Predicting 1-year flexion results in Total Knee Replacement patients Negus JJ MSc 1,2 Parker DA FRACS 1 Coolican MRJ FRACS 1 Galea A MRCS 1 Ogut M 2 1 Sydney Orthopaedic Research Institute 2 University of Sydney Australian Orthopaedic Association 70 th Annual Scientific Meeting Adelaide, 2010

Declarations No conflicts of interest to declare No conflicts of interest to declare

Introduction A knee with poor flexion can be clinically restrictive. A knee with poor flexion can be clinically restrictive. 90˚ often a clinical cut-off 90˚ often a clinical cut-off It is unclear whether a knee with poor flexion at 6-weeks will benefit from a manipulation It is unclear whether a knee with poor flexion at 6-weeks will benefit from a manipulation Postoperative flexion has been shown to correlate to preoperative flexion, but not as a quantitative predictor.* Postoperative flexion has been shown to correlate to preoperative flexion, but not as a quantitative predictor.* * Anouchi et al `96, Lingard et al 04, Ritter et al 03

Aims of Study 1. To identify the value of early postoperative flexion measurements as predictors of 1-year flexion. 2. To identify which knees might benefit from manipulation in the early postoperative phase.

Methods Prospective series of 104 knees in 100 patients Prospective series of 104 knees in 100 patients 2 specialist knee surgeons 2 specialist knee surgeons Age, BMI, Surgeon (implant) Age, BMI, Surgeon (implant) ROM measured ROM measured Pre-op, intra-op, day 2, day 6, 6 weeks, 1 year Pre-op, intra-op, day 2, day 6, 6 weeks, 1 year Functional scores (WOMAC, Oxford) Functional scores (WOMAC, Oxford) Pre-operative Pre-operative 1 year 1 year Discharge 6 days postoperatively Discharge 6 days postoperatively Most commonly to inpatient rehabilitation Most commonly to inpatient rehabilitation Physiotherapy and rehabilitation not standardised Physiotherapy and rehabilitation not standardised

Patients and Methods Knee flexion measured with a goniometer Knee flexion measured with a goniometer Reproducible technique * Reproducible technique * Spinal or general anaesthetic Spinal or general anaesthetic Medial parapatellar approach Medial parapatellar approach Fixed bearing prosthesis; patella resurfaced Fixed bearing prosthesis; patella resurfaced Peri-articular soft tissue infiltration of local anaesthetic Peri-articular soft tissue infiltration of local anaesthetic Closure with knee flexed between 60 – 90˚ Closure with knee flexed between 60 – 90˚ * Edwards et al 04

Demographics GroupMaleFemale Number Pre-op flexion113 (50-135) Age70 (52-86)71 (47-94) BMI28.9

RESULTS

Arc of motion

Correlations with flexion at 1 year Significant correlations between – Significant correlations between – Preoperative flexion & 1 year flexion p= Preoperative flexion & 1 year flexion p= Week 6 flexion & 1 year flexionp=<0.001 Week 6 flexion & 1 year flexionp=<0.001 Preoperative flexionWeek 6 flexion

Predictive equation at 6 weeks 6/52 FlexionMultiply by <100˚ ˚ ˚ ˚1.035 Mean accuracy of 0.22˚ (0.04˚ if 6 week flexion is >100˚) If 6 week flexion >100˚ 4 knees overestimated by >10˚ Only 1 had 1 year flexion <110˚

Clinical course 90˚ at 6 weeks Only 15% of these still had 90˚ at 1-year Only 15% of these still had 90˚ at 1-year 90˚ at 1 year 90˚ at 1 year 75% had 110˚preoperative flexion 75% had 110˚preoperative flexion

Pre-op 90˚ vs. >90˚ *

6 week 90˚ vs. >90˚

Statistical model A regression analysis model taking into account all variables A regression analysis model taking into account all variables It explains 54% of the variance in the results * It explains 54% of the variance in the results * Mean predictive accuracy 1.0˚ (SD 8.0, CI 1.9) Mean predictive accuracy 1.0˚ (SD 8.0, CI 1.9) Only 8 predictions were overestimated by >10˚ Only 8 predictions were overestimated by >10˚ * Anouchi et al 1996

Equation 1 year flexion = ( * BMI -0.5 ) + ( 6.18 * Pre-op flexion 3 ) + ( 2983 * 6 week flexion 2 )

Conclusions 1. 54% of the variance of final flexion accounted for by Preoperative flexion, 6 week flexion and BMI. Preoperative flexion, 6 week flexion and BMI. No effect of age, gender, surgeon and flexion at other time points No effect of age, gender, surgeon and flexion at other time points 1. Flexion at 6 weeks can guide our predictions of final flexion. 1. A statistical model is needed to predict poor flexion results. 2. This study suggests caution before manipulating knees, based on a single postoperative flexion measurement alone.

Discussion The ability to predict which knees are likely to end up with a poor result would benefit surgeons and patients. The ability to predict which knees are likely to end up with a poor result would benefit surgeons and patients. Further work before the model can be used as a clinical tool. Further work before the model can be used as a clinical tool. Retrospective data analysis of extensive database. Retrospective data analysis of extensive database. Regression analysis for all variables. Regression analysis for all variables. Refine predictive equation. Refine predictive equation.

Thank You Many thanks to Dr Corey Scholes 1 PhD for his help with the statistical analysis 1 – Sydney Orthopaedic research Institute

Bibliography Anouchi YS et al. Range of motion in total knee replacement. COOR 1996;331:87-92 Anouchi YS et al. Range of motion in total knee replacement. COOR 1996;331:87-92 Ritter MA et al. Predicting ROM after total knee arthroplasty. JBJS Am 2003;85: Ritter MA et al. Predicting ROM after total knee arthroplasty. JBJS Am 2003;85: Edwards JZ et al. Measuring flexion in knee arthroplasty patients. J Arthroplasty;19:3: Edwards JZ et al. Measuring flexion in knee arthroplasty patients. J Arthroplasty;19:3: Lingard EA et al. Predicting the outcome of total knee arthroplasty. JBJS Am. 2004;86: Lingard EA et al. Predicting the outcome of total knee arthroplasty. JBJS Am. 2004;86: