141
Views
11
CrossRef citations to date
0
Altmetric
Original Research

The DANish Comorbidity Index for Acute Myocardial Infarction (DANCAMI): Development, Validation and Comparison with Existing Comorbidity Indices

ORCID Icon, , ORCID Icon, , ORCID Icon, ORCID Icon & ORCID Icon show all
Pages 1299-1311 | Published online: 20 Nov 2020

References

  • Schmidt M, Jacobsen JB, Lash TL, Botker HE, Sorensen HT. 25 year trends in first time hospitalisation for acute myocardial infarction, subsequent short and long-term mortality, and the prognostic impact of sex and comorbidity: a Danish nationwide cohort study. BMJ. 2012;344(jan25 2):e356. doi:10.1136/bmj.e35622279115
  • Normand SL, Morris CN, Fung KS, McNeil BJ, Epstein AM. Development and validation of a claims based index for adjusting for risk of mortality: the case of acute myocardial infarction. J Clin Epidemiol. 1995;48(2):229–243. doi:10.1016/0895-4356(94)00126-B7869069
  • Qu Z, Zhao LP, Ma X, Zhan S. Building a patient-specific risk score with a large database of discharge summary reports. Med Sci Monit. 2016;22:2097–2104. doi:10.12659/MSM.89926227318825
  • Sanchis J, Nunez J, Bodi V, et al. Influence of comorbid conditions on one-year outcomes in non-ST-segment elevation acute coronary syndrome. Mayo Clin Proc. 2011;86(4):291–296. doi:10.4065/mcp.2010.070221346247
  • Tu JV, Austin PC, Walld R, Roos L, Agras J, McDonald KM. Development and validation of the ontario acute myocardial infarction mortality prediction rules. J Am Coll Cardiol. 2001;37(4):992–997. doi:10.1016/S0735-1097(01)01109-311263626
  • Azzalini L, Chabot-Blanchet M, Southern DA, et al. A disease-specific comorbidity index for predicting mortality in patients admitted to hospital with a cardiac condition. CMAJ. 2019;191(11):E299–E307. doi:10.1503/cmaj.18118630885968
  • Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis. 1987;40(5):373–383. doi:10.1016/0021-9681(87)90171-83558716
  • van Walraven C, Austin PC, Jennings A, Quan H, Forster AJ. A modification of the elixhauser comorbidity measures into a point system for hospital death using administrative data. Med Care. 2009;47(6):626–633. doi:10.1097/MLR.0b013e31819432e519433995
  • Li P, Kim MM, Doshi JA. Comparison of the performance of the CMS Hierarchical Condition Category (CMS-HCC) risk adjuster with the Charlson and Elixhauser comorbidity measures in predicting mortality. BMC Health Serv Res. 2010;10:245. doi:10.1186/1472-6963-10-24520727154
  • Holman CD, Preen DB, Baynham NJ, Finn JC, Semmens JB. A multipurpose comorbidity scoring system performed better than the Charlson index. J Clin Epidemiol. 2005;58(10):1006–1014. doi:10.1016/j.jclinepi.2005.01.02016168346
  • Stirland LE, Gonzalez-Saavedra L, Mullin DS, Ritchie CW, Muniz-Terrera G, Russ TC. Measuring multimorbidity beyond counting diseases: systematic review of community and population studies and guide to index choice. BMJ. 2020;368:m160. doi:10.1136/bmj.m16032071114
  • Schmidt M, Schmidt SAJ, Adelborg K, et al. The Danish health care system and epidemiological research: from health care contacts to database records. Clin Epidemiol. 2019;11:563–591. doi:10.2147/CLEP.S17908331372058
  • Schmidt M, Pedersen L, Sorensen HT. The Danish civil registration system as a tool in epidemiology. Eur J Epidemiol. 2014;29(8):541–549. doi:10.1007/s10654-014-9930-324965263
  • Schmidt M, Schmidt SA, Sandegaard JL, Ehrenstein V, Pedersen L, Sorensen HT. The Danish National Patient Registry: a review of content, data quality, and research potential. Clin Epidemiol. 2015;7:449–490. doi:10.2147/CLEP.S9112526604824
  • Ehrenstein V, Antonsen S, Pedersen L. Existing data sources for clinical epidemiology: Aarhus University Prescription Database. Clin Epidemiol. 2010;2:273–279. doi:10.2147/CLEP.S1345821152254
  • Grann AF, Erichsen R, Nielsen AG, Froslev T, Thomsen RW. Existing data sources for clinical epidemiology: the clinical laboratory information system (LABKA) research database at Aarhus University, Denmark. Clin Epidemiol. 2011;3:133–138. doi:10.2147/CLEP.S1790121487452
  • National Health Board. National Minimum Dataset (Hospital Events) Data Dictionary. Ministry of Health Wellington; 2014.
  • Ministry of Health. Mortality Collection Data Dictionary. Ministry of Health Wellington; 2009.
  • Ministry of Health. Pharmaceutical Claims Data Mart Data Dictionary. Ministry of Health Wellington, 2017.
  • Moons KG, Altman DG, Reitsma JB, et al. Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1–W73. doi:10.7326/M14-069825560730
  • Schoenfeld D. Partial residuals for the proportional hazards regression model. Biometrika. 1982;69(1):239–241. doi:10.1093/biomet/69.1.239
  • Mehta HB, Mehta V, Girman CJ, Adhikari D, Johnson ML. Regression coefficient-based scoring system should be used to assign weights to the risk index. J Clin Epidemiol. 2016;79:22–28. doi:10.1016/j.jclinepi.2016.03.03127181564
  • Knottnerus JA, Tugwell P, Wells G. Editorial comment: ratios should be multiplied, not added. J Clin Epidemiol. 2016;79:30. doi:10.1016/j.jclinepi.2016.11.00727931695
  • Stukenborg GJ, Wagner DP, Connors AF Jr. Comparison of the performance of two comorbidity measures, with and without information from prior hospitalizations. Med Care. 2001;39(7):727–739. doi:10.1097/00005650-200107000-0000911458137
  • Chu Y, Ng Y, Wu S. Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality. BMC Health Serv Res. 2010;10(1). doi:10.1186/1472-6963-10-140
  • Gutacker N, Bloor K, Cookson R. Comparing the performance of the Charlson/Deyo and Elixhauser comorbidity measures across five European countries and three conditions. Eur J Public Health. 2015;25(Suppl 1):15–20. doi:10.1093/eurpub/cku221
  • Yamana H, Matsui H, Sasabuchi Y, Fushimi K, Yasunaga H. Categorized diagnoses and procedure records in an administrative database improved mortality prediction. J Clin Epidemiol. 2015;68(9):1028–1035. doi:10.1016/j.jclinepi.2014.12.00425596112
  • Lash TL, Mor V, Wieland D, Ferrucci L, Satariano W, Silliman RA. Methodology, design, and analytic techniques to address measurement of comorbid disease. J Gerontol a Biol Sci Med Sci. 2007;62(3):281–285.17389725
  • Sundboll J, Adelborg K, Munch T, et al. Positive predictive value of cardiovascular diagnoses in the Danish National Patient Registry: a validation study. BMJ Open. 2016;6(11):e012832. doi:10.1136/bmjopen-2016-012832
  • Thygesen SK, Christiansen CF, Christensen S, Lash TL, Sorensen HT. The predictive value of ICD-10 diagnostic coding used to assess Charlson comorbidity index conditions in the population-based Danish National Registry of patients. BMC Med Res Methodol. 2011;11:83. doi:10.1186/1471-2288-11-8321619668
  • Granger CB, Goldberg RJ, Dabbous O, et al. Predictors of hospital mortality in the global registry of acute coronary events. Arch Intern Med. 2003;163(19):2345–2353. doi:10.1001/archinte.163.19.234514581255