Lucia Calthorpe
Papers
1
Total Citations
7
H-Index
1
About
Lucia Calthorpe is a rising surgical outcomes researcher whose work bridges machine learning and clinical decision-making to improve patient care in colorectal surgery. Her primary research focuses on developing predictive models that move beyond traditional complication-based metrics to define and forecast "textbook outcomes"—the ideal postoperative course. In her highly cited 2023 paper, "A Novel Machine Learning Approach to Predict Textbook Outcome in Colectomy," Calthorpe introduced a sophisticated algorithm that helps surgeons identify which patients are most likely to achieve an uncomplicated recovery after colectomy, a procedure often considered low-risk. This work, already garnering 7 citations in its first year, challenges the field to think beyond avoiding harm and toward optimizing success, particularly for high-risk patients. By reframing surgical quality through the lens of ideal outcomes rather than mere absence of complications, Calthorpe is shaping a new paradigm in perioperative risk stratification. Her contributions stand at the intersection of data science and surgical practice, offering a more nuanced, patient-centered tool for shared decision-making.
Research Focus
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Top Papers
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