Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated encephalopathy

HIGHLIGHTS

• who: Liwei Peng from the Department of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, No, Xinsi Road, Xiu2019an, China have published the article: Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated encephalopathy, in the Journal: (JOURNAL)
• what: This study aimed to investigate independent factors and then develop predictive models to quantitatively predict the likelihood of 30-day mortality in patients with SAE. In this study, fifteen variables were identified as risk factors, involving APSIII, GCS, SOFA, CCI, RDW, BUN, age, respiratory rate, u00adPaO2, temperature, lactate, CRE, malignant cancer . . .
  

   

  

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