 58.99 ± 12.24 ∗ | 62.71 ± 11.52 ∗ |
| Men | 778 (44.1%) † | 122 (51.7%) † |
| Race | ||
| White | 1,108 (62.8%) | 162 (68.6%) |
| Black | 626 (35.5%) | 70 (29.7%) |
| Other | 30 (1.7%) | 4 (1.7%) |
| Hypertension | 1,397 (79.2%) ∗ | 162 (68.6%) ∗ |
| Hyperlipidemia | 883 (50.1%) ∗ | 76 (32.2%) ∗ |
| Diabetes mellitus | 654 (37.1%) | 82 (34.7%) |
| Chronic kidney disease | 459 (26.0%) | 74 (31.4%) |
| End-stage renal disease | 452 (25.6%) | 60 (25.4%) |
| Congestive heart failure | 115 (6.5%) | 19 (8.1%) |
| Peripheral vascular/cerebrovascular disease | 300 (17.0%) | 42 (17.8%) |
| Previous myocardial infarction | 116 (6.6%) | 17 (7.2%) |
| Previous coronary intervention | 214 (12.1%) † | 17 (7.2%) † |
| Previous bypass surgery | 115 (6.5%) | 16 (6.8%) |
| Framingham risk score | 11.26 ± 4.20 † | 11.97 ± 3.70 † |
| Former smoker | 454 (25.7%) † | 84 (35.6%) † |
| Current smoker | 316 (17.9%) | 46 (19.5%) |
| In-patient stress test | 378 (21.4%) | 51 (21.6%) |
| Medication | Alive (n = 1,764) | Dead (n = 236) |
|---|---|---|
| Aspirin | 704 (39.9%) ∗ | 62 (26.3%) ∗ |
| Plavix | 204 (11.6%) † | 15 (6.4%) † |
| β Blockers | 839 (47.6%) † | 88 (37.3%) † |
| Angiotensin-converting enzyme inhibitors/receptor blockers | 850 (48.2%) ∗ | 82 (34.7%) ∗ |
| Calcium channel blockers | 518 (29.4%) | 58 (24.6%) |
| Other antihypertensives | 288 (16.3%) | 36 (15.3%) |
| Thiazide diuretics | 406 (23.0%) † | 34 (14.4%) † |
| Loop diuretics | 392 (22.2%) | 64 (27.1%) |
| Potassium-sparing diuretics | 146 (8.3%) † | 35 (14.8%) † |
| Statins | 732 (41.5%) ∗ | 56 (23.7%) ∗ |
| Insulin | 295 (16.7%) | 41 (17.4%) |
| Metformin | 190 (10.8%) † | 13 (5.5%) † |
| Sulfonylureas | 187 (10.6%) | 18 (7.6%) |
| Glitazones | 84 (4.8%) † | 4 (1.7%) † |
| Parameter | Alive (n = 1,764) | Dead (n = 236) |
|---|---|---|
| Heart rate at rest (beats/min) | 71.37 ± 13.00 ∗ | 75.79 ± 15.15 ∗ |
| Systolic blood pressure at rest (mm Hg) | 132.38 ± 21.54 ∗ | 128.27 ± 21.70 ∗ |
| Diastolic blood pressure at rest (mm Hg) | 75.07 ± 11.26 ∗ | 71.82 ± 11.11 ∗ |
| Heart rate response | 31.91 ± 20.79 ∗ | 21.62 ± 15.95 ∗ |
| Left ventricular ejection fraction (%) | 66.88 ± 9.45 | 67.25 ± 9.80 |
| Alive (n = 1,207) | Dead (n = 111) | |
|---|---|---|
| Total cholesterol (mg/dl) | 177.47 ± 49.99 ∗ | 166.74 ± 44.06 ∗ |
| High-density lipoprotein (mg/dl) | 46.01 ± 18.94 | 47.62 ± 34.05 |
| Low-density lipoprotein (mg/dl) | 103.62 ± 39.31 † | 95.74 ± 38.67 † |
| Triglycerides (mg/dl) | 157.25 ± 116.32 | 159.01 ± 107.31 |
| Serum creatinine (mg/dl) ‡ | 1.18 ± 0.72 | 1.19 ± 0.54 |
| Estimated glomerular filtration rate (ml/min/1.73 m 2 ) | 59.22 ± 36.38 | 56.03 ± 36.29 |
∗ p <0.001 for patients who had died versus those alive at 2 yrs after MPI within same category.
† p <0.05 for patients who had died versus those alive at 2 yrs after MPI within same category.
‡ Serum creatinine and estimated glomerular filtration rate values were averaged for patients without end-stage renal disease and not requiring dialysis.
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