Introduction
Clinical trial and registry data have demonstrated a 31–39% and 21–32% prevalence of two-vessel and three-vessel diseases, respectively, in patients undergoing revascularization.[ 1–3 ] Multi-vessel coronary artery disease (CAD) occurs in 40–50% of patients with acute myocardial infarction (AMI) undergoing primary percutaneous coronary intervention (PCI).[ 4–6 ] Previous studies have shown that complete revascularization is associated with lower rates of long-term adverse events when compared with incomplete revascularization.[ 7,8 ] However, quite a few CAD patients are unable to achieve complete revascularization because of the adverse characteristics pertinent to the lesions and the systemic background of the patients.
The Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) score, an angiographic tool grading the complexity of CAD, was widely used to evaluate clinical outcomes for CAD patients.[ 9–11 ] The residual SYNTAX score, its derivative, reflecting the burden of residual coronary lesions after revascularization, was also a useful tool to quantify the incomplete revascularization and risk-stratify for CAD patients.[ 5,12 ] However, the major fallacy of the SYNTAX score is not accounting for the variability in the coronary anatomy, where the weighting assignment to each segment is nomenclature-based.[ 13 ] We have recently developed a new Coronary Artery Tree description and Lesion EvaluaTion (CatLet) angiographic scoring system.[ 14 ] Our preliminary studies demonstrated that this novel angiographic scoring system was better than the SYNTAX score to account for the variability in the coronary anatomy, to evaluate the severity and the complexity of diseased coronary artery trees, and to predict clinical outcomes for AMI patients,[ 15,16 ] with high reproducibility.[ 17 ] Our prior study also demonstrated that the predictive value of the CatLet score could be improved through a combination with age, serum creatinine, and left ventricular ejection fraction (LVEF).[ 18 ] Thus, we have hypothesized that the residual CatLet (rCatLet) score, defined as a final angiographic score after completion of primary or elective PCI, predicts clinical outcomes for AMI patients and that a combination with age, serum creatinine, and LVEF (clinical variables [CVs]-adjusted rCatLet score) will enhance its predicting values.
Methods
Patients This study was a post hoc study of the CatLet score validation trial and the patient enrollments have been described elsewhere.[ 15 ] Briefly, a total of 434 consecutive patients with chest discomfort ≤12 h after symptom onset, between January 2012 and July 2013, who were suspected of having AMI in The First Affiliated Hospital of Soochow University, and who underwent emergency coronary angiography (CAG), were retrospectively enrolled for potential analysis. AMI was diagnosed according to the fourth universal definition of myocardial infarction (MI).[ 19 ] Exclusion criteria have been described elsewhere and included: (1) prior stenting, (2) undefined culprit vessels, (3) angina pectoris, (4) prior MI, (5) normal CAG results, (6) viral myocarditis, (7) idiopathic dilated cardiomyopathy, (8) chronic total occlusion (CTO), (9) coronary artery embolism, and (10) being transferred elsewhere for further treatment.[ 15 ]
All patients gave written informed consent. The study protocol was approved by the Institute Review Boards of Soochow University in April 2017 (No. 2020089). This study was conducted in accordance with the principles outlined in the Declaration of Helsinki . This CatLet score study has been registered on the website of Clinical Trial Registration (http://www.
The CatLet score and the lesion evaluation The CatLet angiographic scoring system has been described elsewhere in detail.[ 14 ] Its tutorial is available at http://www.catletscore.com [ 20 ] A multiplication factor of 2.0 was used for non-occlusive lesions and 5.0 for occlusive lesions. The rCatLet score was calculated from the final angiographic results after completion of all the emergency or elective percutaneous revascularization procedures. Two experienced observers reviewed the angiograms. The view of a third analyst was sought in the event of disagreement, and the final decision was made by consensus. The observers were blinded to patients' clinical characteristics and outcomes.
Follow-ups and endpoints The follow-ups have been described elsewhere in detail.[ 15 ] The outcomes were ascertained through medical records, phone interviews of patients' relatives or living patients with specific questions, or home visits to patients. We had a 100% follow-up success rate on participants' outcomes. The primary endpoint was major adverse cardiac or cerebrovascular events (MACCE) at a median of 4.3 years follow-up, defined as a composite of all-cause mortality, non-fatal AMI, transient ischemic attack/stroke, and ischemia-driven repeat revascularization. Secondary endpoints were all-cause death and cardiac death. All patients were followed up until these endpoints or the end of this study (September 2017), whichever came first. An independent events committee, including cardiologists, neurologists, and epidemiologists, would adjudicate these outcomes.
Sample size estimation and statistical analysis Statistical analyses and graphics were completed with STATA 16.0 (State Corp LP, College Station, TX, USA). The enrolled sample size calculation has been provided in detail elsewhere.[ 15 ] Briefly, according to the published data, the CatLet score was associated with a 1.05-fold increased risk of adverse cardiovascular events per 1 unit higher, and its standard deviation was 12; previously similar study had reported that the failed probability was around 15% at 1.5-year follow-up.[ 21 ] Therefore, a minimum sample size of 205 could ensure a statistical power of 0.90 with a safe conclusion drawn at the two-sided α of 0.05. In the current study, we had enrolled 308 study subjects with an adequate statistical power to support our conclusions.
Continuous variables were expressed as mean ± standard deviation (SD). Categorical variables were expressed as frequencies and percentages. Continuous variables and categorical variables were compared with Kruskal–Wallis H test or χ 2 test as appropriate. Testing for trends in event rates across the tertiles was completed with the STATA procedures Opartchi. The survival curves were generated using Kaplan–Meier methodology and compared using the Log-rank test. To evaluate the additional prognostic value of CVs, two survival Cox models were created as follows: univariate or multivariate-adjusted model (CVs–age, creatinine, and LVEF). The unadjusted hazard ratios (HRs), adjusted HR, and 95% confidence intervals (CIs) were calculated. Receiver operating characteristic (ROC) curves were generated to assess ability of prognostic prediction in patients and their comparisons were performed by DeLong's method. The agreement between observed and predicted risks was assessed with calibration plots.[ 22 ] Two-tailed P <0.05 was considered to be statistically significant.
Results
Baseline characteristics Out of 434 patients initially enrolled in this study, 126 were excluded, and 308 patients were finally analyzed as shown in Figure 1 . The mean age was 63 ± 13 years, and 79.87% (245/308) were male. The rCatLet score ranged from 0 to 81, with a mean ± SD of 10.46 ± 12.80 and a median of 6.50. Tertiles for rCatLet score were defined as rCatLet_low ≤3, rCatLet_mid 4–11, and rCatLet_top ≥12, respectively. Baseline clinical and angiographic variables of the patients were listed in Table 1 . Patients with higher rCatLet score were older, and higher troponin I peak values, and were more likely to have hypertension. Paradoxically, smoking is less frequently observed in the higher rCatLet score patients.
Figure 1: Flow chart of patient selection. AMI: Acute myocardial infarction ; CAG: Coronary angiography; CatLet: Coronary Artery Tree description and Lesion EvaluaTion; MI: Myocardial infarction; rCatLet: Residual CatLet.
Table 1 -
Baseline clinical and angiographic characteristics stratified by rCatLet score tertiles.
Variables
rCatLet_low (0–3)
rCatLet_mid (4–11)
rCatLet_top (12–81)
χ
2 Values
P values on trend
No. of cases
105
101
102
Age (years)
60 ± 13
62 ± 11
67 ± 13
13.78
0.001
Male
83 (79.05)
84 (83.17)
78 (76.47)
-0.45
0.653
Diabetes
19 (18.10)
25 (24.75)
26 (25.49)
1.27
0.203
Hypertension
52 (49.52)
58 (57.43)
65 (63.73)
2.06
0.039
Previous stroke
6 (5.71)
6 (5.94)
12 (11.76)
1.61
0.107
Smoking
-2.47
0.013
Never
30 (28.57)
32 (31.68)
45 (44.12)
Past
5 (4.76)
10 (9.90)
6 (5.88)
Current
70 (66.67)
59 (58.42)
51 (50.00)
Alcohol consumption
-0.80
0.424
Never
73 (69.52)
76 (75.25)
75 (73.53)
Past
2 (1.90)
3 (2.97)
5 (4.90)
Current
30 (28.57)
22 (21.78)
22 (21.57)
STEMI
99 (94.29)
93 (92.08)
96 (94.12)
-0.05
0.956
LVEF
0.49 ± 0.08
0.48 ± 0.09
0.48 ± 0.10
1.44
0.486
Troponin I (ng/mL)
41.85 ± 30.31
44.66 ± 30.62
51.75 ± 27.73
8.20
0.017
TG (mmol/L)
1.57 ± 1.65
1.65 ± 2.03
1.36 ± 0.87
0.26
0.880
TC (mmol/L)
4.40 ± 1.05
4.46 ± 1.12
4.48 ± 1.18
1.77
0.414
HDL-C (mmol/L)
1.09 ± 0.23
1.10 ± 0.23
1.08 ± 0.27
2.65
0.266
LDL-C (mmol/L)
2.83 ± 0.93
2.83 ± 0.87
2.95 ± 1.0
4.51
0.105
Creatinine (μmol/L)
82.62 ± 78.06
74.80 ± 29.02
94.47 ± 75.04
5.20
0.074
Diagonal size
-0.83
0.406
Small
16 (15.24)
15 (14.85)
16 (15.69)
Intermediate
66 (62.86)
66 (65.35)
70 (68.63)
Large
23 (21.90)
20 (19.80)
16 (15.69)
LAD length
-1.19
0.235
Short
11 (10.48)
11 (10.89)
15 (14.71)
Average
74 (70.48)
60 (59.41)
73 (71.57)
Long
20 (19.05)
30 (29.70)
14 (13.73)
RCA dominance
0.90
0.369
PDA zero
8 (7.62)
7 (6.93)
6 (5.88)
PDA only
8 (7.62)
7 (6.93)
6 (5.88)
Small RCA
25 (23.81)
30 (29.70)
25 (24.51)
Average RCA
37 (35.24)
32 (31.69)
32 (31.38)
Large RCA
22 (20.95)
23 (22.77)
27 (26.47)
Super RCA
5 (4.76)
2 (1.98)
6 (5.88)
No. of lesions/patient
1.32 ± 0.63
2.02 ± 0.81
3.02 ± 1.39
107.90
<0.001
No. of treated lesions/patient
1.15 ± 0.48
1.09 ± 0.47
1.06 ± 0.54
0.30
0.584
Coronary artery treated
LM
0
0
1 (0.98)
1.23
0.218
LAD
65 (61.90)
60 (59.41)
46 (45.10)
-2.27
0.023
LCX
19 (18.10)
11 (10.89)
15 (14.71)
-0.72
0.471
RCA
29 (27.62)
33 (32.67)
38 (37.25)
1.44
0.150
Culprit vessels
LAD
61 (58.10)
59 (58.42)
49 (48.04)
-1.44
0.149
LCX
17 (16.19)
13 (12.87)
15 (14.71)
-0.31
0.759
RCA
27 (25.71)
31 (30.69)
40 (39.22)
2.08
0.038
One-vessel disease
74 (70.48)
23 (22.77)
11 (10.78)
-9.01
<0.001
Two-vessel disease
25 (23.81)
46 (45.55)
23 (22.55)
-0.16
0.870
Three-vessel disease
6 (5.71)
32 (31.68)
68 (66.67)
9.21
<0.001
Left main
0
0
9 (10.47)
3.74
<0.001
No. of implanted stents
0.77 ± 0.59
0.91 ± 0.66
0.69 ± 0.61
0.10
0.749
Total stent lengths/patient (mm)
16.23 ± 14.93
20.57 ± 16.54
14.32 ± 14.2
2.23
0.328
No. of bifurcation/patient
0.52 ± 0.54
0.94 ± 0.72
1.19 ± 0.86
31.58
<0.001
Trifurcation
5 (4.76)
2 (1.98)
7 (6.86)
0.71
0.477
Tortuosity
1 (0.95)
2 (1.98)
4 (3.921)
1.43
0.153
Aorta ostial lesion
2 (1.90)
0
8 (7.84)
2.39
0.017
No. of calcification
3 (2.86)
4 (3.96)
21 (20.59)
4.48
<0.001
No. of lesion length >20 mm
14 (26.67)
22 (26.66)
36 (35.29)
3.91
<0.001
Thrombus
93 (88.57)
88 (87.13)
87 (85.29)
0.84
0.399
Angulation <70˚
41 (39.05)
76 (65.35)
72 (70.59)
5.42
<0.001
Complete revascularization
86 (81.89)
0
0
-13.17
<0.001
Data are presented as mean ± standard deviation or n (%). CatLet: Coronary Artery Tree description and Lesion EvaluaTion; HDL-C: High density lipoprotein cholesterol; LAD: Left anterior descending artery; LCX: Left circumflex coronary artery; LDL-C: Low-density lipoprotein cholesterol; LM: Left main artery; LVEF: Left ventricular ejection fraction; PDA: Posterior descending artery; RCA: Right coronary artery; rCatLet: Residual CatLet; rCatLet_low, rCatLet_mid, and rCatLet_top: Low, mid, and top tertile of rCatLet score, respectively; STEMI: ST-segment elevation myocardial infarction; TC: Total cholesterol; TG: Triglycerides.
Univariate associations between rCatLet score and outcomes Patients were followed up for median of 4.3 years (interquartile range 3.80–4.90). The rates of MACCE, all-cause death, and cardiac death were 20.78%, 18.18%, and 15.26%, respectively. Kaplan–Meier curves for all endpoints showed increasing outcome events with the increasing tertiles of the rCatLet score, with all P values <0.001 on trend test as shown in Figure 2 . Compared with the rCatLet_low group, there were higher risks of MACCE both in rCatLet_top and in rCatLet_mid groups: the HRs (95% CI) being 4.38 (2.17–8.85) and 2.12 (0.98–4.55), respectively. In terms of all-cause death and cardiac death, similar findings were observed as shown in Table 2 .
Figure 2: KM curves for MACCEs (A), all-cause death (B), and cardiac death (C) at 4.3 years according to the rCatLet score tertiles. CatLet: Coronary Artery Tree description and Lesion EvaluaTion; KM: Kaplan–Meier; MACCE: Major adverse cardiovascular and cerebrovascular events; rCatLet: Residual CatLet; rCatLet: Residual CatLet; rCatLet_low, rCatLet_mid, and rCatLet_top: Low, mid, and top tertile of rCatLet score, respectively.
Table 2 -
Univariate or multivariable-adjusted HRs/unit higher for clinical outcomes.
4.3-year KM rate, n (%)
Unadjusted HR (95% CI)
Adjusted HR (95% CI)
Outcomes
rCat
Let_low
(0–3)
rCat
Let_mid
(4–11)
rCat
Let_top
(12–81)
P
* values
rCat
Let_low
(0–3)
rCat
Let_mid
(4–11)
rCat
Let_top
(12–81)
P values on trend
rCat
Let_low
(0–3)
rCat
Let_mid
(4–11)
rCat
Let_top
(12–81)
P values on trend
MACCE
10 (9.52)
19 (18.81)
35 (34.31)
˂0.001
Reference
2.12 (0.98–4.55)
4.38 (2.17–8.85)
˂0.01
Reference
2.38 (1.09–5.21)
2.87 (1.40–5.87)
≤0.004
All-cause death
10 (9.52)
16 (15.84)
30 (29.41)
≤0.001
Reference
1.74 (0.79–3.84)
3.63 (1.78–7.43)
˂0.001
Reference
1.85 (0.83–4.12)
2.09 (1.01–4.33)
0.053
Cardiac death
8 (7.62)
11 (10.89)
28 (27.45)
˂0.001
Reference
1.48 (0.59–3.68)
4.22 (1.92–9.26)
˂0.001
Reference
1.55 (0.62–3.92)
2.37 (1.06–5.29)
0.029
Adjusting for age and creatinine, LVEF. P *
Additional predicting values conferred by CVs For MACCE, all-cause death, and cardiac death, the area under the curves (AUCs) of the rCatLet score were 0.70 (95% CI: 0.63–0.78), 0.69 (95% CI: 0.61–0.77), and 0.71 (95% CI: 0.63–0.79), respectively; after adjustment for the three CVs, the AUCs of the CVs-adjusted rCatLet score were 0.83 (95% CI: 0.78–0.89), 0.87 (95% CI: 0.82–0.92), and 0.89 (95% CI: 0.84–0.94), respectively, as shown in Figure 3 . Figure 3 also showed that the three CVs-adjusted rCatLet score demonstrated a significantly better predictive ability for all endpoints than the stand-alone rCatLet score. Cross-validation also confirmed a reasonably good agreement between the observed and predicted risks as shown in Figure 4 . Multivariable analysis had demonstrated that the rCatLet score remains to be a predictor of clinical outcomes after further including more risk factors significantly associated with the outcomes in univariate analysis as shown in supplementary Table 1, https://links.lww.com/CM9/B491 Figure 5 .
Figure 3: The ROC curves revealed significant differences between rCatLet score and adjusted rCatLet score for predicting MACCEs (A), all-cause death (B), and cardiac death (C) at 4.3 years. Adj-rCS: Adjusted residual CatLet score ; AUC: Area under the curve; CatLet: Coronary Artery Tree description and Lesion EvaluaTion; MACCE: Major adverse cardiovascular and cerebrovascular event; rCatLet: Residual CatLet; rCS: Residual CatLet score ; ROC: Receiver operating characteristic.
Figure 4: Calibration plots of rCatLet score and adjusted rCatLet score at cross-validation with respect to clinical outcomes for rCatLet score (A–C) and adjusted rCatLet score (D–F), respectively. The circle indicates the observed frequencies by tertile of predicted probabilities with a 95% CI. Good agreement was found between the observed and predicted incidence for all endpoints. Intercept also called CITL. A lowess smoothing curve was added to each calibration plot. Intercept of 0 and slope of 1 indicate perfect prediction. AUC: Area under the curve; CatLet: Coronary Artery Tree description and Lesion EvaluaTion; CI: Confidence interval; CITL: Calibration-in-the-large; E:O: Estimation risk/observing risk; MACCE: Major adverse cardiovascular and cerebrovascular event; rCatLet: Residual CatLet.
Figure 5: HRs for MACCE per 1unit higher CatLet score stratified by risk factors, dichotomously or medially, adjusted for age, serum creatinine, and LVEF. For smoking and drinking, "Yes" indicated current smoking or drinking, and "No" indicated never or past smoking or drinking. Black squares represent point estimates and error bars, 95% CI. CatLet: Coronary Artery Tree description and Lesion EvaluaTion; CI: Confidence interval; HDL-C: High density lipoprotein cholesterol; HR: Hazard ratio; LAD: Left anterior descending artery; LCX: Left circumflex coronary artery; LDL-C: Low-density lipoprotein cholesterol; LVEF: Left ventricular ejection fraction; MACCE: Major adverse cardiovascular and cerebrovascular event; PDA: Posterior descending artery; RCA: Right coronary artery; rCatLet: Residual CatLet; rCatLet_low, rCatLet_mid, and rCatLet_top: Low, mid, and top tertile of rCatLet score, respectively; STEMI: ST elevated myocardial infarction; TC: Total cholesterol; TG: Triglycerides.
Discussion
The key findings of the present study have revealed that (1) the stand-alone rCatLet score is an independent predictor of MACCE, all-cause death, or cardiac death in AMI patients undergoing primary PCI, and (2) the three CVs-adjusted rCatLet score had a better predictive ability than the stand-alone rCatLet score model.
Baseline characteristics Expectedly, patients with higher rCatLet score were older, more likely to have hypertension, higher troponin I, and the number of lesions; adverse characteristics, such as bifurcated lesions, aorta ostial lesions, heavy calcification, and lesion length >20 mm, were more frequently observed in patients with higher rCatLet score. Also expectedly, patients with higher rCatLet score were less likely to achieve complete revascularization. Paradoxically, higher rCatLet score was associated with less likelihood of smoking, namely "smoking paradox." In the current study, smokers are younger while non-smokers are older; age is a stronger prognosticator for adverse cardiovascular outcomes. The "smoking paradox" can thus be reasonably explained.
rCatLet score The burden of residual lesions in AMI patients after revascularization has correlation with patients' clinical prognosis .[ 23,24 ] The CatLet score can be utilized to semi-quantify the severity and complexity of the diseased coronary trees,[ 14 ] and the rCatLet score has reflected the burden of residual lesions. Thus, it is not surprising that rCatLet score predicts the clinical outcomes as well. The current study revealed that the higher rCatLet score was associated with the higher incidence of MACCE. The SYNTAX score is another anatomic scoring tool, which can be used to grade the complexity and severity of the CAD, and to predict clinical outcomes in CAD patients.[ 9–11 ] The residual SYNTAX score has also been proven to be an independent predictor for clinical outcomes in CAD patients, with a reported C-index or AUC of 0.590–0.721 for all-cause death.[ 25,26 ] The current study reported a similar or better discriminating ability for all-cause death with the rCatLet score. The overall better performance with the rCatLet score is wholly anticipated given the unique characteristic of the CatLet score in its derivation: adequate reflection of the variability in the coronary anatomy.[ 14 ]
Three CVs-adjusted rCatLet score Age, creatinine, and LVEF were important clinical factors that affected the clinical outcomes in CAD patients. The age, creatinine, and ejection fraction (ACEF) score, just based on three CVs–age, creatinine, and LVEF, has been widely used to predict clinical outcomes for patients with cardiovascular diseases with a better performance than the EuroSCORE, the Parsonnet score, or the Northern New England score.[ 27–29 ] It is thus anticipated that the CVs-adjusted rCatLet score performed better than the stand-alone rCatLet score in outcome predictions revealed in the current study. Previous studies also showed that residual SYNTAX score in combination with the ACEF score had better predictive values for long-term mortality following PCI.[ 30,31 ] Our prior work has similarly demonstrated that the CVs-adjusted CatLet score performed significantly better than the stand-alone CatLet score with respect to outcome predictions.[ 18 ] These studies have lent support to the current observations that the incorporation of the three CVs into the anatomic rCatLet score will add its prognostic values for CAD patients. Glomerular filtration rate (GFR) is a more representative marker of renal function.[ 32 ] However, the AGEF score, with three components of age, GFR, and LVEF, has failed to show its superiority over the ACEF with respect to outcome predictions for cardiovascular diseases.[ 33,34 ] Possible explanations have included that the age, being a component of GFR (age, body weight [kg], creatinine, and sex), will lead to the collinearity issue when the age, GFR, and LVEF, are combined to construct a model. Considering this possible collinearity issue and widely validated prediction values of the serum creatinine, we have thus used the serum creatinine instead of the GFR to adjust the rCatLet model.
Limitations This study had several limitations. First, the CatLet score validation trial was observational in design, and the confounding was unavoidable. Thus, this finding should be considered hypothesis-generating. Second, the moderate sample size was still a concern although the justification of the sample size of 308 was provided. Third, AMI patients were enrolled only in the current study, and the extrapolating of these findings would be restricted. We would further examine the predictive values of the rCatLet score in different CAD populations.
In conclusion, in the present study, we have demonstrated that the rCatLet score has a predicting value for clinical outcomes in AMI patients. CVs-adjusted rCatLet score has performed better than the stand-alone rCatLet score with respect to outcome predictions.
Funding This work was in part supported by the National Key R&D Program (No. 2020YFC2004705), Sci-Tech Supporting Program of Jiangsu Commission of Health (No. M2021019), and Medical Sci-Tech innovation Program for Medical Care of Suzhou City (No. SKY2021005).
Conflicts of interest None.
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