Thyroid Hormone Status in Severely Malnourished Children between 6 Months to 5 Years Admitted to Nutritional Rehabilitation Centre of a Tertiary Care Hospital
Bibliographic record
Abstract
Introduction: Severe malnutrition poses a significant risk to the thyroid gland's function and hormonal balance, which can lead to numerous physiological and developmental complications. Understanding the relationship between severe malnutrition and thyroid hormone status is crucial for the effective management of these children. Aim and Objective: To investigate the prevalence and patterns of thyroid hormone abnormalities in severely malnourished patients with subgroup analysis in Marasmus, Kwashiorkor, and edematous malnourished patients. Methodology: We conducted a cross-sectional study involving 116 children diagnosed with severe acute malnutrition (SAM). The study protocol was approved by the Institution Ethics Committee. Well-informed written consent in the local language was taken from parents. SAM was diagnosed and managed according to WHO criteria (1). Comprehensive laboratory investigations were conducted to assess serum levels of thyroid-stimulating hormone (TSH), free thyroxine (T4), and triiodothyronine (T3). Statistical analysis was performed to examine the associations between these variables and SAM. Results: Most of the 116 subjects included in the study were male (53.4%) and had a lower socioeconomic status (43.9%). The age distribution of the children aged below 5 years revealed that 46.5% were between 12 and 36 months old. In the present study, Marasmus was 55.2%, Kwashiorkor was 12.1%, and edematous malnutrition was 32.7%. Among 116 participants, 94.8% were discharged, while 5.2% were expired during treatment. The mean levels of fT3, fT4, and TSH were 1.88±1.06 pg/ml, 0.99±0.84 ng/dl, and 3.22±0.87 µIU/ml, respectively. Most SAM patients had low fT3, fT4, and TSH levels relative to the normal range. Conclusion: Monitoring of thyroid hormone status in SAM patients is mandatory for this vulnerable population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".