ReviewMedicine international
Blood gas analysis: Clinical applications, interpretation and future directions (Review).
Review in Medicine international. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Unveiling the Gaps: Machine Learning Models for Unmeasured Ions.Diagnostics (Basel, Switzerland) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.