Journal of Clinical Medicine (Mar 2021)

External Validation and Extension of a Clinical Score for the Discrimination of Type 2 Myocardial Infarction

  • Thomas Nestelberger,
  • Pedro Lopez-Ayala,
  • Jasper Boeddinghaus,
  • Ivo Strebel,
  • Maria Rubini Gimenez,
  • Iris Huber,
  • Karin Wildi,
  • Desiree Wussler,
  • Luca Koechlin,
  • Alexandra Prepoudis,
  • Danielle M. Gualandro,
  • Christian Puelacher,
  • Noemi Glarner,
  • Philip Haaf,
  • Simon Frey,
  • Adam Bakula,
  • Rupprecht Wick,
  • Òscar Miró,
  • F. Javier Martin-Sanchez,
  • Damian Kawecki,
  • Dagmar Keller,
  • Raphael Twerenbold,
  • Christian Mueller

DOI
https://doi.org/10.3390/jcm10061264
Journal volume & issue
Vol. 10, no. 6
p. 1264

Abstract

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Background: The early non-invasive discrimination of Type 2 versus Type 1 Myocardial Infarction (T2MI, T1MI) is a major unmet clinical need. We aimed to externally validate a recently derived clinical score (Neumann) combing female sex, no radiating chest pain, and high-sensitivity cardiac troponin I (hs-cTnI) concentration ≤40.8 ng/L. Methods: Patients presenting with acute chest discomfort to the emergency department were prospectively enrolled into an international multicenter diagnostic study. The final diagnoses of T2MI and T1MI were centrally adjudicated by two independent cardiologists using all information including cardiac imaging and serial measurements of hs-cTnT/I according to the fourth universal definition of MI. Model performance for T2MI diagnosis was assessed by formal tests and graphical means of discrimination and calibration. Results: Among 6684 enrolled patients, MI was the adjudicated final diagnosis in 1079 (19%) patients, of which 242 (22%) had T2MI. External validation of the Neumann Score showed a moderate discrimination (C-statistic 0.67 (95%CI 0.64–0.71)). Model calibration showed underestimation of the predicted probabilities of having T2MI for low point scores. Model extension by adding the binary variable heart rate >120/min significantly improved model performance (C-statistic 0.73 (95% CI 0.70–0.76, p 120/min improved the model’s performance.

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