Trial reportBMC medicine2026
Impact of a real-time automatic quality control system for magnetically controlled capsule gastroscopy: a multicenter randomized controlled trial.
Trial report in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04954677 (A Prospective Randomized Controlled Trial of AI-box , a Real-time Quality Control System of Magnetic-controlled Capsule Gastroscopy.), which is not on this map. Not yet cited in PubMed.
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.
A Prospective Randomized Controlled Trial of AI-box , a Real-time Quality Control System of Magnetic-controlled Capsule Gastroscopy.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
18 authors.
Funding
Abstract
backgroundQuality control can reduce variations in operators' performance conducting magnetically controlled capsule gastroscopy (MCCG). However, an optimal method for quality control in routine MCCG procedures is still lacking. This study aimed to develop an automatic quality control system (AQCS) and assess its effectiveness in a clinical trial.
methodsWe developed the AQCS using convolutional neural network (CNN) models to monitor inspection completeness, evaluate gastric cleanliness, and identify suspicious lesions. Then, patients were prospectively randomized to undergo routine MCCG with or without AQCS assistance. The primary outcome was the blind spot rate in the AQCS and control groups.
resultsThe CNN model demonstrated specificity of 98.27-99.30% and sensitivity of 76.33-96.35% in gastric site identification. Between August 27, 2021, and July 28, 2022, a total of 200 patients were randomized, with 98 and 96 patients analyzed in the AQCS and control groups, respectively. Compared to the control group, the AQCS group achieved lower blind spot rates (median: 0.00% vs. 16.67%, P < 0.01), higher lesion detection rates (75.51% vs. 60.42%, P = 0.02), and comparable gastric examination time (28.63 min vs. 27.58 min, P = 0.48). Additionally, AQCS showed high consistency with expert evaluations in cleanliness assessment (Kappa = 0.95, P < 0.01). No serious adverse events occurred in either group.
conclusionsAQCS significantly reduced the blind spot rate during MCCG procedures. It could be a powerful assistant tool to mitigate operator skill variability and enhance the overall quality of routine MCCG examinations.
trial registrationClinicalTrials.gov Identifier NCT04954677.
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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 Socratic graph.