Cigarette smoking exacerbates health problems in young men
Bibliographic record
Abstract
PURPOSE: To examines the hypothesis that smoking exacerbates health problems in young male smokers (age range, 18.6-22.8 yr; mean, 19.4 yr). METHODS: 1169 subjects were recruited, 25.41 % were smokers (2-15 cigarettes daily). All subjects were examined for body mass index, blood pressure, exhaled carbon monoxide content (carboxyl hemoglobin), blood hematology and biochemistry. RESULTS: Data for WBC (P < 0.001), hemoglobin (P=0.001), hematocrit (P=0.004), MCV (P=0.001), MCH (P=0.003), COHB% (P < 0.001), albumin/globulin (P < 0.001) and triglyceride (P < 0.001) were higher for smokers than non-smokers, while total-bilirubin (P < 0.001), total protein (P < 0.001) and globulin (P < 0.001) were markedly lower. The results of WBC (r=0.164, P < 0.004), COHB% (r=0.958, P < 0.001), gamma glutamyl transpeptidase (r=0.159, P=0.006), alkaline-phosphatase (r=-0.154, P=0.008) and triglyceride (r=0.144, P < 0.001) were closely correlated with number of cigarettes smoked daily. Investigation of associations with illness revealed that young smokers had an increased risk of hypertriglyceridemia to young non-smokers (adjusted ORs, 2.124; 95% CIs, 1.414-3.190), hyperglycemia (adjusted ORs, 1.980; 95% CIs, 0.803-4.901), neutrophilia (adjusted ORs, 1.947; 95% CIs, 1.248-3.037), RBC macrocytosis (adjusted ORs, 1.929; 95% CIs, 1.137-3.275), hyperchromia (adjusted ORs, 1.844; 95% CIs, 1.412-2.407) and polycythemia (adjusted ORs, 1.314; 95% CIs, 0.805-2.145) (all P < 0.05 for linear trends). CONCLUSION: The findings emphasize the importance of increasing surveillance of diseases exacerbated by smoking and reducing smoking in the young to prevent cardiovascular illnesses, metabolite disorders and other clinical diseases.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".