A clinically applicable prediction model for the risk of in-hospital mortality in solid cancer patients admitted to intensive care units with sepsis
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cancer Research,Oncology,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00432-023-04661-x.pdf
Reference32 articles.
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2. Awad WB, Nazer L, Elfarr S, Abdullah M, Hawari F (2021) A 12-year study evaluating the outcomes and predictors of mortality in critically ill cancer patients admitted with septic shock. BMC Cancer 21(1):709. https://doi.org/10.1186/s12885-021-08452-w
3. Bou Chebl R, Safa R, Sabra M, Chami A, Berbari I, Jamali S et al (2021) Sepsis in patients with haematological versus solid cancer: a retrospective cohort study. BMJ Open 11(2):e038349. https://doi.org/10.1136/bmjopen-2020-038349
4. Burnham KP, Anderson DR (2004) Multimodel inference—understanding AIC and BIC in model selection. Sociol Methods Res 33(2):261–304. https://doi.org/10.1177/0049124104268644
5. Cheng J, Sun J, Yao K, Xu M, Cao Y (2022) A variable selection method based on mutual information and variance inflation factor. Spectrochim Acta A Mol Biomol Spectrosc 268:120652. https://doi.org/10.1016/j.saa.2021.120652
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1. Interpretable machine learning model for early prediction of delirium in elderly patients following intensive care unit admission: a derivation and validation study;Frontiers in Medicine;2024-05-17
2. Cancer and sepsis;Clinical Science;2023-06
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