BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

212 related articles for article (PubMed ID: 38445262)

  • 1. Improved prediction of sepsis-associated encephalopathy in intensive care unit sepsis patients with an innovative nomogram tool.
    Jin J; Yu L; Zhou Q; Zeng M
    Front Neurol; 2024; 15():1344004. PubMed ID: 38445262
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The nomogram to predict the occurrence of sepsis-associated encephalopathy in elderly patients in the intensive care units: A retrospective cohort study.
    Zhao Q; Xiao J; Liu X; Liu H
    Front Neurol; 2023; 14():1084868. PubMed ID: 36816550
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Nomogram predictive model for in-hospital mortality risk in elderly ICU patients with urosepsis.
    Wei J; Liang R; Liu S; Dong W; Gao J; Hua T; Xiao W; Li H; Zhu H; Hu J; Cao S; Liu Y; Lyu J; Yang M
    BMC Infect Dis; 2024 Apr; 24(1):442. PubMed ID: 38671376
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Development of a nomogram to predict 30-day mortality of patients with sepsis-associated encephalopathy: a retrospective cohort study.
    Yang Y; Liang S; Geng J; Wang Q; Wang P; Cao Y; Li R; Gao G; Li L
    J Intensive Care; 2020; 8():45. PubMed ID: 32637121
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Optimizing the prediction of sepsis-associated encephalopathy with cerebral circulation time utilizing a nomogram: a pilot study in the intensive care unit.
    Mei J; Zhang X; Sun X; Hu L; Song Y
    Front Neurol; 2023; 14():1303075. PubMed ID: 38274881
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Construction and Evaluation of a Sepsis Risk Prediction Model for Urinary Tract Infection.
    Zhang L; Zhang F; Xu F; Wang Z; Ren Y; Han D; Lyu J; Yin H
    Front Med (Lausanne); 2021; 8():671184. PubMed ID: 34095176
    [No Abstract]   [Full Text] [Related]  

  • 7. Development and validation of a nomogram to predict the risk of sepsis-associated encephalopathy for septic patients in PICU: a multicenter retrospective cohort study.
    Wang G; Jiang X; Fu Y; Gao Y; Jiang Q; Guo E; Huang H; Liu X
    J Intensive Care; 2024 Feb; 12(1):8. PubMed ID: 38378667
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predictive nomogram for 28-day mortality risk in mitral valve disorder patients in the intensive care unit: A comprehensive assessment from the MIMIC-III database.
    Qiu Y; Li M; Song X; Li Z; Ma A; Meng Z; Li Y; Tan M
    Int J Cardiol; 2024 Jul; 407():132105. PubMed ID: 38677334
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A New Scoring System for Predicting In-hospital Death in Patients Having Liver Cirrhosis With Esophageal Varices.
    Xu F; Zhang L; Wang Z; Han D; Li C; Zheng S; Yin H; Lyu J
    Front Med (Lausanne); 2021; 8():678646. PubMed ID: 34708050
    [No Abstract]   [Full Text] [Related]  

  • 10. Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures.
    Xing Z; Xu Y; Wu Y; Fu X; Shen P; Che W; Wang J
    Eur J Med Res; 2023 Nov; 28(1):539. PubMed ID: 38001553
    [TBL] [Abstract][Full Text] [Related]  

  • 11. [Development and validation of a prognostic model for patients with sepsis in intensive care unit].
    Jiang Z; Wang H; Wang S; Guan C; Qu Y
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Aug; 35(8):800-806. PubMed ID: 37593856
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Establishment and validation of a prognosis nomogram for MIMIC-III patients with liver cirrhosis complicated with hepatic encephalopathy.
    Yan W; Yao Z; Ou Q; Ye G
    BMC Gastroenterol; 2023 Sep; 23(1):335. PubMed ID: 37770848
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Mechanical Learning for Prediction of Sepsis-Associated Encephalopathy.
    Zhao L; Wang Y; Ge Z; Zhu H; Li Y
    Front Comput Neurosci; 2021; 15():739265. PubMed ID: 34867250
    [No Abstract]   [Full Text] [Related]  

  • 14. Development and validation of a nomogram for predicting in-hospital mortality of patients with cervical spine fractures without spinal cord injury.
    Xing Z; Cai L; Wu Y; Shen P; Fu X; Xu Y; Wang J
    Eur J Med Res; 2024 Jan; 29(1):80. PubMed ID: 38287435
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Construction and validation of a risk assessment model for acute kidney injury in patients with acute pancreatitis in the intensive care unit.
    Jiang Z; An X; Li Y; Xu C; Meng H; Qu Y
    BMC Nephrol; 2023 Oct; 24(1):315. PubMed ID: 37884898
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Development of a novel tool: a nomogram for predicting in-hospital mortality of patients in intensive care unit after percutaneous coronary intervention.
    Yuan M; Ren BC; Wang Y; Ren F; Gao D
    BMC Anesthesiol; 2023 Jan; 23(1):5. PubMed ID: 36609220
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Establishment of a prognostic model for patients with sepsis based on SOFA: a retrospective cohort study.
    Liu H; Zhang L; Xu F; Li S; Wang Z; Han D; Zhang F; Lyu J; Yin H
    J Int Med Res; 2021 Sep; 49(9):3000605211044892. PubMed ID: 34586931
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A predictive model for the risk of sepsis within 30 days of admission in patients with traumatic brain injury in the intensive care unit: a retrospective analysis based on MIMIC-IV database.
    Hu F; Zhu J; Zhang S; Wang C; Zhang L; Zhou H; Shi H
    Eur J Med Res; 2023 Aug; 28(1):290. PubMed ID: 37596695
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Construction and evaluation of a risk prediction model for pulmonary infection-associated acute kidney injury in intensive care units.
    Cao X; Liang Y; Feng H; Chen L; Liu S
    Clin Transl Sci; 2023 Oct; 16(10):1923-1934. PubMed ID: 37488744
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Development and validation of a nomogram for predicting 28-day mortality in patients with ischemic stroke.
    Fang L; Zhou M; Mao F; Diao M; Hu W; Jin G
    PLoS One; 2024; 19(4):e0302227. PubMed ID: 38656987
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.