163 related articles for article (PubMed ID: 17435390)
1. Assessing and using comorbidity measures in elderly veterans with lower extremity amputations.
Kurichi JE; Stineman MG; Kwong PL; Bates BE; Reker DM
Gerontology; 2007; 53(5):255-9. PubMed ID: 17435390
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Predictors of in-hospital mortality following major lower extremity amputations in type 2 diabetic patients using artificial neural networks.
Lopez-de-Andres A; Hernandez-Barrera V; Lopez R; Martin-Junco P; Jimenez-Trujillo I; Alvaro-Meca A; Salinero-Fort MA; Jimenez-Garcia R
BMC Med Res Methodol; 2016 Nov; 16(1):160. PubMed ID: 27876006
[TBL] [Abstract][Full Text] [Related]
4. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.
Quan H; Sundararajan V; Halfon P; Fong A; Burnand B; Luthi JC; Saunders LD; Beck CA; Feasby TE; Ghali WA
Med Care; 2005 Nov; 43(11):1130-9. PubMed ID: 16224307
[TBL] [Abstract][Full Text] [Related]
5. The Elixhauser comorbidity method outperforms the Charlson index in predicting inpatient death after orthopaedic surgery.
Menendez ME; Neuhaus V; van Dijk CN; Ring D
Clin Orthop Relat Res; 2014 Sep; 472(9):2878-86. PubMed ID: 24867450
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. 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]
8. 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]
9. 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]
10. Use of administrative data to risk adjust amputation rates in a national cohort of medicare-enrolled veterans with diabetes.
Tseng CL; Rajan M; Miller DR; Hawley G; Crystal S; Xie M; Tiwari A; Safford M; Pogach L
Med Care; 2005 Jan; 43(1):88-92. PubMed ID: 15626938
[TBL] [Abstract][Full Text] [Related]
11. Impact of different measures of comorbid disease on predicted mortality of intensive care unit patients.
Johnston JA; Wagner DP; Timmons S; Welsh D; Tsevat J; Render ML
Med Care; 2002 Oct; 40(10):929-40. PubMed ID: 12395026
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. A disease-specific comorbidity index for predicting mortality in patients admitted to hospital with a cardiac condition.
Azzalini L; Chabot-Blanchet M; Southern DA; Nozza A; Wilton SB; Graham MM; Gravel GM; Bluteau JP; Rouleau JL; Guertin MC; Jolicoeur EM
CMAJ; 2019 Mar; 191(11):E299-E307. PubMed ID: 30885968
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. 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]
17. Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data.
Sharma N; Schwendimann R; Endrich O; Ausserhofer D; Simon M
BMC Health Serv Res; 2021 Jan; 21(1):13. PubMed ID: 33407455
[TBL] [Abstract][Full Text] [Related]
18. Factors influencing receipt of outpatient rehabilitation services among veterans following lower extremity amputation.
Zhou J; Bates BE; Kurichi JE; Kwong PL; Xie D; Stineman MG
Arch Phys Med Rehabil; 2011 Sep; 92(9):1455-61. PubMed ID: 21878217
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Development and Validation of the Summary Elixhauser Comorbidity Score for Use With ICD-10-CM-Coded Data Among Older Adults.
Mehta HB; Li S; An H; Goodwin JS; Alexander GC; Segal JB
Ann Intern Med; 2022 Oct; 175(10):1423-1430. PubMed ID: 36095314
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]