Abstract 149: Elevated mir-9 in Cerebrospinal Fluid is Associated With Poor Functional Outcome After Subarachnoid Hemorrhage
Bibliographic record
Abstract
Introduction: Aneurysmal subarachnoid hemorrhage (SAH) has a lower incidence than ischemic stroke but affects younger individuals with a high mortality and a high frequency of complications in survivors. The underlying pathways that contribute to poor functional outcome are poorly understood. Hypothesis: MicroRNA (miRNA) changes in cerebrospinal fluid (CSF) are associated with the occurrence of delayed cerebral ischemia and poor functional outcome after SAH. Methods: Using real-time polymerase quantification chain reaction (RT-qPCR), 43 selected miRNAs were measured in daily CSF samples from a discovery cohort of SAH patients admitted to Rigshospitalet, Copenhagen, Denmark, and compared to neurologically healthy patients. Findings were validated in CSF from a replication cohort of SAH patients admitted to Massachusetts General Hospital, Boston, Massachusetts. Outcome measures were delayed cerebral ischemia (DCI), as well as functional outcome three months after ictus measured by the modified Rankin Scale score. Results: MiRNAs were quantified and passed RT-qPCR quality control in 427 CSF samples from 63 SAH patients in the discovery cohort, in 104 CSF samples from 63 SAH patients in the replication cohort and in 11 CSF samples from 11 neurologically healthy patients. Elevated miR-9-3p was associated with a poor functional outcome in both the discovery cohort (p < 0.0001) after correction for multiple testing (q < 0.01) and in the replication cohort (p < 0.01). Furthermore, elevated miR-9-5p was associated with a poor functional outcome in the discovery cohort (p < 0.01) after correction for multiple testing (q < 0.05). No miRNA was associated with DCI in both cohorts. Conclusions: Mir-9-3p is elevated in the CSF following SAH and this elevation is associated with a poor functional 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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".