Nomogram establishment for short-term survival prediction in ICU patients with aplastic anemia based on the MIMIC-IV database.

Autor:	Tu Y; Department of Hematology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China., Zhang J; Department of Hematology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China., Zhao M; Department of Hematology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China., He F; Department of Hematology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China.
Jazyk:	angličtina
Zdroj:	Hematology (Amsterdam, Netherlands) [Hematology] 2024 Dec; Vol. 29 (1), pp. 2339778. Date of Electronic Publication: 2024 Apr 16.
DOI:	10.1080/16078454.2024.2339778
Abstrakt:	Objective: To establish an efficient nomogram model to predict short-term survival in ICU patients with aplastic anemia (AA). Methods: The data of AA patients in the MIMIC-IV database were obtained and randomly assigned to the training set and testing set in a ratio of 7:3. Independent prognosis factors were identified through univariate and multivariate Cox regression analyses. The variance inflation factor was calculated to detect the correlation between variables. A nomogram model was built based on independent prognostic factors and risk scores for factors were generated. Model performance was tested using C-index, receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA) and Kaplan-Meier curve. Results: A total of 1,963 AA patients were included. A nomogram model with 7 variables was built, including SAPS II, chronic pulmonary obstructive disease, body temperature, red cell distribution width, saturation of peripheral oxygen, age and mechanical ventilation. The C-indexes in the training set and testing set were 0.642 and 0.643 respectively, indicating certain accuracy of the model. ROC curve showed favorable classification performance of nomogram. The calibration curve reflected that its probabilistic prediction was reliable. DCA revealed good clinical practicability of the model. Moreover, the Kaplan-Meier curve showed that receiving mechanical ventilation could improve the survival status of AA patients in the short term but did not in the later period. Conclusion: The nomogram model of the short-term survival rate of AA patients was built based on clinical characteristics, and early mechanical ventilation could help improve the short-term survival rate of patients.
Databáze:	MEDLINE
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