Blood gas analysis represents a cornerstone diagnostic method in clinical practice, providing rapid assessment of respiratory and metabolic status through evaluation of pH, partial pressure of oxygen, partial pressure of carbon dioxide and bicarbonate. The present comprehensive review discusses recent advances in blood gas analysis, including emerging artificial intelligence (AI) applications, controversial practices in venous vs. arterial sampling and closed-loop management systems in critical care. The present review critically synthesizes evidence from recent systematic reviews and meta-analyses, addressing key controversies, such as the clinical utility of venous blood gas analysis with venous-to-arterial conversion technology (sensitivity, 97.6%; specificity, 36.9% for respiratory failure diagnosis) and automated interpretation systems. The present review encompasses physiological foundations, evidence-based clinical applications, structured interpretation methodologies and quality improvement strategies. Emphasis is placed on technological innovations including AI-assisted interpretation, non-invasive monitoring technologies and integration with closed-loop therapeutic systems. Through the analysis of >50 recent publications and current guidelines, the present review aimed to provide evidence-based recommendations for modern clinical practice, highlighting when venous sampling provides adequate diagnostic information, while reducing patient discomfort. Future perspectives include predictive algorithms for early clinical deterioration recognition and personalized diagnostic approaches. The present review aimed to provide unique clinical value by bridging traditional blood gas analysis with cutting-edge technological applications, providing practitioners with contemporary, evidence-based guidance for optimal patient care.
Keywords: acid-base disorders; arterial blood gas (ABG); artificial intelligence in medicine; clinical diagnostics; respiratory failure.
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