Abstract TP15: Rationale And Ongoing Status In A Phase 3 Trial Of Nelonemdaz, A Novel Neuroprotection Drug, For Patients With Acute Ischemic Stroke And Reperfusion
Bibliographic record
Abstract
Background: A phase III Rescue On reperfusion Damage in cerebral Infarction by Nelonemdaz (RODIN) trial has been launched since December, 2021 and patients are being enrolled. Rationale: Nelonemdaz (previously, neu2000) targets (1) selectively the 2B subunit of the N-methyl-D-aspartate glutamate receptor, the activation of which causes Na+ and Ca++ influx into neuronal cells and then induces downstream death-signaling pathways, and (2) free radical species, which are released both from the downstream pathways of glutamate receptors and from following reperfusion injury. Phase I and II trials showed its safety and a tendency of clinical outcome improvements. Methods: RODIN is a multicenter, double-blinded clinical trial. A total of 496 patients will be randomly assigned into nelonemdaz and placebo groups. Patients will be included if they have an acute ischemic stroke (National Institutes of Health Stroke Scale score ≥8 scores) caused by intracranial large vessel occlusion in the anterior circulation (Alberta Stroke Program Early CT Score ≥4), and they are expected to undergo endovascular thrombectomy within 12 hours after stroke onset. The primary endpoint is a favorable shift in the modified Rankin Scale (mRS) score at 90 days after the first dose of drug, analyzed by the Cochran-Mantel-Haenszel shift test. Ongoing status: By August 23, 2022, 210 patients have been enrolled. It is expected that enrollment could be finalized until spring season of 2023. Conclusions: This trial will clarify the efficacy and safety of nelonemdaz in patients with acute ischemic stroke and endovascular thrombectomy. This study was registered in ClinicalTrials.gov, number NCT05041010.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".