Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot
Background. Renal replacement therapy (RRT) is a public health problem worldwide. Kidney transplantation (KT) is the best treatment for elderly patients’ longevity and quality of life. Objectives. The primary endpoint was to compare elderly versus younger KT recipients by analyzing the risk covariab...
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Wiley
2020-01-01
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| Series: | Journal of Aging Research |
| Online Access: | http://dx.doi.org/10.1155/2020/7413616 |
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| author | Ubiracé Fernando Elihimas Júnior Jamila Pinho Couto Wallace Pereira Michel Pompeu Barros de Oliveira Sá Eduardo Eriko Tenório de França Filipe Carrilho Aguiar Diogo Buarque Cordeiro Cabral Saulo Barbosa Vasconcelos Alencar Saulo José da Costa Feitosa Thais Oliveira Claizoni dos Santos Helen Conceição dos Santos Elihimas Emilly Pereira Alves Marcio José de Carvalho Lima Frederico Castelo Branco Cavalcanti Paulo Adriano Schwingel |
| author_facet | Ubiracé Fernando Elihimas Júnior Jamila Pinho Couto Wallace Pereira Michel Pompeu Barros de Oliveira Sá Eduardo Eriko Tenório de França Filipe Carrilho Aguiar Diogo Buarque Cordeiro Cabral Saulo Barbosa Vasconcelos Alencar Saulo José da Costa Feitosa Thais Oliveira Claizoni dos Santos Helen Conceição dos Santos Elihimas Emilly Pereira Alves Marcio José de Carvalho Lima Frederico Castelo Branco Cavalcanti Paulo Adriano Schwingel |
| author_sort | Ubiracé Fernando Elihimas Júnior |
| collection | DOAJ |
| description | Background. Renal replacement therapy (RRT) is a public health problem worldwide. Kidney transplantation (KT) is the best treatment for elderly patients’ longevity and quality of life. Objectives. The primary endpoint was to compare elderly versus younger KT recipients by analyzing the risk covariables involved in worsening renal function, proteinuria, graft loss, and death one year after KT. The secondary endpoint was to create a robot based on logistic regression capable of predicting the likelihood that elderly recipients will develop worse renal function one year after KT. Method. Unicentric retrospective analysis of a cohort was performed with individuals aged ≥60 and <60 years old. We analysed medical records of KT recipients from January to December 2017, with a follow-up time of one year after KT. We used multivariable logistic regression to estimate odds ratios for elderly vs younger recipients, controlled for demographic, clinical, laboratory, data pre- and post-KT, and death. Results. 18 elderly and 100 younger KT recipients were included. Pretransplant immune variables were similar between two groups. No significant differences (P>0.05) between groups were observed after KT on laboratory data means and for the prevalences of diabetes mellitus, hypertension, acute rejection, cytomegalovirus, polyomavirus, and urinary infections. One year after KT, the creatinine clearance was higher (P = 0.006) in youngers (70.9 ± 25.2 mL/min/1.73 m2) versus elderlies (53.3 ± 21.1 mL/min/1.73 m2). There was no difference in death outcome comparison. Multivariable analysis among covariables predisposing chronic kidney disease epidemiology collaboration (CKD-EPI) equation <60 mL/min/1.73 m2 presented a statistical significance for age ≥60 years (P = 0.01) and reduction in serum haemoglobin (P = 0.03). The model presented goodness-fit in the evaluation of artificial intelligence metrics (precision: 90%; sensitivity: 71%; and F1 score: 0.79). Conclusion. Renal function in elderly KT recipients was lower than in younger KT recipients. However, patients aged ≥60 years maintained enough renal function to remain off dialysis. Moreover, a learning machine application built a robot (Elderly KTbot) to predict in the elderly populations the likelihood of worse renal function one year after KT. |
| format | Article |
| id | doaj-art-820a1b1f1ea24efc9e47e7d53f546ec4 |
| institution | Kabale University |
| issn | 2090-2204 2090-2212 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Aging Research |
| spelling | doaj-art-820a1b1f1ea24efc9e47e7d53f546ec42025-02-03T01:04:08ZengWileyJournal of Aging Research2090-22042090-22122020-01-01202010.1155/2020/74136167413616Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbotUbiracé Fernando Elihimas Júnior0Jamila Pinho Couto1Wallace Pereira2Michel Pompeu Barros de Oliveira Sá3Eduardo Eriko Tenório de França4Filipe Carrilho Aguiar5Diogo Buarque Cordeiro Cabral6Saulo Barbosa Vasconcelos Alencar7Saulo José da Costa Feitosa8Thais Oliveira Claizoni dos Santos9Helen Conceição dos Santos Elihimas10Emilly Pereira Alves11Marcio José de Carvalho Lima12Frederico Castelo Branco Cavalcanti13Paulo Adriano Schwingel14Programa de Pós-Graduação em Ciências da Saúde (PPGCS), Universidade de Pernambuco (UPE), Recife, PE 50100-130, BrazilUnidade de Nefrologia, RHP/PE, Recife, PE 52010-075, BrazilUnidade de Nefrologia e Divisão de Transplante, Universidade Federal de Pernambuco (UFPE), Recife, PE 50670-901, BrazilPrograma de Pós-Graduação em Ciências da Saúde (PPGCS), Universidade de Pernambuco (UPE), Recife, PE 50100-130, BrazilDepartamento de Fisioterapia, Universidade Federal da Paraíba (UFPB), João Pessoa, PB 58051-900, BrazilUnidade de Nefrologia e Divisão de Transplante, Universidade Federal de Pernambuco (UFPE), Recife, PE 50670-901, BrazilUnidade de Nefrologia, RHP/PE, Recife, PE 52010-075, BrazilUnidade de Nefrologia e Divisão de Transplante, Universidade Federal de Pernambuco (UFPE), Recife, PE 50670-901, BrazilUnidade de Nefrologia e Divisão de Transplante, Universidade Federal de Pernambuco (UFPE), Recife, PE 50670-901, BrazilInstituto de Ensino e Pesquisa Alberto Ferreira da Costa (IEPAFC), Real Hospital Português de Beneficência em Pernambuco (RHP/PE), Recife, PE 52010-075, BrazilPrograma de Pós-Graduação em Ciências da Saúde (PPGCS), Universidade de Pernambuco (UPE), Recife, PE 50100-130, BrazilPrograma de Pós-Graduação em Engenharia de Sistemas (PPGES), UPE, Recife 50720-001, BrazilPrograma de Pós-Graduação em Engenharia de Sistemas (PPGES), UPE, Recife 50720-001, BrazilUnidade de Nefrologia e Divisão de Transplante, Universidade Federal de Pernambuco (UFPE), Recife, PE 50670-901, BrazilPrograma de Pós-Graduação em Ciências da Saúde (PPGCS), Universidade de Pernambuco (UPE), Recife, PE 50100-130, BrazilBackground. Renal replacement therapy (RRT) is a public health problem worldwide. Kidney transplantation (KT) is the best treatment for elderly patients’ longevity and quality of life. Objectives. The primary endpoint was to compare elderly versus younger KT recipients by analyzing the risk covariables involved in worsening renal function, proteinuria, graft loss, and death one year after KT. The secondary endpoint was to create a robot based on logistic regression capable of predicting the likelihood that elderly recipients will develop worse renal function one year after KT. Method. Unicentric retrospective analysis of a cohort was performed with individuals aged ≥60 and <60 years old. We analysed medical records of KT recipients from January to December 2017, with a follow-up time of one year after KT. We used multivariable logistic regression to estimate odds ratios for elderly vs younger recipients, controlled for demographic, clinical, laboratory, data pre- and post-KT, and death. Results. 18 elderly and 100 younger KT recipients were included. Pretransplant immune variables were similar between two groups. No significant differences (P>0.05) between groups were observed after KT on laboratory data means and for the prevalences of diabetes mellitus, hypertension, acute rejection, cytomegalovirus, polyomavirus, and urinary infections. One year after KT, the creatinine clearance was higher (P = 0.006) in youngers (70.9 ± 25.2 mL/min/1.73 m2) versus elderlies (53.3 ± 21.1 mL/min/1.73 m2). There was no difference in death outcome comparison. Multivariable analysis among covariables predisposing chronic kidney disease epidemiology collaboration (CKD-EPI) equation <60 mL/min/1.73 m2 presented a statistical significance for age ≥60 years (P = 0.01) and reduction in serum haemoglobin (P = 0.03). The model presented goodness-fit in the evaluation of artificial intelligence metrics (precision: 90%; sensitivity: 71%; and F1 score: 0.79). Conclusion. Renal function in elderly KT recipients was lower than in younger KT recipients. However, patients aged ≥60 years maintained enough renal function to remain off dialysis. Moreover, a learning machine application built a robot (Elderly KTbot) to predict in the elderly populations the likelihood of worse renal function one year after KT.http://dx.doi.org/10.1155/2020/7413616 |
| spellingShingle | Ubiracé Fernando Elihimas Júnior Jamila Pinho Couto Wallace Pereira Michel Pompeu Barros de Oliveira Sá Eduardo Eriko Tenório de França Filipe Carrilho Aguiar Diogo Buarque Cordeiro Cabral Saulo Barbosa Vasconcelos Alencar Saulo José da Costa Feitosa Thais Oliveira Claizoni dos Santos Helen Conceição dos Santos Elihimas Emilly Pereira Alves Marcio José de Carvalho Lima Frederico Castelo Branco Cavalcanti Paulo Adriano Schwingel Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot Journal of Aging Research |
| title | Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot |
| title_full | Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot |
| title_fullStr | Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot |
| title_full_unstemmed | Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot |
| title_short | Logistic Regression Model in a Machine Learning Application to Predict Elderly Kidney Transplant Recipients with Worse Renal Function One Year after Kidney Transplant: Elderly KTbot |
| title_sort | logistic regression model in a machine learning application to predict elderly kidney transplant recipients with worse renal function one year after kidney transplant elderly ktbot |
| url | http://dx.doi.org/10.1155/2020/7413616 |
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