Evaluating the Effect of Novel Ways of Teaching Symptoms and Treatment of Acute Stroke on Thrombolytic Therapy
Bibliographic record
Abstract
Background and Objective: Given that a small percentage of people with ischemic stroke are treated with recombinant tissue plasminogen activator (rtPA) in Iran, it is necessary to use appropriate educational methods that, in addition to raising the awareness of patients about stroke, lead them to refer health centres early. The purpose of this study was to evaluate the effect of new methods of training warning signs of acute stroke on thrombolytic therapy. Method: This was a community-based empirical intervention study in Ahvaz, Iran, in 2018. Initially, educational content was provided, including warning signs of a stroke, its risk factors, and the need for prompt referral to a well-equipped treatment centre for thrombolytic therapy. This content was used to prepare brochures, pamphlets, posters, and training sessions for health care personnel. Before starting, immediately, and three months after the training course, a questionnaire was used to assess staff knowledge of stroke symptoms and the need for rapid patient referral for FAST-based thrombolytic therapy. Also, the timely referral of patients with suspected stroke to hospital, as well as their thrombolytic therapy during the six months after the intervention and the similar six months in the previous year were compared. Results: The level of knowledge was significantly increased at the end of training (P<0.0001). Although this average was reduced three months after completion of training, the difference was not significant (P = 0.42). Based on the results, the number of stroke patients referred to hospital in golden time (less than 4.5 hours) from the beginning of training to 6 months after the end of the course (n = 54) was increased compared to the same period last year (n=38). The number of thrombolytic patients from the beginning of the training course to 6 months after the course (n=38) increased compared to the same period of the previous year (n=21). Conclusion: Based on the results, the implementation of educational programs was reported to be effective in raising public awareness of stroke symptoms and the need for prompt hospital referral for appropriate and timely treatment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".