Laparoscopic anterior lumbar interbody fusion (L-ALIF), which employs laparoscopic cameras to facilitate a less invasive approach, originally gained traction during the 1990s but has subsequently fallen out of favor. As the envelope for endoscopic approaches continues to be pushed, a recurrence of interest in laparoscopic and/or endoscopic anterior approaches seems possible. Therefore, evaluating the current evidence base in regard to this approach is of much clinical relevance. To this end, a systematic literature search was performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines using the following keywords: “(laparoscopic OR endoscopic) AND (anterior AND lumbar).” Out of the 441 articles retrieved, 22 were selected for quantitative analysis. The primary outcome of interest was the radiographic fusion rate. The secondary outcome was the incidence of perioperative complications. Meta-analysis was performed using RStudio’s “metafor” package. Of the 1,079 included patients (mean age, 41.8±2.9 years), 481 were males (44.6%). The most common indication for L-ALIF surgery was degenerative disk disease (reported by 18 studies, 81.8%). The mean follow-up duration was 18.8±11.2 months (range, 6–43 months). The pooled fusion rate was 78.9% (95% confidence interval [CI], 68.9–90.4). Complications occurred in 19.2% (95% CI, 13.4–27.4) of L-ALIF cases. Additionally, 7.2% (95% CI, 4.6–11.4) of patients required conversion from L-ALIF to open surgery. Although L-ALIF does not appear to be supported by studies available in the literature, it is important to consider the context from which these results have been obtained. Even if these results are taken at face value, the failure of endoscopy to have a role in the ALIF approach does not mean that it should not be incorporated in posterior approaches.

Background/Aims: Patients with cirrhosis and hepatocellular carcinoma (HCC) require extensive and personalized care to improve outcomes. ChatGPT (Generative Pre-trained Transformer), a large language model, holds the potential to provide professional yet patient-friendly support. We aimed to examine the accuracy and reproducibility of ChatGPT in answering questions regarding knowledge, management, and emotional support for cirrhosis and HCC. Methods: ChatGPT’s responses to 164 questions were independently graded by two transplant hepatologists and resolved by a third reviewer. The performance of ChatGPT was also assessed using two published questionnaires and 26 questions formulated from the quality measures of cirrhosis management. Finally, its emotional support capacity was tested. Results: We showed that ChatGPT regurgitated extensive knowledge of cirrhosis (79.1% correct) and HCC (74.0% correct), but only small proportions (47.3% in cirrhosis, 41.1% in HCC) were labeled as comprehensive. The performance was better in basic knowledge, lifestyle, and treatment than in the domains of diagnosis and preventive medicine. For the quality measures, the model answered 76.9% of questions correctly but failed to specify decision-making cut-offs and treatment durations. ChatGPT lacked knowledge of regional guidelines variations, such as HCC screening criteria. However, it provided practical and multifaceted advice to patients and caregivers regarding the next steps and adjusting to a new diagnosis. Conclusions We analyzed the areas of robustness and limitations of ChatGPT’s responses on the management of cirrhosis and HCC and relevant emotional support. ChatGPT may have a role as an adjunct informational tool for patients and physicians to improve outcomes.