Cargando…
Machine Learning Model Development and Validation for Predicting Outcome in Stage 4 Solid Cancer Patients with Septic Shock Visiting the Emergency Department: A Multi-Center, Prospective Cohort Study
A reliable prognostic score for minimizing futile treatments in advanced cancer patients with septic shock is rare. A machine learning (ML) model to classify the risk of advanced cancer patients with septic shock is proposed and compared with the existing scoring systems. A multi-center, retrospecti...
Autores principales: | Ko, Byuk Sung, Jeon, Sanghoon, Son, Donghee, Choi, Sung-Hyuk, Shin, Tae Gun, Jo, You Hwan, Ryoo, Seung Mok, Kim, Youn-Jung, Park, Yoo Seok, Kwon, Woon Yong, Suh, Gil Joon, Lim, Tae Ho, Kim, Won Young |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737041/ https://www.ncbi.nlm.nih.gov/pubmed/36498805 http://dx.doi.org/10.3390/jcm11237231 |
Ejemplares similares
-
Impact of 1-Hour Bundle Achievement in Septic Shock
por: Ko, Byuk Sung, et al.
Publicado: (2021) -
Early Vitamin C and Thiamine Administration to Patients with Septic Shock in Emergency Departments: Propensity Score-Based Analysis of a Before-and-After Cohort Study
por: Shin, Tae Gun, et al.
Publicado: (2019) -
Impact of COVID-19 Pandemic on Management and Outcomes in Patients with Septic Shock in the Emergency Department
por: Jeong, Daun, et al.
Publicado: (2022) -
Prognosis of patients excluded by the definition of septic shock based on their lactate levels after initial fluid resuscitation: a prospective multi-center observational study
por: Ko, Byuk Sung, et al.
Publicado: (2018) -
Prognostic accuracy of initial and 24-h maximum SOFA scores of septic shock patients in the emergency department
por: Kim, Tae Han, et al.
Publicado: (2023)