Do Opium Abusers Develop Lead Toxicity? A Study on Opium Abusers in Hamadan, Iran
Bibliographic record
Abstract
Background:Raw opium is a kind of drug, abused a lot in Iran. In a vast majority of cases, various impurities including lead are added to raw opium. This study aimed to evaluate Blood Lead Level (BLL) and probable clinical symptoms triggered by it among opium abusers. Methods:This study was case control and conducted on 40 patients addicted to raw opium (case group) and 40 patients without any kind of addiction (control group) who were hospitalized in the poisoning ward of Farshchian hospital, Hamadan, Iran. BLL was measured by Atomic Absorption Spectroscopy (AAS) and compared between the two groups. Para clinical tests and peripheral blood smear were also assessed to check basophilic erythrocytes. Results: The patients’ mean age was 51.9±15.8 years in the control group and 53.2±15 years in the case group. Besides, the mean of BLL was 4.02±3.16 µg/dl in the control group and 22.41±21.14 µg/dl in the case group, and the difference was statistically significant (p<0.001). Moreover, routes of exposure included inhalation (72.5%), oral (12.5%), and both (15%). The results indicated no significant associations between the route of exposure and BLL (p<0.281).Furthermore, no special clinical symptoms were observed in most patients in both groups. Nonetheless, anemia and basophilic erythrocytes were detected in 3 patients who had high BLL. Conclusion:With regard to the high BLL in raw opium abuser, it seems that poisoning with lead should be considered if patients with a history of raw opium addiction refer to physicians.
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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) | 0.001 | 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".