Effect of Breastfeeding and Serum Zinc Levels on Childhood Recurrent Tonsillopharyngitis
Bibliographic record
Abstract
Aim: To evaluate serum zinc levels and breast milk intake in pediatric patients with recurrent tonsillopharyngitis Material Method: 40 pediatric patients who were admitted to our polyclinics with the diagnosis of tonsillopharyngitis diagnosed as ≥ 7 times a year were included in Group 1; 40 healthy children who applied to the outpatient clinic for routine control in the same period were defined as Group 2. Serum zinc, blood parameters, C-reactive protein (CRP) values were studied from all patients. Patient complaints, breastfeeding time, and family history were questioned. Results: There was no significant difference between the groups in terms of Hemaoglobin(Hb), hematocrit(Hct), white blood cell count(WBC), platelet count(Plt), mean platelet volume(MPV) and CRP values were significantly higher in the patient group (p=0.001). Serum zinc levels were significantly lower in Group 1 than Group 2 (p=0.000; p <0.05). There was no significant difference between the groups regarding the duration of breastfeeding (p=0.086; p> 0.05). Conclusion: Our study showed that zinc deficiency may play a role in the etiopathogenesis of recurrent tonsillopharyngitis. Zinc supplementation may be recommended for children with recurrent tonsillopharyngitis There is a need for further studies to be done in larger population related to zinc levels in mother's milk content, serum zinc levels in mothers and zinc deficiency.
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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 | 0.000 |
| 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".