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Updated: May 25, 2026
Retinal Detachment Model in Rodents by Subretinal Injection of Sodium Hyaluronate
Published on: September 11, 2013
Surgical outcome and risk stratification for primary retinal detachment repair: results from the Scottish Retinal
1Clinical Research Fellow in Ophthalmology, Department of Public Health Sciences, University of Edinburgh, Teviot Place, Edinburgh, UK. mitryd@gmail.com
Objectives:
To report the early surgical outcome, risk of failure and predictive value of rhegmatogenous retinal detachment (RRD) classification based on all participants in the Scottish Retinal Detachment study.
Methods:
Over 2 years, all incident cases of RRD in Scotland were approached for recruitment. Early postoperative success was defined as an attached retina following one procedure with a minimum follow-up of 6-8 weeks. Using a regression model, the influence of clinical factors on the failure risk was estimated and the sensitivity and specificity of the Royal College of Ophthalmologists (RCOphth) grading for RRD and the vitrectomy in retinal detachment stratification risk formula (VR-SRF) in predicting operative failure were assessed.
Results:
Primary outcome data were available for 86.2% (975/1130) of patients. The overall primary success rate was 80.8% (95% CI 78.1 to 83.3%). The presence of preoperative proliferative vitreoretinopathy of any degree and each additional clock hour of detachment increased the risk of failure by an OR of 2.4 and 1.13 respectively (p<0.05). A specificity of >95% in predicting early surgical failure was noted for highly complex RRDs according to the VR-SRF formula and the RCOphth classification.
Conclusions:
Consistent with previous series, the overall early success rate of RRD repair was 80% after one operation. The type of surgical repair did not influence overall success rates. Significant predictors of failure are the presence of preoperative proliferative vitreoretinopathy of any grade and the extent of detachment. The analytical value of current classification systems in predicting failure is most useful in complex RRDs.
