Literature DB >> 25700999

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, Göran Garellick5,6, Szilard Nemes5,6.   

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.

Entities:  

Mesh:

Year:  2015        PMID: 25700999      PMCID: PMC4586242          DOI: 10.1007/s11999-015-4195-z

Source DB:  PubMed          Journal:  Clin Orthop Relat Res        ISSN: 0009-921X            Impact factor:   4.176


  22 in total

1.  EuroQol--a new facility for the measurement of health-related quality of life.

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Journal:  Health Policy       Date:  1990-12       Impact factor: 2.980

2.  Assessing the results of hip replacement. A comparison of five different rating systems.

Authors:  J J Callaghan; S H Dysart; C F Savory; W J Hopkinson
Journal:  J Bone Joint Surg Br       Date:  1990-11

3.  Comparison of three comorbidity measures for predicting health service use in patients with osteoarthritis.

Authors:  Kelli L Dominick; Tara K Dudley; Cynthia J Coffman; Hayden B Bosworth
Journal:  Arthritis Rheum       Date:  2005-10-15

4.  Comorbidity measures for use with administrative data.

Authors:  A Elixhauser; C Steiner; D R Harris; R M Coffey
Journal:  Med Care       Date:  1998-01       Impact factor: 2.983

5.  Avoiding misclassification bias with the traditional Charnley classification: rationale for a fourth Charnley class BB.

Authors:  C Röder; L P Staub; P Eichler; M Widmer; D Dietrich; S Eggli; U Müller
Journal:  J Orthop Res       Date:  2006-09       Impact factor: 3.494

6.  The long-term results of low-friction arthroplasty of the hip performed as a primary intervention.

Authors:  J Charnley
Journal:  J Bone Joint Surg Br       Date:  1972-02

7.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

Authors:  M E Charlson; P Pompei; K L Ales; C R MacKenzie
Journal:  J Chronic Dis       Date:  1987

8.  Predicting quality-of-life outcomes following total joint arthroplasty. Limitations of the SF-36 Health Status Questionnaire.

Authors:  F X McGuigan; W J Hozack; L Moriarty; K Eng; R H Rothman
Journal:  J Arthroplasty       Date:  1995-12       Impact factor: 4.757

9.  Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

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

10.  What's all that noise? The effect of co-morbidity on health outcome questionnaire results after knee arthroplasty.

Authors:  Michael J Dunbar; Otto Robertsson; Leif Ryd
Journal:  Acta Orthop Scand       Date:  2004-04
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  29 in total

1.  Is Parkinson's Disease Associated with Increased Mortality, Poorer Outcomes Scores, and Revision Risk After THA? Findings from the Swedish Hip Arthroplasty Register.

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

2.  Assessment of the Swedish EQ-5D experience-based value sets in a total hip replacement population.

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

3.  Can patient-reported outcomes predict re-operations after total hip replacement?

Authors:  Ted Eneqvist; Szilárd Nemes; Erik Bülow; Maziar Mohaddes; Ola Rolfson
Journal:  Int Orthop       Date:  2018-01-03       Impact factor: 3.075

4.  Multimorbidity in Medicare Beneficiaries: Performance of an ICD-Coded Multimorbidity-Weighted Index.

Authors:  Melissa Y Wei; David Ratz; Kenneth J Mukamal
Journal:  J Am Geriatr Soc       Date:  2020-01-09       Impact factor: 5.562

5.  Readability of Orthopaedic Patient-reported Outcome Measures: Is There a Fundamental Failure to Communicate?

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

6.  Multimorbidity and Physical and Cognitive Function: Performance of a New Multimorbidity-Weighted Index.

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

7.  Presence of back pain prior total knee arthroplasty and its effects on short-term patient-reported outcome measures.

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

8.  Preoperative medications is one of the factor affecting patient-reported outcomes after total hip arthroplasty.

Authors:  Takanori Miura; Hiroaki Kijima; Natsuo Konishi; Hitoshi Kubota; Shin Yamada; Hiroshi Tazawa; Takayuki Tani; Norio Suzuki; Keiji Kamo; Masashi Fujii; Ken Sasaki; Tetsuya Kawano; Yosuke Iwamoto; Itsuki Nagahata; Naohisa Miyakoshi; Yoichi Shimada
Journal:  J Orthop       Date:  2020-12-30

9.  International variation in distribution of ASA class in patients undergoing total hip arthroplasty and its influence on mortality: data from an international consortium of arthroplasty registries.

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

Review 10.  The Update on Instruments Used for Evaluation of Comorbidities in Total Hip Arthroplasty.

Authors:  Łukasz Pulik; Michał Podgajny; Wiktor Kaczyński; Sylwia Sarzyńska; Paweł Łęgosz
Journal:  Indian J Orthop       Date:  2021-01-26       Impact factor: 1.251

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