Importance of proper patient selection and endpoint selection in evaluation of new therapies in acute stroke: further analysis of the SENTIS trial
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: Observational
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.051
- Threshold uncertainty score
- 0.379
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.260 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
BACKGROUND: The magnitude of treatment effect in acute stroke depends on several factors, including time from symptom onset (TFSO) to treatment and severity of the initial insult. OBJECTIVE: To report further evaluation of NeuroFlo therapy, focusing on the effect of time and stroke severity. METHODS: SENTIS was a prospective randomized trial (N=515) comparing standard medical therapy with/without NeuroFlo therapy. For this analysis, we evaluated outcomes in groups of patients based on TFSO and stroke severity: patients randomized <6 h, 6-10 h, and >10 h with mild (NIHSS<8), moderate (8-14), and severe (>14) symptoms at randomization. 90-Day mRS (modified Rankin Scale) scores and stroke-related death rates were compared between treatment groups. RESULTS: For patients randomized <6 h TFSO (n=128), the OR for mRS 0-2 was 3.11 (CI 1.30 to 7.46, p=0.011) for treated versus non-treated patients. In patients with disease of moderate severity (NIHSS 8-14, n=214), NeuroFlo-treated patients were more likely to have a good outcome (mRS 0-2; OR=1.84, CI 1.02 to 3.33, p=0.043). The stroke-related death rate was better in the treated group with TFSO >10 h and NIHSS >14 (n=42) (OR=7.10, CI 1.13 to 44.55, p=0.036). CONCLUSIONS: The results of our analysis support the importance of careful selection of outcome measures and the impact that rapid treatment and initial stroke severity have on outcome.
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.
The record
- Venue
- Journal of NeuroInterventional Surgery
- Topic
- Acute Ischemic Stroke Management
- Field
- Medicine
- Canadian institutions
- University of Alberta
- Funders
- National Institute of Neurological Disorders and Stroke
- Keywords
- MedicineSelection (genetic algorithm)Stroke (engine)Table (database)Clinical endpointEndpoint DeterminationAcute strokeClinical trialIntensive care medicinePhysical medicine and rehabilitationInternal medicineData miningArtificial intelligenceTissue plasminogen activator
- Has abstract in OpenAlex
- yes