Advanced search
Publication Cover
Clinical Epidemiology Volume 13, 2021 - Issue
Submit an article Journal homepage
1,196
Views
46
CrossRef citations to date
0
Altmetric
Methodology

Adaptation of the Charlson Comorbidity Index for Register-Based Research in Sweden

Jonas F Ludvigsson1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden;2 Department of Pediatrics, Orebro University Hospital, Orebro, Sweden;3 Division of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, UK;4 Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York, USACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-1024-5602View further author information
ORCID Icon,
Peter Appelros5 University Health Care Research Center, Faculty of Medicine and Health, Örebro University, ÖrebroSE-701 82, SwedenView further author information
,
Johan Askling6 Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden;7 Rheumatology, Theme Inflammation and Infection, Karolinska University Hospital, Stockholm, SwedenView further author information
,
Liisa Byberg8 Department of Surgical Sciences, Uppsala University, Uppsala, SwedenView further author information
,
Juan-Jesus Carrero1 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, SwedenORCID Iconhttps://orcid.org/0000-0003-4763-2024View further author information
ORCID Icon,
Anna Mia Ekström9 Global & Sexual Health Research Group (GloSH), Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden;10 Faculty of Medicine, Department of Clinical Sciences Lund, Respiratory Medicine and Allergology, Lund University, Lund, SwedenView further author information
,
Magnus Ekström11 Department of Infectious Diseases, Karolinska University Hospital, Stockholm, SwedenORCID Iconhttps://orcid.org/0000-0002-7227-5113View further author information
ORCID Icon,
Karin Ekström Smedby6 Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, SwedenView further author information
,
Hannes Hagström12 Division of Hepatology, Department of Upper GI Diseases, Karolinska University Hospital, Stockholm, Sweden;6 Clinical Epidemiology Division, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden;14 Department of Medicine, Karolinska Huddinge, Institutet, Stockholm, SwedenView further author information
,
Stefan James15 Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden;16 Uppsala Clinical Research Center, Uppsala University, Uppsala, SwedenView further author information
,
Bengt Järvholm17 Department of Public Health and Clinical Medicine, Umeå University, Umeå, SwedenView further author information
,
Karl Michaelsson8 Department of Surgical Sciences, Uppsala University, Uppsala, SwedenORCID Iconhttps://orcid.org/0000-0003-2815-1217View further author information
ORCID Icon,
Nancy L Pedersen18 Department of Medical Epidemiology, Karolinska Institutet, Stockholm, SwedenView further author information
,
Helene Sundelin19 Neuropediatric Unit, Department of Women’s and Children’s Health, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden;20 Division of Children’s and Women’s Health, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, SwedenView further author information
,
Kristina Sundquist21 Center for Primary Health Care Research, Department of Clinical Sciences, Malmö, Lund University, Lund, SwedenView further author information
&
Johan Sundström22 Department of Medical Sciences, Uppsala University, Uppsala, Sweden;23 The George Institute for Global Health, University of New South Wales, Sydney, Australia;24 Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Community-Based Healthcare Research and Education (CoHRE), Department of Functional Pathology, School of Medicine, Shimane University, JapanORCID Iconhttps://orcid.org/0000-0003-2247-8454View further author information
ORCID Icon show all
Pages 21-41 | Published online: 12 Jan 2021

References

  • Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–383. doi:10.1016/0021-9681(87)90171-83558716
  • Maret-Ouda J, Wahlin K, El-Serag HB, et al. Association between laparoscopic antireflux surgery and recurrence of gastroesophageal reflux. JAMA. 2017;318(10):939–946. doi:10.1001/jama.2017.1098128898377
  • He W, Fang F, Varnum C, et al. Predictors of discontinuation of adjuvant hormone therapy in patients with breast cancer. J Clin Oncol. 2015;33(20):2262–2269. doi:10.1200/JCO.2014.59.367326033800
  • Khalili H, Bergman D, Roelstraete B, et al. Mortality of patients with microscopic colitis in Sweden. Clin Gastroenterol Hepatol. 2019. doi:10.1016/j.cgh.2019.12.012
  • Haider SI, Johnell K, Weitoft GR, et al. The influence of educational level on polypharmacy and inappropriate drug use: a register-based study of more than 600,000 older people. J Am Geriatr Soc. 2009;57(1):62–69. doi:10.1111/j.1532-5415.2008.02040.x19054196
  • Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613–619. doi:10.1016/0895-4356(92)90133-81607900
  • Romano PS, Roos LL, Jollis JG. Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol. 1993;46(10):1075–9;discussion 81–90. doi:10.1016/0895-4356(93)90103-8
  • Roos LL, Sharp SM, Cohen MM, et al. Risk adjustment in claims-based research: the search for efficient approaches. J Clin Epidemiol. 1989;42(12):1193–1206. doi:10.1016/0895-4356(89)90118-22585010
  • D’Hoore W, Sicotte C, Tilquin C. Risk adjustment in outcome assessment: the Charlson comorbidity index. Methods Inf Med. 1993;32(5):382–387.8295545
  • Ghali WA, Hall RE, Rosen AK, et al. Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data. J Clin Epidemiol. 1996;49(3):273–278. doi:10.1016/0895-4356(95)00564-18676173
  • Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43(11):1130–1139. doi:10.1097/01.mlr.0000182534.19832.8316224307
  • Yurkovich M, Avina-Zubieta JA, Thomas J, et al. A systematic review identifies valid comorbidity indices derived from administrative health data. J Clin Epidemiol. 2015;68(1):3–14. doi:10.1016/j.jclinepi.2014.09.01025441702
  • Michaelsson K, Wolk A, Langenskiold S, et al. Milk intake and risk of mortality and fractures in women and men: cohort studies. BMJ. 2014;349:g6015. doi:10.1136/bmj.g601525352269
  • Warensjo Lemming E, Byberg L, Melhus H, et al. Long-term a posteriori dietary patterns and risk of hip fractures in a cohort of women. Eur J Epidemiol. 2017;32(7):605–616. doi:10.1007/s10654-017-0267-628585122
  • Liu B, Wanders A, Wirdefeldt K, et al. Vagotomy and subsequent risk of inflammatory bowel disease: a nationwide register-based matched cohort study. Aliment Pharmacol Ther. 2020;51(11):1022–1030. doi:10.1111/apt.1571532319125
  • Nguyen LH, Ortqvist AK, Cao Y, et al. Antibiotic use and the development of inflammatory bowel disease: a national case-control study in Sweden. Lancet Gastroenterol Hepatol. 2020. doi:10.1016/S2468-1253(20)30267-3
  • Ludvigsson JF, Haberg SE, Knudsen GP, et al. Ethical aspects of registry-based research in the Nordic countries. Clin Epidemiol. 2015;7:491–508. doi:10.2147/CLEP.S9058926648756
  • Emilsson L, Lindahl B, Koster M, et al. Review of 103 Swedish Healthcare Quality Registries. J Intern Med. 2015;277(1):94–136. doi:10.1111/joim.1230325174800
  • Wettermark B, Hammar N, Fored CM, et al. The new Swedish Prescribed Drug Register–opportunities for pharmacoepidemiological research and experience from the first six months. Pharmacoepidemiol Drug Saf. 2007;16(7):726–735. doi:10.1002/pds.129416897791
  • Lieffers JR, Baracos VE, Winget M, et al. A comparison of Charlson and Elixhauser comorbidity measures to predict colorectal cancer survival using administrative health data. Cancer. 2011;117(9):1957–1965. doi:10.1002/cncr.2565321509773
  • 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
  • Ladha KS, Zhao K, Quraishi SA, et al. The Deyo-Charlson and Elixhauser-van Walraven Comorbidity Indices as predictors of mortality in critically ill patients. BMJ Open. 2015;5(9):e008990. doi:10.1136/bmjopen-2015-008990
  • Snow GL, Bledsoe JR, Butler A, et al. Comparative evaluation of the clinical laboratory-based Intermountain risk score with the Charlson and Elixhauser comorbidity indices for mortality prediction. PLoS One. 2020;15(5):e0233495. doi:10.1371/journal.pone.023349532437416
  • Simard M, Sirois C, Candas B. Validation of the combined comorbidity index of Charlson and Elixhauser to predict 30-day mortality across ICD-9 and ICD-10. Med Care. 2018;56(5):441–447. doi:10.1097/MLR.000000000000090529578951

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.