ArticleFrontiers in medicine2025
Comparison of preoperative education by artificial intelligence versus traditional physicians in perioperative management of urolithiasis surgery: a prospective single-blind randomized controlled trial conducted in China.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Efficacy of Rule-Based Versus Large Language Model-Based Chatbots in Alleviating Symptoms of Depression and Anxiety: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Foundation models in healthcare: a comprehensive review from technical advances to clinical translation.Journal of translational medicine · 2026Review
- Artificial intelligence in surgical care within low-income and middle-income countries: a scoping review of development, validation, and deployment.EClinicalMedicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Preoperative anxiety is common in patients awaiting urolithiasis surgery. Although adequate preoperative education can reduce anxiety and improve outcomes, time and resource constraints often limit the depth and personalization of such interventions. Recent advances in AI, particularly large language models like GPT-4o and Ernie Bot, offer potential tools to supplement traditional education. However, their comparative effectiveness remains unclear. Purpose: This randomized controlled trial compared the effectiveness of AI-based preoperative education (ChatGPT, Ernie Bot) to that provided by attending urologists in reducing anxiety, enhancing satisfaction, and improving information quality. Methods: Seventy-five adult patients scheduled for urolithiasis surgery were randomly assigned (1:1:1) to ChatGPT, Ernie Bot, or urologist-led education. All received a standardized consultation 12 h preoperatively. The AI groups then had a 30 min Q&A with their assigned AI, and the physician group received an additional face-to-face session. Anxiety was measured via the State-Trait Anxiety Inventory (STAI) at baseline, immediately post-intervention, 3 h pre-op, and 3 h post-op. Secondary outcomes included patient satisfaction, query count, evaluation of information quality (safety, accuracy, empathy, readability, detail), and postoperative (3 h) pain (VAS). Results: All participants completed the study. Anxiety decreased significantly after intervention in all groups ( Conclusion: AI-assisted education, particularly via ChatGPT, can effectively reduce preoperative anxiety and improve patient engagement, though not to the level of physician-led education. Ernie Bot showed modest benefits. Further refinement of AI may enhance its role as a supplemental educational tool.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.