Validation of the ARIC prediction model for sudden cardiac death in the European population: The ESCAPE-NET project
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Dokumenter
- Fulltext
Forlagets udgivne version, 989 KB, PDF-dokument
Background: Sudden cardiac death is responsible for 10% to 20% of all deaths in Europe. The current study investigates how well the risk of sudden cardiac death can be predicted. To this end, we validated a previously developed prediction model for sudden cardiac death from the Atherosclerosis Risk in Communities study (USA). Methods: Data from participants of the Copenhagen City Heart Study (CCHS) (n=9988) was used to externally validate the previously developed prediction model for sudden cardiac death. The model's performance was assessed through discrimination (C-statistic) and calibration by the Hosmer-Lemeshow goodness-of-fit (HL) statistics suited for censored data and visual inspection of calibration plots. Additional validation was performed using data from the Hoorn Study (N=2045), employing the same methods. Results: During ten years of follow-up of CCHS participants (mean age: 58.7 years, 56.2% women), 425 experienced SCD (4.2%). The prediction model showed good discrimination for sudden cardiac death risk (C-statistic: 0.81, 95% CI: 0.79-0.83). Calibration was robust (HL statistic: P=0.8). Visual inspection of the calibration plot showed that the calibration could be improved. Sensitivity was 89.8%, and specificity was 60.6%. The positive and negative predictive values were 10.1% and 99.2%. Model performance was similar in the Hoorn Study (C-statistic: 0.81, 95% CI: 0.77-0.85 and the HL statistic: 1.00). Conclusion: Our study showed that the previously developed prediction model in North American adults performs equally well in identifying those at risk for sudden cardiac death in a general North-West European population. However, the positive predictive value is low.
Originalsprog | Engelsk |
---|---|
Tidsskrift | American Heart Journal |
Vol/bind | 262 |
Sider (fra-til) | 55-65 |
ISSN | 0002-8703 |
DOI | |
Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:
This work was supported by the European Union's Horizon 2020 research and innovation program ESCAPE-NET [grant number 733381 ] and the COST Action PARQ (grant agreement No CA19137 ) supported by COST (European Cooperation in Science and Technology).
Publisher Copyright:
© 2023 The Author(s)
ID: 348163192