2213Impact of BMI on clinical outcomes in all-comers patients with coronary artery disease undergoing PCI: insights from the Global Leaders study
Notice bibliographique
Résumé
Abstract Background It is uncertain if the obesity paradox still exists in contemporary PCI practice. Purposes We aimed to assess an association between baseline BMI and clinical outcomes at 2 years after PCI and to determine if the outcomes between two antiplatelet strategies depend on baseline BMI. Methods Global Leaders study compared 23-month ticagrelor monotherapy after 1 month of dual antiplatelet therapy (experimental strategy) with 12-month aspirin monotherapy after 12 months of conventional DAPT (reference strategy) in patients undergoing PCI with biolimus-A9 eluting stent. Primary outcome of current study was 2-year all-cause mortality after PCI. Secondary outcomes were net adverse clinical event (NACE) and individual components of the composite endpoint. Association between baseline BMI and outcomes were determined in the Cox model. Non-linearity was assessed using restrict cubic spline function. Patients were categorized according to WHO BMI categories; underweight (BMI <18.5), healthy weight (BMI 18.5–24.9), pre-obese state (BMI 25–29.9) and obesity (BMI ≥30). Interaction between BMI categories and antiplatelet strategies were assessed. Results BMI was available in 15,966 out of 15,968 patients with a median of 27.7 kg/m2 (IQR 25.0–30.7). Baseline BMI had a reverse J-shaped association with 2-year all-cause mortality. 3901 patients (24.4%) were in the group of healthy weight, 79 patients (0.5%) were under-weight, 7220 patients (45.2%) were pre-obese and 4766 patients (29.8%) were obese. Due to small number of underweight patients, outcomes after PCI were compared among three groups; healthy weight, overweight, and obesity. Pre-obese and obese patients had lower risk of 2-year all-cause mortality than healthy-weight patients (HR pre-obesity vs. healthy-weight 0.71, 95% CI 0.58–0.88, HR obesity vs. healthy-weight 0.69, 95% CI 0.54–0.87). The risk of 2-year NACE was similar among three groups (healthy weight vs. pre-obesity; HR 1.04, 95% CI 0.94–1.16, healthy weight vs. obesity; HR 1.04, 95% CI 0.93–1.16). No significant difference in risk of any stroke, any MI, and BARC3 or 5 bleeding was found among three groups. Pre-obese patients had higher risk of revascularization than patients with healthy weight (HR 1.19, 95% CI 1.04–1.35). The risk of revascularization in obese patients was numerically higher than healthy-weight patients (HR 1.14, 95% CI 0.99–1.31). For BARC 3 or 5 bleeding at 2 years, ticagrelor monotherapy was more favorable in obese patients (HR reference/experimental 1.63, 95% CI 1.06–2.52) while conventional DAPT strategy was more favorable in pre-obese patients (HR experimental/reference 0.76, 95% CI 0.55–1.05) (P interaction 0.02). No interaction between treatment strategy, BMI, and other outcomes was seen. BMI and all-cause mortality and NACE Conclusions An obesity paradox, an association between elevated BMI and lower mortality, is still evident in this large PCI population. Effect of two antiplatelet strategies on bleeding may depend on baseline BMI.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».