Prognostic Value of a Classification and Regression Tree Model in Patients with Open-Globe Injuries
Danica T. Esteban, MD1,2, Karlo Marco D. Claudio, MD1, Cheryl A. Arcinue, MD1
1Department of Ophthalmology, Rizal Medical Center, Pasig City, Philippines
2Department of Ophthalmology, Southern Isabela Medical Center, Santiago City, Philippines
Correspondence: Danica Tomas-Esteban, MD
Clinic Address: Department of Ophthalmology, Rizal Medical Center, Pasig City, Philippines
Clinic Phone Number: +639272335051
Email Address: estebandanix@gmail.com
Disclosure: The authors report no conflict of interest.
ABSTRACT
Objective: To evaluate the accuracy of the Classification and Regression Tree (CART) model in prognosticating visual outcomes of patients with open-globe injuries
Methods: This was a retrospective, single-center, cohort study of patients with open-globe injuries seen over a two-year period. Purposive sampling of hospital medical records was done to collect data from both in- and out-patient cases. The CART algorithm was utilized to determine the predicted visual outcome for each case, and the accuracy of prognostication was measured by computing for sensitivity, specificity, positive predictive value, and negative predictive value. The area under the receiver operating characteristic curve was used to check its discriminatory capability.
Results: A total of 65 eyes (65 patients) with the following diagnoses based on the Birmingham Eye Trauma Terminology (BETT) classification were included: penetrating eye injury (n=58), globe rupture (n=2), and intra- ocular foreign body (n=5). Majority were male patients (81.5%) in the 17-39 year age group (40%). The sensitivity and specificity of CART were 100% (95% CI 93.6 to 100%) and 77.8% (95% CI 40 to 97.2%), respectively, with an overall accuracy of 96.9% (95% CI 89.3 to 99.6%). Area under the curve (AUC) was statistically significant at 0.89 (95% CI 0.79 to 0.95), indicating that the CART model can discriminate vision survival versus no vision.
Conclusion: The CART model demonstrated high accuracy in prognosticating visual outcomes after an open- globe injury in the local setting. It may be used as a helpful tool to guide treatment decisions in open-globe injuries.
Keywords: Classification and Regression Tree (CART), penetrating eye injury, open globe injury, intraocular foreign body, globe rupture