Interferon Gamma and Tumor Necrosis Factor Alpha Are Inflammatory Biomarkers for Major Adverse Cardiovascular Events in Patients with Peripheral Artery Disease
Notice bibliographique
Résumé
Background/Objectives: Major adverse cardiovascular events (MACE)—including heart attacks and strokes—are the leading cause of death in patients with peripheral artery disease (PAD), yet biomarker research for MACE prediction in PAD patients remains limited. Inflammatory proteins play a key role in the progression of atherosclerosis and may serve as useful prognostic indicators for systemic cardiovascular risk in PAD. The objective of this study was to evaluate a broad panel of circulating inflammatory proteins to identify those independently associated with 2-year MACE in patients with PAD. Methods: We conducted a prospective cohort study involving 465 patients with PAD. Plasma concentrations of 15 inflammatory proteins were measured at baseline using validated immunoassays. Patients were followed over a two-year period for the development of MACE, defined as a composite endpoint of myocardial infarction, stroke, or mortality. Protein levels were compared between patients with and without MACE using the Mann–Whitney U test. Cox proportional hazards regression was used to determine the independent association of each protein with MACE after adjusting for baseline demographic and clinical variables, including existing coronary and cerebrovascular disease. To validate the findings, a random forest machine learning model was developed to assess the relative importance of each protein for predicting 2-year MACE. Results: The mean age of the cohort was 71 years (SD 10), and 145 participants (31.1%) were female. Over the two-year follow-up, 84 patients (18.1%) experienced MACE. Six proteins were significantly elevated in PAD patients who developed MACE: interferon gamma (IFN-γ; 42.55 [SD 15.11] vs. 33.85 [SD 12.46] pg/mL, p < 0.001), tumor necrosis factor alpha (TNF-α; 9.00 [SD 5.00] vs. 4.65 [SD 4.29] pg/mL, p < 0.001), chemokine (C-X-C motif) ligand 9 (CXCL9; 75.99 [SD 65.14] vs. 5.38 [SD 64.18] pg/mL, p = 0.002), macrophage inflammatory protein-1 beta (MIP-1β; 20.88 [SD 18.10] vs. 15.67 [SD 16.93] pg/mL, p = 0.009), MIP-1δ (25.29 [SD 4.22] vs. 17.98 [SD 4.01] pg/mL, p = 0.026), and interleukin-6 (IL-6; 12.50 [SD 40.00] vs. 6.72 [SD 38.98] pg/mL, p = 0.035). After adjusting for all baseline covariates, only two proteins—TNF-α (adjusted HR 1.66, 95% CI 1.28–2.33, p = 0.001) and IFN-γ (adjusted HR 1.25, 95% CI 1.12–2.29, p = 0.033)—remained significantly and independently associated with 2-year MACE. These findings were corroborated by the random forest model, where TNF-α and IFN-γ received the highest importance scores for predicting 2-year MACE: (TNF-α: 0.15 [95% CI 0.13–0.18], p = 0.002; IFN-γ: 0.19 [95% CI 0.17–0.21], p = 0.001). Conclusions: From a panel of 15 proteins, TNF-α and IFN-γ emerged as inflammatory biomarkers associated with 2-year MACE in PAD patients. Their measurement may aid in cardiovascular risk stratification, helping to identify high-risk individuals who could benefit from early multidisciplinary referrals to cardiology, neurology, and/or vascular medicine specialists to provide intensified medical therapy. Incorporating these biomarkers into PAD management may improve systemic cardiovascular outcomes through more personalized and targeted treatment approaches.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| 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 ».