Aplicaciones de la inteligencia artificial en la enfermería nefrológica: revisión integrativa de las herramientas predictivas y de gestión clínica

Abstract

Introduction: The introduction of artificial intelligence (AI) into the field of nephrology offers a new perspective for analysing technology-mediated real-time data.Objectives: To determine the applications of artificial intelligence in nephrology nursing practice and to characterise predictive, diagnostic, and clinical management tools aimed at patients with kidney disease.Methodology: AWe conducted an integrative literature review in accordance with the PRISMA statement. Original articles with no time restriction were searched in MEDLINE, EBSCO, Cochrane, and LILACS using combinations of terms related to artificial intelligence, nursing, and nephrology. Observational studies, experimental studies, and clinical trials in adult populations published in English, Spanish, or Portuguese were included. Excluded were robotic developments, gynaecological–obstetric patients, and previous reviews. Two reviewers independently extracted data on study design, sample, interventions, comparators, and main outcomes, applying CASPe guidelines to assess methodological quality.Results: From 279 initial records, 30 studies met the inclusion criteria. They were grouped into 2 categories: 16 studies on predictive and diagnostic tools, and 14 on improved care and clinical management (patient classification systems, early warning systems, dialysis optimisation, and readmission prevention). Most demonstrated the superiority of machine learning and deep learning models compared with traditional approaches.Conclusions: AI applied to nephrology nursing shows promising performance in prediction and diagnosis, as well as in the optimisation of care processes. Clinical implementation studies and cost-effectiveness evaluations are needed to consolidate its integration into daily practice and maximise its benefits.

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