Drug abuse and ACS in the very young (less than 30 years): Demographic, clinical and angiographic profile
Bibliographic record
Abstract
AIM: To identify incidence, type of drug abuse study clinical and angiographic profile in very young population presenting with acute coronary syndrome (ACS). MATERIALS AND METHODS: All consecutive patients less than 30 years with ACS included and segregated into Group 1 and 2 (with and without drug abuse respectively) RESULT: n = 153; n = 17 in group 1 of whom 35.29 % consumed opium, 17.64 % energy drinks, 17.64 % whey protein supplements, 17.64 % inhaled marijuana, 5.88 % heroin and spasmoproxyvon and 23.52 % multi-substance abusers. STEMI, Single vessel disease and urban domicile were predominant. Rising trends of drug abuse were identified in prospective (28.20 %) versus retrospective (5.30 %) timeframe (p = 0.011). CONCLUSION: Rising trends of drug abuse, a potentially modifiable risk factor of ACS in the young are alarming. Strict regulations are needed to curb this menace.
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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".