Large language models in de hypertensiezorg: kansen en grenzen

Large language models have emerged as potential tools to support hypertension care, including diagnosis, treatment decision-making, and patient education. However, evidence regarding their validity, performance, and clinical applicability remains limited. The objective is to map current applications of large language models in hypertension care, with emphasis on model optimization strategies, evaluation approaches, and reported limitations. We conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews–compliant scoping review of primary studies published between 2023 and 2025 evaluating large language models in hypertension. Thirty-three studies were included. Data were charted on clinical use cases, model optimization techniques, evaluation metrics, data sets, and limitations. Applications were categorized into clinical decision support systems, patient education, medical education, research support, and administrative functions. GPT-b