Does Opium Consumption Have Shared Impact on Atherosclerotic Cardiovascular Disease and Cancer?
Bibliographic record
Abstract
Although atherosclerotic cardiovascular disease (ASCVD) and cancer are seemingly different types of disease, they have multiple shared underlying mechanisms and lifestyle-related risk factors like smoking, unhealthy diet, excessive alcohol consumption, and inadequate physical activity. Opium abuse is prevalent in developing countries, especially the Middle East region and many Asian countries. Besides recreational purposes, many people use opium based on a traditional belief that opium consumption may confer protection against heart attack and improve the control of the risk factors of ASCVD such as diabetes mellitus, hypertension, and dyslipidemia. However, scientific reports indicate an increased risk of ASCVD and poor control of ASCVD risk factors among opium abusers compared with nonusers. Moreover, there is accumulating evidence that opium consumption exerts potential carcinogenic effects and increases the risk of developing various types of cancer. We conducted a review of the literature to review the current evidence on the relationship between opium consumption and ASCVD as well as various kinds of cancer. In addition, we will discuss the potential shared pathophysiologic mechanisms underlying the association between opium abuse and both ASCVD and cancer.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".