Investigating ethnic differences in risk factors and severity of developing premature coronary artery disease: Predicting the effect of risk factors through decision tree analysis in a multicenter case-control study; Results from Iran Premature Coronary Artery Disease (IPAD study)
Notice bibliographique
Résumé
Introduction: Premature coronary artery disease (PCAD) has an ascending trend especially in developing countries. This study have investigated the risk factors and severity of developing CAD across various Iranian ethnicities. Methods: This case-control study was done on 3015 Iranian patients undergoing coronary artery angiography, across highly populated Iranian ethnicities including Bakhtiari, Azari, Qashqai, Arab, Fars, Kurd, Gilak, and Lur. This study was performed over three years in 14 capitals of provinces in Iran headed by Isfahan Cardiovascular Research Center, by including men≤60 years old and women≤70 years undergoing coronary artery angiography. If they had coronary stenosis above 75% (more than 50% in the left main), they were categorized as Case group.The effects of conventional risk factors as well as psychosocial ones including age, gender, weight, Body mass index (BMI), economic status, cigarette smoking, drugs of abuse, stress, anxiety, diabetes, hypertension, etc. were determined in each ethnicity using decision tree statistical method. Also, via logistic regression method, the odds of incidence of CAD in each ethnicity were specified against the Fars ethnicity (the predominant ethnicity in Iran). Results: The most common risk factor among different ethnicities was age and male gender. Also, among the Iranian ethnicities, Kurd had the lowest chance while Gilak and Azari had the highest chance of developing PCAD as compared to the Fars ethnicity. Investigation of the behavioral and psychological dimensions indicated that stress was significantly higher among those without coronary artery involvement as compared to those with this involvement. The decision tree model could predict that among Gilakis, Fasting blood sugar (FBS) above 126 and in Lurs opium as well as diastolic blood pressure above 85, and in Kurds male gender would considerably increase the odds of developing CAD. Conclusion: The model obtained from the decision tree indicated that although variables of age, gender, cigarette, and opium are among the main risk factors for involvement of coronary arteries among young adult patients, in different ethnicities, the risk level of each of these risk factors in incidence of PCAD is different. This means among Kurds, age, among Gilakis diabetes, and among Lurs opium are more important.
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 | 0,012 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,002 |
| 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 ».