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Thinking outside the Box

Although Voltaire may seem cynical, he reminds us that original thinking may achieve its freshness by borrowing inventively from elsewhere. “Predicting In Vivo Clinical Performance of Anterior Cruciate Ligament Fixation Methods From In Vitro Analysis” by Saweeres et al (this issue) asks us to look at a familiar type of study in a new way. The authors are quick to point out that this “new way” has been used in engineering circles for decades. Saweeres et al compared the fixation properties of 2 types of interference screw, one metal and one composite, in porcine tibiae. The specimens were cyclically loaded between 5 and 330 or 415 N until failure occurred: 415 N was selected because it was just below the single load to failure observed in a previous study, and 330 N was chosen because it was 20% below that level and would thus allow observations over a range of loads. Certainly, failure testing of ligament fixation devices is hardly novel, and use of cyclic loading techniques has become commonplace. This article provokes our thinking not because of what was tested, or how it was tested, but because of how the data were reported and analyzed. The current sports medicine literature is replete with studies of devices to repair or attach ligaments, ligament grafts, menisci, rotator cuff tendons, or shoulder capsules. The data from such experiments are usually reported as means, and the performance of different devices is compared by comparing those means statistically. As readers, we are prone to regard the mean as the representative performance level of the device, forgetting that about half the specimens perform below the mean. We may overlook the SDs or confidence intervals that tell us more about the results. If all biological tissues were precision engineered to exacting standards, with little variation in quality, comparing devices by their mean performance might not be so bad. But tissues do vary, and we cannot always implant fixation devices in a perfectly uniform manner. This variation leads to considerable scatter in the results of fatigue testing, and that scatter leads to large SDs in measurements that may obscure important differences when only means are compared. As in many similar investigations, there was a large scatter in the results. Some specimens failed after the first cycle and some after 10 000 cycles. Using the data generated by their experiments and the load to failure from a previous study, Saweeres et al calculated the mean life and 80/80 lower tolerance limits for each screw. The 80/80 lower tolerance limits indicate the strength that 80% of the devices would achieve with 80% confidence. The authors found that the mean fatigue life of both screws declined dramatically as the level of loading increased. Their analysis also brought out some subtleties in the performance of the 2 screws. Because the slopes of the performance curves differed, they found that the metal screw performed better at higher loads, but the composite screw performed better at lower loads. These differences were lost when the data were analyzed more conventionally. This study was not without its limitations. As with all such studies, the results do not take into account the remodeling that may occur as biological processes take over after surgery. The authors extrapolated the performance of the screws over a range of loading levels from a few data points. Saweeres et al chose the 80/80 standard somewhat arbitrarily. As they themselves point out, they could have chosen 95/95 tolerance limits, although this standard might have been overly conservative. As surgeons, we understand that no intervention has a 100% success rate. On the other hand, when we look individual patients in the eye before surgery, we would like to be able to reassure them that everything has been done to push the success rate as close to 100% as possible. That is why tolerance limits are appealing; they tell us what level of performance is likely to be achieved by an identified percentage of cases. For years, the clinical results of knee ligament surgery were reported with composite numerical rating scores. The convention of reporting total scores may have made the success rate seem higher by glossing over results that were unacceptable by certain parameters. The International Knee Documentation Committee (IKDC) rating scheme improved on this system by requiring that cases that failed in one important area be reported as failures, even if their overall point total was acceptable. Similarly, device performance testing that only reports mean results, even with appropriate statistical analysis, may be obscuring clinically significant information. Reporting tolerance limits might add useful knowledge to these studies. Another benefit of the IKDC scale is that it has become established as a standard rating method, allowing results to be more readily compared among studies. As Saweeres et al point out, it is difficult to compare the results of different fixation studies because there are no widely accepted standards for the failure testing of fixation devices. An international consortium of experts, similar to the IKDC, might develop a consensus standard for conducting and reporting the results of performance testing of soft tissue fixation devices. Although such a consensus would undoubtedly be hard to achieve, standardized testing methods would enormously increase the value of these studies by giving us a new box to think inside.