The performance of artificial intelligence large language model-linked chatbots in surgical decision-making for gastroesophageal reflux disease

Bright Huo; Elisa Calabrese; Patricia Sylla; Sunjay Kumar; Romeo C Ignacio; Rodolfo Oviedo; Imran Hassan; Bethany J Slater; Andreas Kaiser; Danielle S Walsh; Wesley Vosburg

doi:10.1007/s00464-024-10807-w

The performance of artificial intelligence large language model-linked chatbots in surgical decision-making for gastroesophageal reflux disease

Surg Endosc. 2024 Apr 17. doi: 10.1007/s00464-024-10807-w. Online ahead of print.

Authors

Bright Huo¹, Elisa Calabrese², Patricia Sylla³, Sunjay Kumar⁴, Romeo C Ignacio⁵, Rodolfo Oviedo^{6

7

8}, Imran Hassan⁹, Bethany J Slater¹⁰, Andreas Kaiser¹¹, Danielle S Walsh¹², Wesley Vosburg¹³

Affiliations

¹ Division of General Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada.
² University of California South California, East Bay, Oakland, CA, USA.
³ Division of Colon and Rectal Surgery, Department of Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁴ Department of General Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
⁵ Division of Pediatric Surgery/Department of Surgery, San Diego School of Medicine, University of California, California, CA, USA.
⁶ Nacogdoches Center for Metabolic and Weight Loss Surgery, Nacogdoches, TX, USA.
⁷ University of Houston Tilman J. Fertitta Family College of Medicine, Houston, TX, USA.
⁸ Sam Houston State University College of Osteopathic Medicine, Conroe, TX, USA.
⁹ University of Iowa, Iowa City, IA, USA.
¹⁰ Department of Surgery, University of Chicago, Chicago, IL, USA.
¹¹ Division of Colorectal Surgery, Department of Surgery, City of Hope National Medical Center, Duarte, CA, USA.
¹² Department of Surgery, University of Kentucky, Lexington, KY, USA.
¹³ Department of Surgery, Harvard Medical School, Mount Auburn Hospital, Cambridge, MA, USA. wesvosburg@gmail.com.

PMID: 38630178
DOI: 10.1007/s00464-024-10807-w

Abstract

Background: Large language model (LLM)-linked chatbots may be an efficient source of clinical recommendations for healthcare providers and patients. This study evaluated the performance of LLM-linked chatbots in providing recommendations for the surgical management of gastroesophageal reflux disease (GERD).

Methods: Nine patient cases were created based on key questions addressed by the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) guidelines for the surgical treatment of GERD. ChatGPT-3.5, ChatGPT-4, Copilot, Google Bard, and Perplexity AI were queried on November 16th, 2023, for recommendations regarding the surgical management of GERD. Accurate chatbot performance was defined as the number of responses aligning with SAGES guideline recommendations. Outcomes were reported with counts and percentages.

Results: Surgeons were given accurate recommendations for the surgical management of GERD in an adult patient for 5/7 (71.4%) KQs by ChatGPT-4, 3/7 (42.9%) KQs by Copilot, 6/7 (85.7%) KQs by Google Bard, and 3/7 (42.9%) KQs by Perplexity according to the SAGES guidelines. Patients were given accurate recommendations for 3/5 (60.0%) KQs by ChatGPT-4, 2/5 (40.0%) KQs by Copilot, 4/5 (80.0%) KQs by Google Bard, and 1/5 (20.0%) KQs by Perplexity, respectively. In a pediatric patient, surgeons were given accurate recommendations for 2/3 (66.7%) KQs by ChatGPT-4, 3/3 (100.0%) KQs by Copilot, 3/3 (100.0%) KQs by Google Bard, and 2/3 (66.7%) KQs by Perplexity. Patients were given appropriate guidance for 2/2 (100.0%) KQs by ChatGPT-4, 2/2 (100.0%) KQs by Copilot, 1/2 (50.0%) KQs by Google Bard, and 1/2 (50.0%) KQs by Perplexity.

Conclusions: Gastrointestinal surgeons, gastroenterologists, and patients should recognize both the promise and pitfalls of LLM's when utilized for advice on surgical management of GERD. Additional training of LLM's using evidence-based health information is needed.

Keywords: ChatGPT; GERD; Generative artificial intelligence; Guidelines; Large language models; Natural language processing; Surgery.