These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
147 related articles for article (PubMed ID: 37868898)
1. A predictive model for the identification of the risk of sepsis in patients with Gram-positive bacteria in the intensive care unit. Chen X; Zhou Y; Luo L; Peng X; Xiang T J Thorac Dis; 2023 Sep; 15(9):4896-4913. PubMed ID: 37868898 [TBL] [Abstract][Full Text] [Related]
2. [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]
3. 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]
4. Development of a Nomogram to Predict 28-Day Mortality of Patients With Sepsis-Induced Coagulopathy: An Analysis of the MIMIC-III Database. Lu Z; Zhang J; Hong J; Wu J; Liu Y; Xiao W; Hua T; Yang M Front Med (Lausanne); 2021; 8():661710. PubMed ID: 33889591 [No Abstract] [Full Text] [Related]
5. Development and validation of a nomogram for predicting the prognosis in cancer patients with sepsis. Yang Y; Dong J; Li Y; Chen R; Tian X; Wang H; Hao C Cancer Med; 2022 Jun; 11(12):2345-2355. PubMed ID: 35182022 [TBL] [Abstract][Full Text] [Related]
6. An early warning model for predicting major adverse kidney events within 30 days in sepsis patients. Yu X; Xin Q; Hao Y; Zhang J; Ma T Front Med (Lausanne); 2023; 10():1327036. PubMed ID: 38469459 [TBL] [Abstract][Full Text] [Related]
7. 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]
8. [Development and validation of a mechanical power-oriented nomogram model for predicting the risk of weaning failure in mechanically ventilated patients: an analysis using the data from MIMIC-IV]. Yan Y; Xie Y; Luo J; Wang Y; Chen X; Du Z; Li X Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Jul; 35(7):707-713. PubMed ID: 37545447 [TBL] [Abstract][Full Text] [Related]
9. Prediction of 90-Day Mortality among Sepsis Patients Based on a Nomogram Integrating Diverse Clinical Indices. Zeng Q; He L; Zhang N; Lin Q; Zhong L; Song J Biomed Res Int; 2021; 2021():1023513. PubMed ID: 34722755 [TBL] [Abstract][Full Text] [Related]
10. Comparison of risk prediction models for the progression of pelvic inflammatory disease patients to sepsis: Cox regression model and machine learning model. Wang Q; Sun J; Liu X; Ping Y; Feng C; Liu F; Feng X Heliyon; 2024 Jan; 10(1):e23148. PubMed ID: 38163183 [TBL] [Abstract][Full Text] [Related]
11. Development and validation of a survival prediction model for patients received mechanical ventilation in the intensive care unit: a large sample size cohort from the MIMIC database. Lin Z; Huang X; Shan X Ann Palliat Med; 2022 Jun; 11(6):2071-2084. PubMed ID: 35817742 [TBL] [Abstract][Full Text] [Related]
12. Development of a nomogram to predict 30-day mortality of sepsis patients with gastrointestinal bleeding: An analysis of the MIMIC-IV database. Sun B; Man YL; Zhou QY; Wang JD; Chen YM; Fu Y; Chen ZH Heliyon; 2024 Feb; 10(4):e26185. PubMed ID: 38404864 [TBL] [Abstract][Full Text] [Related]
13. Organism type of infection is associated with prognosis in sepsis: an analysis from the MIMIC-IV database. Guo Q; Qu P; Cui W; Liu M; Zhu H; Chen W; Sun N; Geng S; Song W; Li X; Lou A BMC Infect Dis; 2023 Jun; 23(1):431. PubMed ID: 37365506 [TBL] [Abstract][Full Text] [Related]
14. A nomogram for predicting sepsis-associated delirium: a retrospective study in MIMIC III. Gu Q; Yang S; Fei D; Lu Y; Yu H BMC Med Inform Decis Mak; 2023 Sep; 23(1):184. PubMed ID: 37715189 [TBL] [Abstract][Full Text] [Related]
15. 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]
16. A Nomogram Based on Comorbidities and Infection Location to Predict 30 Days Mortality of Immunocompromised Patients in ICU: A Retrospective Cohort Study. Guo X; Guo D Int J Gen Med; 2021; 14():10281-10292. PubMed ID: 34992443 [TBL] [Abstract][Full Text] [Related]
17. Carbapenem-resistant gram-negative bacterial infection in intensive care unit patients: Antibiotic resistance analysis and predictive model development. Liao Q; Feng Z; Lin H; Zhou Y; Lin J; Zhuo H; Chen X Front Cell Infect Microbiol; 2023; 13():1109418. PubMed ID: 36794004 [TBL] [Abstract][Full Text] [Related]
18. A prediction model for assessing hypoglycemia risk in critically ill patients with sepsis. Gao H; Zhao Y Heart Lung; 2023; 62():43-49. PubMed ID: 37302264 [TBL] [Abstract][Full Text] [Related]
19. [Clinical predictive value of short-term dynamic changes in platelet counts for prognosis of sepsis patients in intensive care unit: a retrospective cohort study in adults]. Zhou Z; Xie Y; Feng T; Zhang X; Zhang Y; Jin W; Tian R; Wang R Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2020 Mar; 32(3):301-306. PubMed ID: 32385993 [TBL] [Abstract][Full Text] [Related]
20. Development and Validation of a Dynamic Nomogram for Predicting in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study in the Intensive Care Unit. Zou K; Huang S; Ren W; Xu H; Zhang W; Shi X; Shi L; Zhong X; Peng Y; Lü M; Tang X Int J Gen Med; 2023; 16():2541-2553. PubMed ID: 37351008 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]