OBJECTIVES: To develop and test an appropriateness of indications tool for total knee replacement (TKR) in patients with osteoarthritis. METHODS: Criteria were developed using a modified Delphi panel judgment. Another panel rated the same indications, and the results were compared with the main panel. Test-retest of the main panel was performed. Regression models were used to assess the contribution of each algorithm variable. A classification tree was developed. RESULTS: The procedure was considered appropriate in 167 (26.8%) scenarios, and there was agreement on 112 (67.1%) of them. When the rates of the main panel were compared with those of a second panel, the result was a kappa statistic of 0.75. The test-retest kappa for the main panel was 0.78. Neither in the first case nor in the second was there an instance in which a scenario classified as appropriate shifted to inappropriate or vice versa. The regression models showed that symptomatology and radiology were the variables that explained most of the variability of appropriateness as determined by panelists. In the classification tree performed, the probability of misclassification was 3.8% with 150 scenarios, of the 156 analyzed and classified correctly. CONCLUSIONS: The previous parameters tested showed acceptable results for an evaluation tool. These results support the use of this algorithm as an aid in formulating clinical practice guidelines and to promote the appropriateness of TKR.
OBJECTIVES: To develop and test an appropriateness of indications tool for total knee replacement (TKR) in patients with osteoarthritis. METHODS: Criteria were developed using a modified Delphi panel judgment. Another panel rated the same indications, and the results were compared with the main panel. Test-retest of the main panel was performed. Regression models were used to assess the contribution of each algorithm variable. A classification tree was developed. RESULTS: The procedure was considered appropriate in 167 (26.8%) scenarios, and there was agreement on 112 (67.1%) of them. When the rates of the main panel were compared with those of a second panel, the result was a kappa statistic of 0.75. The test-retest kappa for the main panel was 0.78. Neither in the first case nor in the second was there an instance in which a scenario classified as appropriate shifted to inappropriate or vice versa. The regression models showed that symptomatology and radiology were the variables that explained most of the variability of appropriateness as determined by panelists. In the classification tree performed, the probability of misclassification was 3.8% with 150 scenarios, of the 156 analyzed and classified correctly. CONCLUSIONS: The previous parameters tested showed acceptable results for an evaluation tool. These results support the use of this algorithm as an aid in formulating clinical practice guidelines and to promote the appropriateness of TKR.
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