Epidemiology of Organophosphate Poisoning in North of Iran
Bibliographic record
Abstract
Abstract Introduction: The use of pesticides as one of the main agricultural poles has been increased in Iran in recent years. Organophosphate poisoning has harmful the consequences for human health. This study present clinical and laboratory evidences on the patients exposed to agricultural insecticides poisoning and the cause of these poisons.Methods: We collected clinical data from the patients referred to Razi Hospital, Rasht, Iran who were poisoned with organophosphorus toxins. For this purpose, a checklist was prepared, and data were collected for 414 patients between 2011 and 2016. Results: The results showed that the most cases of poisoning were men (73%) and about 27.2% of the patients was in the age group of 45-60 years (highest frequency in age groups)..The most frequent symptoms were vomiting (65%), nausea (61%), abdominal pain (39%), and perspiration (27%). There was also a decrease in consciousness (16%) and sialorrhea (16%). 186 (46.2%) patients were exposed to organophosphorus toxins by respiratory and 215 (53.4%) orally. Out of the 414 samples, 102 (33%) had abnormal CPK enzymes and 114 (34.5%) abnormal LDHs. Mean hospital length of stay (LOS) was 3.3 days. We found significant relationship of LOS with heart failure, hypertension, and addiction. Conclusion: To better manage the process of treatment of agricultural poisoned patients and to reduce the waste of limited resources available, careful consideration should be given to the type of pesticide used by the patient to prevent overdose and unintentional use of antidote. Act.
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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".