Adaptation of risk prediction equations for cardiovascular outcomes among patients with type 2 diabetes in real-world settings: a cross-institutional study using common data model approach
Authors' conclusion
We provide valid risk prediction equations for MI, stroke, and HF outcomes in Taiwanese type 2 diabetes populations. A framework for adapting risk equations across institutions is also proposed.
Study context
- Population
- Patients with T2D in real-world settings, electronic health records (EHRs) of two medical centers in Taiwan (National Cheng Kung University Hospital (NCKUH), National Taiwan University Hospital (NTUH))NCKUH 11,740
- Comparison
- UKPDS-OM2, RECODe and CHIME risk equations for myocardial infarction (MI), stroke and heart failure (HF)
- Outcome
- External validation of risk equations for MI, stroke and HF: discrimination (AUROC) and calibration (calibration slopes and intercepts, GND test)
Methodological detailselectronic health records, common data model approach, two medical centers
- Electronic health records
- Common data model approach
- Two medical centers
Performance
As reported in the abstract
| Test or model | Value | AUROC |
|---|---|---|
| CHIME | 0.71-0.79 | 0.71-0.79 |
CHIME
Value0.71-0.79
AUROC0.71-0.79
Further findings
Calibration slopes/intercepts after recalibration, NCKUH
- CHIME-MI
- 0.9848/- 0.0008
- CHIME-stroke
- 1.1003/- 0.0046
- CHIME-HF
- 0.9436/0.0063
Calibration slopes/intercepts after recalibration, NTUH
- CHIME-MI
- 1.1060/- 0.0011
- CHIME-stroke
- 0.8714/0.0030
- CHIME-HF
- 1.0476/- 0.0016
Greenwood-Nam-D'Agostino (GND) test after recalibration
- All recalibrated risk equations showed satisfactory calibration
- p-values of GND tests ≥ 0.05
Original publication
Adaptation of risk prediction equations for cardiovascular outcomes among patients with type 2 diabetes in real-world settings: a cross-institutional study using common data model approach. Cardiovasc Diabetol. Published 10 July 2024. doi:10.
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