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Standard Comorbidity Measures Do Not Predict Patient-reported Outcomes 1 Year After Total Hip Arthroplasty
Meridith E Greene1,2,3, Ola Rolfson4,5,6, Max Gordon5,7
1Harris Orthopaedic Laboratory, Massachusetts General Hospital, 55 Fruit Street, GRJ 1125, Boston, MA, 02114, USA. megreene@partners.org.
Insights
Comorbidity measures using ICD-10 codes did not improve predictions of patient outcomes after total hip arthroplasty (THA) when preoperative factors were known. Preoperative health-related quality of life (HRQoL) and Charnley classification were the strongest predictors.
Area of Science:
- Orthopedic surgery outcomes research.
- Health services research and registry data analysis.
- Patient-reported outcome measure (PROM) validation.
Background:
- Comorbidities significantly impact surgical outcomes and are crucial for risk adjustment in predictive models.
- Current methods for incorporating comorbidity data into registry-based predictive models lack standardization.
- Predicting patient-reported outcomes after total hip arthroplasty (THA) requires accurate risk adjustment.
Purpose of the Study:
- To evaluate the added value of International Classification of Diseases, 10th Revision (ICD-10)-based comorbidity measures (Elixhauser, Charlson, RCS-Charlson) in predicting THA outcomes.
- To determine the optimal timeframe for recording diagnoses for comorbidity calculations.
- To assess if comorbidity measures improve prediction of health-related quality of life (HRQoL), pain, and satisfaction post-THA.
Main Methods:
- Analysis of 22,263 THA patients from the Swedish Hip Arthroplasty Register (2002-2007).
- Calculation of three comorbidity indices using ICD-10 codes from 1, 2, and 5 years pre-THA.
- Linear regression modeling to assess the impact of comorbidity indices on PROMs (EQ-5D, EQ VAS, pain VAS, satisfaction VAS), controlling for preoperative factors.
Main Results:
- ICD-10-based comorbidity measures provided minimal additional predictive value for THA outcomes.
- Preoperative HRQoL and Charnley classification were the most significant predictors of postoperative HRQoL, pain, and satisfaction.
- Charnley classification consistently predicted all outcomes regardless of the comorbidity data timeframe.
- Predictive power increased with longer timeframes for comorbidity data calculation.
Conclusions:
- ICD-10-based comorbidity measures do not enhance the prediction of 1-year post-THA outcomes when preoperative factors are considered.
- Preoperative patient characteristics (HRQoL, Charnley classification) are superior predictors of THA outcomes.
- The utility of comorbidity indices in THA outcome prediction models may be limited in the presence of robust preoperative data.
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.
