Assessment of myocardial strain patterns in patients with left bundle branch block using cardiac magnetic resonance.

Recently, a classification with four types of septal longitudinal strain patterns was described using echocardiography, suggesting a pathophysiological continuum of left bundle branch block (LBBB)-induced left ventricle (LV) remodeling. The aim of this study was to assess the feasibility of classifying these strain patterns using cardiovascular magnetic resonance (CMR), and to evaluate their association with LV remodeling and myocardial scar. Single center registry included LBBB patients with septal flash (SF) referred to CMR to assess the cause of LV systolic dysfunction. Semi-automated feature-tracking cardiac resonance (FT-CMR) was used to quantify myocardial strain and detect the four strain patterns. A total of 115 patients were studied (age 66 ± 11 years, 57% men, 28% with ischemic heart disease). In longitudinal strain analysis, 23 patients (20%) were classified in stage LBBB-1, 37 (32.1%) in LBBB-2, 25 (21.7%) in LBBB-3, and 30 (26%) in LBBB-4. Patients at higher stages had more prominent septal flash, higher LV volumes, lower LV ejection fraction, and lower absolute strain values (p < 0.05 for all). Late gadolinium enhancement (LGE) was found in 55% of the patients (n = 63). No differences were found between the strain patterns regarding the presence, distribution or location of LGE. Among patients with LBBB, there was a good association between strain patterns assessed by FT-CMR analysis and the degree of LV remodeling and LV dysfunction. This association seems to be independent from the presence and distribution of LGE.

Implications of three different testing strategies in the diagnostic approach to patients with stable chest pain and low pretest probability of obstructive coronary artery disease.

INTRODUCTION: The clinical implications of a widespread adoption of guideline recommendations for patients with stable chest pain and low pretest probability (PTP) of obstructive coronary artery disease (CAD) remain unclear. We aimed to assess the results of three different testing strategies in this subgroup of patients: A) defer testing; B) perform coronary artery calcium score (CACS), withholding further testing if CACS â€‹= â€‹0 and proceeding to coronary computed tomography angiography (CCTA) if CACS>0; C) perform CCTA in all. METHODS: Two-center cross-sectional study assessing 1328 symptomatic patients undergoing CACS and CCTA for suspected CAD. PTP was calculated based on age, sex and symptom typicality. Obstructive CAD was defined as any luminal stenosis ≥50% on CCTA. RESULTS: The prevalence of obstructive CAD was 8.6% (n â€‹= â€‹114). In the 786 patients (56.8%) with CACS â€‹= â€‹0, 8.5% (n â€‹= â€‹67) had some degree of CAD [1.9% (n â€‹= â€‹15) obstructive, and 6.6% (n â€‹= â€‹52) nonobstructive]. Among those with CACS>0 (n â€‹= â€‹542), 18.3% (n â€‹= â€‹99) had obstructive CAD. The number of patients needed to scan (NNS) to identify one patient with obstructive CAD was 13 for strategy B vs. A, and 91 for strategy C vs. B. CONCLUSIONS: Using CACS as gatekeeper would decrease CCTA use by more than 50%, at the cost of missing obstructive CAD in one in 100 patients. These findings may help inform decisions on testing, which will ultimately depend on the willingness to accept some diagnostic uncertainty.

Coronary artery calcium score as a gatekeeper for further testing in patients with low pretest probability of obstructive coronary artery disease: A cost-effectiveness analysis.

INTRODUCTION AND OBJECTIVES: Current guidelines recommend not routinely testing patients with chest pain and low pretest probability (PTP <15%) of obstructive coronary artery disease (CAD), but envisage the use of risk modifiers, such as coronary artery calcium score (CACS), to refine patient selection for testing. We aimed to assess the cost-effectiveness (CE) of three different testing strategies in this population: (A) defer testing; (B) perform CACS, withholding further testing if CACS=0, and proceeding to coronary CT angiography (CCTA) if CACS>0; (C) CCTA in all. METHODS: We developed a CE model using data from a two-center cross-sectional study of 1385 patients with non-acute chest pain and PTP <15% undergoing CACS followed by CCTA. Key input data included the prevalence of obstructive CAD on CCTA (10.3%), the proportion with CACS=0 (57%), and the negative predictive value of CACS for obstructive CAD on CCTA (98.1%). RESULTS: Not testing would correctly classify 89.7% of cases and at a cost of €121433 per 1000 patients. Using CACS as a gatekeeper for CCTA would correctly diagnose 98.9% of cases and cost €247116/1000 patients. Employing first-line CCTA would correctly classify all patients, at a cost of €271007/1000 diagnosed patients. The added cost for an additional correct diagnosis was €1366 for CACS±CCTA vs. no testing, and €2172 for CCTA vs. CACS±CCTA. CONCLUSIONS: CACS as a gatekeeper for further testing is cost-effective between a threshold of €1366 and €2172 per additional correct diagnosis. CCTA yields the most correct diagnoses and is cost-effective above a threshold of €2172.

The updated pre-test probability model of the 2019 ESC guidelines improves prediction of obstructive coronary artery disease.

INTRODUCTION AND OBJECTIVES: The 2019 ESC guidelines on chronic coronary syndromes updated the method for estimating the pre-test probability (PTP) of obstructive coronary artery disease (CAD). We aimed to compare the performance of the new PTP method against the 2013 prediction model in patients with stable chest pain undergoing coronary computed tomography angiography (CCTA) for suspected CAD. METHODS: We conducted a single-center cross-sectional study enrolling 320 consecutive patients undergoing CCTA for suspected CAD. Obstructive CAD was defined as any ≥50% luminal stenosis on CCTA. Whenever invasive coronary angiography was subsequently performed, patients were reclassified accordingly. The two PTP prediction models were assessed for calibration, discrimination and the ability to change the downstream diagnostic pathway. RESULTS: The observed prevalence of obstructive CAD was 16.3% (n=52). The 2013 prediction model significantly overestimated the likelihood of obstructive CAD (relative overestimation of 130%, p=0.005), while the updated 2019 method showed good calibration (relative underestimation of 6.5%, p=0.712). The two approaches showed similar discriminative power, with C-statistics of 0.73 (95% CI: 0.66-0.80) and 0.74 (95% CI: 0.66-0.81) for the 2013 and 2019 methods, respectively (p=0.933). Reclassification of PTP using the new method resulted in a net reclassification improvement of 0.10 (p=0.001). CONCLUSIONS: The updated 2019 prediction model provides a more accurate estimation of pre-test probabilities of obstructive CAD than the previous model. Adoption of this new score may improve disease prediction and influence the selection of non-invasive testing.

Diagnostic accuracy of computed tomography angiography for the exclusion of coronary artery disease in candidates for transcatheter aortic valve implantation.

Coronary CT angiography (CTA) is currently considered a reliable method to exclude obstructive coronary artery disease (CAD) before valvular heart surgery in patients with low pretest probability. However, its role in excluding obstructive CAD before transcatheter aortic valve implantation (TAVI) is less well established. Single-center retrospective study where patients with severe symptomatic aortic stenosis underwent both CTA and invasive coronary angiography (ICA) as part of TAVI planning. CTA exams were conducted on a 64-slice dual source scanner, with a median interval of 45 days to ICA (IQR 25-75 [13-82]). In both tests, obstructive CAD was defined as a ≥50% stenosis in an epicardial vessel ≥2 mm diameter. Per-patient, per-vessel and per-proximal segment analyses were conducted, excluding and including non-evaluable segments. The study included 200 patients (120 women, mean age 83 ± 6 years). The prevalence of obstructive CAD on ICA was 35.5% (n = 71). On a per-patient analysis (assuming non-evaluable segments as stenotic), CTA showed sensitivity of 100% (95% CI, 95-100%), specificity of 42% (95% CI, 33-51%), and positive and negative predictive values of 48% (95% CI, 44-51%) and 100% (95% CI, 92-100%), respectively. CTA was able to exclude obstructive CAD in 54 patients (27%), in whom ICA could have been safely withheld. Despite the high rate of inconclusive tests, pre-procedural CTA is able to safely exclude obstructive CAD in a significant proportion of patients undergoing TAVI, possibly avoiding the need for ICA in roughly one quarter of the cases.

Additional cardiac investigation prior to the introduction of the CAD-RADS classification in coronary computed tomography angiography reports.

INTRODUCTION: The CAD-RADSTM classification was recently introduced in an attempt to standardize coronary computed tomography angiography (CCTA) reports and to provide recommendations for further management. The aim of this study was to assess how additional cardiac investigations were being ordered before the introduction of the CAD-RADS classification in a tertiary hospital's CCTA reports. METHODS: We conducted a single-center retrospective analysis of 200 patients (103 women, mean age 59±13 years) who underwent CCTA for suspected or known coronary artery disease prior to the systematic introduction of the CAD-RADS classification in the reports. For each case, we assessed whether further cardiac investigation was requested after CCTA and what type of test was performed (functional testing, invasive coronary angiography or viability testing). RESULTS: The majority of patients (n=158; 79%) were classified as CAD-RADS 0-2. In patients with lower (0-2) or higher (4 or 5) scores, further testing was in accordance with CAD-RADS recommendations in 98% of cases (n=168). In patients with CAD-RADS 3 (intermediate stenosis), functional testing was requested as recommended in only 36% of cases (n=5), while 50% (n=7) proceeded directly to invasive coronary angiography. In patients in whom CCTA was non-diagnostic, most did not undergo further cardiac investigation. CONCLUSION: In patients with CAD-RADS classifications at the ends of the spectrum, additional cardiac investigation after CCTA was almost always in accordance with the recommendations. However, in patients with intermediate scores, invasive coronary angiography prevailed over functional testing.

Derivation and external validation of the SHIeLD score for predicting outcome in normotensive pulmonary embolism.

BACKGROUND: Identifying patients with normotensive pulmonary embolism (PE) who may benefit from thrombolysis remains challenging. We sought to develop and validate a score to predict 30-days PE-related mortality and/or rescue thrombolysis. METHODS: We retrospectively assessed 554 patients with normotensive PE. Independent predictors of the studied endpoint were identified from variables available at admission in the emergency department and were used to create a score. The model was validated in 308 patients from a separate hospital. RESULTS: A total of 64 patients died or needed rescue thrombolysis (44 in the derivation cohort). Four independent prognostic factors were identified: Shock index ≥ 1.0 (OR 3.33; 95% CI 1.40-7.93; P = 0.006), HypoxaemIa by the PaO2/FiO2 ratio (OR 0.92 per 10 units; 95% CI 0.88-0.97; P < 0.001), Lactate (OR 1.38 per mmol/L; 95% CI 1.09-1.75; P = 0.008) and cardiovascular Dysfunction (OR 5.67; 95% CI 2.60-12.33; P < 0.001) - SHIeLD score. In the development cohort, event rates for each risk tercile were 0.0%, 2.2%, and 21.6%. In the validation cohort, corresponding rates were 0.0%, 1.9%, and 14.3%. The C-statistic was 0.90 (95% CI 0.86-0.94, P < 0.001) in the derivation cohort and 0.82 (95% CI 0.75-0.89, P < 0.001) in the validation cohort. Decision curve analysis showed that the SHIeLD score is able to accurately identify more true positive cases than the European Society of Cardiology decision criteria. CONCLUSIONS: A risk score to predict 30-days PE-related mortality and/or rescue thrombolysis in patients with normotensive PE was developed and validated. This score may assist physicians in selecting patients for closer monitoring or aggressive treatment strategy.