Effect of intrathecal milrinone injection via lumbar catheter on delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage
Bibliographic record
Abstract
OBJECTIVE Delayed cerebral ischemia (DCI) is an important complication after aneurysmal subarachnoid hemorrhage (aSAH). Although intrathecal milrinone injection via lumbar catheter to prevent DCI has been previously reported to be safe and feasible, its effectiveness remains unknown. The goal of this study was to evaluate whether intrathecal milrinone injection treatment after aSAH significantly reduced the incidence of DCI. METHODS The prospectively maintained aSAH database was used to identify patients treated between January 2010 and December 2015. The cohort included 274 patients, with group assignment based on treatment with intrathecal milrinone injection or not. A propensity score model was generated for each patient group, incorporating relevant patient variables. RESULTS After propensity score matching, 99 patients treated with intrathecal milrinone injection and 99 without treatment were matched on the basis of similarities in their demographic and clinical characteristics. There were significantly fewer DCI events (4% vs 14%, p = 0.024) in patients treated with intrathecal milrinone injection compared with those treated without it. However, there were no significant differences between the 2 groups with respect to their 90-day functional outcomes (46% vs 36%, p = 0.31). The likelihood of chronic secondary hydrocephalus, meningitis, and congestive heart failure as complications of intrathecal milrinone injection therapy was also similar between the groups. CONCLUSIONS In propensity score-matched groups, the intrathecal administration of milrinone via lumbar catheter showed significant reduction of DCI following aSAH, without an associated increase in complications.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 0.000 |
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.
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".