RESUMO
PURPOSE: Coronary computed tomography angiography (CCTA) is an important non-invasive tool for the assessment of coronary artery disease and the delivery of information incremental to coronary anatomy. CCTA measured left ventricular (LV) mid-diastolic volume (LVMDV) and LV mass (LVMass) have important prognostic information but the utility of prospectively ECG-triggered CCTA to predict reduced left ventricular ejection fraction (LVEF) is unknown. The objective of this study was to determine if indexed LVMDV (LVMDVi) and the LVMDV:LVMass ratio on CCTA can identify patients with reduced LVEF. MATERIALS/METHODS: 8179 patients with prospectively ECG-triggered CCTA between November 2014 and December 2019 were reviewed. A subset derivation cohort of 4352 healthy patients was used to define normal LVMDVi and LVMDV:LVMass. Sex-specific thresholds were tested in a validation cohort of 1783 patients, excluded from the derivation cohort, with cardiac disease and known LVEF. The operating characteristics for 1 SD above the mean were tested for the identification of abnormal LVEF, LVEF≤35 â% and ≤30 â%. RESULTS: The derivation cohort had a mean LVMDVi of 61.0 â± â13.7 âmL/m2 and LVMDV:LVMass of 1.11 â± â0.24 âmL/g. LVMDVi and LVMDV:LVMass were both higher in patients with reduced LVEF than those with normal LVEF (98.8 â± â40.8 âmL/m2 vs. 63.3 â± â19.7 âmL/m2, p â< â0.001, and 1.32 â± â0.44 âmL/g vs. 1.05 â± â0.28 âmL/g, p â< â0.001). Both mean LVMDVi and LVMDV:LVMass increased with the severity of LVEF reduction. Sex-specific LVMDVi thresholds were 79 â% and 80 â% specific for identifying abnormal LVEF in females (LVMDVi â≥ â69.9 âmL/m2) and males (LVMDVi â≥ â78.8 âmL/m2), respectively. LVMDV:LVMass thresholds had high specificity (87 â%) in both females (LVMDVi:LVMass â≥ â1.39 âmL/g) and males (LVMDVi:LVMass â≥ â1.30 âmL/g). CONCLUSION: Our study provides reference thresholds for LVMDVi and LVMDV:LVMass on prospectively ECG-triggered CCTA, which may identify patients who require further LV function assessment.
Assuntos
Angiografia por Tomografia Computadorizada , Disfunção Ventricular Esquerda , Masculino , Feminino , Humanos , Angiografia por Tomografia Computadorizada/métodos , Volume Sistólico , Função Ventricular Esquerda , Estudos Prospectivos , Angiografia Coronária/métodos , Valor Preditivo dos Testes , Disfunção Ventricular Esquerda/diagnóstico por imagem , EletrocardiografiaRESUMO
Aims: Indiscriminate coronary computed tomography angiography (CCTA) referrals for suspected coronary artery disease could result in a higher rate of equivocal and non-diagnostic studies, leading to inappropriate downstream resource utilization or delayed time to diagnosis. We sought to develop a simple clinical tool for predicting the likelihood of a non-diagnostic CCTA to help identify patients who might be better served with a different test. Methods and results: We developed a clinical scoring system from a cohort of 21 492 consecutive patients who underwent CCTA between February 2006 and May 2021. Coronary computed tomography angiography study results were categorized as normal, abnormal, or non-diagnostic. Multivariable logistic regression analysis was conducted to produce a model that predicted the likelihood of a non-diagnostic test. Machine learning (ML) models were utilized to validate the predictor selection and prediction performance. Both logistic regression and ML models achieved fair discriminate ability with an area under the curve of 0.630 [95% confidence interval (CI) 0.618-0.641] and 0.634 (95% CI 0.612-0.656), respectively. The presence of a cardiac implant and weight >100 kg were among the most influential predictors of a non-diagnostic study. Conclusion: We developed a model that could be implemented at the 'point-of-scheduling' to identify patients who would be best served by another non-invasive diagnostic test.