Purpose To find models that will explain the variability in postoperative visual acuity (VA) (logarithmic: logMAR) associated with unilateral primary rhegmatogenous retinal detachment (RD). Methods This was a prospective clinical cohort study of 33 patients with proliferative vitreoretinopathy (PVR: PVRoC3) and 33 without PVR, all of whom were candidates for scleral buckling (SB) surgery. Central retinal artery (CRA) Doppler sonography parameters (peak systolic, end diastolic velocities and resistibility index) and intraocular pressure (IOP) were measured before SB. Immunoreactive endothelin-1 (IR-ET-1) levels in both plasma and subretinal fluid (SRF) were measured using a radioimmunoassay. Visual outcomes were analysed by stepwise multivariate linear regression. The preoperative parameters used in the analysis included RD duration, IOP, logMAR VA, CRA parameters, preoperative plasma levels and intraoperative levels of IR-ET-1 in the SRF. ConclusionsThe duration of RD and the levels of IR-ET-1 in the SRF appear to be the best explanatory variables in the models for 8-month-postoperative logMAR VA variability in RD patients. RD surgery should be performed as soon as possible to best preserve VA.

Purpose To analyze if duration of primary rhegmatogenous retinal detachment(RD)influences central retinal artery(CRA) hemodynamics with repercussion on LogMAR visual acuity (VA) Methods Sixty six healthy patients between 42 and 70 years with unilateral RD candidates for scleral buckling(SB)surgery(PVR

Purpose: To study the influence of central retinal artery (CRA) blood velocities, intraocular pressure (IOP) and Endothelin‐1 (ET‐1) on visual acuity (VA) of primary rhegmatogenous retinal detachment (RD) Methods: This is a prospective interventional clinical study of 66 patients undergoing scleral buckling (SB) procedure, with reattachment of the retina 8 months after surgery. CRA Doppler sonography parameters and IOP were measured before SB. Immunoreactive (IR) ET‐1 was assayed (radioimmunoassay) in plasma and subretinal fluid (SRF). Snellen VA and fundus examination were checked before and 8 months after surgery. Stepwise multivariate linear regression analysis allowed us to find models for VA Results: IOP and CRA end diastolic velocity (EDV) explains preoperative VA (R2=0.509, p<0.0001). Preoperative VA, existence of PVR, CRA EDV and plasma IR‐ET‐1 (in PVR) explains postoperative VA (R2=0.908, p<0.0001). But, preoperative VA, SRF IR‐ET‐1 and plasma IR‐ET‐1 improves last model in PVR Conclusions: Preoperative VA, existence of PVR and CRA EDV explains 90% (88% in PVR) of the variability of postoperative VA, but a model with preoperative VA, SRF IR‐ET‐1 and plasma IR‐ET‐1 explains 90% of it in PVR (Supported by grants: FIS PI 040446 and DGES 97/0028)