Abstract TP351: Early Comfort Care Measures in Acute Stroke Patients: Analysis From the Get With the Guidelines Stroke Registry
Bibliographic record
Abstract
Introduction: Mortality after stroke is often hastened by forgoing life-sustaining measures. We sought to determine the patient and hospital characteristics associated with early comfort measures only (CMO) after ischemic stroke (IS), intracranial hemorrhage (ICH), and subarachnoid hemorrhage (SAH) in the Get With the Guidelines-Stroke registry. Methods: We identified patients with IS, ICH, or SAH between November 5, 2009 and September 30, 2013 who: 1) had known early CMO status; 2) were not transferred in from or out to another acute care facility; and 3) from sites with > 10 patients during the study period. Using multivariable logistic regression, we assessed patient and hospital factors associated with early CMO use by stroke type. Early CMO was defined as occurring on hospitals day 1 or 2. Results: Among 963,525 patients from 1,675 hospitals, 54,794 (5.6%) received early CMO (IS: 3.0%; ICH: 19.4%; SAH: 13.1%). There was a decrease in early CMO use (p<0.001) over the study period. In multivariable analysis, several patient (advancing age, female gender, non-white race-ethnicity), hospital (bed size and stroke case volume), and geographic factors (Midwest and West) were independently associated with early versus no early CMO use overall and by stroke type (Table). Conclusions: Nationwide, early CMO is utilized in over 5% of stroke patients being more common in ICH and SAH than IS. Different patient and hospital characteristics influence CMO use among stroke types.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".