Nomogram for Predicting in-Hospital Severe Complications in Patients with Acute Myocardial Infarction Admitted in Emergency Department
Yaqin Song, Kongzhi Yang, Yingjie Su, Kun Song, Ning Ding · 2024
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Description
Yaqin Song and co-authors build a chart-based tool to predict severe complications during hospital care for heart attack patients. Such models are lacking for patients admitted through emergency departments. The study covers 1,024 patients treated at one hospital in Changsha between 2020 and 2023. About 717 patients form the group used to build the model, and 307 form the test group.
Analysis of admission data finds seven factors that independently predict severe complications. They are age, heart rate, mean arterial pressure, diabetes, hypertension, triglycerides, and white blood cell count. The team builds a nomogram, a scoring chart, from these seven factors. The chart predicts well in both groups. Calibration checks show predicted and observed rates agree closely, and a curve analysis shows the tool helps decisions across a wide range of risk thresholds. The authors offer it as practical support for emergency clinicians.
Catalog record
| CREATOR | Yaqin Song, Kongzhi Yang, Yingjie Su, Kun Song, Ning Ding |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 36 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |