Clinical Scorecard: Advancements and Obstacles in the Use of Artificial Intelligence for Clinical Practices in Obstetric Anesthesia and Analgesia: A Brief Review

At a Glance

Key Highlights

• AI shows potential in forecasting complications like preeclampsia and postpartum hemorrhage.
• Current applications include machine learning-enhanced ultrasound for neuraxial interventions.
• AI models can predict maternal fever associated with epidurals and pain after cesarean delivery.
• Challenges include data variability, algorithmic bias, and integration into clinical workflows.
• Most research is retrospective and lacks external validation.

Guideline-Based Recommendations

Diagnosis

• Utilize AI for risk evaluation and predictive modeling in obstetric anesthesia.

Management

• Incorporate AI tools for tailored analgesic protocols and early warning systems.

Monitoring & Follow-up

• Employ real-time surveillance for intraoperative monitoring of anesthesia depth.

Risks

• Address algorithmic bias and ensure data integrity in AI applications.

Patient & Prescribing Data

Pregnant individuals requiring anesthesia during labor or surgery

AI can enhance procedural accuracy and individualized care.

Clinical Best Practices

• Focus on prospective validation and multicenter partnerships for AI models.
• Ensure AI acts as an auxiliary resource, complementing clinician expertise.

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