| Literature DB >> 32394403 |
William E Moody1, Benjamin Holloway2, Parthiban Arumugam3, Sharon Gill2, Yasmin S Wahid2, Chris M Boivin2, Louise E Thomson4, Daniel S Berman4, Matthew J Armstrong5,6, James Ferguson5,6, Richard P Steeds2.
Abstract
BACKGROUND: Although consensus-based guidelines support noninvasive stress testing prior to orthotopic liver transplantation (OLT), the optimal screening strategy for assessment of coronary artery disease in patients with end-stage liver disease (ESLD) is unclear. This study sought to determine the relative predictive value of coronary risk factors, functional capacity, and single photon emission computed tomography (SPECT) on major adverse cardiovascular events and all-cause mortality in liver transplantation candidates.Entities:
Keywords: SPECT; diagnostic and prognostic application; exercise testing; outcomes research; vasodilators
Mesh:
Year: 2020 PMID: 32394403 PMCID: PMC8709822 DOI: 10.1007/s12350-020-02126-z
Source DB: PubMed Journal: J Nucl Cardiol ISSN: 1071-3581 Impact factor: 5.952
Figure 1Study consort diagram. Abbreviations: OLT, orthotopic liver transplantation; PCI, percutaneous coronary intervention; CABG, coronary artery bypass graft surgery
Baseline demographics and clinical characteristics for study cohort
| Variable | N = 158 |
|---|---|
| Age (years) | 56.6 ± 8.9 |
| Male sex | 110 (70%) |
| Ethnicity | |
| White | 135 (85%) |
| Asian | 20 (13%) |
| Afro-Caribbean | 1 (1%) |
| Other | 2 (1%) |
| Body mass index (kg/m2) | 29.9 ± 6.1 |
| Etiology of end-stage liver disease | |
| Alcohol | 36 (23%) |
| Hepatitis B | 1 (1%) |
| Hepatitis C | 21 (17%) |
| Nonalcoholic steatohepatitis | 29 (19%) |
| Primary biliary cirrhosis | 10 (6%) |
| Cryptogenic | 2 (1%) |
| Autoimmune | 2 (1%) |
| Alpha-1-antitrypsin deficiency | 2 (1%) |
| Other | 35 (29%) |
| MELD score | 16 ± 6 |
| Cardiac risk factors | |
| Diabetesa | 79 (50%) |
| Hypertension | 17 (11%) |
| Hypercholesterolemia | 42 (27%) |
| Current smoker | 28 (18%) |
| Family history of CAD | 2 (1%) |
| Number of cardiac risk factors | 1.7 ± 1.0 |
| Symptomatic chest pain | 2 (1%) |
| Typical angina/atypical or noncardiac | 1 (1%)/1 (1%) |
| History of revascularization (PCI or CABG) | 5 (3%) |
| History of myocardial infarction | 5 (3%) |
| Medications | |
| Aspirin | 17 (11%) |
| Beta-blocker | 77 (49%) |
| ACE inhibitor/angiotensin receptor blocker | 15 (9%) |
| Calcium channel blocker | 2 (1%) |
| Loop diuretic | 40 (25%) |
| Mineralocorticoid receptor antagonist | 50 (32%) |
| Statin | 35 (22%) |
| Insulin | 77 (49%) |
| Hemoglobin (g/L) | 117 (105−129) |
| Total cholesterol (mg/dL) | 157 ± 54 |
| INR | 1.36 ± 0.33 |
| Creatinine (mg/dL) | 0.90 (0.75−1.15) |
Data are number (%), mean ± SD or median (IQR)
aOn Insulin or oral hypoglycemic therapy
ACE, angiotensin converting enzyme; CABG, coronary artery bypass graft surgery; CAD, coronary artery disease; IQR, interquartile range; PCI, percutaneous coronary intervention
Functional assessment and imaging characteristics for study cohort
| Variable | N = 158 |
|---|---|
| Exercise treadmill stress | 77 (49%) |
| METs achieveda | 6.3 ± 2.4 |
| Peak VO2 achieved (ml/kg/min)a | 22.2 ± 8.4 |
| Positive/indeterminate/negativea | 2 (3%) / 13 (17%) / 61 (80%) |
| LV ejection fraction, % | 60.9 ± 9.7 |
| Abnormal SPECTb | 32 (20%) |
| Summed stress score ≥ 9 | 9 (6%) |
| Total PDS ≥ 15% | 9 (6%) |
| Ischemic PDS ≥ 10% | 6 (4%) |
| CACS, Agatston units (IQR)c | 11 (0–119) |
Data are number (%), mean ± SD or median (IQR)
aIn the 77 patients that were capable of exercise treadmill exercise stress
bDefined as summed stress score of 4 or more
cIn the 84 patients for whom data were available
CACS, coronary artery calcium score; LV, left ventricular; METs, metabolic equivalents; PDS, perfusion defect size; SPECT, single photon emission computed tomography; VO2, oxygen uptake
Baseline demographics, clinical characteristics, and stress test differences by SPECT results (N = 158)
| Variable | Normal perfusion (N = 126) | Abnormal perfusion (N = 32) | Total PDS <15% (N = 23) | Total PDS ≥15% (N = 9) | ||
|---|---|---|---|---|---|---|
| Age | 56.5 ± 7.9 | 56.9 ± 8.3 | 0.78 | 57.5 ± 9.1 | 55.0 ± 6.0 | 0.16 |
| Male | 84 (67%) | 26 (81%) | 0.10 | 19 (83%) | 7 (78%) | 0.43 |
| Cardiac risk factors | ||||||
| Diabetes | 63 (50%) | 16 (50%) | 0.51 | 13 (57%) | 3 (33%) | 0.19 |
| Hypertension | 15 (12%) | 2 (6%) | 0.33 | 2 (9%) | 0 (0%) | 0.46 |
| Hypercholesterolemia | 27 (21%) | 15 (47%) | 0.26 | 10 (44%) | 5 (56%) | 0.02 |
| Smoking history | 27 (21%) | 7 (22%) | 0.75 | 5 (22%) | 2 (22%) | 0.92 |
| Able to perform exercise stress | 61 (48%) | 16 (50%) | 0.81 | 11 (48%) | 5 (56%) | 0.89 |
| METsc | 6.6 ± 2.5 | 5.5 ± 1.6 | 0.15 | 5.1 ± 1.1 | 7.4 ± 2.8 | 0.12 |
| LV ejection fraction, % | 62.2 ± 9.7 | 55.5 ± 8.2 | 0.01 | 56.6 ± 7.1 | 54.4 ± 9.8 | 0.02 |
| CACS, Agatston units (IQR)d | 7 (0–113) | 38 (11–260) | 0.09 | 48 (11–419) | 11 (1–36) | 0.52 |
Data are N (%), mean ± SD or median (interquartile range)
CACS, coronary artery calcium score; METs, metabolic equivalents; PDS, perfusion defect size; LV, left ventricular
aNormal perfusion versus abnormal perfusion
bNormal SPECT versus total PDS <15% versus total PDS ≥15%. The Kruskal-Wallis analysis of variance was used to identify significant differences in central tendencies of continuously scaled variables between groups. Contingency table analysis was performed using Chi-square or Fisher’s exact tests where appropriate
cIn the 77 subjects capable of treadmill exercise
dCoronary artery calcium scoring was performed in 84 patients without a known history of myocardial infarction or revascularization and with resting heart rates < 80 bpm. The numbers of patients per subgroup were as follows: normal perfusion (n = 60), abnormal perfusion (n = 24); total PDS <15% (n = 20); total PDS ≥15% (n = 4)
Figure 2Relation between CACS severity and stress SPECT results (n = 84). The percentage of subjects with a normal SPECT result was highest in those with minimal CACS (P < 0.001). A 4 × 2 contingency analysis was performed using a two-tailed Fisher’s exact test to determine significance
Follow-up (N = 158)
| Mortality, all-cause | 50 (32%) |
|---|---|
| Cardiovascular | 11 |
| Infection | 10 |
| Bleeding | 2 |
| Malignancy | 17 |
| Multi-organ/renal failure | 3 |
| Recurrent liver disease | 6 |
| Other | 1 |
Values are N (%) or N
aLate revascularization > 90 days after the SPECT/CT imaging
Figure 3Kaplan–Meier curve for unadjusted cumulative survival from (A) cardiovascular death and (B) all-cause death according to perfusion dichotomized by a summed stress score ≥ 4. Two-sided generalized Wilcoxon tests were used to determine significance
Figure 4Kaplan–Meier curve for unadjusted cumulative survival from (A) cardiovascular death and (B) all-cause death according to functional capacity dichotomized by estimated METs ≤ 4. Two-sided generalized Wilcoxon tests were used to determine significance
Figure 5Kaplan–Meier curve for unadjusted cumulative survival from (A) cardiovascular death and (B) all-cause death according to integrated results of SPECT and exercise capacity. Two-sided generalized Wilcoxon tests were used to determine significance
Figure 6Annualized event rates for (A) cardiovascular death and (B) all-cause death according to integrated results of SPECT and exercise capacity. (A) For each subgroup (number of CV deaths/number of patients): METs ≥ 4, normal perfusion (1/59); METs <4, normal perfusion (4/67); METs ≥ 4, abnormal perfusion (2/15); METS <4, abnormal perfusion (4/17). (B) For each subgroup (number of all-cause deaths / number of patients): METs ≥ 4, normal perfusion (15/60); METs <4, normal perfusion (26/66); METs ≥ 4, abnormal perfusion (2/15); METS <4, abnormal perfusion (7/17)
Figure 7Incremental predictive value of exercise capacity and stress SPECT results over clinical information to predict cardiovascular death. The clinical data entered into the global Chi-square analysis model included age, sex, diabetes, smoking history. Abnormality on SPECT (defined as SSS ≥ 4) and exercise capacity (METs < 4) were entered as binary variables
Multivariate predictors of 5-year cardiovascular mortality
| Variable | Cardiovascular death | |
|---|---|---|
| HR (95% CI) | ||
| Age | 0.95 (0.88–1.04) | 0.272 |
| Gender (female) | 2.07 (0.56–7.64) | 0.276 |
| Diabetes | 1.39 (0.87–7.59) | 0.088 |
| Current smoker | 5.23 (1.07–25.46) | 0.041 |
| METs < 4 | 2.73 (0.60–12.54) | 0.196 |
| Abnormal perfusiona | 4.18 (1.43–12.27) | 0.019 |
All variables listed were simultaneously entered into a multivariate Cox regression model
METs, metabolic equivalents
aDefined as summed stress score ≥4