Precision Anesthesia Guided by Biomarkers and Real-Time Metabolic Monitoring: Advancing Personalized Perioperative and Critical Care Medicine
DOI:
https://doi.org/10.64784/229Palabras clave:
precision anesthesia, biomarkers, metabolic monitoring, personalized medicine, perioperative care, critical care, pharmacogenomics, electroencephalography, near-infrared spectroscopy, artificial intelligence, hemodynamic monitoring, glucose monitoring, lactate monitoring, patient safety, precision medicineResumen
Precision medicine has progressively transformed anesthesiology by promoting individualized perioperative management based on biological, physiological, and technological information. Within this context, biomarker-guided anesthesia and real-time metabolic monitoring have emerged as promising approaches for improving patient safety, optimizing anesthetic interventions, and enhancing clinical outcomes in surgical and critically ill populations. This review analyzed current scientific evidence regarding the role of biomarkers, advanced physiological monitoring technologies, pharmacogenomics, artificial intelligence, and metabolic surveillance systems in precision anesthesia. A comprehensive review of the literature published between 2009 and 2025 was conducted using major biomedical databases, including PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, SpringerLink, Wiley Online Library, and the Cochrane Library. The findings demonstrated increasing utilization of cardiovascular and metabolic biomarkers, electroencephalographic monitoring, near-infrared spectroscopy, continuous glucose monitoring, lactate surveillance, advanced hemodynamic assessment, and artificial intelligence-supported decision systems. Collectively, these technologies contributed to improved risk stratification, earlier detection of physiological deterioration, optimization of anesthetic drug administration, enhanced postoperative recovery, and reduction of perioperative complications. The evidence also indicated that multimodal monitoring strategies consistently outperform isolated monitoring approaches by providing a more comprehensive representation of patient physiology. Furthermore, artificial intelligence and automated monitoring platforms showed significant potential for improving predictive accuracy and individualized clinical decision-making. Overall, biomarker-guided precision anesthesia and real-time metabolic monitoring represent transformative developments in perioperative and critical care medicine. The integration of biological indicators, advanced monitoring technologies, and data-driven clinical strategies supports a more personalized approach to anesthetic management and may contribute to safer, more effective, and outcome-oriented patient care. Continued research and technological standardization will be essential to facilitate broader implementation of precision anesthesia within future healthcare systems.
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