DESIGN: Retrospective study.
METHODS: Based on the mean deviation (MD) of the Humphrey Field Analyzer (HFA), the 152 subjects were categorized into mild (MD > - 6 dB, 100), moderate (MD - 6 to - 12 dB, 26), and severe (MD
METHODS: Assessment of neovascular age-related macular degeneration patients with or without PCV after 12 months of ranibizumab treatment during the LUMINOUS study. Outcome measures were visual acuity and central retinal thickness changes from baseline and the rate of ocular adverse events.
RESULTS: At baseline, 572 and 5,644 patients were diagnosed with and without PCV, respectively. The mean visual acuity gain from baseline at Month 12 in the PCV and non-PCV groups was +5.0 and +3.0 letters, respectively; these gains were achieved with a mean of 4.4 and 5.1 ranibizumab injections. Eighty percent of PCV patients and 72.2% of non-PCV patients who had baseline visual acuity ≥73 letters maintained this level of vision at Month 12; 20.6% and 17.9% of patients with baseline visual acuity <73 letters achieved visual acuity ≥73 letters in these groups. Greater reductions in central retinal thickness from baseline were also observed for the PCV group versus the non-PCV group. The rate of serious ocular adverse events was 0.7% (PCV group) and 0.9% (non-PCV group).
CONCLUSION: LUMINOUS confirms the effectiveness and safety of ranibizumab in treatment-naive patients with PCV.
METHODS: This is a non-interventional cohort study of 90 patients with PCV from 16 international trial sites who originally completed the EVEREST II study. The long-term outcomes were assessed during a recall visit at about 6 years from commencement of EVEREST II.
RESULTS: The monotherapy and combination groups contained 41 and 49 participants, respectively. The change in best-corrected visual acuity (BCVA) from baseline to year 6 was not different between the monotherapy and combination groups; - 7.4 ± 23.0 versus - 6.1 ± 22.4 letters, respectively. The combination group had greater central subfield thickness (CST) reduction compared to the monotherapy group at year 6 (- 179.9 vs - 74.2 µm, p = 0.011). Fewer eyes had subretinal fluid (SRF)/intraretinal fluid (IRF) in the combination versus monotherapy group at year 6 (35.4% vs 57.5%, p = 0.032). Factors associated with BCVA at year 6 include BCVA (year 2), CST (year 2), presence of SRF/IRF at year 2, and number of anti-VEGF treatments (years 2-6). Factors associated with presence of SRF/IRF at year 6 include combination arm (OR 0.45, p = 0.033), BCVA (year 2) (OR 1.53, p = 0.046), and presence of SRF/IRF (year 2) (OR 2.59, p = 0.042).
CONCLUSION: At 6 years following the EVEREST II study, one-third of participants still maintained good vision. As most participants continued to require treatment after exiting the initial trial, ongoing monitoring and re-treatment regardless of polypoidal lesion status are necessary in PCV.
TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT01846273.
METHODS: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning.
RESULTS: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83.
CONCLUSION: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.