Calorie and Protein Intake in Acute Rehabilitation Inpatients with Traumatic Spinal Cord Injury Versus Other Diagnoses
Bibliographic record
Abstract
BACKGROUND: Obesity and its consequences affect patients with spinal cord injury (SCI). There is a paucity of data with regard to the dietary intake patterns of patients with SCI in the acute inpatient rehabilitation setting. Our hypothesis is that acute rehabilitation inpatients with SCI consume significantly more calories and protein than other inpatient rehabilitation diagnoses. OBJECTIVE: To compare calorie and protein intake in patients with new SCI versus other diagnoses (new traumatic brain injury [TBI], new stroke, and Parkinson's disease [PD]) in the acute inpatient rehabilitation setting. METHODS: The intake of 78 acute rehabilitation inpatients was recorded by registered dieticians utilizing once-weekly calorie and protein intake calculations. RESULTS: Mean ± SD calorie intake (kcal) for the SCI, TBI, stroke, and PD groups was 1,967.9 ± 611.6, 1,546.8 ± 352.3, 1,459.7 ± 443.2, and 1,459.4 ± 434.6, respectively. ANOVA revealed a significant overall group difference, F(3, 74) = 4.74, P = .004. Mean ± SD protein intake (g) for the SCI, TBI, stroke, and PD groups was 71.5 ± 25.0, 61.1 ± 12.8, 57.6 ± 16.6, and 55.1 ± 19.1, respectively. ANOVA did not reveal an overall group difference, F(3, 74) = 2.50, P = .066. CONCLUSIONS: Given the diet-related comorbidities and energy balance abnormalities associated with SCI, combined with the intake levels demonstrated in this study, education with regard to appropriate calorie intake in patients with SCI should be given in the acute inpatient rehabilitation setting.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".