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ORIGINAL RESEARCH article
Front. Cardiovasc. Med.
Sec. Intensive Care Cardiovascular Medicine
Volume 12 - 2025 | doi: 10.3389/fcvm.2025.1538395
This article is part of the Research Topic Critical Care Cardiology for Cardiovascular Emergencies View all 13 articles
Development and Validation of a Nomogram for Predicting Survival in Patients With Cardiogenic Shock
Provisionally accepted- 1 Department of Geriatrics, Peking University First Hospital, Beijing, China
- 2 Health Science Centre, Peking University, Beijing, Beijing Municipality, China
- 3 Department of Sports Medicine and Cardiopulmonary Rehabilitation Center, Jiangbin Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
Background: There is currently a lack of easy-to-use tools for assessing the severity of cardiogenic shock (CS) patients. This study aims to develop a nomogram for evaluating severity in CS patients regardless of the underlying cause.Results: The MIMIC-IV database was used to identify 1923 CS patients admitted to the ICU. A multivariate Cox model was developed in the training cohort (70%) based on LASSO regression results. Factors such as age, systolic blood pressure, arterial oxygen saturation, hemoglobin, serum creatinine, blood glucose, arterial pH, arterial lactate, and norepinephrine use were incorporated into the final model. This model was visualized as a Cardiogenic Shock Survival Nomogram (CSSN) to predict 30-day survival rates. The model's c-statistic was 0.75 (95% CI 0.73-0.77) in the training cohort and 0.73 (95% CI 0.70-0.77) in the validation cohort, demonstrating good predictive accuracy. The AUC of the CSSN for 30day survival probabilities was 0.76 in the training cohort and 0.73 in the validation cohort. Calibration plots showed strong concordance between predicted and actual survival rates, and decision curve analysis (DCA) affirmed the model's clinical utility. The CSSN outperformed the Cardiogenic Shock Score (CSS) in various metrics, including c-statistic, time-dependent ROC, calibration plots, and DCA (c-statistic: 0.75 versus 0.72; AUC: 0.76 versus 0.73, P<0.01 by Delong test). Subgroup analysis confirmed the model's robustness across both AMI-CS and non-AMI-CS subgroups. Conclusions: The CSSN was developed to predict 30-day survival rates in CS patients irrespective of the underlying cause, showing good performance and potential clinical utility in managing CS.
Keywords: nomogram, Survival, Cardiogenic shock, Mortality, Mechanical circulatory support
Received: 02 Dec 2024; Accepted: 04 Apr 2025.
Copyright: © 2025 Fang, Chen, Geng, Chen and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Meilin Liu, Department of Geriatrics, Peking University First Hospital, Beijing, China
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