Aplicações da Inteligência Artificial no Transplante Renal: Uma Revisão de Escopo ao Longo do Continuum do Cuidado

Bruno Fernandes; Claudia Affonso Silva Araujo; Isabela Braga de Moura

Autores

Bruno Fernandes Universidade Federal do Rio de Janeiro – Instituto Coppead de Administração – Rio de Janeiro (RJ) – Brasil. https://orcid.org/0000-0002-1455-0092
Claudia Affonso Silva Araujo Universidade Federal do Rio de Janeiro – Instituto Coppead de Administração – Rio de Janeiro (RJ) – Brasil.
Isabela Braga de Moura Universidade Federal do Rio de Janeiro – Instituto Coppead de Administração – Rio de Janeiro (RJ) – Brasil. https://orcid.org/0000-0001-9149-0954

Palavras-chave:

Transplante renal, Inteligência Artificial, Aprendizagem de máquina, Revisão de escopo

Resumo

Objetivos: Mapear a literatura científica sobre aplicações de inteligência artificial (IA) no processo de transplante renal, identificando os principais usos, as etapas do cuidado em que se concentram e os desfechos e processos que buscam influenciar. Métodos: Foi realizada uma revisão de escopo, reportada conforme o Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. A busca foi realizada na base Scopus, com termos relacionados à IA e ao transplante renal, contemplando publicações no período de 2019 a 2023. Foram incluídos estudos empíricos revisados por pares que aplicassem IA em qualquer fase do transplante renal. A seleção foi realizada por triagem e elegibilidade, e os estudos incluídos foram analisados por meio de análise de conteúdo indutiva, com categorização iterativa das aplicações, fases do cuidado e desfechos investigados. Resultados: Foram incluídos 181 estudos. As aplicações de IA foram organizadas em sete categorias: previsão de comportamentos do paciente; avaliação radiológica e patológica; previsão de progressão da doença renal pré-transplante; previsão de compatibilidade doador-receptor; otimização da administração de medicamentos imunossupressores; diagnóstico de complicações pós-transplante; e previsão de sobrevivência do enxerto. Observou-se a predominância de aplicações no pós-transplante (65,7%), seguida por estudos que abrangem pré- e pós-transplante (24,3%); a fase pré-transplante concentrou 9,9% das publicações. De modo geral, os estudos buscaram influenciar desfechos relacionados à detecção precoce de complicações, estratificação de risco, otimização terapêutica e sobrevida do enxerto. Conclusão: A literatura evidencia crescimento e heterogeneidade nas aplicações de IA no transplante renal, com forte concentração em tarefas diagnósticas e preditivas no período pós-transplante e lacunas relevantes na fase pré-transplante e em dimensões comportamentais do cuidado. O mapeamento oferece uma visão integrada do campo e pode apoiar pesquisadores, clínicos e gestores na identificação de oportunidades para o desenvolvimento e a incorporação de soluções de IA ao longo do continuum do transplante renal.

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