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Record W4413338005 · doi:10.1161/strokeaha.124.049955

Early Thrombolysis and Outcomes in Central Retinal Artery Occlusion: An Individual Participant Data Meta-Analysis

2025· article· en· W4413338005 on OpenAlexaff
Jim Shenchu Xie, Kirill Zaslavsky, Yuri V. Chaban, Adrien Lusterio, Hargun Kaur, Yasmin Motekalem, Dena Zeraatkar, Marko M. Popovic, Katharina Althaus, Brett Malbin, Christian H. Nolte, Jan F. Scheitz, Jacqueline A. Pettersen, Ronen R. Leker, J. Kim, Se Joon Woo, Celia S. Chen, Nicolas Feltgen, Manya Khrlobyan, Navdeep Sangha, Elena Ardila Jurado, Marcel Arnold, Heinrich P. Mattle, Mirjam R. Heldner, Max Nedelmann, Charlotte Cordonnier, Martin S. Spitzer, Sven Poli, Christian Hametner, Philipp Baumgartner, Susanne Wegener, Lucas Kook, Shima Shahjouei, Oana M. Dumitrascu, Edward Margolin, Patrik Michel

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsUniversity of Northern British ColumbiaUniversity of British ColumbiaMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineThrombolysisVisual acuityOcclusionOphthalmologyCentral retinal artery occlusionSurgeryInternal medicineMyocardial infarction

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.053
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.122
GPT teacher head0.363
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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