Advertisement

Clinical Research in Cardiology

, Volume 108, Issue 2, pp 222–222 | Cite as

Novel ECG-based scoring tool for prediction of takotsubo syndrome

  • Natig GassanovEmail author
  • Minh Tam Le
  • Evren Caglayan
  • Martin Hellmich
  • Erland Erdmann
  • Fikret Er
Letter to the Editors
  • 221 Downloads

Sirs:

We thank Dr. Madias for his interest and valuable comments regarding our manuscript [1].

In the current study, we investigated ECG changes in patients with takotsubo syndrome (TS) and acute myocardial infarction (AMI), and established a scoring tool for discriminating TS from AMI. For this purpose, we analyzed ECG obtained in the very early phase after symptom onset.

The authors agree that diminished QRS voltage along with some other described ECG findings are not static and undergo dynamic transition during further course of the illness [2, 3, 4]. However, we were particularly interested in the initial ECG recording, since our aim was to analyze the diagnostic utility of ECG in acute setting, and possibly, help to select the appropriate treatment strategy.

As expected, the prevalence of diabetes mellitus (DM) in TS patients in our population cohort was lower (13 resp. 11% for evaluation and validation group) compared with AMI patients. The overall prevalence of DM in the surrounding region of Cologne and Gütersloh is approximately 9.3 resp. 8.95% [5]. No exact epidemiological data for DM prevalence in people at 60–70 years age in both regions could be found. According to the statistical data from German statutory health insurance funds, the DM prevalence in German population is currently 14.5% among the 60–69 years old persons [6]. Hence, we assume that DM prevalence for the same age group would be similar in both described geographical parts of Germany.

References

  1. 1.
    Gassanov N, Le MT, Caglayan E, Hellmich M, Erdmann E, Er F (2018) Novel ECG-based scoring tool for prediction of takotsubo syndrome. Clin Res Cardiol.  https://doi.org/10.1007/s00392-018-1314-3 Google Scholar
  2. 2.
    Namgung J (2014) Electrocardiographic findings in takotsubo cardiomyopathy: ECG evolution and its difference from the ECG of acute coronary syndrome. Clin Med Insights Cardiol 8:29–34CrossRefGoogle Scholar
  3. 3.
    Mitsuma W, Kodama M, Ito M, Tanaka K, Yanagawa T, Ikarashi N, Sugiura K, Kimura S, Yagihara N, Kashimura T, Fuse K, Hirono S, Okura Y, Aizawa Y (2007) Serial electrocardiographic findings in women with takotsubo cardiomyopathy. Am J Cardiol 100:106–109CrossRefGoogle Scholar
  4. 4.
    Mugnai G, Vassanelli F, Pasqualin G, Benfari G, Rebonato M, Pesarini G, Zanolla L, Menegatti G, Vassanelli C (2015) Dynamic changes of repolarization abnormalities in takotsubo cardiomyopathy. Acta Cardiol 70:225–232CrossRefGoogle Scholar
  5. 5.
    Goffrier B, Schulz M, Bätzing-Feigenbaum J. Administrative Prävalenzen und Inzidenzen des Diabetes mellitus von 2009 bis 2015. Zentralinstitut für die kassenärztliche Versorgung in Deutschland (Zi). Versorgungsatlas-Bericht Nr. 17/03. Berlin 2017. https://www.versorgungsatlas.de/themen/alle-analysen-nach-datum-sortiert/?tab=1&uid=79. Accessed 2017
  6. 6.
    Tamayo T, Brinks R, Hoyer A, Kuß O, Rathmann W. The prevalence and incidence of diabetes in Germany. Dtsch Arztebl Int 113(11):177–182.  https://doi.org/10.3238/arztebl.2016.0177

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Klinikum GüterslohGüterslohGermany
  2. 2.Department of CardiologyUniversity of RostockRostockGermany
  3. 3.Institute of Medical Statistics, Epidemiology and Computer ScienceUniversity of CologneCologneGermany
  4. 4.Department of Internal Medicine IIIUniversity of CologneCologneGermany

Personalised recommendations