Diagnóstico del síndrome coronario agudo en primer nivel de atención en Colombia e indicaciones de traslado emergente a mayor nivel de complejidad, ¿es posible sin enzimas cardiacas?
Bibliographic record
Abstract
El dolor torácico es un motivo de consulta frecuente en el servicio de urgencias, y la falta de diagnóstico oportuno del síndrome coronario agudo se asocia a una alta mortalidad y a demandas médicas. A pesar de que existen múltiples algoritmos para descartar esta condición, están diseñados para instituciones con disponibilidad de biomarcadores cardiacos, con los cuales cuentan pocos primeros niveles de atención en Colombia. En este artículo se realiza una revisión sobre las herramientas que se han descrito en la literatura para descartar este diagnóstico en el servicio de urgencias de baja complejidad. Se encuentran tres escalas: Vancouver Chest Pain Rule, INTERCHEST y Marburg Heart Score. Esta última es la que tiene mayor evidencia, aunque con algunas limitaciones, pues es desarrollada en el contexto de dolor intermitente y no agudo. Se plantea un algoritmo diagnóstico incluyendo clínica, electrocardiograma y escalas de predicción.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".