Target Trial Emulation: A Robust Method for Observational Outcome Analysis in Surgical Research (Motivated by the Study on COVID-19 Infection and Postoperative Outcomes by O’Brien et al.)

Target trial emulation has become a key methodology for enhancing causal inference in observational studies, particularly when randomized controlled trials are impractical or unavailable. This report examines the application of target trial emulation to evaluate postoperative outcomes among patients with recent COVID-19 infection, based on the study by O’Brien et al. The findings demonstrate that after careful adjustment, recent COVID-19 infection was not independently associated with increased postoperative adverse events, highlighting the importance of minimizing confounding biases in observational research. This report further discusses the strengths and limitations of target trial emulation, emphasizing its value in replicating the rigor of randomized studies using real-world data. We outline the importance of real-world evidence in surgical research and the practical implementation of causal inference techniques in healthcare. The case study demonstrates how target trial emulation improves the validity of findings and supports clinical decision-making. Limitations related to item bank calibration and generalizability are addressed, and future directions highlight opportunities for broader integration into health systems, mobile platforms, and decision-support tools. This report underscores the essential role of adaptive testing in shaping the future of patient-centered outcomes research.