Síndrome de Cuidados Post-Intensivos en adultos con alteraciones oncológicas hospitalizados o de egreso
Bibliographic record
Abstract
Introduccion: En 2010 en Estados Unidos la Sociedad de Medicina de Cuidados Criticos, a partir de estudios de investigacion e intervenciones en pacientes en la Unidad de Cuidados Intensivos, acunaron el termino Post-Intensive Care Syndrom (PICS) definido como “ deterioro nuevo y/o empeoramiento en algun dominio de la cognicion, la salud mental y la funcion fisica despues de una enfermedad critica y que persiste mas alla de la hospitalizacion”. Por otra parte, en Europa la Academia Medica Center de la Universidad de Amsterdam mostro resultados similares en diversos estudios. En Mexico no existen antecedentes del fenomeno. Enfermeria interviene en la prevencion, deteccion, control y manejo de este. Objetivo: Determinar la prevalencia del sindrome de cuidados post-intensivos en pacientes con alteraciones oncologicas en dominios de afectacion fisico, psicologico y cognitivo a partir de 15 dias de egreso de la UCI en el servicio de hospitalizacion y consulta externa en una institucion de tercer nivel. Metodos: Estudio cuantitativo, descriptivo, prospectivo y comparativo, que incluye pacientes >18 a <65 anos que egresaron de la UCI, evaluados desde dia 15 de egreso; a traves del instrumento de calidad de vida SF-36, para los dominios fisico y psicologico, la Escala de Ansiedad y Depresion Hospitalaria; y para el dominio de cognicion la escala de Montreal. Resultados: Se mostraran los resultados de la prueba piloto que se realizara en una institucion de tercer nivel, detectando problemas de sindrome cuidados post-intensivos, asi como variables intervinientes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".