Real-World Effectiveness of Intravenous Stroke Thrombolysis is more than the Expectation of Practicing Neurologists
Bibliographic record
Abstract
BACKGROUND: The objective of the study was to compare the actual results of intravenous thrombolytic therapy (IVTT) in acute ischemic stroke with results anticipated by neurologists in practice. METHODS: Neurologists practicing in Thrissur metropolitan region, covering a population of 1.8 million, were telephonically surveyed about the number of yearly IVTT and their expert opinion/comment about effects of thrombolysis. This was compared with the results of IVTT from a single institution in the same region from 2012 to 2016. RESULTS: Eight neurologists in the region give approximately 140-150 IVTT per year. Nearly 20%-40% (median 32%) patients have good outcome, 5%-10% (median 9%) have intracerebral hematoma (ICH), and 25%-35% (median 30%) have death/bad outcome. Two neurologists from a tertiary care hospital in the region treated 122 cases of ischemic strokes with IVTT from 2012 to 2016. Age ranged from 8 to 88 years and 88 were males. Average delay in reaching hospital was 138.1 min and the door-to-needle time was 56.3 min. There were 26 cases of posterior-circulation strokes and 14 cases of cardioembolic strokes. At presentation, average National Institute of Health Stroke Scale (NIHSS) was 14.7; Modified Rankin Scale (mRS) 0.4; and CT Alberta Stroke Program Early Computerized Tomography Scores was 9.5. Good and sustained benefit (GSB) (>4 reduction in NIHSS at 24 h and 7 days) was there in 49% and no improvement (NI)/worsening in 36%. mRS 0-2 at discharge/30 days was documented in 57.3%. Symptomatic ICH was 10% (12/122) and mortality rate was 11.5% (14/122). GSB in posterior circulation strokes was 69.2% and NI/worsening in only 7.7%. mRS was 0-2 in 77% of posterior circulation strokes. CONCLUSION: Contrary to the popular belief of the practicing neurologists, IVTT has a high percentage of good outcome with a reasonable bleeding risk and low rates of absolute futility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".