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Orthopaedic Proceedings
Vol. 98-B, Issue SUPP_1 | Pages 89 - 89
1 Jan 2016
Cobb J Collins R Manning V Zannotto M Moore E Jones G
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The Oxford Hip Score (OHS), the Harris Hip Score (HHS) and WOMAC are examples of patient reported outcome measures (PROMs) have well documented ceiling effects, with many patients clustered close to full marks following arthroplasty. Any arthroplasty that offers superior function would therefore fail to be detectable using these metrics. Two recent well conducted randomised clinical trials made exactly this error, by using OHS and WOMAC to detect a differences in outcome between hip resurfacing and hip arthroplasty despite published data already showing in single arm studies that these two procedures score close to full marks using both PROMS.

We had observed that patients with hip resurfacing arthroplasty (HRA) were able to walk faster and with more normal stride length than patients with well performing hip replacements, but that these objective differences in gait were not captured by PROMs. In an attempt to capture these differences, we developed a patient centred outcome measure (PCOM) using a method developed by Philip Noble's group. This allows patients to select the functions that matter to them personally against which the success of their own operation will be measured.

Our null hypothesis was that this PCOM would be no more successful than the OHS in discriminating between types of hip arthroplasty.

22 patients with a well performing Hip Resurfacing Arthroplasty were identified. These were closely matched by age, sex, BMI, height, preop diagnosis with 22 patients with a well performing conventional THA. Both were compared with healthy controls using the novel PCOM and in a gait lab.

Results

PROMs for the two groups were similar, while HRA scored higher in the PCOM. The 9% difference was significant (p<0.05).

At top walking speed, HRA were 10% faster, with a 9% longer stride length.

Discussion

Outcome measures should be able to detect differences that are clinically relevant to patients and their surgeons. The currently used hip scores are not capable of delivering this distinction, and assume that most hip replacements are effectively perfect. While the function of hip replacements is indeed very good, with satisfaction rates high, objective measures of function are essential for innovators who are trying to deliver improved functional outcome.

The 9% difference in PCOM found in this small study reflects the higher activity levels reported by many, and of similar magnitude to the 10% difference in top walking speed, despite no detectable difference in conventional PROMS. PCOMs may offer further insight into differences in function. For investigators who wish to develop improvements to hip arthroplasty, PCOMs and objective measures of gait may describe differences that matter more to patients than conventional hip scores.


Orthopaedic Proceedings
Vol. 95-B, Issue SUPP_34 | Pages 33 - 33
1 Dec 2013
Cobb J Andrews B Manning V Zannotto M Harris S
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Outcome measures are an essential element of our industry: comparing a novel procedure against an established one requires a reliable set of metrics that are comprehensible to both the technologist and the layman.

We surmised that a detailed assessment of function before and after knee arthroplasty, combined with a detailed set of personal goals would enable us to test the hypothesis that less invasive joint and ligament preserving operations could be demonstrated to be more successful, and cost effective. We asked the simple question: how well can people walk following arthroplasty, and can we measure this?

Materials and methods

Using a treadmill, instrumented with force plates, we developed a regime of walking at increasing speeds and on varying inclines, both up and down hill. The data from the force plates was then extracted directly, without using the proprietary software that filtered it. Code was written in matlab script to ensure that missed steps were not mistakenly attributed to the wrong leg, automatically downloading of all the gait data at all speeds and inclines.

The pattern of gait of both legs could then be compared over a range of activities.

Results

Wide variation is seen in gait both before and after arthroplasty. The variables that are easiest to explain are these:

width of gait – this appears to be a pre-morbid variable, not easily correctible with surgery. (figure 1)

top walking speed – total knee replacement is associated with 11% lower top speeds than uni knees or normals (p < 0.05)

change in stride length with increasing speed: normal people increase their walking speed by increasing both their cadence and their stride length incrementally until a top stride length is reached. Patients with a total knee replacement do not increase their stride length at a normal rate, having to rely on increasing cadence to deliver speed increase. Patients with uni or bi-compartmental knee replacements increase speed like normal people.

Downhill gait: as many as 40% of fit patients with ‘well functioning’ total knee replacements choose not to walk downhill at all, while all fit patients with ‘well functioning’ partial replacements are able to do this. Those who can manage, can only manage 90% of the normal speed, unlike unis which are indistinguishable from normal (p < 0.05)