Header

UZH-Logo

Maintenance Infos

Inpatient mortality after orthopaedic surgery


Menendez, Mariano E; Neuhaus, Valentin; Ring, David (2015). Inpatient mortality after orthopaedic surgery. International orthopaedics, 39(7):1307-1314.

Abstract

PURPOSE Adequate comorbidity risk adjustment is central for reliable outcome prediction and provider performance evaluation. The two most commonly employed risk-adjustment methods in orthopaedic surgery were not originally validated in this patient population. We sought (1) to develop a single numeric comorbidity score for predicting inpatient mortality in patients undergoing orthopaedic surgery by combining and reweighting the conditions included in the Charlson and Elixhauser measures, and to compare its predictive performance to each of the separate component scores. We also (2) evaluated the new score separately for spine surgery, adult reconstruction, hip fracture, and musculoskeletal oncology admissions. METHODS Data from the National Hospital Discharge Survey for the years 1990 through 2007 were obtained. A comorbidity score for predicting inpatient mortality was developed by combining conditions from the Charlson and Elixhauser measures. Weights were derived from a random sample of 80 % of the cohort (n = 26,454,972), and the predictive ability of the new score was internally validated on the remaining 20 % (n = 6,739,169). Performance of scores was assessed and compared using the area under the receiver operating characteristic curve (AUC) derived from multivariable logistic regression models. RESULTS The new combined comorbidity score (AUC = 0.858, 95 % CI 0.856-0.859) performed 58 % better than the Charlson score (AUC = 0.794, 95 % CI 0.792-0.796) and 12 % better than the Elixhauser score (AUC = 0.845, 95 % CI 0.844-0.847). Of the seven conditions that received the highest weights in the new combined score, only three of them were included in both the Charlson and the Elixhauser indices. The new combined score achieved higher discriminatory power for all orthopaedic admission subgroups. CONCLUSION A single numeric comorbidity score combining conditions from the Charlson and Elixhauser models provided better discrimination of inpatient mortality than either of its constituent scores. Future research should test this score in other populations and data settings.

Abstract

PURPOSE Adequate comorbidity risk adjustment is central for reliable outcome prediction and provider performance evaluation. The two most commonly employed risk-adjustment methods in orthopaedic surgery were not originally validated in this patient population. We sought (1) to develop a single numeric comorbidity score for predicting inpatient mortality in patients undergoing orthopaedic surgery by combining and reweighting the conditions included in the Charlson and Elixhauser measures, and to compare its predictive performance to each of the separate component scores. We also (2) evaluated the new score separately for spine surgery, adult reconstruction, hip fracture, and musculoskeletal oncology admissions. METHODS Data from the National Hospital Discharge Survey for the years 1990 through 2007 were obtained. A comorbidity score for predicting inpatient mortality was developed by combining conditions from the Charlson and Elixhauser measures. Weights were derived from a random sample of 80 % of the cohort (n = 26,454,972), and the predictive ability of the new score was internally validated on the remaining 20 % (n = 6,739,169). Performance of scores was assessed and compared using the area under the receiver operating characteristic curve (AUC) derived from multivariable logistic regression models. RESULTS The new combined comorbidity score (AUC = 0.858, 95 % CI 0.856-0.859) performed 58 % better than the Charlson score (AUC = 0.794, 95 % CI 0.792-0.796) and 12 % better than the Elixhauser score (AUC = 0.845, 95 % CI 0.844-0.847). Of the seven conditions that received the highest weights in the new combined score, only three of them were included in both the Charlson and the Elixhauser indices. The new combined score achieved higher discriminatory power for all orthopaedic admission subgroups. CONCLUSION A single numeric comorbidity score combining conditions from the Charlson and Elixhauser models provided better discrimination of inpatient mortality than either of its constituent scores. Future research should test this score in other populations and data settings.

Statistics

Citations

2 citations in Web of Science®
3 citations in Scopus®
Google Scholar™

Altmetrics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Trauma Surgery
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:25 February 2015
Deposited On:27 May 2015 14:26
Last Modified:27 Jan 2017 08:01
Publisher:Springer
ISSN:0341-2695
Publisher DOI:https://doi.org/10.1007/s00264-015-2702-1
PubMed ID:25711395

Download

Full text not available from this repository.
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations