[Current status of clinical nutrition at the network of public hospitals from Castilla y León].
Bibliographic record
Abstract
INTRODUCTION: Clinical nutrition is an activity realized in most of Health Centres of France, Canada, Great Britain and USA. The aim of our work was to determine activity and resources of Nutrition Units of Hospitals in the Community of Castilla y León. MATERIAL AND METHODS: A questionnaire was send to all Hospitals of Castilla y León (SACYL); Hospital Universitario Rio Hortega, Hospital Clinico Universitario, Hospital Comarcal de Medina del Campo, Hospital General Yagüe-Divino Vallés (Burgos), Complejo Hospitalario de Le6n, Hospital General de Segovia, Hospital Virgen de Sonsoles de Avila, Hospital Virgen de la Concha de Zamora, Hospital Comarcal de Aranda de Duero, Hospital Comarcal de Miranda, Hospital General de Soria, Hospital Clinico Universitario de Salamanca. RESULTS: Nine Centres responded questionnaire (75%). A total of 5 Hospitals had a Unit of Nutrition (55.6%). The results showed an average of 0.37 +/- 0.55 specialists for each 400 beds, 0.87 +/- 0.63 nurses for each 400 beds and 1.91 +/- 2.3 auxiliaries for each 400 beds, with an average of 0.21 +/- 0.41 specialists for each 100,000 habitants, 0.49 +/- 0.36 nurses for each 100,000 habitants and 1.09 +/- 1.2 auxiliaries for each 100,000 habitants. The activity of these Units is demanded by other Units, with an average of 3.2 +/- 3.4 consultations per day. The main diseases of this activity were 33.3% tumoral pathology, 55.6% surgery and 11.1% neurological pathology. Oral supplements were the first intervention tool. Only 3 Centres had a home artificial nutrition consultation. The main diseases of this activity were post surgical patients (33,3%), tumoral pathology (33,3%), neurological pathology (22%) and inflammatory bowel disease (11%). CONCLUSION: Resources in Units of Nutrition of Castilla y Leon were limited. However, activity in Hospital an in home is equal than other areas. New actions of Local Administration are necessaries to follow recommendations of Council of Europe.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".