Machine learning prediction model of acute kidney injury after percutaneous coronary intervention

Acute kidney injury (AKI) after percutaneous coronary intervention (PCI) is associated with a significant risk of morbidity and mortality. The traditional risk model provided by the National Cardiovascular Data Registry (NCDR) is useful for predicting the preprocedural risk of AKI, although the scoring system requires a number of clinical contents. We sought to examine whether machine learning (ML) techniques could predict AKI with fewer NCDR-AKI risk model variables within a comparable PCI database in Japan. We evaluated 19,222 consecutive patients undergoing PCI between 2008 and 2019 in a Japanese multicenter registry. AKI was defined as an absolute or a relative increase in serum creatinine of 0.3 mg/dL or 50%. The data were split into training (N = 16,644; 2008–2017) and testing datasets (N = 2578; 2017–2019). The area under the curve (AUC) was calculated using the light gradient boosting model (GBM) with selected variables by Lasso and SHapley Additive exPlanations (SHAP) methods among 12 traditional variables, excluding the use of an intra-aortic balloon pump, since its use was considered operator-dependent. The incidence of AKI was 9.4% in the cohort. Lasso and SHAP methods demonstrated that seven variables (age, eGFR, preprocedural hemoglobin, ST-elevation myocardial infarction, non-ST-elevation myocardial infarction/unstable angina, heart failure symptoms, and cardiogenic shock) were pertinent. AUC calculated by the light GBM with seven variables had a performance similar to that of the conventional logistic regression prediction model that included 12 variables (light GBM, AUC [training/testing datasets]: 0.779/0.772; logistic regression, AUC [training/testing datasets]: 0.797/0.755). The AKI risk model after PCI using ML enabled adequate risk quantification with fewer variables. ML techniques may aid in enhancing the international use of validated risk models.

Stent Fractures: New Insights into an Old Issue

Percutaneous coronary intervention (PCI) is a safe and effective procedure performed worldwide providing both symptom relief and sustained improved outcomes for millions of patients [...]

Effect of angiotensin converting enzyme gene polymorphism on patients with in-stent restenosis after percutaneous coronary intervention

Purpose: To evaluate the association between common single nucleotide polymorphisms (SNPs) in angiotensin converting enzyme (ACE) gene and the risk of in-stent restenosis (ISR) and/or the response to angiotensin converting enzyme inhibitor ACEI in individuals with stable coronary artery disease (CAD) after stent implantation. Methods: The total population of this study consisted of 200 Egyptian individuals divided into 2 groups - in-stent restenosis (ISR) and non ISR group). Genomic DNA was withdrawn from EDTA whole blood applying a spin column approach and ACE gene insertion/deletion (I/D) polymorphisms were determined by polymerase chain reaction (PCR). Results: Carriers of allele D of ACE gene were significantly more liable to ISR occurrence. However, carriers of allele I were significantly more liable to ISR occurrence after administration of ACEI. There is a negative interaction between DD genotype of ACE gene and ACEI administration on ISR after percutaneous coronary intervention (PCI). However, there is a positive interaction between II and ID genotype of ACE gene and ACEI administration on ISR after PCI with bare metal stents (BMS). Conclusion: It is beneficial to implement ACEI in therapeutic regimen in individuals with ID or II genotypes of ACE gene, especially with BMS implementation.

A Novel Multiple Risk Score Model for Prediction of Long-Term Ischemic Risk in Patients With Coronary Artery Disease Undergoing Percutaneous Coronary Intervention: Insights From the I-LOVE-IT 2 Trial

Backgrounds: A plug-and-play standardized algorithm to identify the ischemic risk in patients with coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI) could play a valuable step to help a wide spectrum of clinic workers. This study intended to investigate the ability to use the accumulation of multiple clinical routine risk scores to predict long-term ischemic events in patients with CAD undergoing PCI.Methods: This was a secondary analysis of the I-LOVE-IT 2 (Evaluate Safety and Effectiveness of the Tivoli drug-eluting stent (DES) and the Firebird DES for Treatment of Coronary Revascularization) trial, which was a prospective, multicenter, and randomized study. The Global Registry for Acute Coronary Events (GRACE), baseline Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX), residual SYNTAX, and age, creatinine, and ejection fraction (ACEF) score were calculated in all patients. Risk stratification was based on the number of these four scores that met the established thresholds for the ischemic risk. The primary end point was ischemic events at 48 months, defined as the composite of cardiac death, nonfatal myocardial infarction, stroke, or definite/probable stent thrombosis (ST).Results: The 48-month ischemic events had a significant trend for higher event rates (from 6.61 to 16.93%) with an incremental number of risk scores presenting the higher ischemic risk from 0 to ≥3 (p trend < 0.001). In addition, the categories were associated with increased risk for all components of ischemic events, including cardiac death (from 1.36 to 3.15%), myocardial infarction (MI) (from 3.31 to 9.84%), stroke (3.31 to 6.10%), definite/probable ST (from 0.58 to 1.97%), and all-cause mortality (from 2.14 to 6.30%) (all p trend < 0.05). The net reclassification index after combined with four risk scores was 12.5% (5.3–20.0%), 9.4% (2.0–16.8%), 12.1% (4.5–19.7%), and 10.7% (3.3–18.1%), which offered statistically significant improvement in the performance, compared with SYNTAX, residual SYNTAX, ACEF, and GRACE score, respectively.Conclusion: The novel multiple risk score model was significantly associated with the risk of long-term ischemic events in these patients with an increment of scores. A meaningful improvement to predict adverse outcomes when multiple risk scores were applied to risk stratification.

A Prognostic Merit of Statins in Patients with Chronic Hemodialysis after Percutaneous Coronary Intervention—A 10-Year Follow-Up Study

Background: Patients with end-stage renal disease (ESRD) on chronic hemodialysis who are complicated by coronary artery disease (CAD) are at very high risk of cardiovascular (CV) events and mortality. However, the prognostic benefit of statins, which is firmly established in the general population, is still under debate in this particular population. Methods: As a part of a prospective single-center percutaneous coronary intervention (PCI) registry database, this study included consecutive patients on chronic hemodialysis who underwent PCI for the first time between 2000 and 2016 (n = 201). Participants were divided into 2 groups by following 2 factors, such as (1) with or without statin, and (2) with or without high LDL-C (> and ≤LDL-C = 93 mg/dL, median) at the time of PCI. The primary endpoint was defined as CV death, and the secondary endpoints included all-cause and non-CV death, and 3 point major cardiovascular adverse events (3P-MACE) which is the composite of CV death, non-fatal myocardial infarction and stroke. The median and range of the follow-up period were 2.8, 0–15.2 years, respectively. Results: Kaplan–Meier analyses showed significantly lower cumulative incidences of primary and secondary endpoints other than non-CV deaths in patients receiving statins. Conversely, no difference was observed when patients were divided by the median LDL-C at the time of PCI (p = 0.11). Multivariate Cox proportional hazard analysis identified statins as an independent predictor of reduced risk of CV death (Hazard ratio of statin use: 0.43, 95% confidence interval 0.18–0.88, p = 0.02), all-cause death (HR: 0.50, 95%CI 0.29–0.84, p = 0.007) and 3P-MACE (HR: 0.50, 95%CI 0.25–0.93, p = 0.03). Conclusions: Statins were associated with reduced risk of adverse outcomes in patients with ESRD following PCI.