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Scoring systems of kidney donation from deceased donors: A systematic review

Renal disease is the most prevalent disease. Kidney failure can cause physical problems. Hence, patients need to use dialysis therapy or kidney transplantation, and actually, people are in the waiting list for a transplant. This research aimed to extract the prognostic models that evaluate the prepa...

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Detalles Bibliográficos
Autores principales: Moghbeli, Fateme, Jangi, Majid, Ebnehoseini, Zahra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826869/
https://www.ncbi.nlm.nih.gov/pubmed/35233403
http://dx.doi.org/10.4103/jehp.jehp_1657_20
Descripción
Sumario:Renal disease is the most prevalent disease. Kidney failure can cause physical problems. Hence, patients need to use dialysis therapy or kidney transplantation, and actually, people are in the waiting list for a transplant. This research aimed to extract the prognostic models that evaluate the preparation of kidney donors diagnosed with brain death (DBD). This research was a systematic review of PubMed, Science Direct, and general explorers up until 2020. It followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-P protocol. The assessment of the articles was done by the authors. This evaluation was supposed to be in the form of scoring, prioritizing, and ranking the donors in terms of their preparation. Eleven sources of information included 9 academic articles along with 2 Grey Sources from 7 different countries. 9 algorithms and models were extracted which included, overall 10 factors. All the models were comprised of 4 factors and about 90% of these models considered 4 or 5 factors to evaluate the preparation of kidney donors DBD. Over 60% of the models had taken into account age, blood pressure history, and creatinine factors. Disease prognosis facilitates a doctor's decision-making on the emergence of the disease. Prognostic models of renal diseases can be a great help to patients. A review of the related literature revealed that all the models received a high score in terms of the two factors they included, age and history of blood pressure.