Next day discharge after elective intracranial aneurysm coiling: is it safe?
Bibliographic record
Abstract
BACKGROUND: There is a paucity of literature on early discharge after elective aneurysm treatment. We hypothesize that patient discharge on the next day is not associated with an increase in post-discharge adverse events. METHODS: We retrospectively reviewed elective coiling procedures between 2009 and 2013. The primary outcome measure was 30-day adverse events (emergency department visits, readmission or prolonged admission >30 days, and death). We evaluated the association between early and standard discharge for the primary outcome using the Fisher exact test. We also assessed the association of the primary outcome with other patient and technical variables as well as findings on pre-discharge diffusion weighted imaging. RESULTS: We included 97 patients. Median length of hospital stay (LOS) was 2.52 days, and in 26 patients (26.8%) LOS was <2 days. There was no significant difference in post-discharge adverse outcome rates between early and standard discharge groups (19.2% vs 18.3%; p=1.000). The primary outcome was significantly associated with the use of flow diverters (p=0.0287) and change in modified Rankin Scale category at discharge (p=0.0329). No significant association was noted between the outcome and the other variables including the presence of diffusion restriction pre-discharge (p>0.05). CONCLUSIONS: Patient discharge the next day after elective intracranial aneurysm coiling is not associated with an increase in 30-day adverse outcomes. A prospective study investigating early discharge in elective treatment is warranted. TRIAL NUMBER: OHSN-REB #20130786-01H.
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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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".