Machine learning models for prediction of adverse events after percutaneous coronary intervention
Niimi N, Shiraishi Y, Sawano M, Ikemura N, Inohara T, Ueda I, Fukuda K, Kohsaka S. Machine learning models for prediction of adverse events after percutaneous coronary intervention. Scientific Reports 2022, 12: 6262. PMID: 35428765, PMCID: PMC9012739, DOI: 10.1038/s41598-022-10346-1.Peer-Reviewed Original ResearchConceptsPercutaneous coronary interventionAdverse eventsRisk scoreHospital mortalityCoronary interventionConsecutive coronary artery disease patientsCoronary artery disease patientsAdverse periprocedural eventsLow-risk patientsMajor adverse eventsGood discriminationMulticenter registryPeriprocedural eventsDisease patientsClinical decisionLogistic regressionSpecific interventionsRisk predictionOverall risk predictionPatientsScoresInterventionMortalityAdequate discriminationOutcomes