Meridith E Greene1,2,3, Ola Rolfson4,5,6, Max Gordon5,7, Göran Garellick5,6, Szilard Nemes5,6. 1. Harris Orthopaedic Laboratory, Massachusetts General Hospital, 55 Fruit Street, GRJ 1125, Boston, MA, 02114, USA. megreene@partners.org. 2. Swedish Hip Arthroplasty Register, Gothenburg, Sweden. megreene@partners.org. 3. Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. megreene@partners.org. 4. Harris Orthopaedic Laboratory, Massachusetts General Hospital, 55 Fruit Street, GRJ 1125, Boston, MA, 02114, USA. 5. Swedish Hip Arthroplasty Register, Gothenburg, Sweden. 6. Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. 7. Department of Clinical Sciences at Danderyd Hospital, Karolinska Institute, Stockholm, Sweden.
Abstract
BACKGROUND: Comorbidities influence surgical outcomes and therefore need to be included in risk adjustment when predicting patient-reported outcomes. However, there is no consensus on how best to use the available data about comorbidities in registry-based predictive models. QUESTIONS/PURPOSES: The purposes of this study were (1) to determine whether the International Classification of Diseases, 10(th) Revision (ICD-10)-based comorbidity measures (Elixhauser, Charlson, and Royal College of Surgeons Charlson) offer added value in explaining patients' health-related quality of life (HRQoL), pain, and satisfaction after total hip arthroplasty (THA) when preoperative HRQoL, pain, and Charnley classification were known; and (2) to determine the ideal timeframe for recording the different diagnoses that serves as the basis for comorbidity measure calculations. METHODS: There were 22,263 patients who had undergone THA with complete pre- and postoperative patient-reported outcome measures (PROMs) included in the Swedish Hip Arthroplasty Register between 2002 and 2007. The three comorbidity indices were calculated with ICD-10 codes identified in the Swedish National Patient Register from 1, 2, and 5 years before the patient underwent THA. The impact of the comorbidity indices on the PROM scores (EQ-5D index, EQ visual analog scale [VAS], pain VAS, and satisfaction VAS) was modeled with linear regression where the 1-year patient postoperative outcome score was the dependent variable and independent variables included patient preoperative Charnley classification, preoperative HRQoL and pain, and comorbidity indices. The partial R(2) value indicated how much each variable uniquely contributed to the predictive capacity of the model. RESULTS: The ICD-10-based comorbidity measures added little predictive value to the models for each of the outcomes of interest (EQ-5D index, EQ VAS, pain VAS, and satisfaction VAS). Charnley classification and the preoperative scores were the strongest predictors of both measures of postoperative HRQoL, of postoperative pain, and postoperative satisfaction with outcomes from surgery. Of all the predictors considered, only the Charnley classification was associated with all outcomes, irrespective of the timeframe considered. For each of the outcomes considered, there was a gradual increase in the models' predictive power with the length of the timeframe considered for calculating the comorbidity measures. CONCLUSIONS: For predicting outcomes 1 year after THA, we found that there was no added value in ICD-10-based comorbidity measures if patient Charnley classification and preoperative HRQoL and pain measures were known. LEVEL OF EVIDENCE: Level III, therapeutic study.
BACKGROUND: Comorbidities influence surgical outcomes and therefore need to be included in risk adjustment when predicting patient-reported outcomes. However, there is no consensus on how best to use the available data about comorbidities in registry-based predictive models. QUESTIONS/PURPOSES: The purposes of this study were (1) to determine whether the International Classification of Diseases, 10(th) Revision (ICD-10)-based comorbidity measures (Elixhauser, Charlson, and Royal College of Surgeons Charlson) offer added value in explaining patients' health-related quality of life (HRQoL), pain, and satisfaction after total hip arthroplasty (THA) when preoperative HRQoL, pain, and Charnley classification were known; and (2) to determine the ideal timeframe for recording the different diagnoses that serves as the basis for comorbidity measure calculations. METHODS: There were 22,263 patients who had undergone THA with complete pre- and postoperative patient-reported outcome measures (PROMs) included in the Swedish Hip Arthroplasty Register between 2002 and 2007. The three comorbidity indices were calculated with ICD-10 codes identified in the Swedish National Patient Register from 1, 2, and 5 years before the patient underwent THA. The impact of the comorbidity indices on the PROM scores (EQ-5D index, EQ visual analog scale [VAS], pain VAS, and satisfaction VAS) was modeled with linear regression where the 1-year patient postoperative outcome score was the dependent variable and independent variables included patient preoperative Charnley classification, preoperative HRQoL and pain, and comorbidity indices. The partial R(2) value indicated how much each variable uniquely contributed to the predictive capacity of the model. RESULTS: The ICD-10-based comorbidity measures added little predictive value to the models for each of the outcomes of interest (EQ-5D index, EQ VAS, pain VAS, and satisfaction VAS). Charnley classification and the preoperative scores were the strongest predictors of both measures of postoperative HRQoL, of postoperative pain, and postoperative satisfaction with outcomes from surgery. Of all the predictors considered, only the Charnley classification was associated with all outcomes, irrespective of the timeframe considered. For each of the outcomes considered, there was a gradual increase in the models' predictive power with the length of the timeframe considered for calculating the comorbidity measures. CONCLUSIONS: For predicting outcomes 1 year after THA, we found that there was no added value in ICD-10-based comorbidity measures if patient Charnley classification and preoperative HRQoL and pain measures were known. LEVEL OF EVIDENCE: Level III, therapeutic study.
Authors: Hude Quan; Vijaya Sundararajan; Patricia Halfon; Andrew Fong; Bernard Burnand; Jean-Christophe Luthi; L Duncan Saunders; Cynthia A Beck; Thomas E Feasby; William A Ghali Journal: Med Care Date: 2005-11 Impact factor: 2.983
Authors: Alex Leigh Wojtowicz; Maziar Mohaddes; Daniel Odin; Erik Bülow; Szilard Nemes; Peter Cnudde Journal: Clin Orthop Relat Res Date: 2019-06 Impact factor: 4.176
Authors: Szilárd Nemes; Kristina Burström; Niklas Zethraeus; Ted Eneqvist; Göran Garellick; Ola Rolfson Journal: Qual Life Res Date: 2015-06-03 Impact factor: 4.147
Authors: Jorge L Perez; Zachary A Mosher; Shawna L Watson; Evan D Sheppard; Eugene W Brabston; Gerald McGwin; Brent A Ponce Journal: Clin Orthop Relat Res Date: 2017-04-03 Impact factor: 4.176
Authors: Melissa Y Wei; Mohammed U Kabeto; Kenneth M Langa; Kenneth J Mukamal Journal: J Gerontol A Biol Sci Med Sci Date: 2018-01-16 Impact factor: 6.053
Authors: Vivek Singh; Stephen Zak; Joseph X Robin; David N Kugelman; Matthew S Hepinstall; William J Long; Ran Schwarzkopf Journal: Eur J Orthop Surg Traumatol Date: 2021-05-26
Authors: Alan J Silman; Christophe Combescure; Rory J Ferguson; Stephen E Graves; Elizabeth W Paxton; Chris Frampton; Ove Furnes; Anne Marie Fenstad; Gary Hooper; Anne Garland; Anneke Spekenbrink-Spooren; J Mark Wilkinson; Keijo Mäkelä; Anne Lübbeke; Ola Rolfson Journal: Acta Orthop Date: 2021-03-01 Impact factor: 3.717