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Feltgen, Nicolas

0000-0002-6857-3003

Mayo Clinic

University of Basel

Citations 2

Early Thrombolysis and Outcomes in Central Retinal Artery Occlusion: An Individual Participant Data Meta-Analysis
Xie, Jim Shenchu , Chaban, Yuri V. , Lusterio, Adrien , Kaur, Hargun , Motekalem, Yasmin, Zeraatkar, Dena , Althaus, Katharina , Malbin, Brett , Nolte, Christian H. , Pettersen, Jacqueline A. , Woo, Se Joon , Chen, Celia S. , Khrlobyan, Manya, Sangha, Navdeep , Jurado, Elena Ardila, Mattle, Heinrich P. , Nedelmann, Max, Spitzer, Martin S. , Poli, Sven , Hametner, Christian , Baumgartner, Philipp , Kook, Lucas , Dumitrascu, Oana M. , Margolin, Edward , Xie, Jim S , Zaslavsky, Kirill , Chaban, Yuri V , Lusterio, Adrien , Popovic, Marko M , Althaus, Katharina , Malbin, Brett , Nolte, Christian H , Scheitz, Jan F , Pettersen, Jacqueline A , Leker, Ronen R , Kim, Joonhyung , Woo, Se Joon , Chen, Celia , Feltgen, Nicolas , Sangha, Navdeep , Arnold, Marcel , Mattle, Heinrich , Heldner, Mirjam R , Cordonnier, Charlotte , Poli, Sven , Hametner, Christian , Baumgartner, Philipp , Wegener, Susanne , Kook, Lucas , Shahjouei, Shima , Dumitrascu, Oana M , Margolin, Edward M , Heldner, Mirjam R. , Shahjouei, Shima , Michel, Patrik

Stroke | August 20, 2025 | Volume: 56 | Issue: 11 | Pages: 3175-3186

10.1161/strokeaha.124.049955 Get It

BACKGROUND: This individual participant data meta-analysis aimed to determine whether time to treatment influences the effect of intraarterial thrombolysis (IAT), intravenous thrombolysis, and conservative standard therapy on visual outcomes in nonarteritic central retinal artery occlusion. METHODS: We searched MEDLINE, CENTRAL, and Embase up to June 2023 for studies reporting treatment modality and peri-treatment best-corrected visual acuity (BCVA) for ≥5 participants, excluding patients with nonsevere vision loss (BCVA <1.0 logarithm of the minimum angle of resolution [logMAR]) or treated after 24 hours of symptom onset. The primary outcome was recovery from severe vision loss (final BCVA <1.0 logMAR). We used mixed-effect models and local polynomial regression to investigate nonlinear relationships between time to treatment and recovery from severe vision loss. RESULTS: Of 4074 screened studies, individual participant data were sought from 52, with 35 contributing individual participant data for 1038 participants. In total, 783 patients met inclusion criteria (age, 64.8±13.3 years; 35.5% female; baseline BCVA, 2.3±0.5 logMAR). For every hour decrease in time to treatment, thrombolysis was associated with greater improvement in BCVA (intraarterial, 0.02 logMAR [95% CI, 0–0.04]; intravenous, 0.04 logMAR [95% CI, 0.00–0.07]) than conservative standard therapy (0.01 logMAR [95% CI, 0–0.02]). A nonlinear relationship was detected for intraarterial thrombolysis with a changepoint at 8 hours (95% CI, 6.7–9.4). Thrombolysis was associated with increased recovery from severe vision loss compared with conservative standard therapy (intraarterial within 6 hours: odds ratio, 2.72 [95% CI, 1.02–7.28], 27.2% versus 12.0%; intravenous within 4.5 hours: odds ratio, 3.32 [95% CI, 1.24–8.92], 28.8% versus 11.1%). Findings were consistent in subgroup analysis restricted to patients receiving recombinant tissue-type plasminogen activator. Monte-Carlo simulations showed that a randomized controlled trial would require 95 participants per group to achieve 80% power to detect an odds ratio of 3.0 for recovery from severe vision loss. CONCLUSIONS: Early intervention in nonarteritic central retinal artery occlusion is associated with improvement in visual recovery, with intraarterial thrombolysis and intravenous thrombolysis outperforming nonthrombolytic treatments. These findings warrant confirmation in sufficiently powered randomized controlled trials.
Artificial Intelligence‐Based Detection of Central Retinal Artery Occlusion Within 4.5 Hours on Standard Fundus Photographs
Gungor, Ayse , Sarbout, Ilias , Gilbert, Aubrey L. , Hamann, Steffen, Lebranchu, Pierre , Gohier, Philippe , Vignal‐Clermont, Catherine, Dumitrascu, Oana M. , Cohen, Salomon Y. , Lagrèze, Wolf A. , Heide, Frank van der, Lamirel, C. , Obadia, Michaël , Miléa, Dan , Gohier, Philippe , Dumitrascu, Oana M , Cohen, Salomon-Yves , Lagrèze, Wolf A , Feltgen, Nicolas , Lamirel, Cédric , Jonas, Jost B , Obadia, Michael , Racoceanu, Daniel , Milea, Dan , Hamann, Steffen , Hobeanu, Cristina , Heide, Frank C. T. van der

Journal of the American Heart Association | June 27, 2025 | Volume: 14 | Issue: 13 | Pages: No page available

10.1161/jaha.124.041441 Get It

Background Prompt diagnosis of acute central retinal artery occlusion (CRAO) is crucial for therapeutic management and stroke prevention. However, most stroke centers lack onsite ophthalmic expertise before considering fibrinolytic treatment. This study aimed to develop, train, and test a deep learning system to detect hyperacute CRAO on retinal fundus photographs within the critical 4.5‐hour treatment window and up to 24 hours after visual loss to aid in secondary stroke prevention. Methods Our retrospective, cross‐sectional study included 1322 color fundus photographs from 771 patients with acute visual loss due to CRAO, central retinal vein occlusion, nonarteritic anterior ischemic optic neuropathy, and healthy controls. Photographs were collected from 9 expert neuro‐ophthalmology centers in 6 countries, including 3 randomized clinical trials. Training included 1039 photographs (517 patients), followed by testing on 2 data sets: (1) hyperacute CRAO (54 photographs, 54 patients) and (2) CRAO within 24 hours after visual loss (110 photographs, 109 patients). Results The deep learning system achieved an area under the receiver operating characteristic curve of 0.96 (95% confidence interval (CI), 0.95–0.98), a sensitivity of 92.6% (95% CI, 87.0–98.0), and a specificity of 85.0% (95% CI, 81.8–92.8) for detecting CRAO at hyperacute stage, with similar results within 24 hours. The deep learning system outperformed stroke neurologists on a subset of hyperacute testing data set (120 photographs, 120 patients). Conclusions A deep learning system can accurately detect hyperacute CRAO on retinal photographs within a time window compatible with urgent fibrinolysis. If further validated, such systems could improve patient selection for fibrinolytic trials and optimize secondary stroke prevention. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT06390579.