{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["15(1)"],"submitter":["Fuchs P"],"pubmed_abstract":["To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monitoring. Real-world data comprising OCT scans and electronic medical records from 148 patients (187 eyes) were extracted from the Fight Retinal Blindness! (FRB! ) Zürich database. OCT scans were analysed using an approved AI algorithm (RetInSight, Vienna, Austria) to quantify fluid volumes by compartements. The impact of fluid persistence and fluctuations on BCVA change was assessed using forward stepwise regression and mixed models. Fluid compartments were further categorized into quartiles (SD-Qs), and the effect of fluid fluctuations on BCVA analysed (SD-Q1 least"],"journal":["Scientific reports"],"pagination":["32881"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12464290"],"repository":["biostudies-literature"],"pubmed_title":["Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naive nAMD from the FRB! registry."],"pmcid":["PMC12464290"],"pubmed_authors":["Fuchs P","Leingang O","Gruber A","Barthelmes D","Schmidt-Erfurth U","Frommlet F","Reiter GS","Mares V","Coulibaly LM","Bogunovic H"],"additional_accession":[]},"is_claimable":false,"name":"Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naive nAMD from the FRB! registry.","description":"To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monitoring. Real-world data comprising OCT scans and electronic medical records from 148 patients (187 eyes) were extracted from the Fight Retinal Blindness! (FRB! ) Zürich database. OCT scans were analysed using an approved AI algorithm (RetInSight, Vienna, Austria) to quantify fluid volumes by compartements. The impact of fluid persistence and fluctuations on BCVA change was assessed using forward stepwise regression and mixed models. Fluid compartments were further categorized into quartiles (SD-Qs), and the effect of fluid fluctuations on BCVA analysed (SD-Q1 least","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-06-03T20:25:18.878Z","creation":"2026-05-01T03:10:28.367Z"},"accession":"S-EPMC12464290","cross_references":{"pubmed":["40998972"],"doi":["10.1038/s41598-025-17417-z"]}}