Use of routine hospital morbidity data together with weight and height of patients to predict in-hospital complications following total joint replacement

Extent: 8p. The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1472-6963/12/380BackgroundRoutinely collected data such as hospital morbidity data (HMD) are increasingly used in studying clinical outcomes among patients undergoing total joint replacement (TJR). These data are readily available and cover large populations. However, since these data were not originally collected for the purpose of health research, a rigorous assessment of their quality is required. We assessed the accuracy of the diagnosis of obesity in HMD and evaluated whether the augmentation of HMD with actual weight and height of patients could improve their ability to predict major in-hospital complications following total joint replacement in men.MethodsThe electronic records of 857 participants in the Health In Men Study (HIMS) who had had TJR were linked with Western Australia HMD. HMD-recorded diagnosis of obesity was validated using the actual weight and height obtained from HIMS. In-hospital major complications were modelled using multivariable logistic regressions that either included the actual weight and height or HMD-recorded obesity. Model discrimination was calculated using area under ROC curve.ResultsThe HMD failed to detect 70% of the obese patients. Only 64 patients (7.5%) were recorded in HMD as obese although 216 (25%) were obese [BMI: ≥30kg/m2] (sensitivity: 0.2, positive predictive value: 0.7). Overall, 174 patients (20%) developed an in-hospital major complication which was significantly higher in the overweight and obese comparing with patients with normal weight. HMD-recorded obesity was not independently associated with major complications, whereas a dose-response relationship between weight and these complications was observed (P=0.004). Using the actual weight and height of the participants instead of HMD-recorded diagnosis of obesity improved model discrimination by 9%, with areas under ROC curve of: 0.69, 95% CI: 0.64-0.73 for the model with HMD-recorded obesity compared with 0.75, 95% CI: 0.70-0.79 for the model with actual weight and height, PConclusionBody weight is an important risk factor for in-hospital complications in patients undergoing TJR. HMD systems do not include weight and height as variables whose recording is mandatory. Augmenting HMD with patients' weight and height may improve prediction of major complications following TJR. Our study suggests making these variables mandatory in any hospital morbidity data system.George Mnatzaganian, Philip Ryan, Paul E Norman, David C Davidson and Janet E Hille

Periprosthetic osteolysis after total hip replacement: molecular pathology and clinical management

Periprosthetic osteolysis is a serious complication of total hip replacement (THR) in the medium to long term. Although often asymptomatic, osteolysis can lead to prosthesis loosening and periprosthetic fracture. These complications cause significant morbidity and require complex revision surgery. Here, we review advances in our understanding of the cell and tissue response to particles produced by wear of the articular and non-articular surfaces of prostheses. We discuss the molecular and cellular regulators of osteoclast formation and bone resorptive activity, a better understanding of which may lead to pharmacological treatments for periprosthetic osteolysis. We describe the development of imaging techniques for the detection and measurement of osteolysis around THR prostheses, which enable improved clinical management of patients, provide a means of evaluating outcomes of non-surgical treatments for periprosthetic osteolysis, and assist in pre-operative planning for revision surgery. Finally, there have been advances in the materials used for bearing surfaces to minimise wear, and we review the literature regarding the performance of these new materials to date.Donald W. Howie, Susan D. Neale, David R. Haynes, Oksana T. Holubowycz, Margaret A. McGee, Lucian B. Solomon, Stuart A. Callary, Gerald J. Atkins, David M. Findla