The Use of Milrinone in Patients with Delayed Cerebral Ischemia Following Subarachnoid Hemorrhage: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to provide a systematic review of the evidence supporting the use of milrinone for the management of delayed cerebral ischemia (DCI) following subarachnoid hemorrhage (SAH). DESIGN: Primary outcomes were functional neurological status and the incidence of cerebral infarction. Search strategies adapted to the different databases were developed by a professional librarian. Medline, EMBASE, the Cochrane Library database, Web of Science, SCOPUS, BIOSIS, Global Health, Health Star, Open SIGLE, Google Scholar and the New York Academy of Medicine Gray Literature were searched as well as clinical trials databases and the proceedings of several scientific meetings. Quality of the evidence for these outcomes across studies was adjudicated using the GRADE Working Group criteria. RESULTS: The search resulted in 284 citations after elimination of duplicates. Of those 9 conference proceedings and 15 studies met inclusion criteria and consisted of case reports, case series and two comparative studies: one non-randomized study with physiological outcomes only and a case series with historical controls. There was considerable variation in dosing and in co-interventions and no case control or randomized controlled studies were found. CONCLUSION: There is currently only very low quality evidence to support the use of milrinone to improve important outcomes in patients with delayed cerebral ischemia secondary to subarachnoid hemorrhage. Further research is needed to clarify the value and risks of this medication in patients with SAH.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".