Delays in Door-to-Needle Times and Their Impact on Treatment Time and Outcomes in Get With The Guidelines-Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Despite quality improvement programs such as the American Heart Association/American Stroke Association Target Stroke initiative, a substantial portion of acute ischemic stroke patients are still treated with tissue-type plasminogen activator (alteplase) later than 60 minutes from arrival. This study aims to describe the documented reasons for delays and the associations between reasons for delays and patient outcomes. METHODS: We analyzed the characteristics of 55 296 patients who received intravenous alteplase in 1422 hospitals participating in Get With The Guidelines-Stroke from October 2012 to April 2015, excluding transferred patients and inpatient strokes. We assessed eligibility, medical, and hospital reasons for delays in door-to-needle time. RESULTS: There were 27 778 patients (50.2%) treated within 60 minutes, 10 086 patients (18.2%) treated >60 minutes without documented delays, and 17 432 patients (31.5%) treated >60 minutes with one or more documented reasons for delay. Delayed door-to-needle times were associated with delayed diagnosis (36 minutes longer than those without delay in diagnosis) and hypoglycemia or seizure (34 minutes longer than without those conditions). The presence of documented delays was associated with higher odds of in-hospital mortality (odds ratio, 1.2; 95% confidence interval, 1.1-1.3) and symptomatic intracranial hemorrhage (odds ratio, 1.2; 95% confidence interval, 1.1-1.3) and lower odds of independent ambulation at discharge (odds ratio, 0.92; 95% confidence interval, 0.9-1.0) after adjusting for patient and hospital characteristics. CONCLUSIONS: Hospital and eligibility delays such as delay diagnosis and inability to determine eligibility were associated with longer door-to-needle times. Improved stroke recognition and management of acute comorbidities may help to reduce door-to-needle times.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".