Abstract
Aims
Mitral annular calcification (MAC) increases the difficulty of mitral valve (MV) surgery and is associated with mortality. However, there is no standardized classification of MAC severity. A multi-parametric MAC score has been proposed using computed tomography. We evaluated the prognostic effect of MAC severity classification using the MAC score.
Methods and results
We included 331 patients with MAC who underwent MV surgery from 2011 through 2019. We calculated the MAC score based on five main components (range: 2–12): MAC Agatston calcium score, MAC angle, extension to left ventricular outflow tract, the involvement of trigones, and myocardial infiltration. According to the proposed MAC score, we classified the top tertile into the severe MAC group (scores: 9–12, n = 63) and the others into non-severe MAC group (scores: 2–8, n = 268). Propensity scores (PS) were estimated using seven clinical variables (age, sex, body mass index, hypertension, diabetes mellitus, heart failure, and chronic kidney disease), with severe MAC as the dependent variable. The median age was 74 years and 57.1% were female. During a median follow-up duration of 220 days, 47 patients (14.2%) died. After PS matching, there were 60 patients in each group. There were no significant differences in in-hospital mortality between the two groups, but patients with severe MAC had statistically significantly higher all-cause mortality compared to patients with non-severe MAC (25.0% vs. 8.3%, P = 0.026).
Conclusion
In patients undergoing MV surgery, systematic classification of MAC severity by MAC score helps predict prognosis.
Keywords: mitral annular calcification, mitral valve surgery, cardiac computed tomography, prognosis
Introduction
Mitral annular calcification (MAC) is a chronic and progressive process related to atherosclerotic calcification.1,2 MAC is defined as the accumulation of calcium along the annulus, with the posterior mitral valve (MV) annulus being involved more frequently than the anterior MV annulus, and extension into the subvalvular apparatus and MV leaflets with increasing severity.3 MAC is complex, and can extend into the left ventricular outflow tract, invade the trigone between the aorta and MV or the adjacent left ventricular myocardium. The prevalence of MAC typically ranges from 8% to 15%, and can be >40% or higher in studies of elderly individuals.4 While MAC often has an asymptomatic course, it can be associated with MV dysfunction, arrhythmia and infective endocarditis.5–7 Survival rates are worsened by increasing severity of MAC or MV dysfunction.8–10 Echocardiography is non-invasive and can evaluate MV dysfunction related to MAC, while computed tomography (CT) allows quantitative evaluation of MAC, which is useful for preoperative planning.11 When MAC is complicated by severe valvular dysfunction or infective endocarditis, MV surgery is warranted. When severe MAC is present, it is essential to carefully consider the surgical plan because severe MAC can cause difficulties for MV surgery due to the risk of complications such as heart rupture at atrioventricular junction or free wall.8,12,13 On the other hand, the imaging classification of MAC severity has not been standardized.14,15 Guerrero et al.15 reported that their proposed MAC score predicts valve embolization or migration during trans-septal or transapical procedures. However, the clinical impact of MAC severity quantification in patients undergoing MV surgery is unclear. The prognostic prediction using the MAC score has not yet been reported. We aimed to evaluate the prognostic value of a novel MAC score for patients with severe MAC undergoing MV surgery (Figure 1).
Figure 1.
Graphic abstract of the study with a summary of the key findings. MAC, mitral annular calcification; CT, computed tomography.
Methods
Study population
Out of 11 296 adult patients undergoing MV surgery at our centre between January 2011 and September 2019, we included patients with MAC confirmed on both echocardiogram and cardiac CT in the final study cohort (Figure 2). We excluded patients as shown in Figure 2.
Figure 2.
Flowchart showing the study design. MAC, mitral annular calcification.
We extracted baseline characteristics and follow-up data from the electronic medical records. Experienced sonographers performed comprehensive echocardiographic examinations using commercially available ultrasound machines. Mitral valvular stenosis and regurgitation were assessed according to the current American Society of Echocardiography guidelines at the time.16,17 The decision to perform MV surgery was based on a consensus between experienced cardiologists and cardiothoracic surgeons. The present study was conducted in accordance with the Declaration of Helsinki Ethical Principles and approved by the Institutional Review Board (IRB: 19-1055). Informed consent was not required due to the retrospective nature of the study. All data are fully de-identified and stored securely. The study data are not available for analysis by external parties, because they belong to the authors’ institution.
Follow-up period and clinical outcome
The primary outcome was all-cause mortality after MV surgery. The secondary outcomes were mortality within 30 days, mortality and stroke on admission, and major adverse cardiovascular events (MACE). MACE was defined as myocardial infarction, coronary artery intervention, stroke, admission for heart failure, and/or death from cardiovascular disease. We obtained the data and the cause of death from electronic medical records and online obituary records. The follow-up period was defined as the date of MV surgery to the last date of follow-up or death.
CT-based MAC score
We calculated the MAC score for each patient as shown in Figure 3 and Supplementary data online, Figure S1. The MAC score ranges between 2 and 12, and consists of five main components: MAC Agatston calcium score, MAC angle, extension to left ventricular outflow tract, and the involvement of trigones, and myocardial infiltration. Myocardial infiltration and extension to the surrounding tissues were included in the score, because this increases surgical complexity and the risk during deep debridement. Patients were divided into three categories according to MAC score (mild: 2–4, moderate: 5–8, and severe: 9–12). CT scans were performed utilizing dedicated multi-detector cardiac computed tomography scanners (Siemens Somatom Force scanner, Siemens Definition AS scanner, Siemens Definition Flash scanner, Siemens Healthineers, Erlangen, Germany; Philips iCT 256 scanner, Koninklijke Philips N.V., Amsterdam). Calcium score quantification was performed using non-contrast electrocardiogram-gated cardiac CT scan with dedicated software (Aquarius iNtuition ver. 4.4.13, TeraRecon Inc., Durham, NC, USA). The Agatston score for MAC was calculated as the sum of cumulative calcification of the mitral valve annulus demonstrated using multi-planar reconstruction on computed tomography, capturing calcification at different image slices, according to the Agatston method.18 This methodology allows calculation of the total Agatston score for the entirety of MAC, taking into account of the three-dimensional nature and complex variations in distributions of MAC.19
Figure 3.
Mitral annular calcification scoring by non-contrast gated cardiac computed tomography imaging. CT, computed tomography; MAC, mitral annular calcification; LVOT, left ventricular outflow tract.
Statistical analysis
Continuous variables were expressed as mean ± standard deviation for normal distribution, or median (interquartile range) for skewed distribution, and categorical data were expressed as numbers and percentages. Differences in clinical variables between patients with severe MAC and non-severe MAC were assessed by the unpaired t-test for continuous variables and the Chi-squared test for categorical variables. Survival rates were estimated using the Kaplan–Meier method and compared between patients with severe MAC and non-severe MAC using log-rank test. Hazard ratios with 95% confidence intervals were also assessed using Cox proportional hazards models with follow-up period. Propensity score was estimated with a multivariable logistic regression model, with severe MAC as the dependent variable and the following seven clinical characteristics as covariates: age, sex, body mass index, hypertension, diabetes mellitus, heart failure, and chronic kidney disease. Hypertension refers to blood pressure readings > 130/90 mmHg. Chronic kidney disease is an estimated glomerular filtration rate of <60 mL/min/1.73 m2 persisting for 3 months or more. These covariates were chosen for their potential association with reference to the risk factor of mortality. Propensity score matching was used to reduce confounding effects related to differences in clinical variables. We performed a 1:1 nearest neighbour matching protocol without replacement and defined the calliper width as 0.2 of the standard deviation of the propensity scores (PS). All statistical tests were two-sided and P values of <0.05 were considered statistically significant. Statistical analysis was performed using SPSS version 25 (SPSS Inc., Chicago, IL) and R 3.6.1 (R foundation for Statistical Computing, Vienna, Austria).
Results
Clinical characteristics
In the final cohort, 331 patients were included; the median age was 74 years and 57.1% were female. According to the MAC score, 131 patients (39.6%) had mild MAC, 137 patients (41.4%) had moderate MAC, 63 patients (19.0%) had severe MAC (Table 1). We categorized the patients into those with severe MAC (n = 63) and those with non-severe MAC group (n = 268). Table 2 presents the clinical characteristics in both groups. Patients with severe MAC had significantly higher rates of history of heart failure, chronic kidney disease, cerebrovascular accident, and chronic lung disease compared to non-severe MAC. After PS matching, 120 patients (60 patients with severe MAC and 60 patients with non-severe MAC) were included in the final analysis. In the matched cohort, there were no statistically significant differences in age, body mass index, and comorbidities between both groups. Table 3 presents medication, laboratory, and echocardiographic data. N-terminal pro B-type natriuretic peptide (NT-pro BNP) was not significantly different between the two groups before and after PS matching. Diuretics was used significantly more in patients with severe MAC after PS matching (78.3% vs. 60.0%, P = 0.03). Patients with severe MAC had a significantly smaller left ventricular end-diastolic (82 mL vs. 104 mL, P < 0.01) and end-systolic volume (31 mL vs. 42 mL, P < 0.01) than patients with non-severe MAC before PS matching, but there was no significant difference after PS matching (P = 0.09, P = 0.22). There was no significant difference in left ventricular ejection fraction before (61% vs. 60%, P = 0.32) and after PS matching (P = 0.62).
Table 1.
Severity of mitral annular calcification according to novel CT based score in the study cohort
| All | Mild | Moderate | Severe | |
|---|---|---|---|---|
| Number (%) | 331 (100%) | 131 (39.6%) | 137 (41.4%) | 63 (19.0%) |
| Agatston score | 3990 (918–8007) |
416 (159–1435) |
5924 (3964–8801) |
10 687 (6484–16 671) |
| MAC angle (degrees) | 160 (57–261) |
45 (16–90) |
217 (157–259) |
300 (265–340) |
| LVOT extension (%) | 16.9 | 0.0 | 9.5 | 68.3 |
| Infiltration of myocardium (%) | 32.6 | 1.5 | 35.8 | 90.5 |
| Involvement of either trigone (%) | 10.0 | 2.3 | 7.3 | 31.7 |
| Involvement of both trigones (%) | 7.3 | 0.0 | 0.7 | 36.5 |
MAC, mitral annular calcification; LVOT, left ventricular outflow tract.
Table 2.
Clinical characteristics before and after propensity score matching in the study cohort
| Before matching | After matching | ||||||
|---|---|---|---|---|---|---|---|
| All | Severe MAC | Non-severe MAC | P-value | Severe MAC | Non-severe MAC | P-value | |
| (n = 331) | (n = 63) | (n = 268) | (n = 60) | (n = 60) | |||
| Age (year) | 74 (66–80) |
73 (61–80) |
74 (66–80) |
0.26 | 74 (32–80) |
73 (61–79) |
0.42 |
| BMI | 28.1 (24.3–32.0) |
29.3 (24.9–33.0) |
27.7 (24.3–31.8) |
0.19 | 29.2 (24.9–32.5) |
28.4 (24.7–34.0) |
0.64 |
| Female (%) | 57.1 | 55.6 | 57.5 | 0.78 | 58.3 | 60.0 | 0.85 |
| Smoker (%) | 52.9 | 50.8 | 53.4 | 0.71 | 48.3 | 48.3 | 1.00 |
| HTN (%) | 83.7 | 88.9 | 82.5 | 0.21 | 88.3 | 88.3 | 1.00 |
| DM (%) | 34.1 | 36.5 | 33.6 | 0.66 | 36.7 | 40.0 | 0.71 |
| HLD (%) | 79.2 | 84.1 | 78.0 | 0.28 | 85.0 | 81.7 | 0.62 |
| IHD (%) | 19.6 | 15.9 | 20.5 | 0.40 | 16.7 | 21.7 | 0.49 |
| AF (%) | 45.3 | 44.4 | 45.5 | 0.88 | 41.7 | 43.3 | 0.85 |
| HF (%) | 64.0 | 79.4 | 60.4 | <0.01 | 78.3 | 76.7 | 0.83 |
| CKD (%) | 15.4 | 28.6 | 12.3 | <0.01 | 25.0 | 21.7 | 0.67 |
| CVA (%) | 12.7 | 20.6 | 10.9 | 0.04 | 21.7 | 10.0 | 0.08 |
| CLD (%) | 41.7 | 55.6 | 38.4 | 0.01 | 53.3 | 38.3 | 0.10 |
BMI, body mass index; HTN, hypertension; DM, diabetes mellitus; HLD, hyperlipidaemia; IHD, ischaemic heart disease; AF, atrial fibrillation; HF, heart failure; CKD, chronic kidney disease; CVA, cerebrovascular disease; CLD, chronic lung disease.
Table 3.
Medication, laboratory, and echocardiographic data of the study cohort
| All | Severe MAC | Non-severe MAC |
P-value | Severe MAC | Non-severe MAC |
P-value | |
|---|---|---|---|---|---|---|---|
| (n = 331) | (n = 63) | (n = 268) | (n = 60) | (n = 60) | |||
| Medication (%) | |||||||
| Aspirin | 59.5 | 68.3 | 57.5 | 0.12 | 66.7 | 60.0 | 0.45 |
| Statin | 62.2 | 66.7 | 61.2 | 0.42 | 68.3 | 68.3 | 1.00 |
| ß-blocker | 64.4 | 68.3 | 63.4 | 0.47 | 70.0 | 71.7 | 0.84 |
| CC blocker | 22.1 | 19.0 | 22.8 | 0.52 | 20.0 | 26.7 | 0.39 |
| ACE-i/ARB | 37.5 | 31.7 | 38.8 | 0.30 | 33.3 | 36.7 | 0.70 |
| Diuretics | 66.2 | 76.2 | 63.8 | 0.06 | 78.3 | 60.0 | 0.03 |
| Warfarin | 38.7 | 47.6 | 36.6 | 0.11 | 46.7 | 45.0 | 0.86 |
| NOAC | 9.1 | 4.8 | 10.1 | 0.18 | 5.0 | 6.7 | 0.70 |
| Blood test | |||||||
| Haemoglobin (g/dL) | 10.3 (9.3–11.7) |
10.3 (9.2–11.2) |
10.4 (9.3–11.8) |
0.36 | 10.3 (9.2–11.3) |
10.0 (9.2–11.2) |
0.60 |
| Albumin (g/dL) | 3.3 (3.0–3.9) |
3.2 (3.0–3.7) |
3.3 (3.0–4.0) |
0.21 | 3.2 (3.0–3.8) |
3.3 (3.0–4.0) |
0.45 |
| Creatinine (mg/dL) | 1.05 (0.86–1.37) |
1.05 (0.88–1.54) |
1.06 (0.85–1.34) |
0.16 | 1.05 (0.87–1.42) |
1.06 (0.81–1.58) |
0.80 |
| GFR (mL/min/1.73 m2) | 62 (42–77) |
56 (37–74) |
62 (43–77) |
0.16 | 59 (40–77) |
63 (33–82) |
0.71 |
| NT-pro BNP (pg/mL) a | 1470 (435–3929) |
1830 (1055–5753) |
1376 (356–3894) |
0.05 | 1780 (1041–4301) |
1553 (348–6402) |
0.48 |
| Echocardiography | |||||||
| LV ejection fraction (%) | 60 (55–65) |
61 (56–66) |
60 (55–65) |
0.32 | 61 (56–66) |
60 (54–65) |
0.62 |
| LV end-diastolic volume (mL) |
101 (79–131) |
82 (62–119) |
104 (82–134) |
<0.01 | 85 (64–120) |
104 (83–126) |
0.09 |
| LV end-systolic volume (mL) |
40 (28–58) |
31 (24–50) |
42 (29–61) |
<0.01 | 34 (23–52) |
39 (29–54) |
0.22 |
| LAVi (mL/m2)b | 47 (37–65) |
49 (37–64) |
47 (37–66) |
0.78 | 44 (38–66) |
47 (38–66) |
0.29 |
| RVSP (mmHg)c | 45 (35–58) |
53 (42–61) |
44 (34–58) |
<0.01 | 53 (42–60) |
49 (38–64) |
0.46 |
MAC, mitral annular calcification; CC, calcium channel; ACE-i, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; NOAC, novel oral anticoagulants; GFR, glomerular filtration rate; NT-pro BNP, N-terminal pro B-type natriuretic peptide; LV, left ventricle; LAVi, left atrial volume index; RVSP, right ventricular systolic pressure.
a n = 272.
b n = 323.
c n = 289.
Mitral valve disease and surgery
The valvular and surgical characteristics in both groups are presented in Table 4. At our institution, MV surgery was supplemented as needed with MAC debridement, patch reinforcement using bovine or autologous pericardium, and Commando operation.20,21 Patients with severe MAC had significantly higher severity of mitral stenosis (MS) (moderate: 17.5% vs. 7.5%, severe: 39.7% vs. 7.5%, P < 0.01) and lower severity of mitral regurgitation (MR) compared to non-severe MAC (moderate: 19.0% vs. 25.4%, severe: 28.6% vs. 47.0%, P < 0.01). Patients with severe MAC underwent more MV replacement than MV repair, compared to non-severe MAC patients (87.3% vs. 56.0%, P < 0.01). Additionally, patients with severe MAC underwent more MAC debridement with reconstruction (22.2% vs. 5.6%, P < 0.01) and more concomitant aortic valve surgery (68.3% vs. 46.3%, P < 0.01). These differences were also significant after PS matching. The aetiologies of MV dysfunction are shown in Supplementary data online, Table S1. The most common aetiology was degenerative MV disease (prolapse and/or flail) in both groups, followed by rheumatic heart disease in the severe MAC group, and non-ischaemic cardiomyopathy in the non-severe MAC group.
Table 4.
Mitral valve dysfunction and surgical treatment in the study cohort
| Before matching | After matching | ||||||
|---|---|---|---|---|---|---|---|
| All | Severe MAC | Non-severe MAC |
P-value | Severe MAC | Non-severe MAC |
P-value | |
| (n = 331) | (n = 63) | (n = 268) | (n = 60) | (n = 60) | |||
| Mitral stenosis (%) | <0.01 | <0.01 | |||||
| Moderate | 9.4 | 17.5 | 7.5 | 18.3 | 15.0 | ||
| Severe | 13.6 | 39.7 | 7.5 | 38.3 | 3.3 | ||
| Mitral regurgitation (%) | <0.01 | <0.01 | |||||
| Moderate | 24.2 | 19.0 | 25.4 | 18.3 | 25.0 | ||
| Severe | 43.5 | 28.6 | 47.0 | 30.0 | 43.3 | ||
| Mitral valve surgery (%) | |||||||
| Mitral valve replacement | 61.9 | 87.3 | 56.0 | <0.01 | 86.7 | 58.3 | <0.01 |
| Commando operation | 3.0 | 3.2 | 3.0 | 0.94 | 3.3 | 3.3 | 1.00 |
| MAC debridement with reconstruction |
8.8 | 22.2 | 5.6 | <0.01 | 21.7 | 6.7 | 0.02 |
| With CABG | 36.3 | 36.5 | 36.2 | 0.96 | 36.7 | 38.3 | 0.85 |
| With aortic valve surgery | 50.5 | 68.3 | 46.3 | <0.01 | 68.3 | 45.0 | 0.01 |
| With tricuspid valve repair | 28.4 | 28.6 | 28.4 | 0.97 | 28.3 | 26.7 | 0.84 |
MAC, mitral annular calcification; CABG, coronary artery bypass grafting.
Mortality and complications
During a median follow-up of 220 days (25th to 75th quartile range: 43–1178 days), 47 patients (14.2%) died (Table 5). A total of 149 patients (45.0%) were followed for more than 1 year, and the mortality of these patients was comparable to that of patients followed for <1 year (17.4% vs. 11.5%; P = 0.125). Cardiovascular death accounted for 19.1% of all deaths. Patients with severe MAC had significantly higher all-cause mortality (25.4% vs. 11.6%, P < 0.01) and death from cardiovascular disease (6.3% vs. 1.9%, P = 0.049), compared to patients without severe MAC. There were no significant differences in in-hospital mortality (4.8% vs. 1.9%, P = 0.18), 30-day mortality (6.3% vs. 2.2%, P = 0.09), and MACE after MV surgery (41.3% vs. 38.4%, P = 0.68). After PS matching, there were no significant differences in outcomes except for all-cause mortality. Mild and moderate grades of MAC were not associated with worsening all-cause mortality, as opposed to severe MAC (see Supplementary data online, Table S2). Furthermore, there was no statistically significant difference in outcomes between patients with mild and moderate MAC.
Table 5.
In-hospital and post-discharge complications before and after propensity matching in the study cohort
| Before matching | After matching | ||||||
|---|---|---|---|---|---|---|---|
| All | Severe MAC | Non-severe MAC |
Severe MAC | Non-severe MAC |
|||
| (n = 331) | (n = 63) | (n = 268) | P-value | (n = 60) | (n = 60) | P-value | |
| All-cause mortality (%) | 14.2 | 25.4 | 11.6 | <0.01 | 25.0 | 8.3 | 0.01 |
| Mortality within 30 days (%) | 3.0 | 6.3 | 2.2 | 0.09 | 6.7 | 1.7 | 0.17 |
| In-hospital complications (%) | |||||||
| Mortality | 2.4 | 4.8 | 1.9 | 0.18 | 5.0 | 0.0 | 0.08 |
| Stroke | 2.1 | 4.8 | 1.5 | 0.11 | 5.0 | 3.3 | 0.65 |
| Post-discharge complications (%) | |||||||
| MACE | 39.0 | 41.3 | 38.4 | 0.68 | 40.0 | 35.0 | 0.57 |
| Cardiovascular death | 2.7 | 6.3 | 1.9 | 0.049 | 5.0 | 0.0 | 0.08 |
| Myocardial infarction | 6.6 | 6.3 | 6.7 | 0.92 | 6.7 | 8.3 | 0.73 |
| Coronary revascularization | 5.1 | 6.3 | 4.9 | 0.63 | 6.7 | 6.7 | 1.00 |
| Stroke | 11.8 | 12.7 | 11.6 | 0.80 | 13.3 | 10.0 | 0.57 |
| Admission for heart failure | 29.9 | 30.2 | 29.9 | 0.96 | 30.0 | 28.3 | 0.84 |
MAC, mitral annular calcification; MACE, major adverse cardiovascular events.
Kaplan–Meier curves of all-cause mortality after PS matching are shown in Figure 4. In this analysis, patients with severe MAC had a significantly higher mortality compared to those with non-severe MAC before (P = 0.005) and after PS matching (P = 0.026). In Cox proportional hazards models during the follow-up period, severe MAC significantly increased all-cause mortality [hazard ratio, 2.32; 95% confidence interval (CI), 1.26–4.25; P < 0.01]. There was no change in outcome after PS matching (hazard ratio, 2.99; 95% CI, 1.08–8.20; P = 0.03). When MV replacement and combined aortic valve surgery were included as covariates, severe MAC was significantly associated with all-cause mortality before PS matching (hazard ratio: 2.00; 95% CI: 1.07–3.75; P = 0.03). However, after PS matching, the association was no longer statistically significant after PS matching (hazard ratio: 2.43; 95% CI: 0.87–6.82; P = 0.09).
Figure 4.
Survival curves stratified according to severe mitral annular calcification before and after propensity score matching. PS, propensity score; MAC, mitral annular calcification.
Reproducibility of MAC score
Intra- and inter-observer variabilities were assessed through independent evaluation of MAC score in 20 randomly selected patients by two physicians on two separate occasions.22 The intra-observer and inter-observer variabilities for the MAC score were 2.6% and 4.1%, respectively. The intra-observer and inter-observer variabilities for MAC severity based on the MAC score were 3.5% and 3.5%, respectively.
Discussion
The main findings of the study were (i) 19% of patients with MAC undergoing MV surgery had quantitatively severe MAC by the novel CT score; and (ii) patients with severe MAC had significantly higher all-cause mortality compared to patients without severe MAC.
MAC and prognosis
The presence of MAC has been reported to be associated with mortality.8,23 Ribeiro et al.23 reported that MAC was associated with midterm mortality after MV surgery (risk ratio: 1.32; 95% CI, 1.05–1.67; P = 0.02), but there were no significant differences in perioperative mortality between patients with and without MAC (risk ratio, 1.15; 95% CI, 0.50–2.65; P = 0.74). The hazard ratio of overall mortality was higher in this study compared to the previous studies. This likely relates to a systematic approach to quantification of MAC, which identified patients with truly severe MAC in our study in a systematic way. In this study, there were no statistically significant differences in in-hospital mortality and 30-day mortality between patients with severe MAC and non-severe MAC. This shows that MV surgery can indeed be performed safely in patients with complex MAC, when it has been assessed systematically by CT quantification and if MV surgery is performed by experienced cardiothoracic surgeons at experienced centres. On the other hand, patients with severe MAC had a statistically significantly higher all-cause mortality. Increased all-cause mortality may reflect underlying intrinsic factors of patients. Careful clinical follow-up may be warranted after MV surgery for patients with severe MAC. Surgery remains the gold standard treatment for patients with severe MV dysfunction due to MAC.24 Severe MAC causes more rapid progression of MS compared to non-severe MAC, and therefore increasing the need for surgical treatment.25 A single-centre echocardiographic study that included 200 patients with MAC and severe MS (MVA ≤ 1.5 cm2) showed that survival rates were 72% at 1 year and 52% at 3 years without MV intervention.9 Saijo et al.26 reported that patients with severe MS due to MAC who underwent mitral valve replacement had a significantly lower mortality rate than those who did not, particularly during long-term follow-up beyond the first 2 years. In addition, female patients with calcific MS due to MAC may particularly benefit from MV intervention, as opposed to conservative treatment.27
MAC has been reported to be associated with increased risk of perioperative complications and periprosthetic leak.13,28 Since MAC is related to atherosclerotic calcification, the progression of MAC sometimes means the progression of systemic atherosclerotic changes. This may help to explain the higher mortality in patients observed with severe MAC. Additionally, an association has been reported between patients with MAC and frailty, as opposed to patients without MAC. The association between frailty and prognosis has also been shown in patients with calcific mitral stenosis due to MAC.26 Furthermore, MAC may result in MR and MS by means of restricting annular expansion during diastole and mitral leaflet motion.29–31 In this study, patients with severe MAC had a lower prevalence of severe MR compared to patients with non-severe MAC, whereas more than five times higher prevalence of severe MS. Severe MS due to MAC has been associated with high mortality. Patients with severe MAC classified by the MAC score underwent more MV replacement and more concomitant aortic valve surgeries. After adding these covariates to the Cox proportional hazards models, after PS matching, there was no longer a statistically significant association between severe MAC and all-cause mortality. These additional factors may have affected the prognosis.
MAC classification
Echocardiography is non-invasive, and superior for assessing MV function; however, it can be limited in evaluation of the full extent of MAC. Although maximum MAC thickness has been used to assess severity on echocardiography,32 this method has not been incorporated into the contemporary clinical guidelines.33 Arguably, this method is also semi-quantitative, and subject to measurement error depending on the echocardiographic image chosen. Compared to echocardiography, CT imaging is not significantly influenced by body habitus shape, or chronic pulmonary disease, and the data acquired are objective and reproducible. Additionally, the novel MAC score based on non-contrast enhanced cardiac CT can be performed even for patients with chronic kidney disease or contrast allergy.
Some studies have defined severe MAC only by the extent of calcification on CT.13,34 However, it should be noted that the severity of MAC was assessed differently in each study. Guerrero et al.15 reported that a higher score based on four categories (calcium thickness, calcium distribution, trigone involvement, and leaflet involvement) correlated with a lower embolization risk during transcatheter MV replacement. It is important to note that Guerrero et al. did not include patients undergoing surgical MV therapy. Additionally, Guerrero’s scoring system was based on contrast enhanced CT scans. This did not allow systematic quantification of MAC score using the Agatston score, which was originally validated using non-contrast CT scans.18 Xu et al.14 reported higher MAC score was significantly associated with increased total operative time, cross-clamp time, and in-hospital complications for patients with MV dysfunction undergoing MV surgery. In this study, we used this novel MAC score which was reported to be associated with surgical outcomes to assess its prognostic impact.
Clinical implication
Patients with MAC undergoing MV surgery are often elderly.35 This is related to the progressive nature of MAC with age as occurs with atherosclerotic disease.2 It is not clear if systematic quantification of MAC assists with surgical planning. The prognostic impact of systematic quantification of MAC in patients undergoing MV surgery is also unknown. The current study systematically classified the severity of MAC using CT imaging in patients undergoing MV surgery. We found that while severe MAC by the MAC score was not associated with statistically significant impact on short-term prognosis, it statistically significantly affected all-cause mortality. Understanding post-operative prognosis in patients with MAC undergoing MV surgery is important for post-operative management and ongoing clinical surveillance. The current study may provide valuable insight for guiding surgical intervention in patients with MAC undergoing MV surgery and predict patient outcomes.
Perspective
Patients underwent MV surgery were included and we examined the association between MAC scoring and prognosis after MV surgery in this study. It would be desirable to examine the association between the new MAC score and prognosis in all patients with MAC, including those who have not had surgery.
Limitations
This study is a single-centre study from a quaternary referral centre with highly experienced cardiac surgeons and cardiologists. MV surgery on patients with truly severe MAC may be less common in other centres, and therefore, the findings of this work in patients with severe MAC may not apply fully to other centres. This is a retrospective analysis, with its inherent biases. This study excluded patients without a pre-operative CT scan. In order to design a systematic quantitative MAC score using CT features, our study included patients with all grades of MAC, rather than only severe MAC. This would have minimized any potential bias towards only patients with severe MAC. As can be seen in our study, we have included a spectrum of MAC severity, classified by our score (131 patients with mild MAC by our score, 137 patients with moderate MAC by our score, 63 patients with severe MAC by our score). PS matching adjusts the potential difference between the groups; however, there may be additional confounding variables which are not adjusted for. Frailty, a history of radiation therapy to the chest, systemic inflammation, chronic immunosuppression, and additional factors has been reported to affect outcomes in patients with MAC undergoing cardiac surgery.36 We did not evaluate the impact of the frailty score, functional status, and socio-economic status in this study. These factors may be relevant in patients with severe MAC undergoing mitral valve surgery. Further research related to the impact of these factors on outcomes of patients with severe MAC undergoing mitral valve surgery is warranted. The median follow-up in this study was <1 year. Therefore, data related to the impact of the MAC score on long-term prognosis in patients undergoing MV surgery is not available. Several parameters were limited by missing data. Since these variables were not included as covariates in the propensity score model, their absence is unlikely to have influenced the study findings. It is important to note that comprehensive assessment of all laboratory and echocardiographic parameters in every patient may not always be feasible in real-world clinical settings.
Conclusion
In patients with MAC and MV dysfunction undergoing MV surgery, systematic classification of MAC severity by CT-based MAC score helps predict prognosis. Patients with severe MAC were more likely to undergo MV replacement.
Supplementary Material
Contributor Information
Yuichiro Okushi, Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
Shinya Unai, Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, OH 44195, USA.
Gösta B Pettersson, Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, OH 44195, USA.
Haytham Elgharably, Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, OH 44195, USA.
A Marc Gillinov, Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, OH 44195, USA.
Richard A Grimm, Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
Brian P Griffin, Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
Bo Xu, Section of Cardiovascular Imaging, Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart, Vascular and Thoracic Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
Supplementary data
Supplementary data are available at European Heart Journal - Imaging Methods and Practice online.
Funding
None.
Data availability
The data reported in this work cannot be shared with external sources, as they belongs to the Cleveland Clinic.
Lead author biography
Dr. Yuichiro Okushi is an Imaging Research Fellow at the Cleveland Clinic in the USA. In addition, he is a cardiologist in the Department of Cardiovascular Medicine at Tokushima University Hospital in Japan, where he is engaged in advanced cardiovascular imaging research to enhance the diagnosis of cardiovascular diseases.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data reported in this work cannot be shared with external sources, as they belongs to the Cleveland Clinic.