Serum Selenium Levels in Patients with Head and Neck Cancer
Bibliographic record
Abstract
OBJECTIVE: The objective of this research was to estimate serum selenium levels in patients with head and neck cancer and to correlate them with tumour burden, as well as to study the effect of radiotherapy on serum selenium levels to determine its prognostic significance. DESIGN: This prospective study was carried out by selection of head and neck cancer patients using periodic random numbers. SETTING: This was a hospital-based study. METHODS: Estimation of serum selenium was done using the Atomic Absorption Spectrophotometer (Model AAS 4129; Electronic Corporation of India Ltd., Hydrabad, India) with a hydride generator after digestion of the serum sample. MAIN OUTCOME MEASURES: Patients were followed for 1 year postradiotherapy for any change in serum selenium level and its correlation with the outcome of the treatment. RESULTS: All 30 patients had serum selenium levels significantly lower as compared with controls, and these levels decreased further as tumour burden increased. Levels came within normal range after 1 year of radiotherapy in 10 patients who were cured but in the remaining patients who had residual disease, levels remained persistently low. CONCLUSIONS: The serum selenium level may serve as a useful marker in head and neck cancer.
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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 | 0.000 | 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".