Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased Donor
Jiashan Pan, Guiyi Liao Department of Urology, The First Affiliated Hospital of Anhui Medical University and Institute of Urology and Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, Anhui, 230022, People’s Republic of ChinaCorrespondence: Guiyi LiaoDepartmen...
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Dove Medical Press
2021-11-01
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| Series: | International Journal of General Medicine |
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| Online Access: | https://www.dovepress.com/development-and-validation-of-nomogram-for-predicting-delayed-graft-fu-peer-reviewed-fulltext-article-IJGM |
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| author | Pan J Liao G |
| author_facet | Pan J Liao G |
| author_sort | Pan J |
| collection | DOAJ |
| description | Jiashan Pan, Guiyi Liao Department of Urology, The First Affiliated Hospital of Anhui Medical University and Institute of Urology and Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, Anhui, 230022, People’s Republic of ChinaCorrespondence: Guiyi LiaoDepartment of Urology, The First Affiliated Hospital of Anhui Medical University and Institute of Urology and Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, Anhui, 230022, People’s Republic of ChinaEmail liaoguiyi@ahmu.edu.cnBackground: Delayed graft function (DGF) is a major complication of kidney transplantation (KT), especially in patients receiving donor of decease (DD) KT. Therefore, the kidney donor pool is rare worldwide, it is critical to evaluate the risk coefficient of DGF using preoperative data of donors and recipients and provide a reference for clinical decision-making and resource allocation.Method and Analysis: A total of 238 DD recipients were performed in our center. Finally, 211 patients were included. The clinical database was divided into 34 clinical blood indicators (CBIs) and 6 demographics indexes (DIs). CBIs and DIs were screened for variables with P< 0.05 and demonstrated the best cut-off value using multivariable logistics regression. The selected CBIs were passed through the least absolute shrinkage and selection operator (LASSO) to obtain the predictive factors and synthesized into a Riskscore, forming a nomogram with the selected DIs. We used receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) to verify the discrimination and clinical effects of this nomogram. Finally, 10-fold cross-validation was conducted internally to show the effect of the model.Results: The 34 CBIs of the database finally screened out 12 predictors, which were synthesized into Riskscore. The 6 DIs selected 3 variables. Riskscore and 3 DIswere constructed into a nomogram, and the ROC of the nomogram has an AUC value of 0.725. Calibration and DCA showed excellent verification effects on the nomogram. The 10-fold crossover internal validation also demonstrated the model’s excellent discrepancy.Conclusion: The nomogram has an excellent ability to predict DGF and provides an essential reference for decision-making and resource allocation in a clinical setting.Keywords: kidney transplantation, donor of decease, delayed graft function, clinical blood indicators, demographics indexes, nomogram |
| first_indexed | 2024-12-14T07:40:38Z |
| format | Article |
| id | doaj.art-ac5a48467ec84248994e81f778905c30 |
| institution | Directory Open Access Journal |
| issn | 1178-7074 |
| language | English |
| last_indexed | 2024-12-14T07:40:38Z |
| publishDate | 2021-11-01 |
| publisher | Dove Medical Press |
| record_format | Article |
| series | International Journal of General Medicine |
| spelling | doaj.art-ac5a48467ec84248994e81f778905c302022-12-21T23:11:03ZengDove Medical PressInternational Journal of General Medicine1178-70742021-11-01Volume 149103911571053Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased DonorPan JLiao GJiashan Pan, Guiyi Liao Department of Urology, The First Affiliated Hospital of Anhui Medical University and Institute of Urology and Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, Anhui, 230022, People’s Republic of ChinaCorrespondence: Guiyi LiaoDepartment of Urology, The First Affiliated Hospital of Anhui Medical University and Institute of Urology and Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, Anhui, 230022, People’s Republic of ChinaEmail liaoguiyi@ahmu.edu.cnBackground: Delayed graft function (DGF) is a major complication of kidney transplantation (KT), especially in patients receiving donor of decease (DD) KT. Therefore, the kidney donor pool is rare worldwide, it is critical to evaluate the risk coefficient of DGF using preoperative data of donors and recipients and provide a reference for clinical decision-making and resource allocation.Method and Analysis: A total of 238 DD recipients were performed in our center. Finally, 211 patients were included. The clinical database was divided into 34 clinical blood indicators (CBIs) and 6 demographics indexes (DIs). CBIs and DIs were screened for variables with P< 0.05 and demonstrated the best cut-off value using multivariable logistics regression. The selected CBIs were passed through the least absolute shrinkage and selection operator (LASSO) to obtain the predictive factors and synthesized into a Riskscore, forming a nomogram with the selected DIs. We used receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) to verify the discrimination and clinical effects of this nomogram. Finally, 10-fold cross-validation was conducted internally to show the effect of the model.Results: The 34 CBIs of the database finally screened out 12 predictors, which were synthesized into Riskscore. The 6 DIs selected 3 variables. Riskscore and 3 DIswere constructed into a nomogram, and the ROC of the nomogram has an AUC value of 0.725. Calibration and DCA showed excellent verification effects on the nomogram. The 10-fold crossover internal validation also demonstrated the model’s excellent discrepancy.Conclusion: The nomogram has an excellent ability to predict DGF and provides an essential reference for decision-making and resource allocation in a clinical setting.Keywords: kidney transplantation, donor of decease, delayed graft function, clinical blood indicators, demographics indexes, nomogramhttps://www.dovepress.com/development-and-validation-of-nomogram-for-predicting-delayed-graft-fu-peer-reviewed-fulltext-article-IJGMkidney transplantationdonor of deceasedelayed graft functionclinical blood indicatorsdemographics indexesnomogram |
| spellingShingle | Pan J Liao G Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased Donor International Journal of General Medicine kidney transplantation donor of decease delayed graft function clinical blood indicators demographics indexes nomogram |
| title | Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased Donor |
| title_full | Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased Donor |
| title_fullStr | Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased Donor |
| title_full_unstemmed | Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased Donor |
| title_short | Development and Validation of Nomogram for Predicting Delayed Graft Function After Kidney Transplantation of Deceased Donor |
| title_sort | development and validation of nomogram for predicting delayed graft function after kidney transplantation of deceased donor |
| topic | kidney transplantation donor of decease delayed graft function clinical blood indicators demographics indexes nomogram |
| url | https://www.dovepress.com/development-and-validation-of-nomogram-for-predicting-delayed-graft-fu-peer-reviewed-fulltext-article-IJGM |
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