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Updated: Nov 9, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of a nomogram to predict the mortality risk in elderly patients with ARF
Junnan Xu1, Jie Weng2, Jingwen Yang3
1Department of Emergency Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China, China.
Background:
Acute respiratory failure (ARF) is a life-threatening complication in elderly patients. We developed a nomogram model to explore the risk factors of prognosis and the short-term mortality in elderly patients with ARF.
Methods:
A total of 759 patients from MIMIC-III database were categorized into the training set and 673 patients from our hospital were categorized into the validation set. Demographical, laboratory variables, SOFA score and APS-III score were collected within the first 24 h after the ICU admission. A 30-day follow-up was performed for all patients.
Results:
Multivariate logistic regression analysis showed that the heart rate, respiratoryrate, systolic pressure, SPO2, albumin and 24 h urine output were independent prognostic factors for 30-day mortality in ARF patients. A nomogram was established based on above independent prognostic factors. This nomogram had a C-index of 0.741 (95% CI [0.7058-0.7766]), and the C-index was 0.687 (95% CI [0.6458-0.7272]) in the validation set. The calibration curves both in training and validation set were close to the ideal model. The SOFA had a C-index of 0.653 and the APS-III had a C-index of 0.707 in predicting 30-day mortality.
Conclusion:
Our nomogram performed better than APS-III and SOFA scores and should be useful as decision support on the prediction of mortality risk in elderly patients with ARF.
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