Development and validation of multiple linear regression models for predicting total hip arthroplasty acetabular prosthesis

Abstract

Purpose To establish a multivariate linear equation to predict the diameter (outer diameter) of the acetabular prosthesis used in total hip arthroplasty. Methods A cohort of 258 individuals who underwent THA at our medical facility were included in this study. The independent variables encompassed the patients' height, weight, foot length, gender, age, and surgical access. The dependent variable in this study was the diameter of the acetabular prosthesis utilized during the surgical procedure. The entire cohort dataset was randomly partitioned into a training cohort and a validation cohort, with a ratio of 7:3, employing the SPSS 26.0 software. Pearson correlation analysis was conducted to examine the relationships between the patients' height, weight, foot length, gender, age, surgical access, and the diameter of the acetabular prosthesis in the training cohort. Additionally, a multiple linear regression equation was developed using the independent variables from the training cohort and the diameter of the acetabular prosthesis as the dependent variable. This equation aimed to predict the diameter of the acetabular prosthesis based on the patients' characteristics. The accuracy of the equation was evaluated by substituting the data of the validation cohort into the multiple linear equation. The predicted acetabular prosthesis diameters were then compared with the actual diameters used in the operation. Results The correlation analysis conducted on the training cohort revealed that surgical access (r = 0.054) and age (r = −0.120) exhibited no significant correlation with the diameter of the acetabular prosthesis utilized during the intraoperative procedure. Conversely, height (r = 0.687), weight (r = 0.654), foot length (r = 0.687), and sex (r = 0.354) demonstrated a significant correlation with the diameter of the acetabular prosthesis used intraoperatively. Furthermore, a predictive equation, denoted as Y (acetabular prosthesis diameter in mm) = 20.592 + 0.548 × foot length (cm) + 0.083 × height (cm) + 0.077 × weight (kg), was derived. This equation accurately predicted the diameter within one size with an accuracy rate of 64.94% and within two sizes with an accuracy rate of 94.81%. Conclusion Anthropometric data can accurately predict the diameter of acetabular prosthesis during total hip arthroplasty.

A computed tomography-based nomogram for neoadjuvant chemotherapy plus immunotherapy response prediction in patients with advanced esophageal squamous cell carcinoma

“…Therefore, future work will involve collecting data from multiple centers and large samples to confirm our findings. On the other hand, we did not apply the K-fold cross-validation but the SPSS (version 25, Chicago, IL, USA) for data grouping because the latter has been commonly used in similar research ( 20 ). We will compare the utility of K-fold cross-validation to perform the relevant study with the utility of SPSS in the future.…”

“…Therefore, 17 cases were excluded from our study, and 158 patients were ultimately included in the study. All participants were randomly assigned to a training cohort (TC, n = 121) and a validation cohort (VC, n = 37) with SPSS (version 25, Chicago, IL, USA) ( 20 ). All the patients underwent CT examinations before and after two cycles of neoadjuvant chemotherapy plus immunotherapy.…”