Are All Stroke Patients Eligible for Fast Alteplase Treatment? An Analysis of Unavoidable Delays
Bibliographic record
Abstract
OBJECTIVES: The National Quality Forum recently endorsed a performance measure for time to intravenous thrombolytic therapy which allows exclusions for circumstances in which fast alteplase treatment may not be possible. However, the frequency and impact of unavoidable patient reasons for long door-to-needle time (DNT), such as need for medical stabilization, are largely unknown in clinical practice. As part of the Hurry Acute Stroke Treatment and Evaluation-2 (HASTE-2) project, we sought to identify patient and systems reasons associated with longer DNT. METHODS: From June 2012 to June 2013 we collected data on DNT and potential reasons for delays from 102 consecutive patients presenting directly to the emergency department who were treated with alteplase within 4.5 hours of symptom onset. RESULTS: Mean age was 71 years, 56/113 (54%) were women, median NIH Stroke Scale score was 13, and median DNT was 53 minutes. Potential delays were noted in 59/102 (58%), of which 31/102 (31%) were unavoidable patient-related or eligibility reasons. Median DNT was longer when patient-related or eligibility reasons for delay were present (60 minutes) than when absent (45 minutes, p = 0.005). Multivariable modeling showed that need for urgent medical stabilization, presentation with seizure and inability to confirm eligibility were associated with 35%-50% longer DNT times. CONCLUSIONS: Up to 31% of patients have delays due to medical or eligibility-related causes that may be legitimate reasons for providing alteplase later than the benchmark time of 60 minutes.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".