The prognosis of patients with complex coronary heart disease (CAD) depends on anatomical complexity, patients’ clinical characteristics, and comorbidities. It has been shown that the clinical outcome of patients with incomplete revascularization (IR) after percutaneous coronary intervention (PCI) is worse than that of patients with complete revascularization (CR) [1, 2]. However, in most previous studies, the completeness of revascularization was judged based on the severity of anatomical stenosis without considering the functional significance of the remaining stenosis [3, 4].

The SYNTAX score (SS) is a comprehensive angiographic scoring system based on coronary artery anatomy and lesion characteristics [5]. However, with the advancement of coronary intervention technologies and coronary stents, purely anatomical SSs can no longer objectively predict the prognosis or outcome of patients. Therefore, based on SS, some scholars calculated patients’ clinical factors, including age, comorbidities, and other factors, and applied them to the SS, defined as the SYNTAX II score (SSII) [2, 6, 7].

However, even though the SSII can effectively reduce data deviations in SYNTAX studies, with increased research on coronary artery hemodynamics and pathophysiology, coronary angiography alone can no longer meet the clinical requirements for the anatomical characteristics or physiological functions of stenotic lesions [8]. The main reason for the need for additional assessments is that coronary angiography cannot be used to accurately evaluate the relationship between stenosis and myocardial ischemia. Many studies have shown that the prognosis of patients with coronary heart disease mainly depends on the presence or absence of myocardial ischemia rather than the degree of coronary stenosis. Interventions for stenosis without functional significance will not benefit patients [9, 10]. Therefore, functional disease is even more important in treating multivessel or diffuse segmental lesions.

Several studies have shown that through SS combined with fractional flow reserve (FFR), the prognosis of patients can be effectively predicted [1, 11, 12]. Quantitative flow ratio (QFR) is a novel method for deriving FFR without the use of pressure wires or the induction of hyperemia [13, 14]. The diagnostic ability of SS combined with QFR in the prognosis of patients with multivessel disease has also been confirmed [15, 16]. In this study, we aimed to test the diagnostic value of these scores by calculating the preoperative and postoperative SSs and those corrected based on QFR in combination with the incidence of major adverse cardiovascular events (MACEs) among patients after 1 year. In addition, we used the final 1-year incidence of MACEs in patients to verify the correct rate of risk stratification and patients’ outcomes.

The main finding of this study was that either SS or SSII combined with the functional score system could decrease the portion of high-risk and medium-risk patients. Furthermore, the study also showed that SSII and FSSII had accurate predictive abilities. Risk stratification based on FSSII showed a better MACE predictive ability. These findings revealed that a non-invasive QFR-based SYNTAX score II might be a good prognostic predictor in multivessel disease patients with different risk stratification.

SYNTAX score was a classical anatomy score system to predict the prognosis of multivessel disease patients. In high-risk SS multivessel disease patients, coronary artery bypass surgery (CABG) showed a mortality benefit over PCI [19, 20]. SYNTAX score II decreased the bias of clinical factors by bringing the factors of age, creatinine clearance (CrCl), LVEF, sex, left main lesion, chronic obstructive pulmonary disease (COPD), and peripheral vascular disease (PVD) into the calculation. It even showed a better predictive ability than SS in PCI patients with complex coronary disease [2, 21]. In this study, we calculated SSII cut-off values of 28, 28–38, and $>$38 based on the ROC analysis (AUC = 0.669, 95% CI: 0.590–0.741, p = 0.033, Fig. 4). Using this criterion, high-, medium- and low-risk groups showed significant differences in the survival-free ratio from MACEs (log-rank risk, p 0.001). Considering the unclear cut-off value of SSII in most studies, 28, 28–38, $>$38 were used for risk stratification in the SSII criterion.

Fig. 4.

Receiver-operator characteristic (ROC) curve analysis of SS and SSII for MACE patients. (A) The predictive ability of SS in diagnosis of MACE in all patients. (B) The predictive ability of SSII in diagnosis of MACEs in all patients. SSII, SYNTAX score II; AUC, area under the curve; SS, SYNTAX score; MACE, major adverse cardiovascular event.

Nam et al. [11] integrated the SS and FFR to develop the concept of the functional SYNTAX score. They calculated the SS only in vessels with low FFR ($\le$0.8) and showed that the FSS better predicted clinical outcomes than SS. Subsequently, 38% of patients in the high-risk SS tertile were moved to the medium- or lowest-risk FSS groups, whereas 59% of the medium-risk SS tertile moved to the lowest-risk FSS group [11]. In this study, we sought to prove the ability of non-invasive functional integrated scores such as the SS or SSII to predict MACEs. The accuracy of QFR has been shown to better identify hemodynamically significant coronary stenosis compared with FFR [13]. In a study by Smit et al. [18], 181 (54.2%) coronary arteries had a QFR value $\ge$0.86, and only 9 (5.0%) of these coronary arteries had an invasive FFR of $\le$0.80. Based on the cut-off value of 0.85, functional SS and SSII were used to reclassify the risk stratification groups of patients in our study. The results showed that high-risk patients were resigned into medium- and low-risk patients after either SS or SSII were corrected by QFR (Fig. 1). There was no significant difference in the different groups in SS score; however, FSS, SSII, and FSSII showed marked differences in these corresponding groups. Only 4 (2.5%) patients were reassigned from the high-risk group into the medium-risk group, guided by FSSII (Fig. 1).

Studies on the value of FFR after PCI when predicting the prognosis of patients are relatively common [11], but there are still few studies on QFR after PCI [16]. In the study by Xu et al. [22], a QFR-guided PCI strategy improved 1-year clinical outcomes of patients compared with standard angiography guidance. We analyzed the Kaplan–Meier curves in different groups under different scoring systems to evaluate the prognostic value of the different score systems. We found that after recalculation using FSS, the survival free ratio from MACEs in different risk stratifications showed significant differences in high-, medium- and low-risk groups compared with SS (log-risk p = 0.089 in SS, log-risk p = 0.014 in FSS). In Table 3, the univariable analysis showed no significant impact on MACEs when clinical factors were independently assessed, except LVEF. However, when clinical factors were integrated into SS for SSII, either SSII (HR: 1.072, 95% CI: 1.026–1.120, p = 0.002) or FSSII (HR: 1.069, 95% CI: 1.025–1.115, p = 0.002) showed significant effects on MACEs. In addition, based on FSSII risk stratification, survival-free from the MACE ratio decreased from 38.48% to 27.27% in the high-risk group and increased from 84.09% to 86.05% in the low-risk group compared with SSII risk stratification. Considering these results, FSSII may be an appropriate scoring system to predict MACEs in patients with different risk stratification.

Unfortunately, FSSII showed better AUC in predicting MACEs, but it did not result in statistically significant results compared with the FSS system (p = 0.881). rSS, rFSS, rSSII, and rFSSII were also analyzed in this study. Even though they were independent predictors of MACEs, they did not meet statistical significance when compared. In recent studies, 0.80 was used for the cut-off value to decide the physiological function of lesions [22, 23]. A lower cut-off value will change the number of patients in different risk stratification based on the FSSII system. Considering the cut-off value and sample size, a further study based on the results of this study may enhance the predictive ability of FSSII.

This study’s limitation was its small sample size, which lowered its statistical efficiency. Furthermore, some studies showed that 0.80 could be a possible cut-off value for QFR. Therefore, the different criteria of QFR may also affect the efficacy of FSSII in predicting MACEs. Moreover, the discrepancy between different methods of calculating QFR was also a factor that may affect the result. Considering these limitations, our ongoing prospective study with a bigger sample may provide more definitive results in the near future.

Compared with classical SS and SSII, FSS and FSSII provided better risk stratification criteria to predict the occurrence of MACEs by regrouping patients. SSII and FSSII might be good predictors for MACEs in multivessel patients.

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

SYZ, MW and QG: Conceptualization, Investigation, Writing – original draft. XRZ, YC and SFG: Patient follow-up management, Data collection, Writing – review & editing. XXX, JSW and XKQ: Data analysis, Statistics and Writing – review & editing; WZH: Conceptualization, Design, Critical article revision. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

This observational study was approved by the lead ethical committee of Huadong Hospital (No. 2020K064). Written informed consent was obtained from the parents.

Not applicable.

This study was supported by Research subject of Shanghai Municipal Health Commission (202040298) and Clinical research project of Huadong Hospital (HDLC2022014).

The authors declare no conflict of interest.