ORIGINAL ARTICLES Year : 2021  Volume : 26  Issue : 2  Page : 8490 Regressional analysis of the patella parameters of male cadaveric knees found among South East Nigerians: A useful guide to patella replacement during total knee replacement Amechi Uchenna Katchy^{1}, Augustine Uchenna Agu^{1}, Ikenna Theophilus Ikele^{1}, Chioma Nneka Ikele^{2}, Augustus Uchenna Ugwu^{1}, ^{1} Department of Anatomy, University of Nigeria Enugu Campus, Nsukka, Enugu State, Nigeria ^{2} Department of Medical Rehabilitation, University of Nigeria Enugu Campus, Nsukka, Enugu State, Nigeria Correspondence Address: Background: Total knee replacement (TKR) is a viable option for the management of osteoarthritis, and it has proven to be both effective and successful. Optimization of the patellofemoral joint kinematics is important for surgeons who choose to resurface the patella during TKR. The whole idea is to get the final patellar boneprosthesis composite thickness to match the original patellar thickness before the surgery. Aim: To correlate patella height (PH) and patella width (PW) with patella thickness (PT) as well as build a regression model through which the dimensions can predict the thickness among the native knees of the South East Nigerians. Materials and Methods: This is a correlational, nonexperimental, and observational study conducted on 60 knees from 30 male cadavers taken from the anatomy laboratory of the University of Nigeria, Enugu Campus. The PH, PW, and PT were measured by using specific endpoints and the observed data were subjected to statistical correlation analysis. Results: PH and PT were strongly positively correlated, r(59) = 0.797, P < 0.001. Results of the multiple linear regression indicated that there was a collective significant effect between the PH, PW, and PT (F(2, 57) = 51.486, P < 0.001, R^{2} = 0.644). The individual predictors were examined further and indicated that PH (t = 4.931, P < 0.001) was a significant predictor whereas PW (t = 1.153, P = 0.254) was not a significant predictor in the model. The patella’s predicted thickness is equal to 1.734+0.328 (PH in cm) +0. PT increased 0.328 cm for each centimeter of height. The PH was the only significant predictor of PT. Conclusion: This study was able to establish a correlation between the PH, PW, and PT, and it was able to demonstrate PH and PW as predictors of PT among the population of South East Nigeria.
Introduction TKR is a viable option for the management of osteoarthritis, and it has proven to be effective and successful. Patellar replacement was not part of TKRs at the early beginning. However, after reports of anterior knee pain, it got included in TKR based on the belief that it reduced anterior knee pain. This inclusion as a part of primary TKR was further accompanied by new complications. Component failure, fracture, instability, tendon rupture, and soft tissue impingement are all part of the complications identified. These complications are attributed to inferior implant design and improper surgical techniques. The fear of having these complications has made surgeons stay away from routine patellar resurfacing during TKR.[1] This decision has continued to stir the controversy about whether or not to resurface the patella during primary TKR.[2] Optimization of the patellofemoral joint kinematics is important for surgeons who choose to resurface the patella during TKR. To achieve this, establishing appropriate thickness of the patellar implant bone composite and balancing of its soft tissues is important.[3] Increased thickness of the patellar prosthesisbone composite can decrease the range of movement of the knee after a TKR.[4] Laboratory studies[5],[6],[7] have reported other detrimental effects of overstuffing the patellofemoral joint, such as lateral patellar subluxation, increased patellofemoral contact pressure on the lateral condyle, and increased patellofemoral compression forces. Resecting the amount of bone that corresponds to the thickness of the patellar implant surgeons tends to avoid overstuffing the patellofemoral joint. The whole idea is to get the final patellar boneprosthesis composite thickness to match the original PT before the surgery. This may not be easy, because the thickness is difficult to estimate for the simple reason that it has been substantially reduced by the wearing process. The patella may be excavated and the median ridge altered in most advanced cases. The patella could be quite thin and may not reflect the original thickness in these advanced cases. The measurement of the thickness of the patella before the resection during TKR is usually measured as the anteroposterior dimension from the anterior surface of the patella to the deepest part of the median ridge of the patella.[8] However, in patellae, whose articular surfaces are worn, two principal methods of reconstructing the patella without reference to the articular surface have been described: (1) the lateral facet subchondral bone thickness method,[9],[10] in which resection of all bone that is farther from the anterior surface than the most shallow part of the patella—typically on the lateral facet—is done, and (2) the tendon capsule method, in which all bone is resected deep to the posterior limit of the quadriceps tendon and the patellar tendon attachment[11],[12],[13] or the capsular attachment onto the patella.[14] Unfortunately, there is a paucity of literature on the PH, PW, and PT dimensions of South East Nigerians. The study had posed two questions for determination: First, is there any correlation between the patella dimensions and PT? Second, can the PH and PW predict the PT? The study had hypothesized that there is no statistically significant correlation between the patella dimensions and PT and that the patella dimensions cannot predict the PT. Therefore, the aim of this study is to correlate PH and PW with PT as well as to build a regression model through which the dimensions can predict the thickness among the native knees of South East Nigerians. Materials and Methods A 15cm incision was made on the medial sides of both knees of the cadaver [Figure 1], after which the skin and fascia lata covering both knees had to be carefully removed to expose the quadriceps tendon, the patella, and the patellar ligament. The tendon of the quadriceps femoris and the patellar ligament were carefully freed from the underlying structures without causing any damage or alteration to the desired structures. With the knee flexed as much as possible but not in excess of 45°, using a Vernier caliper the following measurements were taken from these end points:{Figure 1} PH: Linear distance between the superior border and the apex [Figure 2] PW: Linear distance between the medial and the lateral border [Figure 3] PT: Linear distance between the anterior surface and the median ridge on the posterior surface [Figure 4]{Figure 2} {Figure 3} {Figure 4} Statistical analysis The IBM SPSS package (IBM Corp., IBM SPSS Statistics for Windows, Version 25.0, Armonk, NY, USA), developed by International Business Machines Corporation (IBM) was used to analyze our data. Descriptive statistics were calculated for all variables of interest. Continuous measures were summarized as means and standard deviations. The P values for comparing means of continuous variables, selection of coefficients and models were determined after selecting a level of significance (α = 0.05). The Pearson correlation coefficient was used to determine correlation between the knee parameters. To ensure that the assumptions for multiple regression analysis were met, the following tests and checks were carried out: removal of outliers, collinearity, independent errors, random normally distributed errors, homoscedasticity, nonzero variances, and linearity. Results Descriptive statistics The determined values of the parameters of the cadaveric knees in centimeters are as follows: PH: M = 4.6, SD = 0.47, PW: M = 4.69, SD = 0.29, PT: M = 2.66, SD = 0.15 [Table 1].{Table 1} Test for assumptions of multiple regressions Nonzero variances The data also met the assumption of nonzero variances (PH, variance = 0.218; PW, variance = 0.083; PT, variance = 0.023) [Table 1]. Removal of outliers To check for outliers, an analysis of standard residuals using a minimum value equal to or below −3.29, and a maximum value equal to or above 3.29 as the bench mark was carried out. This analysis showed that data contained no outliers (std. residual min = −2.146, std. residual max = 1.695) [Table 2].{Table 2} Collinearity To check multicollinearity, a benchmark of a VIF value not greater than 10, or a tolerance not less than 0.1, was applied to the data. The test that met the assumption of collinearity indicated that multicollinearity was not a concern (patella height, tolerance = 0.147, VIF = 6.797; patella width, tolerance = 0.147, VIF = 6.797) [Table 3].{Table 3} Independent errors The model summary table was examined by looking at the Durbin–Watson value by using a benchmark of a value less than 1 or greater than 3 [Table 4].{Table 4} The data met the assumption of independent errors (Durbin–Watson value =1.119). Random normally distributed errors The histogram of standardized residuals indicated that the data contained approximately normally distributed errors, as did the normal PP plot of standardized residuals, which showed points that were not completely on the line, but close [Figure 5] and [Figure 6].{Figure 5} {Figure 6} Homoscedasticity The scatterplot of standardized residuals showed that the data met the assumptions of homogeneity of variance and linearity [Figure 7][Figure 8][Figure 9].{Figure 7} {Figure 8} {Figure 9} Nonzero variances The data also met the assumption of nonzero variances (PH, variance = 0.218; PW, variance = 0.083; PT, variance = 0.023) [Table 1]. Multiple regression analysis A multiple regression was conducted to see whether PH and PW predicted the PT [Table 4][Table 5][Table 6].{Table 5} {Table 6} Correlations PH and PT were strongly positively correlated, r(59) = 0.797, P < 0.001. PW and PT were strongly positively correlated, r(59) = 0.701, P < 0.001 [Table 5]. Regression model Results of the multiple linear regression indicated that there was a collective significant effect between the PH, PW, and PT (F(2, 57) = 51.486, P < 0.001, R2 = 0.644). The individual predictors were examined further and indicated that PH (t = 4.931, P < 0.001) was a significant predictor whereas PW (t = −1.153, P = 0.254) was not a significant predictor in the model. Regression model equation The patella’s predicted thickness is equal to 1.734+0.328 (PH in cm) +0. PT increased by 0.328 cm for each centimeter of height. Only PH was a significant predictor of PT. Discussion During TKR, reestablishment of the physiological thickness of the patella plays an important role in the biomechanics of the knee once the decision of the resurfacing of the patella is taken.[15],[16] Therefore, the aim should be to reestablish the original PT. A preservation of 12 to 15 mm of bone thickness is recommended during preparation of the patella, and it is recommended to maintain an overall thickness to at least onethird of the original size of the patella to avoid overstuffing and the complications associated with it.[17],[18] In severe osteoarthritis that involves the patella, advanced degenerative change, severe deformation, or erosion, all of which will invariably distort the surface anatomy make this extremely difficult. Under those circumstances, one should aim at reestablishing average PT by using other reliable methods, hence the importance of this study. The aim of the study was to establish a strong positive correlation between the PT, PW, and PH. This is in contrast with many other studies,[19],[20] in which plain Xrays and CT were used, with the authors claiming more accuracy. Apart from being considerably much more expensive than the direct measurements on the cadaver, they are not usually the method used intraoperatively. This study believes that measurements using Vernier calipers just the same way it is measured intraoperatively will provide a more reliable measurement with a decreased margin of error. In this study, the PH and PW jointly predicted the PT significantly. However, on individual examination of the predictors, the coefficient of the width was not significant; hence, it was eliminated from the model, leaving the height alone as a significant predictor. The PH was able to predict a PT increase of 0.328 cm for each centimeter of height. This regression model equation will be a valuable tool in decision making of the selection of component sizes of the patella during the TKR procedure involving the patients of South East Nigerians origins. Conclusion This study was able to establish a correlation between the PH, PW, and PT and it was able to demonstrate PH and PW as predictors of PT among the population of South East Nigeria. It supports the theory that these may be useful during TKR; hence, the regression model equation is recommended as a useful decisionmaking tool. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest. References


