Impact of Nutrition Counseling in Head and Neck Cancer Sufferers Undergoing Antineoplastic Therapy: A Randomized Controlled Pilot Study
Bibliographic record
Abstract
Head and neck cancer (HNC) sufferers usually encounter arduous nutritional problems when they are receiving antineoplastic therapy. Consequently, the presence of anxiety and depression is commonly observed in this population. This study aimed to explore the physical and psychological influence of nutritional counseling in patients with HNC. Patients receiving concurrent chemo-radiotherapy were randomly assigned to the nutritional counseling group (n = 32, 52.45%) and the control group (n = 29, 47.54%) according to their treatment patterns. In the nutritional counseling group, registered dietitians provided face-to-face counseling during the antineoplastic treatment course at least every two weeks. Nutrient intake amount, relevant nutritional indexes, quality of life, and the degree of anxiety and depression were compared between the two groups. We observed a decrease in the calorie and protein intake amount in both groups, while the decrease in the control group is even worse. The weight loss is more obvious in the control group. The HADS scores in the intervention group were significantly lower than that in the control group (p < 0.05). The Karnofsky Performance Status (KPS) scores in the intervention group were significantly higher than that in the control group (p < 0.05). The level of serum total protein, serum albumin, transferrin, and the thickness of the triceps skin fold decreased less in the intervention group (p < 0.05). Our findings suggest that nutrition counseling is essential for the maintenance of calorie and protein intake in HNC suffers, which contributes to an improvement in the physical and psychological states. The impacts observed in this pilot study warrant further exploration in a larger prospective trial.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".