Performance of 2019 ESC risk classification and the Steno type 1 risk engine in predicting cardiovascular events in adults with type 1 diabetes: A retrospective study
| Autor: | Nicola Tecce, Maria Masulli, Luisa Palmisano, Salvatore Gianfrancesco, Roberto Piccolo, Daniela Pacella, Lutgarda Bozzetto, Elena Massimino, Giuseppe Della Pepa, Roberta Lupoli, Olga Vaccaro, Gabriele Riccardi, Brunella Capaldo |
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| Přispěvatelé: | Tecce, Nicola, Masulli, Maria, Palmisano, Luisa, Gianfrancesco, Salvatore, Piccolo, Roberto, Pacella, Daniela, Bozzetto, Lutgarda, Massimino, Elena, Della Pepa, Giuseppe, Lupoli, Roberta, Vaccaro, Olga, Riccardi, Gabriele, Capaldo, Brunella |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Adult
Type 1 diabete Endocrinology Diabetes and Metabolism Risk Factor Cardiology General Medicine Risk Assessment STENO Type 1 risk engine Endocrinology Diabetes Mellitus Type 1 Cardiovascular Diseases Risk Factors Retrospective Studie Cardiovascular Disease Internal Medicine Humans Retrospective Studies 2019 ESC guideline Human |
| Popis: | The study compares the performance of the European Society of Cardiology (ESC) risk criteria and the Steno Type 1 Risk Engine (ST1RE) in the prediction of cardiovascular (CV) events.456 adults with type 1 diabetes (T1D) were retrospectively studied. During 8.5 ± 5.5 years of observation, twenty-four patients (5.2%) experienced a CV event. The predictive performance of the two risk models was evaluated by classical metrics and the event-free survival analysis.The ESC criteria show excellent sensitivity (91.7%) and suboptimal specificity (64.4 %) in predicting CV events in the very high CV risk group, but a poor performance in the high/moderate risk groups. The ST1RE algorithm shows a good predictive performance in all CV risk categories. Using ESC classification, the event-free survival analysis shows a significantly higher event rate in the very high CV risk group compared to the high/moderate risk group (p 0.0019). Using the ST1RE algorithm, a significant difference in the event-free survival curve was found between the three CV risk categories (p 0.0001).In T1D the ESC classification has a good performance in predicting CV events only in those at very high CV risk, whereas the ST1RE algorithm has a good performance in all risk categories. |
| Databáze: | OpenAIRE |
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