Interpretación de pruebas genéticas y biomarcadores en la distrofia muscular de Duchenne
Bibliographic record
Abstract
Entre las principales alteraciones que caracterizan la distrofia muscular de Duchenne (DMD) se encuentran: daño de las fibras musculares durante la contracción, daño muscular crónico subsecuente, inflamación y posterior reemplazo de las fibras musculares por tejido fibroso. Este tipo de alteraciones puede reflejarse a través de biomarcadores de la enfermedad. Los biomarcadores en DMD son útiles para hacer el diagnóstico, el seguimiento y la evaluación de la respuesta al tratamiento. La indicación para solicitar los distintos biomarcadores varía de acuerdo con la edad y la historia natural de la enfermedad y su correcta utilización permite realizar un enfoque terapéutico adecuado, un seguimiento correcto y una rehabilitación satisfactoria. En la presente revisión se describen los diferentes tipos de biomarcadores y métodos diagnósticos utilizados en pacientes con DMD, y se recomienda su adecuada utilización de acuerdo con la edad y la historia natural de la enfermedad.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".