Impacto del trasplante renal en la función ventricular izquierda medida por ecocardiografía y electrocardiografía en una Unidad de Tercer Nivel
Bibliographic record
Abstract
Introducción: la enfermedad renal crónica representa un problema de salud pública con prevalencia mundial de 697 millones de casos y que condiciona un alto riesgo cardiovascular, incrementando la mortalidad.El trasplante renal mejora la función cardiaca con un aumento de la fracción de expulsión del ventrículo izquierdo (FEVI), reducción de la hipertrofia ventricular entre otros, lo que impacta en la supervivencia.La ecocardiografía es una herramienta práctica disponible para la detección de estos cambios cardiacos antes y después del trasplante renal.Objetivo: determinar el impacto a corto, mediano y largo plazo del trasplante renal sobre la función cardiaca a través de ecocardiograma y electrocardiograma en pacientes trasplantados en la Unidad Médica de Alta Especialidad (UMAE) Hospital de Especialidades No. 14 de Veracruz.Material y métodos: estu-
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".