The development and validation of a multivariable model to predict whether patients referred for total knee replacement are suitable surgical candidates at the time of initial consultation

Laura Churchill, Samuel J Malian, Bert M Chesworth, Dianne Bryant, Steven J MacDonald, Jacquelyn D Marsh, J Robert Giffin, Laura Churchill, Samuel J Malian, Bert M Chesworth, Dianne Bryant, Steven J MacDonald, Jacquelyn D Marsh, J Robert Giffin

Abstract

Background: In previous studies, 50%-70% of patients referred to orthopedic surgeons for total knee replacement (TKR) were not surgical candidates at the time of initial assessment. The purpose of our study was to identify and cross-validate patient self-reported predictors of suitability for TKR and to determine the clinical utility of a predictive model to guide the timing and appropriateness of referral to a surgeon.

Methods: We assessed pre-consultation patient data as well as the surgeon's findings and post-consultation recommendations. We used multivariate logistic regression to detect self-reported items that could identify suitable surgical candidates.

Results: Patients' willingness to undergo surgery, higher rating of pain, greater physical function, previous intra-articular injections and patient age were the factors predictive of patients being offered and electing to undergo TKR.

Conclusion: The application of the model developed in our study would effectively reduce the proportion of nonsurgical referrals by 25%, while identifying the vast majority of surgical candidates (> 90%). Using patient-reported information, we can correctly predict the outcome of specialist consultation for TKR in 70% of cases. To reduce long waits for first consultation with a surgeon, it may be possible to use these items to educate and guide referring clinicians and patients to understand when specialist consultation is the next step in managing the patient with severe osteoarthritis of the knee.

Figures

Fig. 1
Fig. 1
Flow of participants through the study. TKA = total knee arthroplasty
Fig. 2
Fig. 2
Reasons why patients were considered nonoperative, as indicated by their surgeon.
Fig. 3
Fig. 3
Algorithm for patient referral to total knee replacement (TKR). Based on model findings, willingness to undergo surgery should be determined before a referral to TKR is made. Physicians should direct unwilling patients to education and support groups. In patients who are willing to undergo surgery, pain, function and age should be further considered before referral. In patients whose symptoms are mild, referral to allied health may be the most appropriate avenue. Physicians should follow up with these patients regularly to monitor and reassess status for referral to TKR. PT = physiotherapy.

Source: PubMed

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