The application of a neural network to predict hypotension and vasopressor requirements non-invasively in obstetric patients having spinal anesthesia for elective cesarean section (C/S)

Artificial intelligence and its clinical application in Anesthesiology: a systematic review

PURPOSE

Application of artificial intelligence (AI) in medicine is quickly expanding. Despite the amount of evidence and promising results, a thorough overview of the current state of AI in clinical practice of anesthesiology is needed. Therefore, our study aims to systematically review the application of AI in this context.

METHODS

A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched Medline and Web of Science for articles published up to November 2022 using terms related with AI and clinical practice of anesthesiology. Articles that involved animals, editorials, reviews and sample size lower than 10 patients were excluded. Characteristics and accuracy measures from each study were extracted.

RESULTS

A total of 46 articles were included in this review. We have grouped them into 4 categories with regard to their clinical applicability: (1) Depth of Anesthesia Monitoring; (2) Image-guided techniques related to Anesthesia; (3) Prediction of events/risks related to Anesthesia; (4) Drug administration control. Each group was analyzed, and the main findings were summarized. Across all fields, the majority of AI methods tested showed superior performance results compared to traditional methods.

CONCLUSION

AI systems are being integrated into anesthesiology clinical practice, enhancing medical professionals' skills of decision-making, diagnostic accuracy, and therapeutic response.

Spinal hypotension in obstetrics: Context-sensitive prevention and management

Spinal hypotension during caesarean section remains a common complication, with important attendant maternal and fetal adverse outcomes. Research elucidating the mechanisms of spinal hypotension has led to the development and refinement of effective management strategies, with a particular emphasis on prophylactic vasopressor administration. This has proved effective in well-resourced settings, with maternal comfort and the elimination of nausea now considered the primary aim of treatment. In resource-limited settings, sophisticated strategies are not feasible due to insufficient equipment, staff, and expertise. Therefore, in these areas spinal hypotension remains an important cause of maternal and fetal morbidity and mortality. Translational, context-sensitive research in resource-limited settings has shown promise in implementing pragmatic strategies based on research from resource-rich environments. We review the current best practice for the prevention and treatment of spinal hypotension, with a special emphasis on effective strategies in resource-limited settings. We further suggest a research agenda to address the knowledge gap in specific contexts.