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ObjectivesThis process evaluation explores patient and healthcare professional acceptability of community-based monitoring versus hospital-based care for patients with quiescent neovascular age-related macular degeneration (QnAMD).DesignQualitative process evaluation was conducted as part of a randomised controlled trial.SettingSix hospitals and six community-based practices.Participants25 patients and 16 healthcare professionals (ophthalmologists and optometrists). This approach helped differentiate between common issues and those specific to community-based monitoring.InterventionThe Quality-Assured Follow-Up of QnAMD by non-medical practitioners trial aimed to examine whether non-medical practitioners follow-up patients with QnAMD in the community in a safe and clinically and cost-effective way. The process evaluation aimed to examine whether the intervention was acceptable by patients and professionals. The process evaluation was based on interviews which contained open-ended questions focused on patient experience and confidence in community-based care, issues concerning the practicalities of the organisation and management of the clinic, and resources including IT and digital equipment. The theory of acceptability framework was used to interpret the findings.ResultsPatients reported positively on the experience of receiving QnAMD services in the community and highlighted staff professionalism and clear communication. Key themes were the proximity of care provision for patients, IT interoperability and the real-world costs of running the service. Some patients randomised to the hospital showed preference for the intervention to take place in the hospital, mediated mainly by prior experience of hospital care and travel distance. The location of the clinic and transport routes affected the experience of attending appointments, with strong preference expressed for proximity to one’s home. Inaccessibility due to non-modifiable internal building structures in the community and parking in hospital eye services was reported by a small proportion of patients. Healthcare professionals reported positively about their ability to deliver QnAMD services in community settings but raised concerns about the compatibility of technological infrastructure that facilitates the sharing of optical coherence tomography image and video files. Some optometrists were also concerned about the financial sustainability of the intervention after the end of the trial due to the costs involved in the administration of QnAMD follow-up care.ConclusionsThe delivery of QnAMD services in the community by non-medical personnel was broadly accepted by both patients and practitioners. This implies that non-medical practitioners can follow up patients with QnAMD in the community in a safe way. Further research would be needed to establish whether similar results would be obtained during routine practice outside a research project and whether the long-term follow-up for QnAMD would be financially sustainable for independent as well as chain community optometry practices.Trial registration numberNCT03893474.

To evaluate the feasibility of integrating genetic, imaging, and demographic data for predictive modelling of treatment outcomes in neovascular age-related macular degeneration (nAMD). Proof-of-concept retrospective cohort study with prospective DNA collection. Patients with unilateral nAMD receiving anti-vascular endothelial growth factor (anti-VEGF) therapy on a treat-and-extend regimen at a single tertiary centre were recruited. Polygenic risk scores (PRS) for AMD were derived from genotyping data (NIHR Bioresource). Optical coherence tomography (OCT) biomarkers-intraretinal fluid (IRF), subretinal fluid (SRF), pigment epithelial detachment (PED), and subretinal hyperreflective material (SHRM)-were automatically quantified using a deep learning segmentation model. Predictors of treatment outcomes included PRS, age at first injection, and OCT feature volumes at baseline. XGBoost was used for binary outcomes and linear regression for continuous outcomes, employing five-fold cross-validation. (1) macular dryness (no IRF/SRF) at 24 months, (2) average treatment interval in year 2, and (3) age at first injection. 106 participants were included. The multimodal model integrating age, imaging, and PRS predicted macular dryness at 24 months with AUC = 0.903, outperforming imaging alone (AUC = 0.701). PRS was associated with younger age at first injection (β = –4.69, 95% CI [–8.93, –0.44], P = 0.031) but not with treatment burden (β = –6.39, P = 0.13). Integrating PRS with OCT-derived imaging biomarkers and patient age is technically feasible and improves predictive performance of modelling for anatomical treatment outcomes in nAMD. PRS reflects genetic susceptibility to nAMD and contextualizes the predictive value of imaging biomarkers for treatment response.