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A Nomogram to Predict Major Complications After Hip and Knee Arthroplasty
Authors:Thomas H. Wuerz  David M. Kent  Henrik Malchau  Harry E. Rubash
Affiliation:1. Center for Predictive Medicine Research, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts;2. Clinical Research Program, Sackler School of Graduate Biomedical Sciences, Tufts University, Boston, Massachusetts;3. Department of Orthopaedic Surgery, Massachusetts General Hospital, Boston, Massachusetts;4. Department of Orthopaedic Surgery, Cleveland Clinic Foundation, Cleveland, Ohio
Abstract:
We aimed to develop a nomogram for risk stratification of major postoperative complications in hip and knee arthroplasty based on preoperative and intraoperative variables, and assessed whether this tool would have better predictive performance compared to the Surgical Apgar Score (SAS). Logistic regression analysis was performed to develop a nomogram. Discrimination and calibration were assessed. Net reclassification improvement (NRI) was used to compare to the SAS. All variables were found to be statistically significant predictors of post-operative complications except race and lowest heart rate. The concordance index was 0.76 with good calibration. Compared to the SAS, the NRI was 71.5% overall. We developed a clinical prediction tool, the Morbidity and Mortality Acute Predictor for arthroplasty (arthro-MAP) that might be useful for postoperative risk stratification.
Keywords:postoperative complications   primary and revision hip and knee arthroplasty   outcomes   predictive model
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