Assessment of Nutritional Status for Identifying Nutritional Rickets in Children Less Than Five Years of Age
Bibliographic record
Abstract
Aim: To assess the nutritional status for identifying nutritional rickets in children less than five years of age. Study design: Prospective study Place and duration of study: Department of Medicine Paediatrics, Arif Memorial Teaching Hospital Lahore from 1st April 2021 30th September 2021. Methodology: Sixty children suffering from rickets were enrolled. Blood sample 3cc was taken from each child and serum was separated by centrifugation. The serum was stored at -20°C until analysis. Biochemical tests including 25-OH vitamin D3, serum calcium and alanine phosphatase were done. The radiological imaging (X-ray) pictures completely demonstrated the rickets status. Demographical information, age, body mass index of each child was documented on a well-structured questionnaire. Food frequency charts related to vitamin D rich foods as well as calcium rich diet was used for assessing the nutritional status of children. Results: The mean age of the children was 3.5±1.9 years. The clinical symptoms of the enrolled children showed that sweating was most common symptoms in all sixty children suffering from rickets. Forty-eight percent cases were under weight and stunting was presented in 73% while wasting was observed in 23% of the cases. The radiological x ray imaging showed Cupping of the bones was presented in 51% of the cases followed by wrist widening in 24%. The food frequency results also presented similar findings in which serum calcium was observed inadequate in 86.6% of cases while ALP and vitamin D3 was inadequate in 90% and 100% of cases respectively. Conclusion: Vitamin D status of Pakistan children was very alarming as 100% of the cases was vitamin D deficient. Calcium deficiency was also significantly associated with nutritional rickets. Keywords: Nutritional rickets, Vitamin D deficiency, Geological location, Bone deformities
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".