Please use this identifier to cite or link to this item:
Title: New models for donor-recipient matching in lung transplantations
Authors: Dueñas-Jurado, J. M.
Gutiérrez, P. A.
Casado-Adam, A.
Santos-Luna, F.
Salvatierra-Velázquez, A.
Cárcel, S.
Robles-Arista, C. J. C.
Hervás-Martínez, C.
metadata.dc.contributor.authoraffiliation: [Dueñas-Jurado,JM; Cárcel,S; Robles-Arista,CJC] Intensive Care Unit, Reina Sofia University Hospital, Cordoba, Spain. [Gutiérrez,PA; Hervás-Martínez,C] Department of Computer Science and Numerical Analysis, Universidad de Córdoba, Córdoba, Spain. [Casado-Adam,A] General and Digestive Surgery Unit, Reina Sofia University Hospital, Cordoba, Spain. [Santos-Luna,F] Pneumology and Lung Transplant Service, Reina Sofia University Hospital, Cordoba, Spain. [Salvatierra-Velázquez,A] Thoracic Surgery and Lung Transplantation Service, Reina Sofia University Hospital, Cordoba, Spain. [Cárcel,S] Maimonides Institute for Research in Biomedicine of Cordoba (IMIBIC), Cordoba, Spain.
Keywords: Donor;Lung transplantations;Tissue and organ procurement;Transplantation;Transplant recipients;Concepción de donantes;Trasplante de pulmón;Obtención de tejidos y órganos;Trasplante;Receptores de trasplantes
metadata.dc.subject.mesh: Medical Subject Headings::Check Tags::Female
Medical Subject Headings::Phenomena and Processes::Immune System Phenomena::Immune System Processes::Transplantation Immunology::Host vs Graft Reaction::Graft Survival
Medical Subject Headings::Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans
Medical Subject Headings::Analytical, Diagnostic and Therapeutic Techniques and Equipment::Surgical Procedures, Operative::Transplantation::Organ Transplantation::Lung Transplantation
Medical Subject Headings::Check Tags::Male
Medical Subject Headings::Geographical Locations::Geographic Locations::Europe::Spain
Medical Subject Headings::Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Data Collection::Vital Statistics::Mortality::Survival Rate
Medical Subject Headings::Persons::Persons::Tissue Donors
Medical Subject Headings::Health Care::Health Care Facilities, Manpower, and Services::Health Services::Tissue and Organ Procurement
Issue Date: 4-Jun-2021
Publisher: Public Library of Science
Citation: Dueñas-Jurado JM, Gutiérrez PA, Casado-Adam A, Santos-Luna F, Salvatierra-Velázquez A, Cárcel S, et al. New models for donor-recipient matching in lung transplantations. PLoS One. 2021 Jun 4;16(6):e0252148
Abstract: Objective One of the main problems of lung transplantation is the shortage of organs as well asreduced survival rates. In the absence of an international standardized model for lung donor-recipient allocation, we set out to develop such a model based on the characteristics of past experiences with lung donors and recipients with the aim of improving the outcomes of the entire transplantation process. Methods This was a retrospective analysis of 404 lung transplants carried out at the Reina Sofía University Hospital (Córdoba, Spain) over 23 years. We analyzed various clinical variables obtained via our experience of clinical practice in the donation and transplantation process. These were used to create various classification models, including classical statistical meth ods and also incorporating newer machine-learning approaches. Results The proposed model represents a powerful tool for donor-recipient matching, which in this current work, exceeded the capacity of classical statistical methods. The variables that pre dicted an increase in the probability of survival were: higher pre-transplant and post-trans plant functional vital capacity (FVC), lower pre-transplant carbon dioxide (PCO2) pressure, lower donor mechanical ventilation, and shorter ischemia time. The variables that negatively influenced transplant survival were low forced expiratory volume in the first second (FEV1) pre-transplant, lower arterial oxygen pressure (PaO2)/fraction of inspired oxygen (FiO2) ratio, bilobar transplant, elderly recipient and donor, donor-recipient graft disproportion requiring a surgical reduction (Tailor), type of combined transplant, need for cardiopulmonary bypass during the surgery, death of the donor due to head trauma, hospi talization status before surgery, and female and male recipient donor sex. Conclusions These results show the difficulty of the problem which required the introduction of other variables into the analysis. The combination of classical statistical methods and machine learn ing can support decision-making about the compatibility between donors and recipients. This helps to facilitate reliable prediction and to optimize the grafts for transplantation, thereby improving the transplanted patient survival rate.
metadata.dc.identifier.doi: 10.1371/journal.pone.0252148
ISSN: 1932-6203 (Online)
Appears in Collections:01- Artículos - Hospital Reina Sofía
01- Artículos - IMIBIC. Instituto Maimónides de Investigación Biomédica de Córdoba

Files in This Item:
File Description SizeFormat 
DueñasJurado_NewModels.pdfArtículo publicado480,42 kBAdobe PDFView/Open
DueñasJurado_NewModels_Tabla1.xlsxMaterial suplementario36,53 kBMicrosoft Excel XMLView/Open
DueñasJurado_NewModels_Tabla2.xlsxMaterial suplementario52,23 kBMicrosoft Excel XMLView/Open

This item is protected by original copyright

This item is licensed under a Creative Commons License Creative Commons