Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching

Lai, Honghao; Wu, Guoying; Zhong, Yu; Chen, Guangping; Zhang, Wei; Shi, Shengjun; Xia, Zenan

doi:10.1016/j.jointm.2023.02.005

Journal of Intensive Medicine

2023

DOI: 10.1016/j.jointm.2023.02.005

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Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching

Honghao Lai¹,

Guoying Wu²,

Yu Zhong³

et al.

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Early prediction of sepsis using a high-order Markov dynamic Bayesian network (HMDBN) classifier

Zhang,

Duan,

Hou

et al. 2023

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Early prediction of sepsis using a high-order Markov dynamic Bayesian network (HMDBN) classifier

Zhang,

Duan,

Hou

et al. 2023

Appl Intell

View full text Add to dashboard Cite

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Red blood cell distribution width improves the prediction of 28-day mortality for patients with sepsis-induced acute kidney injury: A retrospective analysis from MIMIC-IV database using propensity score matching

Cited by 1 publication

References 43 publications

Early prediction of sepsis using a high-order Markov dynamic Bayesian network (HMDBN) classifier

Early prediction of sepsis using a high-order Markov dynamic Bayesian network (HMDBN) classifier

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