Addiction to 'Gul' and 'Gutkha' Leading to Acute Pulmonary Thrombosis and Acute Psychosis in a Young Pregnant Lady
Bibliographic record
Abstract
Gul is an oral tobacco powder which is rubbed over the gum and teeth. Being a tobacco preparation it is addictive in nature. It is popular among rural women in the south Asian countries. Not much is known about long term of gul on atherogenesis and/or pregnancy. Gul alone may or may not exert harmful effect on future course of pregnancy, however when combined with another tobacco preparation 'gutkha' which contains tobacco and betel nut, it may be dangerous for the foetus as well as for the mother. So far little has been reported regarding the atherogenic potential of gul and gutkha during pregnancy. We recently came across a young pregnant lady who was addicted to gul and gutkha for long. She developed acute pulmonary thrombosis during 32nd week of pregnancy and had previous two episodes of abortions. Her thrombophilic profile was normal. The pulmonary thrombosis resolved after preterm delivery and anticoagulant therapy. However, sh e developed acute craving for gul and gutkha and acute psychosis on 5th day of delivery which responded to antipsychotic regimen. Present case highlights the highly addictive and potentially atherogenic effects of gul, considered innocuous by users. The case focuses the catastrophic effect of gul and gutkha which may lead to thrombophilic state when taken during pregnancy. doi:10.4021/jmc7w
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".