Warfarin-Related Intracerebral Hemorrhage: Predictors of Hematoma Expansion and In-Hospital Mortality (P6.055)
Bibliographic record
Abstract
Objective: To evaluate the predictors of hematoma expansion (HE) and in-hospital mortality in warfarin-related intracerebral hemorrhage (wr-ICH), and their relationship to INR reversal. Background: Wr-ICH is a devastating disease with fatality rate of 55[percnt]. Acute therapy entails INR reversal, however whether this improves outcomes is not well established. Methods: Consecutive cases of ICH admitted to Boston Medical Center between 11/2008-04/2014 and Hamilton Health Sciences between 01/2010-12/2013 were reviewed for patients with wr-ICH and INR values >1.4 presenting with 24 hours of symptom onset. HE was defined as > 6 ml or 33[percnt] growth between baseline and follow-up CT scans. We compared baseline characteristics and time-to-INR reversal between patients with HE, as well as in-hospital mortality, and those without. Results: In 56 patients with wr-ICH, median ICH volume was 25.9 ml and median time from CT to INR reversal was 443.5 minutes. INR was reversed within 6 hours in 36[percnt]. Patients with larger ICH volumes had shorter duration to INR reversal (Spearman’s correlation coefficient: -0.41,p<0.01), higher NIHSS (0.57,p<0.001) and lower Glasgow coma scale (GCS, -0.54,p<0.001). HE and in-hospital mortality occurred in 67[percnt] and 36[percnt] of cases, respectively. In comparison to patients without HE, those with HE had overrepresentation of lobar ICH (59[percnt] vs. 18[percnt],p=0.03). Patients with in-hospital mortality had higher baseline ICH volumes (median: 61 ml vs. 20 ml,p=0.02), lower GCS (median: 11 vs. 14,p<0.01), higher NIHSS (median: 25 vs. 10,p=0.01), and were more likely to have a ‘do not resuscitate’ order (DNR) during their admission (85[percnt] vs. 36[percnt],p=0.001). There did not exist a relationship between time-to-INR reversal and HE or mortality. Conclusions: Our preliminary results suggest that patients with larger wr-ICH volumes receive more urgent INR reversal, yet time-to-INR reversal did not correlate with HE or in-hospital mortality in our limited sample. DNR seems to be associated with wr-ICH mortality.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".