Concerns with the new SYNTAX score

A nomogram model for predicting intramyocardial hemorrhage post-PCI based on SYNTAX score and clinical features

OBJECTIVE

The aim of this study is to develop a nomogram model for predicting the occurrence of intramyocardial hemorrhage (IMH) in patients with Acute Myocardial Infarction (AMI) following Percutaneous Coronary Intervention (PCI). The model is constructed utilizing clinical data and the SYNTAX Score (SS), and its predictive value is thoroughly evaluated.

METHODS

A retrospective study was conducted, including 216 patients with AMI who underwent Cardiac Magnetic Resonance (CMR) within a week post-PCI. Clinical data were collected for all patients, and their SS were calculated based on coronary angiography results. Based on the presence or absence of IMH as indicated by CMR, patients were categorized into two groups: the IMH group (109 patients) and the non-IMH group (107 patients). The patients were randomly divided in a 7:3 ratio into a training set (151 patients) and a validation set (65 patients). A nomogram model was constructed using univariate and multivariate logistic regression analyses. The predictive capability of the model was assessed using Receiver Operating Characteristic (ROC) curve analysis, comparing the predictive value based on the area under the ROC curve (AUC).

RESULTS

In the training set, IMH post-PCI was observed in 78 AMI patients on CMR, while 73 did not show IMH. Variables with a significance level of P < 0.05 were screened using univariate logistic regression analysis. Twelve indicators were selected for multivariate logistic regression analysis: heart rate, diastolic blood pressure, ST segment elevation on electrocardiogram, culprit vessel, symptom onset to reperfusion time, C-reactive protein, aspartate aminotransferase, lactate dehydrogenase, creatine kinase, creatine kinase-MB, high-sensitivity troponin T (HS-TnT), and SYNTAX Score. Based on multivariate logistic regression results, two independent predictive factors were identified: HS-TnT (Odds Ratio [OR] = 1.61, 95% Confidence Interval [CI]: 1.21-2.25, P = 0.003) and SS (OR = 2.54, 95% CI: 1.42-4.90, P = 0.003). Consequently, a nomogram model was constructed based on these findings. The AUC of the nomogram model in the training set was 0.893 (95% CI: 0.840-0.946), and in the validation set, it was 0.910 (95% CI: 0.823-0.970). Good consistency and accuracy of the model were demonstrated by calibration and decision curve analysis.

CONCLUSION

The nomogram model, constructed utilizing HS-TnT and SS, demonstrates accurate predictive capability for the risk of IMH post-PCI in patients with AMI. This model offers significant guidance and theoretical support for the clinical diagnosis and treatment of these patients.

Validation of UK-BCIS CHIP Score to Predict 1-Year Outcomes in a Contemporary United States Population

BACKGROUND

A complex high-risk indicated percutaneous coronary intervention (CHIP) score was recently developed from the British Cardiovascular Intervention Society (BCIS) database to define CHIP cases and their risk of in-hospital major adverse cardiac or cerebrovascular events (MACCE).

OBJECTIVES

The authors sought to apply this score to a contemporary U.S. population for the prediction of adverse events at 1 year following percutaneous coronary intervention (PCI).

METHODS

Consecutive patients undergoing PCI at a large tertiary care center between 2011 and 2020 were considered for inclusion. Patients were categorized into 4 groups based on their BCIS-CHIP score (0, 1-2, 3-4, ≥5). In each category, we assessed the 1-year risk of MACCE, a composite of all-cause death, myocardial infarction, and stroke. Secondary outcomes were the individual components of MACCE, and major bleeding at 1 year.

RESULTS

Among 20,799 patients included, MACCE at 1 year occurred in 1.7% patients with score 0 (reference), 3.0% with score 1 or 2 (HR: 1.72; 95% CI: 1.32-2.24), 6.1% with score 3 or 4 (HR: 3.60; 95% CI: 2.78-4.66), and 12.0% with score ≥5 (HR: 7.40; 95% CI: 5.75-9.51). Each point increase of the BCIS-CHIP score conferred a 28.0% increase of MACCE risk. The BCIS-CHIP score demonstrated good discrimination for the prediction of 1-year MACCE (C-index 0.70). The risk of secondary outcomes also progressively increased with higher score values.

CONCLUSIONS

In a large PCI registry, the BCIS-CHIP score had a good predictive value for MACCE at 1 year. The utilization of this score can facilitate an accurate risk stratification of patients undergoing PCI.

Comparative efficacy of eight therapeutic methods in the treatment of left main coronary artery disease: a Bayesian network meta-analysis protocol

INTRODUCTION

As for coronary artery bypass grafting, although there are many direct comparative studies on different minimally invasive methods and traditional thoracotomy (off-pump/on-pump), there is still a lack of further ranking and summary of the efficacy of all surgical methods for left main coronary artery (LMCA) lesions. Combined with the current controversial views, this study aims to introduce a planned network meta-analysis (NMA) in detail, with a view to comparing the long-term efficacy and safety of multiple therapeutic methods in the treatment of patients with LMCA disease, and finally providing some reference bases for the best selection of clinical schemes.

METHOD AND ANALYSIS

PubMed, Embase, Web of Science and The Cochrane Library databases will be collected from inception to June 2022 to compare the efficacy of different surgical methods in randomised controlled trials (RCTs) for LMCA disease. Main outcome endpoints: major adverse cardiovascular events, including mortality, myocardial infarction, stroke and revascularisation. Secondary outcome endpoints: (1) operation-related time, (2) the amount of blood transfusion, (3) complications including secondary thoracotomy, postoperative new atrial fibrillation, wound infection, (4) physiological score and psychological score, (5) time return to work and (6) total hospitalisation costs. The methodological quality of included RCTs will be assessed according to the Cochrane bias risk table. The Bayesian NMA will be conducted by STATA V.16.0.

ETHICS AND DISSEMINATION

The essence of this study is to summarise and analyse the original data without the approval of the ethics committee. Our research does not involve ethical issues, and the results will be published in peer-review journals.

PROSPERO REGISTRATION NUMBER

CRD42021274712.