header advert
Orthopaedic Proceedings Logo

Receive monthly Table of Contents alerts from Orthopaedic Proceedings

Comprehensive article alerts can be set up and managed through your account settings

View my account settings

Visit Orthopaedic Proceedings at:

Loading...

Loading...

Full Access

General Orthopaedics

PATIENT-SPECIFIC RECOVERY EXPECTATIONS FOLLOWING TOTAL KNEE REPLACEMENT

The International Society for Technology in Arthroplasty (ISTA), 29th Annual Congress, October 2016. PART 2.



Abstract

Introduction & aims

Satisfaction following total knee replacement (TKR) surgery remains suboptimal at around 80%. Prediction of factors influencing satisfaction may help manage expectations and thus improve satisfaction. We investigated preoperative variables that estimate the probability of achieving a successful surgical outcome following TKR in several outcomes important to patients.

Method

9 pre-operative variables (easily obtained on initial consultation) of 591 unilateral TKRs were selected for univariant then multivariant analyses. These variables included Oxford Knee Score (OKS), age, sex, BMI, ASA score, pain score, mobility aids, SF12 PCS & SF12 MCS. Using the relative predictive strengths of these variables we modeled the probabilities a successful result would be achieved for 6 patient reported outcomes at 3 and 12 months following surgery. These were ‘Excellent/good OKS’, ‘Mild/no pain’, ‘Walking without/at first a limp’, ‘No/little interference with normal work’, ‘Kneeling with little/no difficulty’ and ‘Satisfaction with surgery’.

Results

Pre-operative OKS was the most useful single predictor, having impact at three months and/or one year on all outcomes examined, except kneeling. SF12 MCS affected pain scores, pain with usual activity, and limp at three months and/or one year. At three months, BMI, age, gender, ASA and pain also influenced one or more of 6 post-operative outcomes studied.

After inputting pre-operative OKS, adding other predictors did not significantly improve the statistical model.

Conclusions

Our model provides objective probability estimates based on the outcomes of our previous TKRs, which we can use to give specific objective information to prospective TKR patients regarding their likely postoperative trajectory. We hope this will modulate patient expectations, assist preparation for their surgical experience and in turn increase satisfaction.


*Email: