Sleep disturbances and memory impairment among pregnant women consuming khat: An under-recognized problem
Bibliographic record
Abstract
) is a evergreen flowering shrub that is cultivated at high altitudes, especially in East Africa and the southwest of the Arabian Peninsula. The plant contains alkaloids, of which cathinone and cathine have structural similarity and pharmacological action similar to amphetamines. The leaves are, therefore, consumed in some regions as a psychoactive stimulant due to cultural beliefs and misperceptions on the health benefits of khat consumption. This resulted in a growing prevalence of khat consumption among pregnant women. The myriad of physiological changes associated with pregnancy impairs sleep and memory. Moreover, khat has also been shown to have adverse effects on memory and sleep. Therefore, its use during pregnancy may further aggravate those impairments. The purpose of this mini-review is to summarize the changes in sleep and memory during pregnancy and the evidence supporting a relationship between khat consumption and neurocognitive deficits and sleep dysfunctions. The misperceptions of beneficial effects of khat, the high prevalence of consumption among pregnant women, and the possibility of under-reporting of khat abuse do necessitate the development of alternative methodologies to identify cases of unreported khat abuse in pregnant women. It is proposed that screening for sleep problems and memory deficits may help identify under-reported cases of khat abuse in pregnant women.
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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) | 0.001 | 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".