ABSTRACT
PURPOSE: Enhanced recovery after surgery (ERAS) protocols have shown beneficial outcomes in the last 20 years. Nevertheless, simultaneously implemented technical improvements such as minimally invasive access or modified anesthesia care may play a crucial role in optimizing patient outcome. The aim of the study was to investigate the effect of ERAS implementation in a highly specialized colorectal center. METHODS: This is a propensity score matched single-center study comparing the short-term outcomes of patients undergoing elective colorectal surgery in a society-indepedent ERAS program from January 2021 to August 2022 to standard perioperative care from January 2019 to December 2020. RESULTS: Four hundred fifty-six patients were included in the propensity score matched analysis with 228 patients per group (ERAS vs. standard care). Minimally invasive access was used in 80.2% vs. 77.6% (p = 0.88), and there were 16.6% vs. 18.8% (p = 0.92) rectal procedures in the ERAS and standard care group, respectively. Major complications occurred in 10.1% vs. 11.4% (p = 0.65) and anastomotic leakage demanding operative revision in 2.2% vs. 2.6% (p = 0.68) in the ERAS and standard care group, respectively. ERAS lead to a lower number of non-surgical complications compared to standard care (57 vs. 79; p = 0.02). Mean length of stay (LOS) and mean costs per case were lower in ERAS compared to standard care (9.2 ± 5.6 days vs. 12.7 ± 7.4 days, p < 0.01; costs 33,727 ± 15,883 USD vs. 40,309 ± 29,738 USD, p < 0.01). CONCLUSION: The implementation of an ERAS protocol may lead to a reduction of LOS, costs, and a lower number of non-surgical complications even in a highly specialized colorectal unit using modern surgical and anesthetic care. ( ClinialTrials.gov number NCT05773248).
Subject(s)
Anesthetics , Colorectal Neoplasms , Colorectal Surgery , Enhanced Recovery After Surgery , Humans , Postoperative Complications/epidemiology , Length of StayABSTRACT
BACKGROUND: ChatGPT-4 is the latest release of a novel artificial intelligence (AI) chatbot able to answer freely formulated and complex questions. In the near future, ChatGPT could become the new standard for health care professionals and patients to access medical information. However, little is known about the quality of medical information provided by the AI. OBJECTIVE: We aimed to assess the reliability of medical information provided by ChatGPT. METHODS: Medical information provided by ChatGPT-4 on the 5 hepato-pancreatico-biliary (HPB) conditions with the highest global disease burden was measured with the Ensuring Quality Information for Patients (EQIP) tool. The EQIP tool is used to measure the quality of internet-available information and consists of 36 items that are divided into 3 subsections. In addition, 5 guideline recommendations per analyzed condition were rephrased as questions and input to ChatGPT, and agreement between the guidelines and the AI answer was measured by 2 authors independently. All queries were repeated 3 times to measure the internal consistency of ChatGPT. RESULTS: Five conditions were identified (gallstone disease, pancreatitis, liver cirrhosis, pancreatic cancer, and hepatocellular carcinoma). The median EQIP score across all conditions was 16 (IQR 14.5-18) for the total of 36 items. Divided by subsection, median scores for content, identification, and structure data were 10 (IQR 9.5-12.5), 1 (IQR 1-1), and 4 (IQR 4-5), respectively. Agreement between guideline recommendations and answers provided by ChatGPT was 60% (15/25). Interrater agreement as measured by the Fleiss κ was 0.78 (P<.001), indicating substantial agreement. Internal consistency of the answers provided by ChatGPT was 100%. CONCLUSIONS: ChatGPT provides medical information of comparable quality to available static internet information. Although currently of limited quality, large language models could become the future standard for patients and health care professionals to gather medical information.
