Effective assessment model for improving capacity of diagnosis and early treatment of st-advanced miscellaneous immediate patients: The case in Vietnam
Bibliographic record
Abstract
We conducted an initial evaluation of the effectiveness of the application of the model of capacity building for early diagnosis and treatment with PCI in STEMI patients in Nghe An to contribute to solving the problems and to be able to replicate the model. STEMI patients received PCI from 7/2018 - 8/2020 at Nghe An General Hospital. Retrospective and prospective cross-sectional study, intervention with comparison before and after intervention included 280 patients, mean age 71.9 ± 14.59 (years); men accounted for 69.3%. After implementing the model, the number of patients increased by 135%, the time of the door - the ball decreased (71.3 ± 71.8 compared to 152.29 ± 167.3 minutes), the length of hospital stays, and the mortality rate decreased significantly.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".