[Prognosis of the course of postoperative period after aortocoronary bypass procedure based on laboratory data]

Area of Science:

• Cardiovascular Surgery
• Medical Informatics
• Clinical Pathology

Context:

• Coronary artery bypass grafting (CABG) involves complex procedures with potential postoperative complications.
• Accurate prognostication is crucial for timely clinical intervention and patient management.
• Extracorporeal circulation during CABG necessitates careful monitoring of patient recovery.

Purpose:

• To establish decision rules for predicting the early postoperative clinical course following CABG using laboratory data.
• To develop discriminative functions for forecasting lethality, inflammatory complications, and lethal outcomes.
• To leverage biochemical and hematological parameters for enhanced patient risk assessment.

Summary:

• Discriminant analysis of 508 CABG patients identified predictive laboratory parameters.
• Linear discriminative functions were constructed for daily postoperative prognostication.
• High probabilities were achieved for forecasting lethality (85.71%), inflammatory complications (91.67%), and mortality (83.33%).

Impact:

• Provides a data-driven approach to early risk stratification in CABG patients.
• Enables proactive management strategies by predicting adverse postoperative events.
• Improves clinical decision-making through reliable prognostic tools based on laboratory diagnostics.