Machine learning for prediction of all-cause mortality after transcatheter aortic valve implantation

AIMS

Prediction of adverse events in mid-term follow-up after transcatheter aortic valve implantation (TAVI) is challenging. We sought to develop and validate a machine learning model for prediction of 1-year all-cause mortality in patients who underwent TAVI and were discharged following the index procedure.

METHODS AND RESULTS

The model was developed on data of patients who underwent TAVI at a high-volume centre between January 2013 and March 2019. Machine learning by extreme gradient boosting was trained and tested with repeated 10-fold hold-out testing using 34 pre- and 25 peri-procedural clinical variables. External validation was performed on unseen data from two other independent high-volume TAVI centres. Six hundred four patients (43% men, 81 ± 5 years old, EuroSCORE II 4.8 [3.0-6.3]%) in the derivation and 823 patients (46% men, 82 ± 5 years old, EuroSCORE II 4.7 [2.9-6.0]%) in the validation cohort underwent TAVI and were discharged home following the index procedure. Over the 12 months of follow-up, 68 (11%) and 95 (12%) subjects died in the derivation and validation cohorts, respectively. In external validation, the machine learning model had an area under the receiver-operator curve of 0.82 (0.78-0.87) for prediction of 1-year all-cause mortality following hospital discharge after TAVI, which was superior to pre- and peri-procedural clinical variables including age 0.52 (0.46-0.59) and the EuroSCORE II 0.57 (0.51-0.64), P < 0.001 for a difference.

CONCLUSION

Machine learning based on readily available clinical data allows accurate prediction of 1-year all-cause mortality following a successful TAVI.

Influence of cusp morphology and sex on quantitative valve composition in severe aortic stenosis

AIMS

Aortic stenosis is characterized by fibrosis and calcification of the valve, with a higher proportion of fibrosis observed in women. Stenotic bicuspid aortic valves progress more rapidly than tricuspid valves, which may also influence the relative composition of the valve. We aimed to investigate the influence of cusp morphology on quantitative aortic valve composition quantified from contrast-enhanced computed tomography angiography in severe aortic stenosis.

METHODS AND RESULTS

Patients undergoing transcatheter aortic valve implantation with bicuspid and tricuspid valves were propensity matched 1:1 by age, sex, and comorbidities. Computed tomography angiograms were analysed using semi-automated software to quantify the fibrotic and calcific scores (volume/valve annular area) and the fibro-calcific ratio (fibrotic score/calcific score). The study population (n = 140) was elderly (76 ± 10 years, 62% male) and had a peak aortic jet velocity of 4.1 ± 0.7 m/s. Compared with those with tricuspid valves (n = 70), patients with bicuspid valves (n = 70) had higher fibrotic scores [204 (interquartile range 118-267) vs. 144 (99-208) mm3/cm2, P = 0.006] with similar calcific scores (P = 0.614). Women had greater fibrotic scores than men in bicuspid [224 (181-307) vs. 169 (109-247) mm3/cm2, P = 0.042] but not tricuspid valves (P = 0.232). Men had greater calcific scores than women in both bicuspid [203 (124-355) vs. 130 (70-182) mm3/cm2, P = 0.008] and tricuspid [177 (136-249) vs. 100 (62-150) mm3/cm2, P = 0.004] valves. Among both valve types, women had a greater fibro-calcific ratio compared with men [tricuspid 1.86 (0.94-2.56) vs. 0.86 (0.54-1.24), P = 0.001 and bicuspid 1.78 (1.21-2.90) vs. 0.74 (0.44-1.53), P = 0.001].

CONCLUSIONS

In severe aortic stenosis, bicuspid valves have proportionately more fibrosis than tricuspid valves, especially in women.

Impact of previous coronary artery revascularization on outcomes in patients undergoing transcatheter aortic valve implantation

Introduction

Coexistence of coronary artery disease (CAD) in patients with severe aortic stenosis (AS) referred for transcatheter aortic valve implantation (TAVI) raises questions regarding the safety and efficacy of TAVI in this subset of patients.

Aim

To evaluate the impact of previous coronary revascularization in terms of percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) on clinical outcomes after TAVI.

Material and methods

A total of 507 consecutive patients who underwent TAVI were divided into: non-revascularization (NR), post-PCI and post-CABG groups. The endpoints were established according to VARC-2 definitions.

Results

Patients with previous coronary revascularization (36.7% of the population) were younger, more often male and their EuroSCORE II risk evaluation was significantly higher (NR 7.9% vs. post-PCI 8.0% vs. post-CABG 20.5%, p < 0.0001). Patients after PCI or CABG prior to TAVI had similar 30-day all-cause mortality rates as those without coronary revascularization at baseline (NR vs. post-PCI vs. post-CABG: 8.1% vs. 5.5% vs. 6.8%, respectively; p = 0.6). There were no differences in 12-month all-cause mortality rates between groups (NR vs. post-PCI vs. post-CABG: 15.3% vs. 14.2% vs. 16.9%, respectively; log-rank p = 0.67). In the Cox proportional-hazards regression model, acute kidney injury stage 2-3 (HR = 3.7, 95% CI: 2.14-6.33; p < 0.001) and post-TAVI stroke (HR = 3.5, 95% CI: 1.57-7.8; p = 0.002) were independently correlated with 1-year mortality.

Conclusions

TAVI seems to be a safe and effective procedure for the treatment of severe AS in patients with previous coronary revascularization.

Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems

OBJECTIVE

We aimed to evaluate the effectiveness of utilizing artificial intelligence (AI) to quantify the extent of pneumonia from chest CT scans, and to determine its ability to predict clinical deterioration or mortality in patients admitted to the hospital with COVID-19 in comparison to semi-quantitative visual scoring systems.

METHODS

A deep-learning algorithm was utilized to quantify the pneumonia burden, while semi-quantitative pneumonia severity scores were estimated through visual means. The primary outcome was clinical deterioration, the composite end point including admission to the intensive care unit, need for invasive mechanical ventilation, or vasopressor therapy, as well as in-hospital death.

RESULTS

The final population comprised 743 patients (mean age 65  ±  17 years, 55% men), of whom 175 (23.5%) experienced clinical deterioration or death. The area under the receiver operating characteristic curve (AUC) for predicting the primary outcome was significantly higher for AI-assisted quantitative pneumonia burden (0.739, p = 0.021) compared with the visual lobar severity score (0.711, p < 0.001) and visual segmental severity score (0.722, p = 0.042). AI-assisted pneumonia assessment exhibited lower performance when applied for calculation of the lobar severity score (AUC of 0.723, p = 0.021). Time taken for AI-assisted quantification of pneumonia burden was lower (38 ± 10 s) compared to that of visual lobar (328 ± 54 s, p < 0.001) and segmental (698 ± 147 s, p < 0.001) severity scores.

CONCLUSION

Utilizing AI-assisted quantification of pneumonia burden from chest CT scans offers a more accurate prediction of clinical deterioration in patients with COVID-19 compared to semi-quantitative severity scores, while requiring only a fraction of the analysis time.

ADVANCES IN KNOWLEDGE

Quantitative pneumonia burden assessed using AI demonstrated higher performance for predicting clinical deterioration compared to current semi-quantitative scoring systems. Such an AI system has the potential to be applied for image-based triage of COVID-19 patients in clinical practice.

Monocyte-to-lymphocyte ratio correlates with parathyroid hormone concentration in patients with severe symptomatic aortic stenosis

PURPOSE

The normal healthy valve is devoid of inflammatory cells, however background of aortic stenosis (AS) may include inflammatory processes. Moreover, the link between hyperparathyroidism and heart failure is postulated. Simple whole blood analysis with indices is a beneficial tool in cardiovascular diseases' assessment. The purpose of the study was to evaluate correlation between parathyroid hormone (PTH) and simple blood parameters in severe AS.

MATERIAL AND METHODS

The study included 62 patients with severe AS. Patients with inflammatory or autoimmune co-morbidities were excluded. Blood samples were collected, and clinical and demographic data were analyzed.

RESULTS

The final study group comprised 55 patients (31 females, 56.4%; mean age 77.13 (SD 6.76)). In 23 patients (41.8%), PTH concentration was markedly increased. The study group was divided into two subgroups according to the PTH concentration. Patients from both groups did not differ significantly in terms of age and co-morbidities. PTH concentration correlated positively with monocyte-lymphocyte ratio (MLR) (p ​= ​0.008, Spearman rho 0.356) and platelet-lymphocyte ratio (PLR) (p ​= ​0.047, Spearman rho 0.269), creatinine level (p ​= ​0.001, Spearman rho 0.425) and glomerular filtration rate (GFR-MDRD) (p ​= ​0.009, Spearman rho -0.349). The multivariable logistic regression with backward analysis revealed MLR (p ​= ​0.029) and GFR (p ​= ​0.028) as independent significant predictors of abnormal PTH values. The receiver operator characteristics (ROC) curve was performed for the model of MLR and GFR-MDRD (AUC ​= ​0.777), yielding the sensitivity of 60.9% and specificity of 90.6%.

CONCLUSIONS

PTH concentration correlates with monocyte-to-lymphocyte and platelet-to-lymphocyte ratios in calcified AS.

Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trial

BACKGROUND

Positron emission tomography (PET) is the clinical gold standard for quantifying myocardial blood flow (MBF). Pericoronary adipose tissue (PCAT) attenuation may detect vascular inflammation indirectly. We examined the relationship between MBF by PET and plaque burden and PCAT on coronary CT angiography (CCTA).

METHODS

This post hoc analysis of the PACIFIC trial included 208 patients with suspected coronary artery disease (CAD) who underwent [15O]H2O PET and CCTA. Low-attenuation plaque (LAP, < 30HU), non-calcified plaque (NCP), and PCAT attenuation were measured by CCTA.

RESULTS

In 582 vessels, 211 (36.3%) had impaired per-vessel hyperemic MBF (≤ 2.30 mL/min/g). In multivariable analysis, LAP burden was independently and consistently associated with impaired hyperemic MBF (P = 0.016); over NCP burden (P = 0.997). Addition of LAP burden improved predictive performance for impaired hyperemic MBF from a model with CAD severity and calcified plaque burden (P < 0.001). There was no correlation between PCAT attenuation and hyperemic MBF (r = - 0.11), and PCAT attenuation was not associated with impaired hyperemic MBF in univariable or multivariable analysis of all vessels (P > 0.1).

CONCLUSION

In patients with stable CAD, LAP burden was independently associated with impaired hyperemic MBF and a stronger predictor of impaired hyperemic MBF than NCP burden. There was no association between PCAT attenuation and hyperemic MBF.

Advanced Cardiac Imaging in the Assessment of Aortic Stenosis

Aortic stenosis is the most common form of valve disease in the Western world and a major healthcare burden. Although echocardiography remains the central modality for the diagnosis and assessment of aortic stenosis, recently, advanced cardiac imaging with cardiovascular magnetic resonance, computed tomography, and positron emission tomography have provided invaluable pathological insights that may guide the personalized management of the disease. In this review, we discuss applications of these novel non-invasive imaging modalities for establishing the diagnosis, monitoring disease progression, and eventually planning the invasive treatment of aortic stenosis.

Valve-in-valve transcatheter transfemoral mitral valve implantation (ViV-TMVI): Characteristics and early results from nationwide registry

BACKGROUND

Valve-in-valve transcatheter transfemoral mitral valve implantation (ViV-TMVI) is an emerging treatment alternative to reoperation in high surgical risk patients with a failed mitral bioprostheses.

AIM

To describe characteristics and evaluate 30-day outcomes of ViV-TMVI in the Polish population.

METHODS

Nationwide registry was initiated to collect data of all patients with failed mitral bioprosthesis undergoing ViV-TMVI in Poland. This study presents 30-days clinical and echocardiographic follow-up.

RESULTS

Overall, 27 ViV-TMVI were performed in 8 centers until May 2022 (85% since 2020). Mean (standard deviation [SD]) age was 73 (11.6) years with the median (interquartile range [IQR]) STS score of 5.3% (4.3%-14.3%). Mean (SD) time between surgical implantation and ViV-TMVI was 8.2 (3.2) years. Failed Hancock II (29%) and Perimount Magna (22%) were most frequently treated. Mechanisms of failure were equally often pure mitral regurgitation or stenosis (both 37%) with mixed etiology in 26%. Balloon-expandable Sapien 3/Ultra were used in all but 1 patient. Technical success was 96.3% (1 patient required additional prosthesis). Mean (SD) transvalvular mitral gradient reached 6.7 (2.2) mm Hg and mitral valve area was 1.8 (0.4) cm². None of the patients had moderate or severe mitral regurgitation with only 14.8% graded as mild. In 92.6% device success (2 patients had mean gradient ≥10 mm Hg) and in 85.6% procedural success was present. There were no deaths, cerebrovascular events or need for mitral valve surgery during 30-day follow-up.

CONCLUSIONS

In short-term observation ViV-TMVI is safe and effective alternative for patients with failed mitral bioprosthesis at high surgical risk of re-operation. Longer observations on larger sample are warranted.

Sex differences in computed tomography angiography-derived coronary plaque burden in relation to invasive fractional flow reserve

BACKGROUND

Distinct sex-related differences exist in coronary artery plaque burden and distribution. We aimed to explore sex differences in quantitative plaque burden by coronary CT angiography (CCTA) in relation to ischemia by invasive fractional flow reserve (FFR).

METHODS

This post-hoc analysis of the PACIFIC trial included 581 vessels in 203 patients (mean age 58.1 ​± ​8.7 years, 63.5% male) who underwent CCTA and per-vessel invasive FFR. Quantitative assessment of total, calcified, non-calcified, and low-density non-calcified plaque burden were performed using semiautomated software. Significant ischemia was defined as invasive FFR ≤0.8.

RESULTS

The per-vessel frequency of ischemia was higher in men than women (33.5% vs. 7.5%, p ​< ​0.001). Women had a smaller burden of all plaque subtypes (all p ​< ​0.01). There was no sex difference on total, calcified, or non-calcified plaque burdens in vessels with ischemia; only low-density non-calcified plaque burden was significantly lower in women (beta: -0.183, p ​= ​0.035). The burdens of all plaque subtypes were independently associated with ischemia in both men and women (For total plaque burden (5% increase): Men, OR: 1.15, 95%CI: 1.06-1.24, p ​= ​0.001; Women, OR: 1.96, 95%CI: 1.11-3.46, p ​= ​0.02). No significant interaction existed between sex and total plaque burden for predicting ischemia (interaction p ​= ​0.108). The addition of quantitative plaque burdens to stenosis severity and adverse plaque characteristics improved the discrimination of ischemia in both men and women.

CONCLUSIONS

In symptomatic patients with suspected CAD, women have a lower CCTA-derived burden of all plaque subtypes compared to men. Quantitative plaque burden provides independent and incremental predictive value for ischemia, irrespective of sex.

Nationwide experience with transcarotid transcatheter aortic valve implantation: Insights from the POL-CAROTID registry

BACKGROUND:

To investigate the feasibility and safety of transcarotid (TC) access for transcatheter aortic valve implantation (TAVI) in comparison to the transfemoral (TF) approach in a multicenter setting.

METHODS:

A total of 41 patients, treated between December 2014 and December 2018, were retrospectively reported to the Polish Registry of Common Carotid Artery Access for TAVI (POL-CAROTID). The median follow-up time was 619 (365 - 944) days and Valve Academic Research Consortium-2 (VARC-2) definitions were applied. Clinical outcomes were compared with 41 propensity-matched TF-TAVI patients.

RESULTS:

The mean (SD) patients' age was 78.0 (7.2) years and 29 patients (70.7%) were men. Prohibitive iliofemoral anatomy and/or obesity (46.3%) and/or the presence of stent graft in the abdominal aorta (31.7%) were the most common indications for TC-TAVI. Device success for TC-TAVI was comparable with matched TF-TAVI group (90.2% vs 95.3%, P=0.396) and no periprocedural mortality was observed. Moreover, early safety was similar between the two groups (92.7% vs 95.3%, respectively, log-rank P=0.658) with only 1 case of non-disabling stroke during the first month after TC-TAVI. Consequently, no cerebrovascular events were observed in the mid-term, and the clinical efficacy of TC-TAVI corresponded well with TF-TAVI (90.2% vs 92.7%, log-rank P=0.716). A total of 4 (9.8%) deaths were noted in the TC-TAVI cohort in comparison to 3 (7.3%) in the TF-TAVI group.

CONCLUSIONS:

The results of the study indicated that the first cohort of transcarotid transcatheter heart valves of second-generation implantations in Poland were associated with a similar prognosis to TF-TAVI with regard to safety and feasibility. TC access may be considered an optimal alternative for patients, in whom the TF approach is precluded.

Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow

BACKGROUND

A pathophysiological interplay exists between plaque morphology and coronary physiology. Machine learning (ML) is increasingly being applied to coronary computed tomography angiography (CCTA) for cardiovascular risk stratification. We sought to assess the performance of a ML score integrating CCTA-based quantitative plaque features for predicting vessel-specific ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by positron emission tomography (PET).

METHODS

This post-hoc analysis of the PACIFIC trial (Prospective Comparison of Cardiac Positron Emission Tomography/Computed Tomography [CT]' Single Photon Emission Computed Tomography/CT Perfusion Imaging and CT Coronary Angiography with Invasive Coronary Angiography) included 208 patients with suspected coronary artery disease who prospectively underwent CCTA' [15O]H2O PET, and invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. An ML algorithm trained on the prospective NXT trial (484 vessels) was used to develop a ML score for the prediction of ischemia (FFR≤0.80), which was then evaluated in 581 vessels from the PACIFIC trial. Thereafter, the ML score was applied for predicting impaired hyperemic MBF (≤2.30 mL/min per g) from corresponding PET scans. The performance of the ML score was compared with CCTA reads and noninvasive FFR derived from CCTA (FFRCT).

RESULTS

One hundred thirty-nine (23.9%) vessels had FFR-defined ischemia, and 195 (33.6%) vessels had impaired hyperemic MBF. For the prediction of FFR-defined ischemia, the ML score yielded an area under the receiver-operating characteristic curve of 0.92, which was significantly higher than that of visual stenosis grade (0.84; P<0.001) and comparable with that of FFRCT (0.93; P=0.34). Quantitative percent diameter stenosis and low-density noncalcified plaque volume had the greatest ML feature importance for predicting FFR-defined ischemia. When applied for impaired MBF prediction, the ML score exhibited an area under the receiver-operating characteristic curve of 0.80; significantly higher than visual stenosis grade (area under the receiver-operating characteristic curve 0.74; P=0.02) and comparable with FFRCT (area under the receiver-operating characteristic curve 0.77; P=0.16).

CONCLUSIONS

An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and impaired MBF by PET, performing superiorly to standard CCTA stenosis evaluation and comparably to FFRCT.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks

Purpose: Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease 2019 (COVID-19) patients but are not part of clinical routine because the required manual segmentation of lung lesions is prohibitively time consuming. We aim to automatically segment ground-glass opacities and high opacities (comprising consolidation and pleural effusion). Approach: We propose a new fully automated deep-learning framework for fast multi-class segmentation of lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional long short-term memory (ConvLSTM) networks. Utilizing the expert annotations, model training was performed using five-fold cross-validation to segment COVID-19 lesions. The performance of the method was evaluated on CT datasets from 197 patients with a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2, 68 unseen test cases, and 695 independent controls. Results: Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score of 0.89 ± 0.07 ; excellent correlations of 0.93 and 0.98 for ground-glass opacity (GGO) and high opacity volumes, respectively, were obtained. In the external testing set of 68 patients, we observed a Dice score of 0.89 ± 0.06 as well as excellent correlations of 0.99 and 0.98 for GGO and high opacity volumes, respectively. Computations for a CT scan comprising 120 slices were performed under 3 s on a computer equipped with an NVIDIA TITAN RTX GPU. Diagnostically, the automated quantification of the lung burden % discriminate COVID-19 patients from controls with an area under the receiver operating curve of 0.96 (0.95-0.98). Conclusions: Our method allows for the rapid fully automated quantitative measurement of the pneumonia burden from CT, which can be used to rapidly assess the severity of COVID-19 pneumonia on chest CT.

Pericoronary Adipose Tissue Attenuation, Low-Attenuation Plaque Burden, and 5-Year Risk of Myocardial Infarction

BACKGROUND

Pericoronary adipose tissue (PCAT) attenuation and low-attenuation noncalcified plaque (LAP) burden can both predict outcomes.

OBJECTIVES

This study sought to assess the relative and additive values of PCAT attenuation and LAP to predict future risk of myocardial infarction.

METHODS

In a post hoc analysis of the multicenter SCOT-HEART (Scottish Computed Tomography of the Heart) trial, the authors investigated the relationships between the future risk of fatal or nonfatal myocardial infarction and PCAT attenuation measured from coronary computed tomography angiography (CTA) using multivariable Cox regression models including plaque burden, obstructive coronary disease, and cardiac risk score (incorporating age, sex, diabetes, smoking, hypertension, hyperlipidemia, and family history).

RESULTS

In 1,697 evaluable participants (age: 58 ± 10 years), there were 37 myocardial infarctions after a median follow-up of 4.7 years. Mean PCAT was -76 ± 8 HU and median LAP burden was 4.20% (IQR: 0%-6.86%). PCAT attenuation of the right coronary artery (RCA) was predictive of myocardial infarction (HR: 1.55; P = 0.017, per 1 SD increment) with an optimum threshold of -70.5 HU (HR: 2.45; P = 0.01). In multivariable analysis, adding PCAT-RCA of ≥-70.5 HU to an LAP burden of >4% (the optimum threshold for future myocardial infarction; HR: 4.87; P < 0.0001) led to improved prediction of future myocardial infarction (HR: 11.7; P < 0.0001). LAP burden showed higher area under the curve compared to PCAT attenuation for the prediction of myocardial infarction (AUC = 0.71 [95% CI: 0.62-0.80] vs AUC = 0.64 [95% CI: 0.54-0.74]; P < 0.001), with increased area under the curve when the 2 metrics are combined (AUC = 0.75 [95% CI: 0.65-0.85]; P = 0.037).

CONCLUSION

Coronary CTA-defined LAP burden and PCAT attenuation have marked and complementary predictive value for the risk of fatal or nonfatal myocardial infarction.

Pulmonary artery systolic pressure at 1-month predicts 1-year survival after transcatheter aortic valve implantation

BACKGROUND

Pulmonary hypertension related to left ventricle heart disease is a common finding in patients with severe aortic stenosis treated with transcatheter aortic valve implantation (TAVI) and is associated with a higher mortality rate.

AIMS

The study aimed to analyze the influence of pulmonary artery systolic pressure (PASP) changes after TAVI on long-term survival.

METHODS

TAVI was performed in 362 patients between January 2013 and December 2018. The study group comprised 210 patients who underwent a detailed 1-month follow-up.

RESULTS

At 1-month, 142 had a stable or decreased PASP value (Group 1), while in 68 patients an increase was observed (Group 2). During 1-year follow-up, 20 patients died (9.5%), 9 in Group 1 and 11 in Group 2 (P = 0.02). The receiver operating characteristic (ROC) curve analysis (area under the curve [AUC], 0.750) revealed a significant value of 1-month measurement for 1-year mortality prediction. The cutoff for the PASP value predictive of mortality was ≤41 mm Hg. A Kaplan-Meier analysis showed significantly higher mortality in patients without a 1-month PASP decrease. In the multivariable analysis, PASP measured at 1-month after TAVI (hazard ratio, 1.040; 95% confidence interval, 1.019-1.062; P < 0.001) was an independent predictor of 1-year mortality. Each 1 mm Hg increase in PASP predicts a 4% increase in the risk of death.

CONCLUSION

Decreased or stable value of PASP at 1-month follow-up may predict better 1-year survival after TAVI, while each 1 mm Hg increase in PASP confers a 4% greater risk of 1-year mortality.

Neutrophil-to-lymphocyte ratio as a predictor of inflammatory response in patients with acute kidney injury after transcatheter aortic valve implantation

BACKGROUND

Persistent inflammatory response after transcatheter aortic valve implantation (TAVI) is one of the possible causes of early and mid-term postprocedural adverse events.

OBJECTIVES

To establish the predictive role of whole blood parameters on inflammatory response characteristics within a 1-year follow-up.

MATERIAL AND METHODS

The study group comprised 163 consecutive patients (52.1% females), mean age 78.6 (±6.6) years (± standard deviation (SD)) who underwent TAVI and completed 1-year follow-up on-site examinations. Patients were retrospectively divided into acute kidney injury (AKI) and non-AKI subgroups. Clinical and laboratory data were collected. In-hospital and follow-up outcomes were assessed.

RESULTS

The clinical and procedural details did not show significant differences between AKI and non-AKI groups. Neutrophil-to-lymphocyte ratio (NLR) decreased from baseline to measurement after 1 year with a statistically significant decline in the whole study population and non-AKI subgroup (both p = 0.005). The baseline NLR cutoff value of 4.2 for the non-AKI group ((area under the curve (AUC) = 0.718, p < 0.0001; sensitivity 46.27%, specificity 92.31%) and of 3.8 for the AKI group (AUC = 0.673, p = 0.0174; sensitivity 59.25%, specificity 84%) had prognostic properties for persistent NLR elevation.

CONCLUSIONS

The NLR decreases after TAVI, and this phenomenon is more evident in patients without AKI. Furthermore, baseline NLR cutoff values may be considered predictors of persistence of inflammatory response.

Radiomorphological signs and clinical severity of SARS-CoV-2 lineage B.1.1.7

Objective

We aimed to assess the differences in the severity and chest-CT radiomorphological signs of SARS-CoV-2 B.1.1.7 and non-B.1.1.7 variants.

Methods

We collected clinical data of consecutive patients with laboratory-confirmed COVID-19 and chest-CT imaging who were admitted to the Emergency Department between September 1- November 13, 2020 (non-B.1.1.7 cases) and March 1-March 18, 2021 (B.1.1.7 cases). We also examined the differences in the severity and radiomorphological features associated with COVID-19 pneumonia. Total pneumonia burden (%), mean attenuation of ground-glass opacities and consolidation were quantified using deep-learning research software.

Results

The final population comprised 500 B.1.1.7 and 500 non-B.1.1.7 cases. Patients with B.1.1.7 infection were younger (58.5 ± 15.6 vs 64.8 ± 17.3; p < .001) and had less comorbidities. Total pneumonia burden was higher in the B.1.1.7 patient group (16.1% [interquartile range (IQR):6.0-34.2%] vs 6.6% [IQR:1.2-18.3%]; p < .001). In the age-specific analysis, in patients <60 years B.1.1.7 pneumonia had increased consolidation burden (0.1% [IQR:0.0-0.7%] vs 0.1% [IQR:0.0-0.2%]; p < .001), and severe COVID-19 was more prevalent (11.5% vs  4.9%; p = .032). Mortality rate was similar in all age groups.

Conclusion

Despite B.1.1.7 patients were younger and had fewer comorbidities, they experienced more severe disease than non-B.1.1.7 patients, however, the risk of death was the same between the two groups.

Advances in knowledge

Our study provides data on deep-learning based quantitative lung lesion burden and clinical outcomes of patients infected by B.1.1.7 VOC. Our findings might serve as a model for later investigations, as new variants are emerging across the globe.

Bypass Grafting and Native Coronary Artery Disease Activity

OBJECTIVES

The aim of this study was to describe the potential of 18F-sodium fluoride (18F-NaF) positron emission tomography (PET) to identify graft vasculopathy and to investigate the influence of coronary artery bypass graft (CABG) surgery on native coronary artery disease activity and progression.

BACKGROUND

As well as developing graft vasculopathy, CABGs have been proposed to accelerate native coronary atherosclerosis.

METHODS

Patients with established coronary artery disease underwent baseline 18F-NaF PET, coronary artery calcium scoring, coronary computed tomographic angiography, and 1-year repeat coronary artery calcium scoring. Whole-vessel coronary microcalcification activity (CMA) on 18F-NaF PET and change in calcium scores were quantified in patients with and without CABG surgery.

RESULTS

Among 293 participants (mean age 65 ± 9 years, 84% men), 48 (16%) underwent CABG surgery 2.7 years [IQR: 1.4-10.4 years] previously. Although all arterial and the majority (120 of 128 [94%]) of vein grafts showed no 18F-NaF uptake, 8 saphenous vein grafts in 7 subjects had detectable CMA. Bypassed native coronary arteries had 3 times higher CMA values (2.1 [IQR: 0.4-7.5] vs 0.6 [IQR: 0-2.7]; P < 0.001) and greater progression of 1-year calcium scores (118 Agatston unit [IQR: 48-194 Agatston unit] vs 69 [IQR: 21-142 Agatston unit]; P = 0.01) compared with patients who had not undergone CABG, an effect confined largely to native coronary plaques proximal to the graft anastomosis. In sensitivity analysis, bypassed native coronary arteries had higher CMA (2.0 [IQR: 0.4-7.5] vs 0.8 [IQR: 0.3-3.2]; P < 0.001) and faster disease progression (24% [IQR: 16%-43%] vs 8% [IQR: 0%-24%]; P = 0.002) than matched patients (n = 48) with comparable burdens of coronary artery disease and cardiovascular comorbidities in the absence of bypass grafting.

CONCLUSIONS

Native coronary arteries that have been bypassed demonstrate increased disease activity and more rapid disease progression than nonbypassed arteries, an observation that appears independent of baseline atherosclerotic plaque burden. Microcalcification activity is not a dominant feature of graft vasculopathy.

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study

BACKGROUND

Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of plaque volume and stenosis severity.

METHODS

This international, multicentre study included nine cohorts of patients undergoing CCTA at 11 sites, who were assigned into training and test sets. Data were retrospectively collected on patients with a wide range of clinical presentations of coronary artery disease who underwent CCTA between Nov 18, 2010, and Jan 25, 2019. A novel deep learning convolutional neural network was trained to segment coronary plaque in 921 patients (5045 lesions). The deep learning network was then applied to an independent test set, which included an external validation cohort of 175 patients (1081 lesions) and 50 patients (84 lesions) assessed by intravascular ultrasound within 1 month of CCTA. We evaluated the prognostic value of deep learning-based plaque measurements for fatal or non-fatal myocardial infarction (our primary outcome) in 1611 patients from the prospective SCOT-HEART trial, assessed as dichotomous variables using multivariable Cox regression analysis, with adjustment for the ASSIGN clinical risk score.

FINDINGS

In the overall test set, there was excellent or good agreement, respectively, between deep learning and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0·964) and percent diameter stenosis (ICC 0·879; both p<0·0001). When compared with intravascular ultrasound, there was excellent agreement for deep learning total plaque volume (ICC 0·949) and minimal luminal area (ICC 0·904). The mean per-patient deep learning plaque analysis time was 5·65 s (SD 1·87) versus 25·66 min (6·79) taken by experts. Over a median follow-up of 4·7 years (IQR 4·0-5·7), myocardial infarction occurred in 41 (2·5%) of 1611 patients from the SCOT-HEART trial. A deep learning-based total plaque volume of 238·5 mm3 or higher was associated with an increased risk of myocardial infarction (hazard ratio [HR] 5·36, 95% CI 1·70-16·86; p=0·0042) after adjustment for the presence of deep learning-based obstructive stenosis (HR 2·49, 1·07-5·50; p=0·0089) and the ASSIGN clinical risk score (HR 1·01, 0·99-1·04; p=0·35).

INTERPRETATION

Our novel, externally validated deep learning system provides rapid measurements of plaque volume and stenosis severity from CCTA that agree closely with expert readers and intravascular ultrasound, and could have prognostic value for future myocardial infarction.

FUNDING

National Heart, Lung, and Blood Institute and the Miriam & Sheldon G Adelson Medical Research Foundation.

Machine Learning with 18F-Sodium Fluoride PET and Quantitative Plaque Analysis on CT Angiography for the Future Risk of Myocardial Infarction

Coronary 18F-sodium fluoride (18F-NaF) PET and CT angiography-based quantitative plaque analysis have shown promise in refining risk stratification in patients with coronary artery disease. We combined both of these novel imaging approaches to develop an optimal machine-learning model for the future risk of myocardial infarction in patients with stable coronary disease. Methods: Patients with known coronary artery disease underwent coronary 18F-NaF PET and CT angiography on a hybrid PET/CT scanner. Machine-learning by extreme gradient boosting was trained using clinical data, CT quantitative plaque analysis, measures and 18F-NaF PET, and it was tested using repeated 10-fold hold-out testing. Results: Among 293 study participants (65 ± 9 y; 84% male), 22 subjects experienced a myocardial infarction over the 53 (40-59) months of follow-up. On univariable receiver-operator-curve analysis, only 18F-NaF coronary uptake emerged as a predictor of myocardial infarction (c-statistic 0.76, 95% CI 0.68-0.83). When incorporated into machine-learning models, clinical characteristics showed limited predictive performance (c-statistic 0.64, 95% CI 0.53-0.76) and were outperformed by a quantitative plaque analysis-based machine-learning model (c-statistic 0.72, 95% CI 0.60-0.84). After inclusion of all available data (clinical, quantitative plaque and 18F-NaF PET), we achieved a substantial improvement (P = 0.008 versus 18F-NaF PET alone) in the model performance (c-statistic 0.85, 95% CI 0.79-0.91). Conclusion: Both 18F-NaF uptake and quantitative plaque analysis measures are additive and strong predictors of outcome in patients with established coronary artery disease. Optimal risk stratification can be achieved by combining clinical data with these approaches in a machine-learning model.

Transcatheter aortic valve-in-valve implantation for failed surgical bioprostheses: results from Polish Transcatheter Aortic Valve-in-Valve Implantation (ViV-TAVI) Registry

INTRODUCTION

Transcatheter aortic valve-in-valve implantation (ViV-TAVI) emerged recently as an alternative to re-do surgery for patients with failed surgical aortic valve (SAV).

OBJECTIVES

To evaluate the safety and efficacy of transcatheter aortic valves (TAV) in failed SAV in Poland.

PATIENTS AND METHODS

Data was acquired using a nationwide, multicenter (n=14) Polish Transcatheter Aortic Valve-in-Valve Implantation (ViV-TAVI) Registry (ClinicalTrials.gov Identifier, NCT03361046) with online form collection and 1-year follow-up.

RESULTS

ViV-TAVI procedures (n=130) constituted 1.9% of all TAVI in Poland with increasing numbers since 2018 (n=59, 45% of all). Hancock II® (21%), Freestyle® (13%), and homograft (11.5%) were identified as the most frequently treated SAV's with self-expanding, supra-annular Corevalve/Evolut® TAV used in the majority of cases (76%). Average post-procedural pressure gradient (average PG) >20 mmHg was found in 21% and 1-year all-cause mortality was 10.8%. SAV stenosis compared to regurgitation/mixed disease was associated with higher average (16, IQR 13.5 - 22.5 vs 14.5, IQR 10-19 mmHg, p=0.004) whereas implantation of supra-annular TAV resulted in lower average PG (14, IQR 10.5-20 vs. intra-annular 19, IQR 16-26 mmHg, P=0.004). After introduction of 2nd generation TAV, shorter procedure time (120, IQR 80-165 min. vs. 135, IQR 108-200 min., P=0.04), less frequent need for additional TAV (2% vs. 10%, P=0.04) and better 1-year freedrom from cardiovascular deaths (95% vs. 82.8%, hazard ratio 0.25, 95% confidence intervals 0.17-0.88, P=0.03) was observed vs. 1st generation.

CONCLUSIONS

Transcatheter treatment of failed SAV is becoming more frequent, showing the best hemodynamic effect with the use of supra-annular TAV and improved procedural as well as clinical results with the introduction of 2nd generation TAV.

Pericoronary adipose tissue attenuation, low-attenuation plaque burden and 5-year risk of myocardial infarction

Introduction

Pericoronary adipose tissue (PCAT) attenuation has emerged as a surrogate marker of pericoronary inflammation. To date, no studies have compared the impact of pericoronary adipose tissue (PCAT) attenuation and quantitative plaque burden on cardiac outcomes.

Purpose

We aimed to establish the relative merits of these approaches to risk prediction and hypothesised that the combination of PCAT attenuation and quantitative plaque burden measures could provide additive and improved prediction of myocardial infarction in patients with stable chest pain.

Methods

In a post-hoc analysis of a randomized controlled trial, we investigated the association between the future risk of fatal or non-fatal myocardial infarction and PCAT attenuation measured from CT coronary angiography using multivariable Cox regression models including plaque burden, obstructive coronary disease and cardiac risk score (incorporating age, sex, diabetes, smoking, hypertension, hyperlipidaemia and family history of cardiovascular disease).

Results

In 1697 evaluable participants (mean age 58±10 years), there were 37 myocardial infarctions after a median follow-up of 4.7 [interquartile interval, 4.0–5.7] years. Median low-attenuation plaque burden was 4.20 [0–6.86] % and mean PCAT −76±8 Hounsfield units (HU).

PCAT attenuation of the right coronary artery (RCA) was predictive of myocardial infarction (hazard ratio [HR] 1.55, 95% CI 1.08–2.22; p=0.017, per 1 standard deviation increment) with an optimum threshold of −70.5 HU [Hazards ratio (HR) 2.45, 95% CI 1.2–4.9; p=0.01]. Univariable analysis also identified the burden of non-calcified, low-attenuation and calcified plaque as well as Agatston coronary calcium score, presence of obstructive coronary artery disease and cardiovascular risk score were predictors of myocardial infarction (Figure 1). In multivariable analysis, only the low-attenuation plaque burden (HR 1.80, 95% CI 1.16 to 2.81, p=0.011, per doubling) and PCAT-RCA (HR 1.47 95%1.02 to 2.13, p=0.040, per standard deviation increment) remained predictors of myocardial infarction (Figure 1).

In multivariable analysis, adding PCAT-RCA ≥-70.5 HU to low-attenuation plaque burden &gt;4% (optimum threshold for future myocardial infarction; HR = 4.87, 95% CI 2.03–11.78; p&lt;0.0001) led to improved prediction of future myocardial infarction (HR 11.7, 95% CI 3.3–40.9; p&lt;0.0001); Figure 2. In ROC analysis, integration of PCAT-RCA attenuation and LAP burden, increased the prediction for myocardial infarction compared to LAP alone (ΔAUC=0.04; p=0.01).

Conclusion

CT coronary angiography defined PCAT attenuation and low-attenuation plaque have marked and additive predictive value for the risk of fatal or non-fatal myocardial infarction.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): The Chief Scientist Office of the Scottish Government Health and Social Care Directorates, British Heart Foundation, National Institute of Health/National Heart, Lung, and Blood Institute grant

Non-calcific aortic tissue quantified from computed tomography angiography improves diagnosis and prognostication of patients referred for transcatheter aortic valve implantation

AIMS

We aimed to investigate the role of aortic valve tissue composition from quantitative cardiac computed tomography angiography (CTA) in patients with severe aortic stenosis (AS) for the differentiation of disease subtypes and prognostication after transcatheter aortic valve implantation (TAVI).

METHODS AND RESULTS

Our study included 447 consecutive AS patients from six high-volume centres reporting to a prospective nationwide registry of TAVI procedures (POL-TAVI), who underwent cardiac CTA before TAVI, and 224 matched controls with normal aortic valves. Components of aortic valve tissue were identified using semi-automated software as calcific and non-calcific. Volumes of each tissue component and composition [(tissue component volume/total tissue volume) × 100%] were quantified. Relationship of aortic valve composition with clinical outcomes post-TAVI was evaluated using Valve Academic Research Consortium (VARC)-2 definitions.High-gradient (HG) AS patients had significantly higher aortic tissue volume compared to low-flow low-gradient (LFLG)-AS (1672.7 vs. 1395.3 mm3, P < 0.001) as well as controls (509.9 mm3, P < 0.001), but increased non-calcific tissue was observed in LFLG compared to HG patients (1063.6 vs. 860.2 mm3, P < 0.001). Predictive value of aortic valve calcium score [area under the curve (AUC) 0.989, 95% confidence interval (CI): 0.981-0.996] for severe AS was improved after addition of non-calcific tissue volume (AUC 0.995, 95% CI: 0.991-0.999, P = 0.011). In the multivariable analysis of clinical and quantitative computed tomography parameters of aortic valve tissue, non-calcific tissue volume [odds ratio (OR) 5.2, 95% CI 1.8-15.4, P = 0.003] and history of stroke (OR 2.6, 95% CI 1.1-6.5, P = 0.037) were independent predictors of 30-day major adverse cardiovascular event (MACE).

CONCLUSION

Quantitative CTA assessment of aortic valve tissue volume and composition can improve detection of severe AS, differentiation between HG and LFLG-AS in patients referred for TAVI as well as prediction of 30-day MACEs post-TAVI, over the current clinical standard.

Protamine sulfate during transcatheter aortic valve implantation (PS TAVI) - a single-center, single-blind, randomized placebo-controlled trial

BACKGROUND

Bleeding complications after transcatheter aortic valve implantation (TAVI) negatively affect the post-procedural prognosis. Routine use of protamine sulfate (PS) to reverse unfractionated heparin after TAVI was never assessed in a randomized controlled trial.

AIMS

The aim of this study was to assess the impact of PS on bleeding complications after TAVI.

METHODS

Between December 2016 and July 2020 311 patients qualified to TAVI in one academic center were screened. Patients that met the inclusion criteria were randomized to either PS or normal saline administration at the moment of optimal valve deployment. Baseline, procedural and follow-up data up to 30 days were collected and analyzed. The primary endpoint (PE) was a composite of life-threatening and major bleeding according to Valve Academic Research Consortium within 48 hours after the procedure.

RESULTS

Overall, 100 patients (48 males, median age 82 years) met the inclusion criteria and were included in the study. Forty-seven subjects (47%) were randomized to PS. The primary endpoint occurred in the 29% of the study population. Despite a numerically lower rates of PE in patients randomized to PS, a statistical significance was not reached (21% in the PS group and 36% in the placebo group; odds ratio [OR], 0.48; 95% confidence intervals [CI] 0.2-1.2; P = 0.11). There were no significant differences in secondary endpoints.

CONCLUSIONS

Routine protamine sulfate administration did not significantly decrease the rate of major and life-threatening bleeding complications after TAVI. Larger studies are required to assess the impact of routine PS use.

Temporal trends of transcatheter aortic valve implantation in high-volume academic center over 10 years

BACKGROUND

Indications for transcatheter aortic valve implantation (TAVI) have gradually expanded since its introduction.

AIM

The aim was to analyze temporal trends in TAVI characteristics based on experience of high-volume academic center over the period of 10 years.

METHODS

Five hundred and six consecutive (n = 506) patients with 1-year follow-up were divided into early (G1, years 2010-2013, n = 130), intermediate (G2, 2014-2016, n = 164) and recent (G3, 2017-2019, n = 212) experience groups.

RESULTS

Patient's age remained constant over time (mean [SD]; G1 = 79.1 [7.1] years vs G2 = 79.1 [7.1] years vs G3 = 79.7 [6.6] years, P = 0.73) but surgical risk in G3 was lower (log Euroscore, median [IQR]: G1 = 14.0 [8.4-20.2] vs G2 = 12.0 [7.0-22.2] vs G3 = 5.1 [3.5-8.5], P < 0.001). Major/life-threatening bleeding (G1 = 26.9% vs G2 = 12.8% vs G3 = 9.4%; P < 0.001), major vascular complications (G1 = 15.4% vs G2 = 8.5% vs G3 = 5.7%; P = 0.02) and moderate/severe paravalvular leak (G1 = 16.2% vs G2 = 11% vs G3 = 7.5%; P = 0.046) were decreasing with time. There was a significant drop in all-cause 1-year mortality in G3 (G1 = 20% vs G2 = 17.7% vs G3 = 9.1%; log rank = 0.01).

CONCLUSION

Age of TAVI recipients remained unchanged over the last decade. Decreasing surgical risk coupled with improvements in procedural technique and care resulted in fewer periprocedural complications and better 1-year survival.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks

Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in Coronavirus disease 2019 (COVID-19) patients, but are not part of the clinical routine since required manual segmentation of lung lesions is prohibitively time-consuming. We propose a new fully automated deep learning framework for quantification and differentiation between lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional Long Short-Term Memory (LSTM) networks. Utilizing the expert annotations, model training was performed using 5-fold cross-validation to segment ground-glass opacity and high opacity (including consolidation and pleural effusion). The performance of the method was evaluated on CT data sets from 197 patients with positive reverse transcription polymerase chain reaction test result for SARS-CoV-2. Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score coefficient of 0.876 ± 0.005; excellent correlations of 0.978 and 0.981 for ground-glass opacity and high opacity volumes. In the external validation set of 67 patients, there was dice score coefficient of 0.767 ± 0.009 as well as excellent correlations of 0.989 and 0.996 for ground-glass opacity and high opacity volumes. Computations for a CT scan comprising 120 slices were performed under 2 seconds on a personal computer equipped with NVIDIA Titan RTX graphics processing unit. Therefore, our deep learning-based method allows rapid fully-automated quantitative measurement of pneumonia burden from CT and may generate the big data with an accuracy similar to the expert readers.

Epicardial adipose tissue is associated with extent of pneumonia and adverse outcomes in patients with COVID-19

AIM

We sought to examine the association of epicardial adipose tissue (EAT) quantified on chest computed tomography (CT) with the extent of pneumonia and adverse outcomes in patients with coronavirus disease 2019 (COVID-19).

METHODS

We performed a post-hoc analysis of a prospective international registry comprising 109 consecutive patients (age 64 ± 16 years; 62% male) with laboratory-confirmed COVID-19 and noncontrast chest CT imaging. Using semi-automated software, we quantified the burden (%) of lung abnormalities associated with COVID-19 pneumonia. EAT volume (mL) and attenuation (Hounsfield units) were measured using deep learning software. The primary outcome was clinical deterioration (intensive care unit admission, invasive mechanical ventilation, or vasopressor therapy) or in-hospital death.

RESULTS

In multivariable linear regression analysis adjusted for patient comorbidities, the total burden of COVID-19 pneumonia was associated with EAT volume (β = 10.6, p = 0.005) and EAT attenuation (β = 5.2, p = 0.004). EAT volume correlated with serum levels of lactate dehydrogenase (r = 0.361, p = 0.001) and C-reactive protein (r = 0.450, p < 0.001). Clinical deterioration or death occurred in 23 (21.1%) patients at a median of 3 days (IQR 1-13 days) following the chest CT. In multivariable logistic regression analysis, EAT volume (OR 5.1 [95% CI 1.8-14.1] per doubling p = 0.011) and EAT attenuation (OR 3.4 [95% CI 1.5-7.5] per 5 Hounsfield unit increase, p = 0.003) were independent predictors of clinical deterioration or death, as was total pneumonia burden (OR 2.5, 95% CI 1.4-4.6, p = 0.002), chronic lung disease (OR 1.3 [95% CI 1.1-1.7], p = 0.011), and history of heart failure (OR 3.5 [95% 1.1-8.2], p = 0.037).

CONCLUSIONS

EAT measures quantified from chest CT are independently associated with extent of pneumonia and adverse outcomes in patients with COVID-19, lending support to their use in clinical risk stratification.

Impact of transcatheter aortic valve implantation on coexistent mitral regurgitation parameters

BACKGROUND

Data on the impact of transcatheter aortic valve implantation (TAVI) on coexisting mitral regurgitation (MR) are still inconsistent.

AIMS

The study aimed to evaluate the impact of TAVI on coexistent MR depending on its etiology.

METHODS

Out of 311 patients treated with TAVI, we selected 48 with coexistent MR: functional (FMR; n = 26) or nonfunctional (nFMR; n = 22). The impact of the procedure on MR was quantitatively assessed during a 1‑year follow‑up using MR effective regurgitant orifice area (MR‑EROA) and volume (MRV).

RESULTS

Compared with baseline, no change of MR‑EROA was observed at 1‑year follow‑up in all patients with MR (median [interquartile range (IQR)], 0.2 [0.17-0.23]cm2 vs 0.17 [0.14-0.2]cm2 ; P = 0.054). No change in MR‑EROA was also noted either in FMR (median [IQR], 0.21 [0.17-0.27]cm2 vs 0.19 [0.14-0.25]cm2 ; P = 0.142) or nFMR (median [IQR], 0.17 [0.12-0.23] cm2 vs 0.17 [0.1-0.2] cm2 ; P = 0.238) cohorts. Decreased MRV was seen in theoverall MR population after TAVI (median [IQR], 32 [28-36]ml/beat vs 26 [22-28]ml/beat; P = 0.002). Similarly, decreased MRV was noted in both FMR (median [IQR], 33 [26-42] ml/beat vs 26 [20-40] ml/beat; P = 0.042) and nFMR (median [IQR], 30 [20-46] ml/beat vs 24 [15-33] ml/beat; P = 0.015) cohorts.

CONCLUSIONS

Transcatheter aortic valve implantation had no impact on MR‑EROA regardless of the etiology of regurgitation. However, the procedure reduced MRV in both FMR and nFMR.

Non-invasive quantitative characterization of aortic valve tissue composition from computed tomography angiography improves patient risk stratification in transcatheter aortic valve implantation

Background

Computed tomography angiography (CTA) performed for procedural planning of transcatheter aortic valve implantation (TAVI) can be used for a more complete characterization of aortic valve tissue beyond calcium assessment. Combining quantitative data on both noncalcified and calcified tissues may improve differentiation of aortic stenosis (AS) subtypes and prognostication post-TAVI.

Purpose

We sought to noninvasively assess aortic valve tissue composition with quantitative cardiac CTA in patients with AS and its prognostic vaalue in those who underwent TAVI.

Methods

In 185 consecutive AS patients in a prospective registry who underwent cardiac CTA before TAVR and 90 matched controls with normal aortic valves, non-luminal aortic valve tissue were identified using semi-automated software as non-calcified (low-attenuation [−30 to 30 Hounsfield Units (HU)], fibro-fatty (31 to 130 HU), fibrous (131 to 350 HU) and calcified (&gt;650 HU) tissue; with total tissue as (non-calcified + calcified components). Volumes of each component and composition [(tissue component volume/total tissue volume) ×100%] were quantified. The association of aortic valve composition and clinical outcomes post-TAVI including all-cause mortality was evaluated using Valve Academic Research Consortium (VARC)-2 definitions.

Results

AS patients had greater aortic valve tissue volume (median 2000.2, vs 527.8 mm3, p&lt;0.001) with a higher calcified tissue composition (41.8% vs 3.4%, p&lt;0.001) compared to controls. Total aortic valve tissue (noncalcified and calcified) volume yielded the highest area under the operating curve (AUC) for diagnosing severe AS (0.93,95% CI:0.93–0.99) as compared to calcified tissue volume alone (0.87,95% CI:0.81–0.94, p=0.002). Low-flow low-gradient AS was associated with increase in total tissue volume compared to controls (1515.3 vs 527.8 mm3, p&lt;0.001), with lower volumes of calcified tissue than high-gradient AS (412.5 vs 829.6 mm3, p&lt;0.001). Device success was achieved in 88% (164 of 185) patients and prevalence of moderate or severe paravalvular leak was 3.8%, however no differences between in aortic valve composition were observed in patients with and without device success. Early safety endpoints occurred in 16.1% (29 of 180) patients and 30-day all-cause mortality was 4.4%. Whereas only calcified tissue volume was related to VARC-2 early safety, AUC for prediction of 30-day mortality post-TAVI was 0.793 (95% CI:0.685–0.901) for total tissue volume and 0.776 (95% CI:0.676–0.876) for calcified tissue volume.

Conclusions

Quantitative CTA assessment of aortic valve tissue volume and composition can improve identification of high-gradient AS and low-flow low-gradient AS patients referred for TAVI and predict 30-day mortality post-TAVI.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute (NHLBI)

Quantitative Burden of COVID-19 Pneumonia on Chest CT Predicts Adverse Outcomes: A Post-Hoc Analysis of a Prospective International Registry

PURPOSE

To examine the independent and incremental value of CT-derived quantitative burden and attenuation of COVID-19 pneumonia for the prediction of clinical deterioration or death.

METHODS

This was a retrospective analysis of a prospective international registry of consecutive patients with laboratory-confirmed COVID-19 and chest CT imaging, admitted to four centers between January 10 and May 6, 2020. Total burden (expressed as a percentage) and mean attenuation of ground glass opacities (GGO) and consolidation were quantified from CT using semi-automated research software. The primary outcome was clinical deterioration (intensive care unit admission, invasive mechanical ventilation, or vasopressor therapy) or in-hospital death. Logistic regression was performed to assess the predictive value of clinical and CT parameters for the primary outcome.

RESULTS

The final population comprised 120 patients (mean age 64 ± 16 years, 78 men), of whom 39 (32.5%) experienced clinical deterioration or death. In multivariable regression of clinical and CT parameters, consolidation burden (odds ratio [OR], 3.4; 95% confidence interval [CI]: 1.7, 6.9 per doubling; P = .001) and increasing GGO attenuation (OR, 3.2; 95% CI: 1.3, 8.3 per standard deviation, P = .02) were independent predictors of deterioration or death; as was C-reactive protein (OR, 2.1; 95% CI: 1.3, 3.4 per doubling; P = .004), history of heart failure (OR 1.3; 95% CI: 1.1, 1.6, P = .01), and chronic lung disease (OR, 1.3; 95% CI: 1.0, 1.6; P = .02). Quantitative CT measures added incremental predictive value beyond a model with only clinical parameters (area under the curve, 0.93 vs 0.82, P = .006). The optimal prognostic cutoffs for burden of COVID-19 pneumonia as determined by Youden's index were consolidation of greater than or equal to 1.8% and GGO of greater than or equal to 13.5%.

CONCLUSIONS

Quantitative burden of consolidation or GGO on chest CT independently predict clinical deterioration or death in patients with COVID-19 pneumonia. CT-derived measures have incremental prognostic value over and above clinical parameters, and may be useful for risk stratifying patients with COVID-19.

Comparison of Computed Tomography Angiography Versus Invasive Angiography to Assess Medina Classification in Coronary Bifurcations

The Medina classification is used to determine the presence of significant stenosis (≥50%) within each of the 3 arterial segments of coronary bifurcation in invasive coronary angiography (ICA). The utility of coronary computed tomography angiography (coronary CTA) for assessment of Medina classification is unknown. We aimed to compare the agreement and reproducibility of Medina classification between ICA and coronary CTA, and evaluate its ability to predict side branch (SB) occlusion following percutaneous coronary intervention (PCI). In total 363 patients with 400 bifurcations were included, and 28 (7%) SB occlusions among 26 patients were noted. Total agreement between CTA and ICA for assessment of Medina class was poor (kappa = 0.189), and discordance between both modalities was noted in 253 (63.3%) lesions. Larger diameter ratio between main vessel and SB in CTA, and larger bifurcation angle in ICA were independently associated with discordant Medina assessment. Whereas the interobserver agreement on Medina classification in CTA was moderate (kappa = 0.557), only fair agreement (kappa = 0.346) was observed for ICA. Finally, Medina class with any proximal involvement of main vessel and SB (1.X.1) on CTA or ICA was the most predictive of SB occlusion following PCI with no significant differences between both modalities (area under the curve 0.686 vs 0.663, p = 0.693, respectively). In conclusion, Medina classification was significantly affected by the imaging modality, and coronary CTA improved reproducibility of Medina classification compared with ICA. Both CTA and ICA-derived Medina class with any involvement of the proximal main vessel and SB was predictive of SB occlusion following PCI.

Accuracy of RESOLVE score derived from coronary computed tomography versus visual angiography to predict side branch occlusion in percutaneous bifurcation intervention

INTRODUCTION

Visually estimated angiographic V-RESOLVE score was developed as a simple and accurate prediction tool for side branch (SB) occlusion in patients undergoing coronary bifurcation intervention. Data on the use of coronary computed tomography angiography (coronary CTA) for guiding percutaneous coronary intervention in bifurcation lesions is scarce.

OBJECTIVES

We aimed to validate the ability of quantitative CTA-derived RESOLVE score for predicting SB occlusion in coronary bifurcation intervention and to compare its predictive value with that of the angiography-based V-RESOLVE score.

METHODS

We included 363 patients with 400 bifurcation lesions. Angiographic V-RESOLVE score and CTA-derived RESOLVE score were calculated utilizing the weights from the QCA-based RESOLVE score. The scoring systems were divided into quartiles, and classified as the non-high-risk group and the high-risk group. Accuracy was assessed using areas under the receiver-operator characteristic curve (AUC). SB occlusion was defined as any decrease in Thrombolysis in Myocardial Infarction flow grade (including the absence of flow) in the SB after main vessel stenting.

RESULTS

In total, 28 SB occlusions (7%) occurred. CTA-derived RESOLVE and V-RESOLVE scores achieved comparable predictive accuracy (0.709 vs. 0.752, respectively, p = 0.531) for predicting SB occlusion, and the analysis of AUC for each constituent element of the scores did not show any significant difference between CTA and visual angiography. The total net reclassification index was -18.6% (p = 0.194), and there were no significant differences in the rates of SB occlusion in the non-high-risk group (4.9% vs. 3.8%, p = 0.510) and the high-risk group (13.8% vs. 18.6%, p = 0.384) between CTA-derived RESOLVE and V-RESOLVE scores.

CONCLUSIONS

The quantitative CTA-derived RESOLVE score is an accurate and reliable alternative to the visually estimated angiographic V-RESOLVE score for prediction of SB occlusion in coronary bifurcation intervention.

CLINICAL TRIAL REGISTRATION

URL: https://www.clinicaltrials.gov. Unique identifier: NCT03709836.

Different types of endocarditis after transcatheter aortic valve implantation

INTRODUCTION

Infective endocarditis (IE) may take different faces in patients after transcatheter aortic valve implantation (TAVI).

OBJECTIVES

The primary aim of this study was to describe echocardiographic and clinical characteristics of TAVI's patients suffered from IE.

METHODS

In a single-center, retrospective study we analyzed 311 consecutive patients treated with TAVI for severe aortic stenosis between 2010 and 2018.

RESULTS

According to modified Duke criteria, we confirmed IE in 2.2% of the cohort, however PVE of TAVI's valve in 1.2% only; rest of the group suffered from CDRiE and IE of the mitral valve. In PVE's group vegetations were localized inside the frame with or without bioprosthesis moderate stenosis or regurgitation. Only 1 pts developed significant TAVI's bioprosthesis' paravalvular leak. We observed no native aortic anulus involvement. Mortality rate in the PVE-TAVI's group was 75% regardless of the type of treatment.

CONCLUSIONS

The above findings show that IE following TAVI is a serious complication and various scenarios (also CDRiE and native valve IE) should be considered.