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Clinical research on the application of AI-assisted computing systems in the treatment of intermittent exotropia
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Journal Article
Clinical research on the application of AI-assisted computing systems in the treatment of intermittent exotropia
2025
Overview
Objective
To explore the impact of AI-assisted computing systems on the effects of surgery, stereoscopic vision, and quality of life in patients with intermittent exotropia after treatment.
Methods
Data from a total of 108 children with intermittent exotropia were collected and randomly divided into Group A and Group B. Group A used the traditional prism calculation method, whereas Group B used the AI-assisted calculation system method. The success rate of surgery, the strabismus correction effect, postoperative stereoscopic function, far strabismus, near strabismus, horizontal and vertical perceptual eye positions, externally skewed deviation, and quality of life (Child-IXTQ score) were compared between the two groups.
Results
At different time points (1 day, 1 month, 3 months, and 6 months after surgery), the success rate of surgery in Group B was significantly higher than that in Group A, with an average difference in the success rate of 8.47 ± 1.92% (all
P
< 0.05). Compared with those at 1 day after surgery, the incidence rates of 6-m strabismus and 33-cm strabismus in the two groups of children were significantly lower at 1, 3, and 6 months after surgery (all
P
< 0.05). Compared with the preoperative conditions, the central stereoscopic vision of the two groups of children significantly increased at 1, 3, and 6 months after surgery, whereas the proportion of children without stereoscopic vision significantly decreased (all
P
< 0.05). Moreover, compared with preoperative conditions and 1 month postoperatively, the proportion of far-standing stereopsis gradually increased in both groups of patients at 3 and 6 months postoperatively (all
P
< 0.05). However, in terms of both central and far-standing stereoscopic vision, the rate of increase displayed by children in Group B was significantly greater than that in Group A (all
P
< 0.05). At various postoperative time points, the Child-IXTQ score of Group B was higher than that of Group A. At 6 months after surgery, the Child-IXTQ score of Group B reached its highest value (84.57 ± 5.32) (all
P
< 0.05).
Conclusion
AI-assisted computing systems can effectively improve the success rate of paediatric surgery, enhance the establishment of stereoscopic vision function, improve visual quality, and significantly improve quality of life.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Child
/ Children
/ Depth Perception - physiology
/ Disease
/ Female
/ Humans
/ Male
/ Medicine
/ Methods
/ Oculomotor Muscles - physiopathology
/ Oculomotor Muscles - surgery
/ Ophthalmologic Surgical Procedures - methods
/ Patients
/ Surgery
/ Surgery, Computer-Assisted - methods
/ Vision
/ Vision disorders in children
