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New scoring system for predicting percutaneous coronary intervention of chronic total occlusion success: Impact of operator’s experience

BACKGROUND: Several scoring systems have been developed in order to predict percutaneous coronary intervention (PCI) result of chronic total occlusion (CTO). The scores principally include anatomic and clinical variables. Operator experience is a decisive factor for achieving successful result. We s...

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Detalles Bibliográficos
Autores principales: Mohandes, Mohsen, Moreno, Cristina, Fuertes, Mónica, Rojas, Sergio, Pernigotti, Alberto, Zambrano, Diego, Doblas, Victor, Fernández, Francisco, Guarinos, Jordi, Bardají, Alfredo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Via Medica 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10508064/
https://www.ncbi.nlm.nih.gov/pubmed/34581426
http://dx.doi.org/10.5603/CJ.a2021.0109
Descripción
Sumario:BACKGROUND: Several scoring systems have been developed in order to predict percutaneous coronary intervention (PCI) result of chronic total occlusion (CTO). The scores principally include anatomic and clinical variables. Operator experience is a decisive factor for achieving successful result. We sought to assess the real impact of operator growing experience on CTO-PCI success. METHODS: The angiographic and clinical variables of CTO-PCIs performed in our center between May 2007 and April 2021 were collected, and variables with potential association with procedural result were thoroughly reviewed. The influence of operator experience based on the number of previous CTO-PCIs was statistically assessed. A scoring system with combination of anatomic variables and operator experience was devised. RESULTS: A total of 540 PCIs in 457 patients were performed in our institution. The scoring model was developed from the derivation set (2/3 of the cohort). The final variables in logistic regression model were CTO length ≥ 20 mm, blunt stump, vessel tortuosity > 45° and operator experience < 100 PCIs. The model showed good performance in the derivation set (area under curve [AUC]: 0.768; confidence interval [CI]: 0706–0.830; p < 0.001) with no significant shrinkage in the validation set (AUC: 0.704; CI: 0.613–0.796; p < 0.001). CONCLUSIONS: This new score (E-CTO score) adequately predict the probability of CTO-PCI failure. The model includes a variable representing operator experience along with other anatomic variables.