Estudio observacional transversal del manejo del dolor irruptivo asociado a los tratamientos en pacientes con ulceras cutaneas
Bibliographic record
Abstract
espanolObjetivos: Conocer el tratamiento base del dolor irruptivo en el tratamiento de ulceras cronicas y valorar el dolor irruptivo producido durante la cura topica Metodo: Estudio observacional transversal. Medicion y valoracion del dolor mediante el uso de la escala EVA y McGill. Valoracion de la ansiedad por la Escala de Ansiedad de Hamilton. Estadistica descriptiva. Resutados: Fueron evaluados 20 pacientes que acudieron a la Unidad de Enfermeria Dermatologica, Ulceras y Heridas del Hospital General Universitario de Valencia. Los pacientes tratados con Fentanilo disminuyen notablemente su sensacion de dolor frente a otros que son tratados de base con Paracetamol y/o Metamizol. Conclusiones: Los pacientes tratados con opiodes como es el Fentanilo, son mas proclives a sentir menos dolor irruptivo durante las curas topicas. La mayoria de pacientes observados describen el dolor cualitativamente como: aprieta, acalambra, destelleo, pincha. EnglishObjective: Know the treatment basis of breakthrough pain in the treatment of chronic ulcers and assess the breakthrough pain occurred during the topical cure Method: Observational and cross-sectional study. Measurement and assessment of pain using the scale EVA and McGill. Valuation of anxiety about the scale of Anxiety of Hamilton. Descriptive statistics. Results: Were evaluated 20 patients who attended the Dermatology Nursing Unit, sores and wounds of the University General Hospital of Valencia. Patients treated with fentanyl significantly decrease your feeling of pain compared to others that are basic treaties with acetaminophen and/ or metamizole. Conclusions: Patients treated with opioids as is the fentanyl, are more likely to feel less breakthrough pain during the topical cures. The majority of patients observed describe the pain qualitatively as: Press, cramp, flashing, prick.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".