Human vs machine: identifying ChatGPT-generated abstracts in Gynecology and Urogynecology.

BACKGROUND: ChatGPT, a publicly available artificial intelligence large language model, has allowed for sophisticated artificial intelligence technology on demand. Indeed, use of ChatGPT has already begun to make its way into medical research. However, the medical community has yet to understand the capabilities and ethical considerations of artificial intelligence within this context, and unknowns exist regarding ChatGPT's writing abilities, accuracy, and implications for authorship. OBJECTIVE: We hypothesize that human reviewers and artificial intelligence detection software differ in their ability to correctly identify original published abstracts and artificial intelligence-written abstracts in the subjects of Gynecology and Urogynecology. We also suspect that concrete differences in writing errors, readability, and perceived writing quality exist between original and artificial intelligence-generated text. STUDY DESIGN: Twenty-five articles published in high-impact medical journals and a collection of Gynecology and Urogynecology journals were selected. ChatGPT was prompted to write 25 corresponding artificial intelligence-generated abstracts, providing the abstract title, journal-dictated abstract requirements, and select original results. The original and artificial intelligence-generated abstracts were reviewed by blinded Gynecology and Urogynecology faculty and fellows to identify the writing as original or artificial intelligence-generated. All abstracts were analyzed by publicly available artificial intelligence detection software GPTZero, Originality, and Copyleaks, and were assessed for writing errors and quality by artificial intelligence writing assistant Grammarly. RESULTS: A total of 157 reviews of 25 original and 25 artificial intelligence-generated abstracts were conducted by 26 faculty and 4 fellows; 57% of original abstracts and 42.3% of artificial intelligence-generated abstracts were correctly identified, yielding an average accuracy of 49.7% across all abstracts. All 3 artificial intelligence detectors rated the original abstracts as less likely to be artificial intelligence-written than the ChatGPT-generated abstracts (GPTZero, 5.8% vs 73.3%; P<.001; Originality, 10.9% vs 98.1%; P<.001; Copyleaks, 18.6% vs 58.2%; P<.001). The performance of the 3 artificial intelligence detection software differed when analyzing all abstracts (P=.03), original abstracts (P<.001), and artificial intelligence-generated abstracts (P<.001). Grammarly text analysis identified more writing issues and correctness errors in original than in artificial intelligence abstracts, including lower Grammarly score reflective of poorer writing quality (82.3 vs 88.1; P=.006), more total writing issues (19.2 vs 12.8; P<.001), critical issues (5.4 vs 1.3; P<.001), confusing words (0.8 vs 0.1; P=.006), misspelled words (1.7 vs 0.6; P=.02), incorrect determiner use (1.2 vs 0.2; P=.002), and comma misuse (0.3 vs 0.0; P=.005). CONCLUSION: Human reviewers are unable to detect the subtle differences between human and ChatGPT-generated scientific writing because of artificial intelligence's ability to generate tremendously realistic text. Artificial intelligence detection software improves the identification of artificial intelligence-generated writing, but still lacks complete accuracy and requires programmatic improvements to achieve optimal detection. Given that reviewers and editors may be unable to reliably detect artificial intelligence-generated texts, clear guidelines for reporting artificial intelligence use by authors and implementing artificial intelligence detection software in the review process will need to be established as artificial intelligence chatbots gain more widespread use.

Evaluation and Disposition of Fetal Myelomeningocele Repair Candidates: A Large Referral Center Experience.

BACKGROUND: Fetal myelomeningocele (fMMC) repair yields superior outcomes to postnatal repair and is increasingly offered at select fetal centers. OBJECTIVES: To report the fMMC referral process from initial referral to evaluation and surgical intervention in a large fetal referral center. METHODS: We conducted a retrospective cohort study of patients referred to Texas Children's Fetal Center for fMMC between September 2013 and January 2018, reviewing the process from referral to final disposition. The stepwise evaluation included a phone interview followed by multidisciplinary consultation at our fetal center. We modified the Management of Myelomeningocele Study inclusion and exclusion criteria to allow a maternal body mass index of 35-40 on an individual basis. RESULTS: A total of 204 referrals were contacted for a phone interview; 175 (86%) pursued outpatient evaluation, and 80 (46%) of them qualified for repair. Among the eligible patients, 37 (46%) underwent fetoscopic repair, 20 (25%) underwent open repair, and 17 (21%) declined prenatal surgery. Of the 89 noneligible patients (53%) excluded upon outpatient evaluation, 64 (72%) were excluded for fetal and 17 (19%) for maternal reasons. No hindbrain herniation (16%) and maternal BMI and/or hypertension (5%) were the most common reasons for fetal and maternal exclusion, respectively. A total of 31% of our referral population underwent fetal surgery. CONCLUSIONS: A small percentage of fMMC referrals ultimately undergo prenatal surgery. Stepwise evaluation and multidisciplinary teams are key to the success of large referral programs.

Cold ischemia time is an important risk factor for post-liver transplant prolonged length of stay.

Risk analysis of cold ischemia time (CIT) in liver transplantation has largely focused on patient and graft survival. Posttransplant length of stay is a sensitive marker of morbidity and cost. We hypothesize that CIT is a risk factor for posttransplant prolonged length of stay (PLOS) and aim to conduct an hour-by-hour analysis of CIT and PLOS. We retrospectively reviewed all adult, first-time liver transplants between March 2002 and September 2016 in the United Network for Organ Sharing database. The 67,426 recipients were categorized by hourly CIT increments. Multivariate logistic regression of PLOS (defined as >30 days), CIT groups, and an extensive list of confounding variables was performed. Linear regression between length of stay and CIT as continuous variables was also performed. CIT 1-6 hours was protective against PLOS, whereas CIT >7 hours was associated with increased odds for PLOS. The lowest odds for PLOS were observed with 1-2 hours (odds ratio [OR], 0.65; 95% confidence interval [CI], 0.45-0.92) and 2-3 hours (OR, 0.65; 95% CI, 0.55-0.78) of CIT. OR for PLOS steadily increased with increasing CIT, reaching the greatest odds for PLOS with 13-14 hours (OR, 2.05; 95% CI, 1.57-2.67) and 15-16 hours (OR, 2.06; 95% CI, 1.27-3.33) of CIT. Linear regression revealed a positive correlation between length of stay and CIT with a correlation coefficient of +0.35 (P < 0.001). In conclusion, post-liver transplant length of stay is sensitive to CIT, with a substantial increase in the odds of PLOS observed with nearly every additional hour of cold ischemia. We conclude that CIT should be minimized to protect against the morbidity and cost associated with posttransplant PLOS. Liver Transplantation 24 762-768 2018 AASLD.

Liver transplantation as definitive treatment of an unresectable mesenchymal hamartoma in a child with Beckwith-Wiedemann Syndrome.

Mesenchymal liver hamartomas are benign tumors that can cause life-threatening abdominal distension and carry a risk for malignant transformation. In this case report, we describe a 13-month-old male with Beckwith-Wiedemann Syndrome (BWS) who presented with multiple mesenchymal liver hamartomas causing severe intra-abdominal mass effect. Imaging revealed six large multi-locular cystic lesions, ranging from 3.8 to 8.9 cm in diameter. The large size and spread of the tumors necessitated liver transplantation for complete removal. The patient successfully underwent cadaveric piggyback liver transplantation at 25 months of age. He was alive at 16-month follow-up without evidence of tumor recurrence or graft rejection. Histological examination of the hepatic masses revealed mucinous epithelial lining and abundant hepatocytes in varying stages of differentiation, supporting the diagnosis of mesenchymal hamartoma. To the best of our knowledge, this is the first reported case of liver transplantation in a patient with BWS as definitive treatment for unresectable mesenchymal liver hamartoma.