Serum Lead Level in Children with Acute Leukemia
Bibliographic record
Abstract
Background: Lead toxicity is one of the most frequently reported unintentional toxic heavy metal exposures and the leading cause of single metal toxicity in children. Lead has no known beneficial function in human metabolism, rather its exposure has various detrimental effect on child health. Lead exposure causes activation of several cellular and molecular processer in leukemic cells so the purpose of the study was to measure serum concentration of lead in newly diagnosed acute lymphoblastic leukemia (ALL) patients.Methodology: The study group consisted of newly diagnosed ALL patients ranging from 2 to 12 years who were admitted at the Department of Pediatrics in Dhaka Medical College Hospital (DMCH), from February 2013 to January 2014 and age and sex matched healthy children’s were selected as controls. Serum measurements for lead were performed by Atomic absorption spectrophotometer in Analytical Chemistry Laboratory of Atomic Energy Centre Ramna, Dhaka.Results: The ALL group composed of 30 patients and 33 healthy children in the control group. There was no significant difference in the age (p=0.781) and sex (p=0.572) of the two groups. The mean serum lead level of ALL patient group (234.8±162.9 μg/L) was significantly higher than that of the control group (23.6±12.6 μg/L). There was significant difference of serum lead level in children with ALL and control group (p<0.05).Conclusion: Serum lead (PB) level was significantly raised in acute lymphoblastic leukemia patients.Bangladesh J Child Health 2018; VOL 42 (1) :26-29
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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 | 0.000 | 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) | 0.002 | 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".