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Abstract
Background
Fractional flow reserve (FFR) is the gatekeeper for lesion-specific revascularization
decision-making in patients with stable coronary artery disease (CAD). The potential
of noninvasive calculation of FFR from coronary computed tomographic angiography (CCTA)
to identify ischemia-causing lesions has not been sufficiently assessed. The objective
of this study was to evaluate the feasibility and diagnostic accuracy of a novel computational
fluid dynamics (CFD)-based technology, termed as AccuFFRct, for the diagnosis of functionally
significant lesions from CCTA, using wire-based FFR as a reference standard.
Methods
A total of 191 consecutive patients who underwent CCTA and FFR measurement for suspected
or known CAD were retrospectively enrolled at 2 medical centers. Three-dimensional
anatomic model of coronary tree was extracted from CCTA data, CFD was applied subsequently
with a novel strategy for the computation of FFR in a blinded fashion by professionals.
Results were compared to invasive FFR, a threshold of ≤0.80 was used to indicate the
hemodynamically relevant stenosis.
Results
On a per-patient basis, the overall accuracy, sensitivity, specificity of AccuFFRct
for detecting ischemia were 91.78% (95% CI: 86.08% to 95.68%), 92.31% (95% CI: 81.46%
to 97.86%) and 91.49% (95% CI: 83.92% to 96.25%), respectively; those for per-vessel
basis were 91.05% (95% CI: 86.06% to 94.70%), 92.73% (95% CI: 82.41% to 97.98%) and
90.37% (95% CI: 84.10% to 94.77%), respectively. The AccuFFRct and FFR was well correlated
on per-patient (
r=0.709, P<0.001) and per-vessel basis (
r=0.655, P<0.001). The AUC of AccuFFRct determination was 0.935 (95% CI: 0.881 to 0.969)
and 0.927 (95% CI: 0.880 to 0.960) on per-patient and per-vessel basis.
Conclusions
This novel CFD-based CCTA-derived FFR shows good diagnostic performance for detecting
hemodynamic significance of coronary stenoses and may potentially become a new gatekeeper
for invasive coronary angiography (ICA).
Summary Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4–61·9) in 1980 to 71·8 years (71·5–72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7–17·4), to 62·6 years (56·5–70·2). Total deaths increased by 4·1% (2·6–5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8–18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6–16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9–14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1–44·6), malaria (43·1%, 34·7–51·8), neonatal preterm birth complications (29·8%, 24·8–34·9), and maternal disorders (29·1%, 19·3–37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000–183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000–532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation.
[4
]Department of Cardiology , The First People’s Hospital of Linping District, Hangzhou, China;
[5
]deptDepartment of Radiology, The Affiliated Hospital of Medical School , Ningbo University , Ningbo, China;
[6
]deptDepartment of Cardiovascular Medicine , Jinhua Municipal Central Hospital , Jinhua, China;
[7
]deptDepartment of Electrophysiology , Jinhua Municipal Central Hospital , Jinhua, China
Author notes
Contributions: (I) Conception and design: All authors; (II) Administrative support: JA Wang, L Tang,
J Xiang; (III) Provision of study materials or patients: J Jiang, C Du; (IV) Collection
and assembly of data: All authors; (V) Data analysis and interpretation: Y Hu, H Yuan;
(VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.
[#]
These authors contributed equally to this work.
Correspondence to: Jianping Xiang, PhD. ArteryFlow Technology Co., Ltd., 459 Qianmo Road, Hangzhou 310051,
China. Email:
jianping.xiang@
123456arteryflow.com
; Lijiang Tang, MD. Department of Cardiology, Zhejiang Hospital, 12 Lingyin Road,
Hangzhou 310013, China. Email:
zjyytang@
123456163.com
; Jian’an Wang, MD. Department of Cardiology, The Second Affiliated Hospital of Zhejiang
University School of Medicine, 88 Jiefang Road, Hangzhou 310009, China. Email:
wangjianan111@
123456zju.edu.cn
.
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See:
https://creativecommons.org/licenses/by-nc-nd/4.0.
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