ArticleRisk management and healthcare policy2023
A Prediction Nomogram for Recurrent Retinal Detachment.
Article in Risk management and healthcare policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Deep Learning Algorithm Prognosticating Retinal Tears and Detachments From Optical Coherence Tomography.Translational vision science & technology · 2025Article
- Comparison of gas and silicone oil tamponades for inferior quadrant recurrence in patients undergoing pars plana vitrectomy for rhegmatogenous retinal detachment.International ophthalmology · 2025Article
- Incidence and risk factors for recurrence after surgical treatment of rhegmatogenous retinal detachment: a retrospective cohort study.International journal of retina and vitreous · 2025Article
- Development and Validation of a Nomogram to Predict the Risk of Special Uterine Leiomyoma Pathological Types or Leiomyosarcoma in Postmenopausal Women: A Retrospective Study.Risk management and healthcare policy · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Recurrent retinal detachment (re-RD) is one of the complications in rhegmatogenous retinal detachment patients who underwent surgical treatment. We investigated the risk factors for re-RD and developed a nomogram for estimating clinical risk. Methods: Univariate and multivariable logistic regression models were performed to determine the association between variables and re-RD, and a nomogram was then developed for re-RD. The nomogram performance was assessed based on its discrimination, calibration, and clinical usefulness. Results: This study analyzed 15 potential variables of re-RD in 403 rhegmatogenous retinal detachment patients who underwent initial surgical treatment. Axial length, inferior breaks, retinal break diameter, and surgical methods were independent risk factors for re-RD. A clinical nomogram incorporating these four independent risk factors was constructed. The diagnostic performance of the nomogram was excellent (area under the curve = 0.892, 95% CI: 0.831-0.953). Our study further validated this nomogram by bootstrapping for 500 repetitions. The area under the curve of the bootstrap model was 0.797 (95% CI: 0.712-0.881). This model showed good calibration curve fitting and a positive net benefit in decision curve analysis. Conclusion: Axial length, inferior breaks, retinal break diameter, and surgical methods could be risk factors for re-RD. We have developed a prediction nomogram of re-RD for rhegmatogenous retinal detachment following initial surgical treatment.
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