Orthopedic diseases are common in dogs, and visual evaluation of gait is often used for localizing and diagnosing musculoskeletal disease.1 A more objective method to diagnose abnormal gait in dogs is IGA, with the most commonly used equipment being force plates and pressure-sensing walkway systems.2–4 However, it is difficult to compare IGA data obtained in separate laboratories because of a lack of standardization of data acquisition methods and because IGA procedures are not always described in detail in published reports. For example, the definition of a valid trial varies among laboratories,5–7 and descriptions of equilibration and calibration of the pressure-sensing walkway are not always reported.8,9
In addition to variations in IGA data collection and interpretation, lack of statistical power has also been an issue. This is exemplified in a recent study10 that evaluated randomized controlled clinical trials involving small animals in which only 14 of the 103 (14%) trials with negative results were sufficiently powered to detect a 25% relative difference in outcome between treatments. To improve the power (ie, increase sample size) of IGA research, collaborative studies with gait data obtained in separate gait laboratories may be needed. Although a study11 shows that cooperative work on IGA has occurred, differences in gait analysis systems and brands and data acquisition protocols largely prevent such collaborative research, unless the transferability of IGA data between laboratories is first established. To our knowledge, methods for animal gait laboratories to validate the use of IGA data from other animal gait laboratories are not available.
Historically, most IGA research in animals has been performed by comparing results of IGA between groups (eg, experimental vs control) of dogs when evaluating outcomes following particular treatments.12,13 However, in a clinical setting, the interest is in an individual dog. Two approaches have been used to discern clinically normal versus abnormal gaits in individual dogs. With 1 approach, IGA results for dogs with known lameness (ie, cases) versus results for dogs without lameness (ie, noncases or controls) are evaluated with ROC curve analysis.14 For each gait variable assessed with ROC curve analysis, a single statistically optimal cutoff value and its sensitivity and specificity for detection of gait abnormalities can be determined. With another approach, IGA results from clinically normal dogs free of orthopedic and neurologic disease are used to establish clinically normal values or RIs, each with a lower and upper reference limit and a corresponding specificity, usually set at a 95% CI. Both ROC curve analysis and development of RIs need sufficient sample size and sample makeup that are representative of the population of interest. Because case animals are included in ROC curve analysis, such derived sensitivity can be directly generalized only to the disease or diseases represented in the case animals. This restriction does not apply to RIs because, in their development, only noncase animals are included; however, RI sensitivity can only be determined post hoc. In the PU-AGL, RIs for kinetic variables in walking dogs were recently established15,a with methods recommended by the CLSI and comparable to those recommended by the CLSI for clinical pathology laboratories that define, establish, and verify clinicopathologic RIs.16–18
Establishing RIs for laboratory variables can be time-consuming and costly; therefore, it is not always feasible for each laboratory to develop its own RIs. An alternative is to adopt RIs established in another laboratory, and from our experience, this approach is particularly attractive in veterinary research that is often constrained by small sample sizes. However, for such RIs to be valid for the adopting laboratory, a transference process needs to be followed. To validate the transference of RIs, the CLSI recommends 3 approaches: subjective assessment for comparability of the analytic system and the test subject population, evaluation of a large number of reference individuals, or statistical assessment of a small number of reference individuals (ie, the small data approach).16,18,19 The objective of the study reported here was to use the small data approach of the CLSI as a method to evaluate the transferability of RIs for kinetic variables of IGA in walking dogs from an RI-originator laboratory (the PU-AGL) to another laboratory (the CSU-AGL) that used the same data acquisition and analytic techniques for IGA in dogs. We hypothesized that the RIs developed at the PU-AGL would be transferable to the CSU-AGL.
Clinical and Laboratory Standards Institute
Colorado State University Animal Gait Laboratory
Coefficient of variation
Dynamic weight distribution
Instrumented gait analysis
Pounds per square inch
Purdue University Animal Gait Laboratory
Peak vertical force
Receiver operating characteristic
Alshehabat MA. Instrumented gait analysis to characterize pelvic limb ataxia in dogs. PhD thesis, Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Purdue University, West Lafayette, Indiana, 2012.
HRV Walkway 6 VersaTek System, Tekscan Inc, South Boston, Mass.
Smooth Top Easy Liner (20 inches × 6 feet), ShurTech Brands LLC, Avon, Ohio.
EQ900F, EverFocus Co Ltd, New Taipei City, Taiwan.
SPSS Statistics, version 24, IBM Corp, Armonk, NY.
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