Over the past decades, several ECG-based parameters have been identified as independent predictors of worsened prognosis in affected patients. In addition to visual assessment of morphology, methods of computer-based machine ECG analysis have gained importance in recent years. These methods allow the detection of systemic abnormalities in ECGs that are not visible to the naked eye. An example of this is provided by the so-called "QRS microfragmentations".

The aim of this evaluation is to retrospectively collect all established as well as new quantitative and qualitative ECG parameters (such as QRS microfragmentation) in a large patient collective. Subsequently, after characterization of the patients, an independent multivariate risk prediction model should be developed based on computer-based ECG analysis using maschnine learning algorithms.

Inclusion Criteria:

• Patients who presented to the Department of Internal Medicine at the Medical University in Innsbruck between 01.01.2000 and 31.07.2022 and received an ECG recording as part of routine clinical practice.
• Age ≥ 18 years
• Residence in Austria

Exclusion Criteria:

• Insuffizient ECG Recording quality

Patients who presented to the Department of Internal Medicine at the Medical University in Innsbruck between 01.01.2000 and 31.07.2022 and received an ECG recording as part of routine clinical practice.

IPD will be shared upon reasonable request and after concluding all legal and ethic formalities.