E Bülow1, P Cnudde2, C Rogmark3, O Rolfson1, S Nemes4. 1. The Swedish Hip Arthroplasty Register, Centre of Registers Västra Götaland, Gothenburg, Sweden; Department of Orthopedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. 2. The Swedish Hip Arthroplasty Register, Centre of Registers Västra Götaland, Gothenburg, Sweden; Department of Orthopedics, Hywel Dda University Healthboard, Prince Philip Hospital, Bryngwyn Mawr, Dafen, Llanelli, UK. 3. Orthopaedic Surgeon, The Swedish Hip Arthroplasty Register, Centre of Registers Västra Götaland, Gothenburg, Sweden; Department of Orthopedics, Lund University, Skåne University Hospital, Malmö, Sweden. 4. Department of Orthopedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Abstract
AIMS: Our aim was to examine the Elixhauser and Charlson comorbidity indices, based on administrative data available before surgery, and to establish their predictive value for mortality for patients who underwent hip arthroplasty in the management of a femoral neck fracture. PATIENTS AND METHODS: We analyzed data from 42 354 patients from the Swedish Hip Arthroplasty Register between 2005 and 2012. Only the first operated hip was included for patients with bilateral arthroplasty. We obtained comorbidity data by linkage from the Swedish National Patient Register, as well as death dates from the national population register. We used univariable Cox regression models to predict mortality based on the comorbidity indices, as well as multivariable regression with age and gender. Predictive power was evaluated by a concordance index, ranging from 0.5 to 1 (with the higher value being the better predictive power). A concordance index less than 0.7 was considered poor. We used bootstrapping for internal validation of the results. RESULTS: The predictive power of mortality was poor for both the Elixhauser and Charlson comorbidity indices (concordance indices less than 0.7). The Charlson Comorbidity Index was superior to Elixhauser, and a model with age and gender was superior to both indices. CONCLUSION: Preoperative comorbidity from administrative data did not predict mortality for patients with a hip fracture treated by arthroplasty. This was true even if association on group level existed.
AIMS: Our aim was to examine the Elixhauser and Charlson comorbidity indices, based on administrative data available before surgery, and to establish their predictive value for mortality for patients who underwent hip arthroplasty in the management of a femoral neck fracture. PATIENTS AND METHODS: We analyzed data from 42 354 patients from the Swedish Hip Arthroplasty Register between 2005 and 2012. Only the first operated hip was included for patients with bilateral arthroplasty. We obtained comorbidity data by linkage from the Swedish National Patient Register, as well as death dates from the national population register. We used univariable Cox regression models to predict mortality based on the comorbidity indices, as well as multivariable regression with age and gender. Predictive power was evaluated by a concordance index, ranging from 0.5 to 1 (with the higher value being the better predictive power). A concordance index less than 0.7 was considered poor. We used bootstrapping for internal validation of the results. RESULTS: The predictive power of mortality was poor for both the Elixhauser and Charlson comorbidity indices (concordance indices less than 0.7). The Charlson Comorbidity Index was superior to Elixhauser, and a model with age and gender was superior to both indices. CONCLUSION: Preoperative comorbidity from administrative data did not predict mortality for patients with a hip fracture treated by arthroplasty. This was true even if association on group level existed.
Entities:
Keywords:
Comorbidity; Hip arthroplasty; Hip fracture; Mortality; Prediction; Survival
Authors: Olof Wolf; Sebastian Mukka; Jan Ekelund; Cecilia Rogmark; Michael Möller; Nils P Hailer Journal: Acta Orthop Date: 2022-01-03 Impact factor: 3.717