Construction of risk prediction model and risk score table for infant heart failure hospital death based on white blood cell count to total protein ratio
The study analyzed 544 infants (1–36 months) with heart failure, aiming to correlate WBC/TP ratio with mortality and create a predictive model. Lasso regression identified significant mortality-associated clinical indices; logistic regression then built a death prediction model with an AUC of 0.755....
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
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| Series: | Heliyon |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025007455 |
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| Summary: | The study analyzed 544 infants (1–36 months) with heart failure, aiming to correlate WBC/TP ratio with mortality and create a predictive model. Lasso regression identified significant mortality-associated clinical indices; logistic regression then built a death prediction model with an AUC of 0.755. Calibration and DCA curves indicated model accuracy and clinical utility. Risk stratification revealed higher mortality in the high-risk group, emphasizing WBC/TP as predictors and the model's value for early high-risk patient identification in infant heart failure. |
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| ISSN: | 2405-8440 |