Trial reportBMC anesthesiology2022
Evaluating the effect of an artificial intelligence system on the anesthesia quality control during gastrointestinal endoscopy with sedation: a randomized controlled trial.
Trial report in BMC anesthesiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
What it found
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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
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Artificial intelligence-assisted interventions for perioperative anesthetic management: a systematic review and meta-analysis.BMC anesthesiology · 2024Pooled it
- Artificial intelligence and its clinical application in Anesthesiology: a systematic review.Journal of clinical monitoring and computing · 2024Pooled it
- Article
- Sedation in Gastrointestinal Endoscopy: From Drug-Centered Protocols to Personalized, Technology-Supported Pathways: A Narrative Review.Journal of clinical medicine · 2026Review
- Development and validation of a real-time AI model for differentiating benign and malignant gastric ulcers : a multicenter retrospective study.BMC gastroenterology · 2026Article
- Advancing a Hybrid Decision-Making Model in Anesthesiology: Applications of Artificial Intelligence in the Perioperative Setting.Healthcare (Basel, Switzerland) · 2025Review
- Artificial intelligence revolutionizing anesthesia management: advances and prospects in intelligent anesthesia technology.Frontiers in medicine · 2025Review
- Reshaping Anesthesia with Artificial Intelligence: From Concept to Reality.Anesthesia and critical care (Houston, Tex.) · 2025Article
- Emerging strategies in outpatient endoscopy sedation management: Recent trends and developments.World journal of gastrointestinal endoscopy · 2024Article
- Training and Resources Related to the Administration of Sedation by Nurses During Digestive Endoscopy: A Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSedative gastrointestinal endoscopy is extensively used worldwide. An appropriate degree of sedation leads to more acceptability and satisfaction. Artificial intelligence has rapidly developed in the field of digestive endoscopy in recent years and we have constructed a mature computer-aided diagnosis (CAD) system. This system can identify the remaining parts to be examined in real-time endoscopic procedures, which may help anesthetists use anesthetics properly to keep patients in an appropriate degree of sedation.
aimsThis study aimed to evaluate the effects of the CAD system on anesthesia quality control during gastrointestinal endoscopy.
methodsWe recruited 154 consecutive patients at Renmin Hospital of Wuhan University, including 76 patients in the CAD group and 78 in the control group. Anesthetists in the CAD group were able to see the CAD system's indications, while anesthetists in the control group could not. The primary outcomes included emergence time (from examination completion to spontaneous eye opening when doctors called the patients' names), recovery time (from examination completion to achievement of the primary recovery endpoints) and patient satisfaction scores. The secondary outcomes included anesthesia induction time (from sedative administration to successful sedation), procedure time (from scope insertion to scope withdrawal), total dose of propofol, vital signs, etc. This trial was registered in the Primary Registries of the WHO Registry Network, with registration number ChiCTR2100042621.
resultsEmergence time in the CAD group was significantly shorter than that in the control group (p < 0.01). The recovery time was also significantly shorter in the CAD group (p < 0.01). Patients in the CAD group were significantly more satisfied with their sedation than those in control group (p < 0.01). Vital signs were stable during the examinations in both groups. Propofol doses during the examinations were comparable between the two groups.
conclusionThis CAD system possesses great potential for anesthesia quality control. It can improve patient satisfaction during endoscopic examinations with sedation.
trial registrationChiCTR2100042621.
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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.