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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

224 related articles for article (PubMed ID: 23385106)

  • 1. Dynamic data during hypotensive episode improves mortality predictions among patients with sepsis and hypotension.
    Mayaud L; Lai PS; Clifford GD; Tarassenko L; Celi LA; Annane D
    Crit Care Med; 2013 Apr; 41(4):954-62. PubMed ID: 23385106
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today's critically ill patients.
    Zimmerman JE; Kramer AA; McNair DS; Malila FM
    Crit Care Med; 2006 May; 34(5):1297-310. PubMed ID: 16540951
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Comparison of the Mortality Probability Admission Model III, National Quality Forum, and Acute Physiology and Chronic Health Evaluation IV hospital mortality models: implications for national benchmarking*.
    Kramer AA; Higgins TL; Zimmerman JE
    Crit Care Med; 2014 Mar; 42(3):544-53. PubMed ID: 24158174
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Renin Kinetics Are Superior to Lactate Kinetics for Predicting In-Hospital Mortality in Hypotensive Critically Ill Patients.
    Jeyaraju M; McCurdy MT; Levine AR; Devarajan P; Mazzeffi MA; Mullins KE; Reif M; Yim DN; Parrino C; Lankford AS; Chow JH
    Crit Care Med; 2022 Jan; 50(1):50-60. PubMed ID: 34166293
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Prediction of outcome for critically ill patients with unexplained hypotension.
    Heidenreich PA; Foster E; Cohen NH
    Crit Care Med; 1996 Nov; 24(11):1835-40. PubMed ID: 8917034
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development and validation of a model that uses enhanced administrative data to predict mortality in patients with sepsis.
    Lagu T; Lindenauer PK; Rothberg MB; Nathanson BH; Pekow PS; Steingrub JS; Higgins TL
    Crit Care Med; 2011 Nov; 39(11):2425-30. PubMed ID: 22005222
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction of outcome from intensive care: a prospective cohort study comparing Acute Physiology and Chronic Health Evaluation II and III prognostic systems in a United Kingdom intensive care unit.
    Beck DH; Taylor BL; Millar B; Smith GB
    Crit Care Med; 1997 Jan; 25(1):9-15. PubMed ID: 8989170
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Evaluation of acute physiology and chronic health evaluation III predictions of hospital mortality in an independent database.
    Zimmerman JE; Wagner DP; Draper EA; Wright L; Alzola C; Knaus WA
    Crit Care Med; 1998 Aug; 26(8):1317-26. PubMed ID: 9710088
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU.
    Kong G; Lin K; Hu Y
    BMC Med Inform Decis Mak; 2020 Oct; 20(1):251. PubMed ID: 33008381
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Derivation and validation of the acute organ failure score to predict outcome in critically ill patients: a cohort study.
    Elias KM; Moromizato T; Gibbons FK; Christopher KB
    Crit Care Med; 2015 Apr; 43(4):856-64. PubMed ID: 25746746
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Risk prediction of hospital mortality for adult patients admitted to Australian and New Zealand intensive care units: development and validation of the Australian and New Zealand Risk of Death model.
    Paul E; Bailey M; Pilcher D
    J Crit Care; 2013 Dec; 28(6):935-41. PubMed ID: 24074958
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Simplified prognostic model for critically ill patients in resource limited settings in South Asia.
    Haniffa R; Mukaka M; Munasinghe SB; De Silva AP; Jayasinghe KSA; Beane A; de Keizer N; Dondorp AM
    Crit Care; 2017 Oct; 21(1):250. PubMed ID: 29041985
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Outcome predictors and new score of critically ill cirrhotic patients with acute renal failure.
    Fang JT; Tsai MH; Tian YC; Jenq CC; Lin CY; Chen YC; Lien JM; Chen PC; Yang CW
    Nephrol Dial Transplant; 2008 Jun; 23(6):1961-9. PubMed ID: 18187499
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predictive Accuracy of Quick Sequential Organ Failure Assessment for Hospital Mortality Decreases With Increasing Comorbidity Burden Among Patients Admitted for Suspected Infection.
    Parks Taylor S; McWilliams A; Taylor BT; Heffner AC; Chou SH; Runyon M; Cunningham K; Evans SL; Gibbs M; Russo M; Rossman W; Murphy SE; Kowalkowski MA;
    Crit Care Med; 2019 Aug; 47(8):1081-1088. PubMed ID: 31306256
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting Mortality in Low-Income Country ICUs: The Rwanda Mortality Probability Model (R-MPM).
    Riviello ED; Kiviri W; Fowler RA; Mueller A; Novack V; Banner-Goodspeed VM; Weinkauf JL; Talmor DS; Twagirumugabe T
    PLoS One; 2016; 11(5):e0155858. PubMed ID: 27196252
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Community-wide assessment of intensive care outcomes using a physiologically based prognostic measure: implications for critical care delivery from Cleveland Health Quality Choice.
    Sirio CA; Shepardson LB; Rotondi AJ; Cooper GS; Angus DC; Harper DL; Rosenthal GE
    Chest; 1999 Mar; 115(3):793-801. PubMed ID: 10084494
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.
    Thorsen-Meyer HC; Nielsen AB; Nielsen AP; Kaas-Hansen BS; Toft P; Schierbeck J; Strøm T; Chmura PJ; Heimann M; Dybdahl L; Spangsege L; Hulsen P; Belling K; Brunak S; Perner A
    Lancet Digit Health; 2020 Apr; 2(4):e179-e191. PubMed ID: 33328078
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Mortality rates increase dramatically below a systolic blood pressure of 105-mm Hg in septic surgical patients.
    Clarke DL; Chipps JA; Sartorius B; Bruce J; Laing GL; Brysiewicz P
    Am J Surg; 2016 Nov; 212(5):941-945. PubMed ID: 27290634
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Risks for developing critical illness with GI hemorrhage.
    Inayet N; Amoateng-Adjepong Y; Upadya A; Manthous CA
    Chest; 2000 Aug; 118(2):473-8. PubMed ID: 10936143
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Short-term mortality prediction for acute lung injury patients: external validation of the Acute Respiratory Distress Syndrome Network prediction model.
    Damluji A; Colantuoni E; Mendez-Tellez PA; Sevransky JE; Fan E; Shanholtz C; Wojnar M; Pronovost PJ; Needham DM
    Crit Care Med; 2011 May; 39(5):1023-8. PubMed ID: 21761595
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.