BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

245 related articles for article (PubMed ID: 21764557)

  • 1. Comorbidity scores for administrative data benefited from adaptation to local coding and diagnostic practices.
    Bottle A; Aylin P
    J Clin Epidemiol; 2011 Dec; 64(12):1426-33. PubMed ID: 21764557
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Risk adjustment performance of Charlson and Elixhauser comorbidities in ICD-9 and ICD-10 administrative databases.
    Li B; Evans D; Faris P; Dean S; Quan H
    BMC Health Serv Res; 2008 Jan; 8():12. PubMed ID: 18194561
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Stroke: the Elixhauser Index for comorbidity adjustment of in-hospital case fatality.
    Zhu H; Hill MD
    Neurology; 2008 Jul; 71(4):283-7. PubMed ID: 18645167
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Cross-national comparative performance of three versions of the ICD-10 Charlson index.
    Sundararajan V; Quan H; Halfon P; Fushimi K; Luthi JC; Burnand B; Ghali WA;
    Med Care; 2007 Dec; 45(12):1210-5. PubMed ID: 18007172
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data.
    van Walraven C; Austin PC; Jennings A; Quan H; Forster AJ
    Med Care; 2009 Jun; 47(6):626-33. PubMed ID: 19433995
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development and testing of a systemic lupus-specific risk adjustment index for in-hospital mortality.
    Ward MM
    J Rheumatol; 2000 Jun; 27(6):1408-13. PubMed ID: 10852262
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Accuracy of hospital morbidity data and the performance of comorbidity scores as predictors of mortality.
    Mnatzaganian G; Ryan P; Norman PE; Hiller JE
    J Clin Epidemiol; 2012 Jan; 65(1):107-15. PubMed ID: 21803545
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predicting in-hospital mortality in patients undergoing complex gastrointestinal surgery: determining the optimal risk adjustment method.
    Grendar J; Shaheen AA; Myers RP; Parker R; Vollmer CM; Ball CG; Quan ML; Kaplan GG; Al-Manasra T; Dixon E
    Arch Surg; 2012 Feb; 147(2):126-35. PubMed ID: 22006854
    [TBL] [Abstract][Full Text] [Related]  

  • 9. [Comparative study on three algorithms of the ICD-10 Charlson comorbidity index with myocardial infarction patients].
    Kim KH
    J Prev Med Public Health; 2010 Jan; 43(1):42-9. PubMed ID: 20185982
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparison of the Elixhauser and Charlson/Deyo methods of comorbidity measurement in administrative data.
    Southern DA; Quan H; Ghali WA
    Med Care; 2004 Apr; 42(4):355-60. PubMed ID: 15076812
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Charlson scores based on ICD-10 administrative data were valid in assessing comorbidity in patients undergoing urological cancer surgery.
    Nuttall M; van der Meulen J; Emberton M
    J Clin Epidemiol; 2006 Mar; 59(3):265-73. PubMed ID: 16488357
    [TBL] [Abstract][Full Text] [Related]  

  • 12. [Impact of comorbidities on in-hospital mortality from acute myocardial infarction, 2003-2009].
    Gili M; Sala J; López J; Carrión A; Béjar L; Moreno J; Rosales A; Sánchez G
    Rev Esp Cardiol; 2011 Dec; 64(12):1130-7. PubMed ID: 22018686
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality.
    Chu YT; Ng YY; Wu SC
    BMC Health Serv Res; 2010 May; 10():140. PubMed ID: 20507593
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Evaluation of comorbidity indices for inpatient mortality prediction models.
    Martins M; Blais R
    J Clin Epidemiol; 2006 Jul; 59(7):665-9. PubMed ID: 16765268
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development of an epilepsy-specific risk adjustment comorbidity index.
    St Germaine-Smith C; Liu M; Quan H; Wiebe S; Jette N
    Epilepsia; 2011 Dec; 52(12):2161-7. PubMed ID: 22004000
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Categorized diagnoses and procedure records in an administrative database improved mortality prediction.
    Yamana H; Matsui H; Sasabuchi Y; Fushimi K; Yasunaga H
    J Clin Epidemiol; 2015 Sep; 68(9):1028-35. PubMed ID: 25596112
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Validation of the Combined Comorbidity Index of Charlson and Elixhauser to Predict 30-Day Mortality Across ICD-9 and ICD-10.
    Simard M; Sirois C; Candas B
    Med Care; 2018 May; 56(5):441-447. PubMed ID: 29578951
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparing the performance of the Charlson/Deyo and Elixhauser comorbidity measures across five European countries and three conditions.
    Gutacker N; Bloor K; Cookson R
    Eur J Public Health; 2015 Feb; 25 Suppl 1():15-20. PubMed ID: 25690125
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicting In-Hospital Mortality in Elderly Patients With Cervical Spine Fractures: A Comparison of the Charlson and Elixhauser Comorbidity Measures.
    Menendez ME; Ring D; Harris MB; Cha TD
    Spine (Phila Pa 1976); 2015 Jun; 40(11):809-15. PubMed ID: 25785957
    [TBL] [Abstract][Full Text] [Related]  

  • 20. ICD-10 adaptations of the Ontario acute myocardial infarction mortality prediction rules performed as well as the original versions.
    Vermeulen MJ; Tu JV; Schull MJ
    J Clin Epidemiol; 2007 Sep; 60(9):971-4. PubMed ID: 17689814
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.