The best marker for assessing glycaemic control prior to total knee arthroplasty (TKA) remains unknown. The purpose of this study was to assess the utility of fructosamine compared with glycated haemoglobin (HbA1c) in predicting early complications following TKA, and to determine the threshold above which the risk of complications increased markedly. This prospective multi-institutional study evaluated primary TKA patients from four academic institutions. Patients (both diabetics and non-diabetics) were assessed using fructosamine and HbA1c levels within 30 days of surgery. Complications were assessed for 12 weeks from surgery and included prosthetic joint infection (PJI), wound complication, re-admission, re-operation, and death. The Youden’s index was used to determine the cut-off for fructosamine and HbA1c associated with complications. Two additional cut-offs for HbA1c were examined: 7% and 7.5% and compared with fructosamine as a predictor for complications.Aims
Patients and Methods
There is a paucity of studies analyzing the rates of revision total knee arthroplasty in diabetic patients stratified by glycated hemoglobin levels. The purpose of this study was to: 1) determine the incidence of revision TKA; 2) correlate the percent of glycated hemoglobin with incidence of revision; and 3) determine the cause of revision in diabetic patients stratified by glycated hemoglobin level. We utilized a national private payer dataset within the PearlDiver database from 2007 to 2015 quarter 1 to determine who had diabetes and underwent TKA. There were 424,107 patients who were included in the analysis. We determined the incidence of revision TKA in the overall cohort, in addition to stratifying the incidence by glycated hemoglobin levels. To determine the effect of glycated hemoglobin levels on revision TKA rate, we performed a correlation analysis between the level of glycated hemoglobin and the incidence of revision TKA. We performed descriptive statistics of the underlying cause of revision TKA in both the overall and stratified cohortsIntroduction
Methods
