Impact of age, sex, and cardiac size on the diagnostic performance of myocardial perfusion single-photon emission computed tomography: insights from the REFINE SPECT registry
Notice bibliographique
Résumé
Abstract Background Single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI) is a well-validated non-invasive method for detecting coronary artery disease (CAD). Variations in diagnostic performance due to age and sex have been thoroughly investigated in the literature yet have demonstrated conflicting results. Several studies have associated female sex with reduced accuracy, although others have discovered no significant difference (1). Similarly, while SPECT MPI in the elderly has shown prognostic utility, cardiac event rates are elevated compared to younger patients despite a normal study (2). Additional analyses have suggested that cardiac chamber size may contribute to these observed differences due to its relationship with spatial resolution; however, the interaction of age, sex, and cardiac size remains unknown. Purpose We aimed to leverage a large, multicenter, international registry to assess the impact of age, sex, and left ventricular size on the diagnostic accuracy of contemporary SPECT MPI. Methods In 9 centers, 2067 patients (67% male, 64.7±11.2 years) in the REFINE SPECT database (REgistry of Fast Myocardial Perfusion Imaging with NExt Generation SPECT) underwent MPI with new generation solid-state scanners followed by invasive coronary angiography within 6 months (3). Stress total perfusion deficit was quantified automatically, and obstructive CAD was defined as >70% stenosis or >50% for left main. Receiver-operating characteristic curves and corresponding areas under the curve (AUC) were computed to compare diagnostic performance between cohorts created based on age (<75 vs. ≥75 years), sex, and end-diastolic volume (EDV; ≥20th vs. <20th sex-specific percentile). Results Female and elderly patients had a significantly lower EDV than male and younger patients respectively (p<0.001, Figure 1). Diagnostic accuracy of SPECT was similar by sex (p=0.63). Elderly patients (AUC 0.72 vs. 0.78, p=0.025) and patients with reduced volumes (AUC 0.72 vs. 0.79, p=0.009) exhibited significantly worse performance. When isolating male patients with reduced volumes, a significant difference in accuracy was observed (AUC 0.69 vs. 0.79, p=0.001; Figure 2A), while female patients trended towards significance (p=0.32). Likewise, SPECT performed poorly for elderly patients with reduced volumes (AUC 0.64 vs. 0.78, p=0.01; Figure 2B). If patients possessed any two characteristics of male sex, age ≥75, or low EDV, prediction of CAD with SPECT was significantly decreased (p=0.002; Figure 2C). Conclusions Our findings suggest that men with reduced cardiac volumes display worse diagnostic SPECT performance, although it is uncertain whether a pathophysiologic reason exists or further investigation is required for female patients. Patients age ≥75 tended to have lower cardiac volumes as well as lower diagnostic performance. Given these results, alternative diagnostic modalities may better diagnose CAD in patients with these characteristics. Funding Acknowledgement Type of funding sources: None. Figure 1Figure 2
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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 | 0,004 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».