Eficacia de un apósito autoadhesivo de poliuretano para prevenir la formación de cicatrices hipertróficas
Bibliographic record
Abstract
Valoramos la eficacia de un apósito autoadhesivo para prevenir las cicatrices hipertróficas sobre un grupo de pacientes sometidas a cirugÃa de reducción mamaria. Tras la curación de las heridas, aplicamos en todas las pacientes un protocolo preventivo mediante compresión y apósito adhesivo: 66 pacientes (35,6±10,8 años de edad) utilizaron Trofolastin® reductor de cicatrices como adhesivo (sujetos) y 47 pacientes (38,7±12 años de edad) fueron tratadas con otros adhesivos (controles). En el grupo control, el 23,4 % de los casos presentó cicatrices hipertróficas, mientras que en el grupo de sujetos el porcentaje fue sólo del 9,1 % (p < 0,05). Por otra parte, 27 casos del grupo control (56,5 %) tuvieron una puntuación igual o superior a 4 en la escala de Vancouver, frente a sólo 6 casos (9,1 %) en el grupo de sujetos (p < 0,0001). ConcluÃmos que el uso profiláctico de Trofolastin® reductor de cicatrices, una vez finalizado el proceso de curación de la herida, disminuye significativamente el riesgo de cicatrización hipertrófica (riesgo relativo 6,32 [95 % IC 2,83-14,09], según la prueba exacta de Fisher).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".