Clinical Research Directory

Perioperative HALP and Surgical Outcomes

Esophagectomy is associated with substantial postoperative morbidity despite advances in perioperative care. The Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score has been proposed as a composite biomarker reflecting nutritional, inflammatory, and immune status; however, its perioperative behavior and clinical significance after esophagectomy remain unclear. This retrospective cohort study evaluates perioperative changes in HALP and examines the associations of preoperative, postoperative day 1, and postoperative day 7 HALP measurements with postoperative complications, including overall and major complications, anastomotic leakage, ICU readmission, and length of hospital stay. The study aims to clarify the potential role of perioperative HALP as a marker of postoperative recovery and adverse clinical outcomes following esophagectomy.

Frailty Assessment Reveals Cognitive Differences in ASA Classification: Anesthesiologists vs Large Language Models

The American Society of Anesthesiologists (ASA) Physical Status Classification System is widely used to assess perioperative risk, but it does not explicitly include frailty as a standardized variable. In daily clinical practice, anesthesiologists may implicitly incorporate frailty-related information into ASA classification based on individual clinical judgment, which may lead to variability between evaluators. In recent years, large language models (LLMs), a type of artificial intelligence, have been increasingly used in medical decision-support research. Unlike human clinicians, these models process information in a structured and explicit manner, without relying on intuition or implicit reasoning. The primary objective of this study is to compare ASA Physical Status classifications assigned by anesthesiologists and by two different large language models using standardized preoperative clinical data from adult patients undergoing elective surgery. A secondary objective is to evaluate how the addition of a frailty index influences ASA classification decisions made by human experts and artificial intelligence models. This prospective observational study aims to improve understanding of differences in clinical reasoning between anesthesiologists and artificial intelligence systems and to explore the role of frailty in perioperative risk assessment.