Cardiovascular outcomes following percutaneous coronary intervention with drug-eluting balloons in chronic kidney disease: a retrospective analysis

Predictive modeling for acute kidney injury after percutaneous coronary intervention in patients with acute coronary syndrome: a machine learning approach

BACKGROUND

Acute kidney injury (AKI) is one of the preventable complications of percutaneous coronary intervention (PCI). This study aimed to develop machine learning (ML) models to predict AKI after PCI in patients with acute coronary syndrome (ACS).

METHODS

This study was conducted at Tehran Heart Center from 2015 to 2020. Several variables were used to design five ML models: Naïve Bayes (NB), Logistic Regression (LR), CatBoost (CB), Multi-layer Perception (MLP), and Random Forest (RF). Feature importance was evaluated with the RF model, CB model, and LR coefficients while SHAP beeswarm plots based on the CB model were also used for deriving the importance of variables in the population using pre-procedural variables and all variables. Sensitivity, specificity, and the area under the receiver operating characteristics curve (ROC-AUC) were used as the evaluation measures.

RESULTS

A total of 4592 patients were included, and 646 (14.1%) experienced AKI. The train data consisted of 3672 and the test data included 920 cases. The patient population had a mean age of 65.6 ± 11.2 years and 73.1% male predominance. Notably, left ventricular ejection fraction (LVEF) and fasting plasma glucose (FPG) had the highest feature importance when training the RF model on only pre-procedural features. SHAP plots for all features demonstrated LVEF and age as the top features. With pre-procedural variables only, CB had the highest AUC for the prediction of AKI (AUC 0.755, 95% CI 0.713 to 0.797), while RF had the highest sensitivity (75.9%) and MLP had the highest specificity (64.35%). However, when considering pre-procedural, procedural, and post-procedural features, RF outperformed other models (AUC: 0.775). In this analysis, CB achieved the highest sensitivity (82.95%) and NB had the highest specificity (82.93%).

CONCLUSION

Our analyses showed that ML models can predict AKI with acceptable performance. This has potential clinical utility for assessing the individualized risk of AKI in ACS patients undergoing PCI. Additionally, the identified features in the models may aid in mitigating these risk factors.

Clinical Outcome of Paclitaxel-Coated Balloon Angioplasty Versus Drug-Eluting Stent Implantation for the Treatment of Coronary Drug-Eluting Stent In-Stent Chronic Total Occlusion

AIMS

In-stent chronic total occlusion (IS-CTO) represents a unique challenge for percutaneous coronary intervention. Whether the optimal treatment for IS-CTO is angioplasty with paclitaxel-coated balloons (PCBs) or repeat stenting with drug-eluting stents (DESs) is unclear. We aimed to evaluate the long-term clinical outcome of PCB angioplasty and DES repeat stenting for DES IS-CTO.

METHODS

We retrospectively included patients with DES IS-CTO who underwent successful PCB angioplasty or DES repeat stenting from January 2016 to December 2019. The primary endpoints were major adverse cardiac events (MACEs), including cardiac death, myocardial infarction, and target lesion revascularization (TLR). Cox proportional hazards model was performed to compare the risk of MACEs between PCB angioplasty and DES repeat stenting, and to further explore the prognostic factors of patients with DES IS-CTO.

RESULTS

A total of 214 patients with DES IS-CTO were enrolled: 78 patients (36.4%) treated with PCB and 136 patients (63.6%) treated with DES respectively. The median follow-up was 1160 days, and MACEs were observed in 28.2% of patients with PCB angioplasty versus 26.5% of patients with DES repeat stenting (P = 0.784), mainly driven by TLR (21.8% vs. 19.9%, P = 0.735). There was no significant difference in the risk of MACEs between the PCB group and the DES group (hazard ratio [HR] 1.25, 95% confidence interval [CI] 0.64-2.46, P = 0.512). Multivariate Cox analysis revealed that chronic kidney disease and ≥ 3 stent layers in the lesion were independent predictors of MACEs, while switching to another antiproliferative drug was an independent protective factor (all P < 0.05).

CONCLUSIONS

PCB angioplasty was an effective alternative treatment strategy for DES IS-CTO, which had similar long-term outcomes to DES repeat stenting in contemporary practice, but both were accompanied by a high rate of long-term MACEs. Improving the poor prognosis of patients with DES IS-CTO remains a challenge.

Effect of glomerular filtration rate in patients undergoing percutaneous coronary intervention: A systematic review and meta-analysis

BACKGROUND

Through meta-analysis of the relationship between glomerular filtration rate and major adverse cardiovascular events (MACE) after percutaneous coronary intervention (PCI), we studied the impact of glomerular filtration rate on the prognosis of PCI.

METHODS

We collected literature on the incidence of MACE in patients with chronic kidney disease (CKD; estimated glomerular filtration rate < 60 mL/minute/1.73 m2) and patients with nonchronic kidney disease undergoing PCI. The search period was from January 1, 2000, to November 1, 2021. The searched databases included CNKI, Chinese Wanfang Data, China Biology Medicine disc, Web of Science, PubMed, and Cochrane Library. We used subgroup analysis and meta-regression to assess heterogeneity.

RESULTS

Twenty-one eligible studies were included, with 46,255 samples included, 4903 cases of MACE (10.6%), and patients with CKD had a higher risk of MACE after PCI (Risk ratios = 1.67; 95% confidence interval: 1.51-1.85). Multivariate meta regression results show that heterogeneity is related to region. The risk of MACEs in patients with CKD is different in different regions, and North America has the lowest risk, with an risk ratios value of 1.21 (95% confidence interval: 1.08-1.35).

CONCLUSION

Chronic kidney disease will increase the probability of MACE in patients with myocardial infarction after PCI and affect the prognosis of PCI. Therefore, clinical attention should be given to assessing glomerular filtration rate effects while treating patients with myocardial infarction with the PCI procedure.