Risk factors and Nomogram for Predicting Carotid Blowout Syndrome Based on Computed Tomography Angiography

Oral Diseases ◽  
2021 ◽  
Author(s):  
Kun Feng ◽  
Jing Hu ◽  
Qiuyu Huang ◽  
Weixin Cai ◽  
Zehang Zhuang ◽  
...  
Author(s):  
Po-Yi Li ◽  
Ru-Yih Chen ◽  
Fu-Zong Wu ◽  
Guang-Yuan Mar ◽  
Ming-Ting Wu ◽  
...  

The objective of this study was to determine how coronary computed tomography angiography (CCTA) can be employed to detect coronary artery disease in hospital employees, enabling early treatment and minimizing damage. All employees of our hospital were assessed using the Framingham Risk Score. Those with a 10-year risk of myocardial infarction or death of >10% were offered CCTA; the Coronary Artery Disease Reporting and Data System (CAD-RADS) score was the outcome. A total of 3923 hospital employees were included, and the number who had received CCTA was 309. Among these 309, 31 (10.0%) had a CAD-RADS score of 3–5, with 10 of the 31 (32.3%) requiring further cardiac catheterization; 161 (52.1%) had a score of 1–2; and 117 (37.9%) had a score of 0. In the multivariate logistic regression, only age of ≥ 55 years (p < 0.05), hypertension (p < 0.05), and hyperlipidemia (p < 0.05) were discovered to be significant risk factors for a CAD-RADS score of 3–5. Thus, regular and adequate control of chronic diseases is critical for patients, and more studies are required to be confirmed if there are more significant risk factors.


2020 ◽  
Vol 21 (5) ◽  
pp. 479-488 ◽  
Author(s):  
Alexander R van Rosendael ◽  
A Maxim Bax ◽  
Jeff M Smit ◽  
Inge J van den Hoogen ◽  
Xiaoyue Ma ◽  
...  

Abstract Aims In patients without obstructive coronary artery disease (CAD), we examined the prognostic value of risk factors and atherosclerotic extent. Methods and results Patients from the long-term CONFIRM registry without prior CAD and without obstructive (≥50%) stenosis were included. Within the groups of normal coronary computed tomography angiography (CCTA) (N = 1849) and non-obstructive CAD (N = 1698), the prognostic value of traditional clinical risk factors and atherosclerotic extent (segment involvement score, SIS) was assessed with Cox models. Major adverse cardiac events (MACE) were defined as all-cause mortality, non-fatal myocardial infarction, or late revascularization. In total, 3547 patients were included (age 57.9 ± 12.1 years, 57.8% male), experiencing 460 MACE during 5.4 years of follow-up. Age, body mass index, hypertension, and diabetes were the clinical variables associated with increased MACE risk, but the magnitude of risk was higher for CCTA defined atherosclerotic extent; adjusted hazard ratio (HR) for SIS &gt;5 was 3.4 (95% confidence interval [CI] 2.3–4.9) while HR for diabetes and hypertension were 1.7 (95% CI 1.3–2.2) and 1.4 (95% CI 1.1–1.7), respectively. Exclusion of revascularization as endpoint did not modify the results. In normal CCTA, presence of ≥1 traditional risk factors did not worsen prognosis (log-rank P = 0.248), while it did in non-obstructive CAD (log-rank P = 0.025). Adjusted for SIS, hypertension and diabetes predicted MACE risk in non-obstructive CAD, while diabetes did not increase risk in absence of CAD (P-interaction = 0.004). Conclusion Among patients without obstructive CAD, the extent of CAD provides more prognostic information for MACE than traditional cardiovascular risk factors. An interaction was observed between risk factors and CAD burden, suggesting synergistic effects of both.


Neurosurgery ◽  
2013 ◽  
Vol 73 (5) ◽  
pp. 825-837 ◽  
Author(s):  
Ahmed Elsharkawy ◽  
Martin Lehečka ◽  
Mika Niemelä ◽  
Juri Kivelev ◽  
Romain Billon-Grand ◽  
...  

Abstract BACKGROUND: The middle cerebral artery (MCA) is the most frequent location for unruptured intracranial aneurysms. Controversy remains as to which unruptured MCA aneurysms should be treated prophylactically. OBJECTIVE: To identify independent topographical and morphological variables that could predict increased rupture risk of MCA aneurysms. METHODS: A retrospective analysis of computed tomography angiography data of 1009 consecutive patients with 1309 MCA aneurysms, referred between 2000 and 2009 to Helsinki University Hospital, was carried out. Morphological and topographical parameters examined for MCA aneurysms comprised aneurysm wall regularity, size, neck width, aspect ratio, bottleneck factor, height-width ratio, location along the MCA, side, distance from the internal carotid artery bifurcation, and dome projection in axial and coronal computed tomography angiography views. Univariate and multivariate logistic regression analyses were performed to determine independent risk factors for rupture. RESULTS: Of the 1309 MCA aneurysms, 69% were unruptured and 31% were ruptured. Most unruptured MCA aneurysms were smaller than 7 mm (78%), with a smooth wall (80%) and a height-width ratio of 1 (47%) and were located at the main bifurcation (57%). Ruptured MCA aneurysms, mostly 7 to 14 mm in size (55%), had an irregular wall (78%) and a height-width ratio greater than 1 (72%) and were located at the main bifurcation (77%). Thirty-eight percent of MCA bifurcation aneurysms, 74% of large aneurysms, 64% of aneurysms with an irregular wall, and 49% of aneurysms with a height-width ratio greater than 1 were ruptured. CONCLUSION: Location at the main MCA bifurcation, wall irregularity, and less spherical geometry were independently associated with rupture of MCA aneurysms with a correlation with aneurysm size.


2012 ◽  
Vol 117 (4) ◽  
pp. 761-766 ◽  
Author(s):  
Kimon Bekelis ◽  
Atman Desai ◽  
Wenyan Zhao ◽  
Dan Gibson ◽  
Daniel Gologorsky ◽  
...  

Object Computed tomography angiography (CTA) is increasingly used as a screening tool in the investigation of spontaneous intracerebral hemorrhage (ICH). However, CTA carries additional costs and risks, necessitating its judicious use. The authors hypothesized that subsets of patients with nontraumatic, nonsubarachnoid ICH are unlikely to benefit from CTA as part of the diagnostic workup and that particular patient risk factors may be used to increase the yield of CTA in the detection of vascular sources. Methods The authors performed a retrospective analysis of 1376 patients admitted to Dartmouth-Hitchcock Medical Center with ICH over an 8-year period. Patients with subarachnoid hemorrhage, hemorrhagic conversion of ischemic infarcts, trauma, and known prior malignancy were excluded from the analysis, resulting in 257 patients for final analysis. Records were reviewed for medical risk factors, hemorrhage location, and correlation of CTA findings with final diagnosis. Multiple logistic regression analysis was used to investigate the combined effects of baseline variables of interest. Model selection was conducted using the stepwise method with p = 0.10 as the significance level for variable entry and p = 0.05 the significance level for variable retention. Results Computed tomography angiography studies detected vascular pathology in 34 patients (13.2%). Patient characteristics that were associated with a significantly higher likelihood of identifying a structural vascular lesion as the source of hemorrhage included patient age younger than 65 years (OR = 16.36, p = 0.0039), female sex (OR = 14.9, p = 0.0126), nonsmokers (OR = 103.8, p = 0.0008), patients with intraventricular hemorrhage (OR = 9.42, p = 0.0379), and patients without hypertension (OR = 515.78, p < 0.0001). Patients who were older than 65 years of age, with a history of hypertension, and hemorrhage located in the cerebellum or basal ganglia were never found to have an identified structural source of hemorrhage on CTA. Conclusions Patient characteristics and risk factors are important considerations when ordering diagnostic tests in the workup of nonsubarachnoid, nontraumatic spontaneous ICH. Although CTA is an accurate diagnostic examination, it can usually be omitted in the workup of patients with the described characteristics. The use of this algorithm has the potential to increase the yield, and thus the safety and cost effectiveness, of this diagnostic tool.


2018 ◽  
Vol 115 ◽  
pp. e27-e32 ◽  
Author(s):  
Guang-xian Wang ◽  
Ming-fu Gong ◽  
Li Wen ◽  
Lan-lan Liu ◽  
Jin-bo Yin ◽  
...  

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