Assessing Nutritional Status in Chronically Critically Ill Adult Patients
Bibliographic record
Abstract
BACKGROUND: Numerous methods are used to measure and assess nutritional status of chronically critically ill patients. OBJECTIVES: To discuss the multiple methods used to assess nutritional status in chronically critically ill patients, describe the nutritional status of chronically critically ill patients, and assess the relationship between nutritional indicators and outcomes of mechanical ventilation. METHODS: A descriptive, longitudinal design was used to collect weekly data on 360 adult patients who required more than 72 hours of mechanical ventilation and had a hospital stay of 7 days or more. Data on body mass index and biochemical markers of nutritional status were collected. Patients' nutritional intake compared with physicians' orders, dieticians' recommendations, and indirect calorimetry and physicians' orders compared with dieticians' recommendations were used to assess nutritional status. Relationships between nutritional indicators and variables of mechanical ventilation were determined. RESULTS: Inconsistencies among nurses' implementation, physicians' orders, and dieticians' recommendations resulted in wide variations in patients' calculated nutritional adequacy. Patients received a mean of 83% of the energy intake ordered by their physicians (SD 33%, range 0%-200%). Patients who required partial or total ventilator support upon discharge had a lower body mass index at admission than did patients with spontaneous respirations (Mann-Whitney U = 8441, P = .001). CONCLUSIONS: In this sample, the variability in weaning progression and outcomes most likely reflects illness severity and complexity rather than nutritional status or nutritional therapies. Further studies are needed to determine the best methods to define nutritional adequacy and to evaluate nutritional status.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".