Prognostic capabilities of coronary computed tomographic angiography before non-cardiac surgery: prospective cohort study
Notice bibliographique
Résumé
OBJECTIVES: To determine if coronary computed tomographic angiography enhances prediction of perioperative risk in patients before non-cardiac surgery and to assess the preoperative coronary anatomy in patients who experience a myocardial infarction after non-cardiac surgery. DESIGN: Prospective cohort study. SETTING: 12 centers in eight countries. PARTICIPANTS: 955 patients with, or at risk of, atherosclerotic disease who underwent non-cardiac surgery. INTERVENTIONS: Coronary computed tomographic angiography was performed preoperatively; clinicians were blinded to the results unless left main disease was suspected. Results were classified as normal, non-obstructive (<50% stenosis), obstructive (one or two vessels with ≥ 50% stenosis), or extensive obstructive (≥ 50% stenosis in two vessels including the proximal left anterior descending artery, three vessels, or left main). MAIN OUTCOME MEASURE: Composite of cardiovascular death and non-fatal myocardial infarction within 30 days after surgery (primary outcome). This was the dependent variable in Cox regression. The independent variables were scores on the revised cardiac risk index and findings on coronary computed tomographic angiography. RESULTS: The primary outcome occurred in 74 patients (8%). The model that included both scores on the revised cardiac risk index and findings on coronary computed tomographic angiography showed that coronary computed tomographic angiography provided independent prognostic information (P=0.014; C index=0.66). The adjusted hazard ratios were 1.51 (95% confidence interval 0.45 to 5.10) for non-obstructive disease; 2.05 (0.62 to 6.74) for obstructive disease; and 3.76 (1.12 to 12.62) for extensive obstructive disease. For the model with coronary computed tomographic angiography compared with the model based on the revised cardiac risk index alone, with 30 day risk categories of <5%, 5-15%, and >15% for the primary outcome, the results of risk reclassification indicate that in a sample of 1000 patients that coronary computed tomographic angiography would have resulted appropriately in 17 net patients receiving a higher risk estimation among the 77 patients who would have experienced the primary outcome (P<0.001). Coronary computed tomographic angiography, however, would have resulted inappropriately in 98 net patients receiving a higher risk estimation, among the 923 patients who would not have experienced the primary outcome (P<0.001). Among patients who had a perioperative myocardial infarction, preoperative coronary anatomy showed extensive obstructive disease in 31% (22/71), obstructive disease in 41% (29/71), non-obstructive disease in 24% (17/71), and normal findings in 4% (3/71). CONCLUSIONS: Though findings on coronary computed tomographic angiography can improve estimation of risk for patients who will experience perioperative cardiovascular death or myocardial infarction, findings are more than five times as likely to lead to an inappropriate overestimation of risk among patients who will not experience these outcomes. Perioperative myocardial infarction occurs across the spectrum of coronary artery disease, suggesting that there could be several pathophysiologic mechanisms.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 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 | 0,000 |
| 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 ».