Evaluation of Serum Zinc Status in Patients With Neurologic Impairment Under Controlled Enteral Nutrition
Bibliographic record
Abstract
BACKGROUND: Patients with neurologic impairment (NI) often require long-term enteral nutrition. Zinc plays a vital role in neurological and immune function, yet data on zinc intake and status in NI patients remain limited. This study aimed to evaluate whether serum zinc concentrations reflect standardized daily zinc intake in patients with NI receiving fixed-content enteral formulas (EFs) and to identify factors associated with serum zinc levels. METHODS: This retrospective study included bedridden NI patients aged ≥16 years who received EFs via nasogastric or gastrostomy feeding. Clinical parameters, serum biochemical markers, and daily nutrient intake were assessed. Patients were stratified by serum zinc levels (<60 μg/dL or ≥60 μg/dL). Univariate and multivariate linear regression analyses were performed to identify factors independently associated with serum zinc concentrations. RESULTS: Of 31 patients analyzed, 8 (25.8%) exhibited serum zinc deficiency. Zinc intake was significantly lower in the low zinc group compared to the normal zinc group (9.2 vs. 13.5 mg/day, p = 0.0157). Notably, zinc deficiency was observed even in individuals whose zinc intake exceeded the Estimated Average Requirement (EAR) or Recommended Dietary Allowance (RDA). In regression analyses, both daily zinc intake (β = 1.28, p = 0.0273) and serum albumin (β = 14.87, p = 0.0407) were independently associated with serum zinc levels. CONCLUSIONS: Despite controlled enteral nutrition, a substantial proportion of patients with NI exhibited zinc deficiency. Although limited by a small sample size, these findings highlight the importance of individualized monitoring and potential supplementation beyond standardized intake levels.
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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) | 0.000 | 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".