Abstract 63: The Smoking Paradox in Patients Hospitalized with Coronary Artery Disease: Findings from Get With The Guidelines - CAD
Notice bibliographique
Résumé
Introduction: Despite evidence of smoking as a potent risk factor for coronary artery disease (CAD), there have been reports of lower in-hospital mortality among smokers hospitalized for CAD events. Method: We analyzed all consecutive CAD admissions (n=158,054) without a prior history of Stroke/TIA from 2002-2008 in Get With The Guidelines (GWTG)-CAD. Categorical data were analyzed by Pearson Chi-square and continuous data by Wilcoxon test. Multivariable models with generalized estimating equations for in-hospital clustering were used to estimate odds ratios of in-hospital mortality. All significant predictors on univariate analysis were included in the multivariable model. Results: Among all CAD patients, 30.4% were current smokers, defined as any cigarette use in the past year. Smokers were substantially younger (12 years), more often male and less often had pre-existing hypertension, dyslipidemia, heart failure, renal failure and atrial fibrillation, and more often had COPD/Asthma. Smokers were more likely to be admitted to large, academic hospitals, and more often in the South. Smokers had shorter length of stay in hospital and were more often discharged home. In-hospital mortality was lower in smokers as compared to non-smokers (Table 1). The significant univariate mortality difference attenuated dramatically after adjusting for age and other covariates in the multivariable model, OR increased from 0.57 (0.53, 0.61) on univariate analysis to 0.88 (0.81, 0.95) on multivariable model. Other independent predictors of mortality were increasing age [1.51 (1.46, 1.56)], history of diabetes mellitus [1.25 (1.18, 1.33)], Asthma/COPD [1.30 (1.23, 1.38)], peripheral vascular disease [1.34 (1.24, 1.44)], heart failure [1.48 (1.38, 1.58)] and renal insufficiency [1.61 (1.48, 1.74)]. Conclusion: Smoking continues to be a major risk factor for presenting with CAD at a much younger age and with fewer risk factors. It is likely that the continued modest association with lower in-hospital mortality in smokers in this analysis after adjustment reflects residual or unmeasured confounding. This apparent smoker’s paradox in CAD should not be interpreted as a benefit of cigarette smoking.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».