Optimization of the Ocular Surface Prior to Cataract Surgery Using Cryopreserved Amniotic Membrane - Wongskhaluang J (Clinical Ophthalmology, 2025)
Jeff Wongskhaluang Ophthalmology, Grin Eye Care, Olathe, KS, USACorrespondence: Jeff Wongskhaluang, Grin Eye Care, 21020 W 151st St, Olathe, KS, 66061, USA, Tel +1 (913) 829-5511, Email jeff.wongs@grineyecare.comPurpose: To assess the benefit of cryopreserved amniotic membrane (cAM) in restoring corneal surface health prior to cataract surgery and enhancing post-operative refractive outcomes in patients with moderate to severe dry eye disease (DED).Methods: A prospective, repeated-measures, self-controlled study of 64 eyes with moderate to severe DED that were treated with cAM prior to cataract surgery. Biometry, topography, corneal staining (NEI scale), SPEED scores, and best corrected visual acuity (BCVA) were assessed before and after treatment and 1-month post-operatively. Primary outcome was refractive accuracy before and after treatment based on manifest refraction at 1 month post-operatively.Results: A total of 55 eyes of 37 patients (95% female) completed the study. SPEED scores and NEI scores significantly improved at 1- and 2-weeks post-treatment, with sustained benefit at 1 month post-operatively (P < 0.0001). Spherical equivalent was within ± 0.25 D in 36% of eyes before and 70% of eyes after cAM treatment (P = 0.002); within ± 0.5 D in 66% of eyes before and 94% of eyes after (P < 0.001); within ± 0.75 D in 76% of eyes before and 98% of eyes after (P < 0.001); and within ± 1D in 86% eyes before and 100% of eyes after (P = 0.016). Emmetropia was attained in 84% of eyes, and 93% (51/55) of eyes had 20/20 BCVA post-operatively.Conclusion: Treatment with cAM prior to cataract surgery can significantly improve both signs and symptoms of moderate to severe DED, with continued improvement post-operatively. Furthermore, CAM may ultimately improve biometry accuracy, mitigating the risk of surgical delay.Keywords: amniotic membrane, cataract surgery, dry eye, ocular surface optimization