Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplasty
Abstract Purpose The Forgotten Joint Score (FJS-12) was designed to assess the extent to which patients were unaware of their artificial joints during daily activities, representing an ideal outcome of TKA. This study aimed to identify the individual predictors and develop a nomogram to predict a fo...
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BMC
2025-05-01
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| Series: | BMC Musculoskeletal Disorders |
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| Online Access: | https://doi.org/10.1186/s12891-025-08789-4 |
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| author | Chengshuai Zhang Zhaolun Wang Jianzeng Zhang Qi Wang Dejin Yang Yixin Zhou |
| author_facet | Chengshuai Zhang Zhaolun Wang Jianzeng Zhang Qi Wang Dejin Yang Yixin Zhou |
| author_sort | Chengshuai Zhang |
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| description | Abstract Purpose The Forgotten Joint Score (FJS-12) was designed to assess the extent to which patients were unaware of their artificial joints during daily activities, representing an ideal outcome of TKA. This study aimed to identify the individual predictors and develop a nomogram to predict a forgotten joint in patients 1 year after robotic-assisted total knee arthroplasty (RA-TKA). Methods This retrospective study involved 199 patients with knee osteoarthritis who underwent RA-TKA. All participants completed the FJS-12 questionnaire at 1-year follow-up, with scores above 77.1 considered indicative of a forgotten joint. The demographic data, surgical data, preoperative and postoperative imaging data were collected for analysis. Univariate and multivariate logistic regression analyses were conducted to determine predictors and establish a predictive model. The receiver operating characteristic curve, calibration curve analysis and decision curve analysis (DCA) were used to evaluate the discriminatory ability, calibration and clinical usefulness of the model. Results Overall, 44.22% (88/199) of knees achieved a forgotten joint 1 year after RA-TKA. Five variables were identified as independent predictors, including age, sex, prothesis type, operative time and changes in the arithmetic hip-knee-ankle angle (aHKA). The area under the curve (AUC) of the nomogram was 0.726 and 0.725 (95% CI 0.660–0.788) using 500 bootstrap resampling. The Hosmer–Lemeshow test showed that the model was of goodness-of-fit (p = 0.886). And the DCA showed net benefits when the threshold probability was between 20 and 75%. Conclusions A nomogram was developed and internally validated for predicting a forgotten joint 1 year after RA-TKA. Its implementation may enhance patient selection, refine preoperative counseling, and optimize surgical decision-making, potentially improving functional outcomes. Further external validation in broader populations is required to confirm its generalizability. Clinical trial number Not applicable. |
| format | Article |
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| institution | DOAJ |
| issn | 1471-2474 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
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| series | BMC Musculoskeletal Disorders |
| spelling | doaj-art-1ea4971e747647b6907eabf7c70ab22f2025-08-20T03:22:15ZengBMCBMC Musculoskeletal Disorders1471-24742025-05-0126111110.1186/s12891-025-08789-4Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplastyChengshuai Zhang0Zhaolun Wang1Jianzeng Zhang2Qi Wang3Dejin Yang4Yixin Zhou5Department of Orthopaedic Surgery, Beijing Jishuitan Hospital, Capital Medical UniversityDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Capital Medical UniversityDepartment of Orthopedic Surgery, The First Hospital of Jilin UniversityDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Capital Medical UniversityDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Capital Medical UniversityDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Capital Medical UniversityAbstract Purpose The Forgotten Joint Score (FJS-12) was designed to assess the extent to which patients were unaware of their artificial joints during daily activities, representing an ideal outcome of TKA. This study aimed to identify the individual predictors and develop a nomogram to predict a forgotten joint in patients 1 year after robotic-assisted total knee arthroplasty (RA-TKA). Methods This retrospective study involved 199 patients with knee osteoarthritis who underwent RA-TKA. All participants completed the FJS-12 questionnaire at 1-year follow-up, with scores above 77.1 considered indicative of a forgotten joint. The demographic data, surgical data, preoperative and postoperative imaging data were collected for analysis. Univariate and multivariate logistic regression analyses were conducted to determine predictors and establish a predictive model. The receiver operating characteristic curve, calibration curve analysis and decision curve analysis (DCA) were used to evaluate the discriminatory ability, calibration and clinical usefulness of the model. Results Overall, 44.22% (88/199) of knees achieved a forgotten joint 1 year after RA-TKA. Five variables were identified as independent predictors, including age, sex, prothesis type, operative time and changes in the arithmetic hip-knee-ankle angle (aHKA). The area under the curve (AUC) of the nomogram was 0.726 and 0.725 (95% CI 0.660–0.788) using 500 bootstrap resampling. The Hosmer–Lemeshow test showed that the model was of goodness-of-fit (p = 0.886). And the DCA showed net benefits when the threshold probability was between 20 and 75%. Conclusions A nomogram was developed and internally validated for predicting a forgotten joint 1 year after RA-TKA. Its implementation may enhance patient selection, refine preoperative counseling, and optimize surgical decision-making, potentially improving functional outcomes. Further external validation in broader populations is required to confirm its generalizability. Clinical trial number Not applicable.https://doi.org/10.1186/s12891-025-08789-4Robotic-assisted total knee arthroplastyForgotten joint scoreClinical prediction modelNomogram |
| spellingShingle | Chengshuai Zhang Zhaolun Wang Jianzeng Zhang Qi Wang Dejin Yang Yixin Zhou Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplasty BMC Musculoskeletal Disorders Robotic-assisted total knee arthroplasty Forgotten joint score Clinical prediction model Nomogram |
| title | Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplasty |
| title_full | Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplasty |
| title_fullStr | Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplasty |
| title_full_unstemmed | Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplasty |
| title_short | Development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic-assisted total knee arthroplasty |
| title_sort | development and validation of a nomogram for predicting a forgotten joint in patients one year after robotic assisted total knee arthroplasty |
| topic | Robotic-assisted total knee arthroplasty Forgotten joint score Clinical prediction model Nomogram |
| url | https://doi.org/10.1186/s12891-025-08789-4 |
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