Objective To investigate the influencing factor of the morphology of unruptured intracranial aneurysms for aneurysm wall enhancement under the high-resolution magnetic resonance imaging. Methods From January 2015 to December 2016,the clinical and imaging data of 68 consecutive patients with unruptured intracranial aneurysm (86 aneurysms) in Changhai Hospital,the Second Military Medical University were enrolled retrospectively. Vascular wall imaging technology was used to conduct aneurysm scan,and the aneurysm wall enhancement was identified by the imaging features before and after contrast enhancement. They were divided into either an enhancement group ( n=32,34 aneurysms) or a non-enhancement group (n=45,52 aneurysms) according to whether having the abnormal enhancement of aneurysm wall or not ( because some patients also have enhanced aneurysms and non-enhanced aneurysms, the number of cases of the enhanced or not was calculated seperately in both groups ) . Morphological parameters were calculated by 3D image data,including aneurysm size,ratio of height to width,volume ratio, dome-to-neck ratio, transverse length ratio, bottleneck factor, and inflow angle. Univariate and multivariate logistic analyses were used to determine the morphological influence factors of aneurysm wall enhancement. Results (1) A total of 34 (39. 5%) aneurysms had aneurysm wall enhancement and 52 (60. 5％) aneurysms did not have aneurysm wall enhancement. There were no significant differences in sex, age, hypertension,diabetes, smoking, family history of subarachnoid hemorrhage, and aneurysm site in both groups (all P>0. 05). (2) The aneurysm size,ratio of height to width,volume ratio,dome-to-neck ratio, and bottleneck factor in the enhancement group were larger than those of the non-enhancement group. There were significant differences between the 2 groups (9. 19 [6. 54,11. 04] mm vs. 5. 31 [4. 17,7. 37] mm, (1. 18 [1. 01,1. 69] vs. 0. 91 [0. 72,1. 25],(3. 62 [2. 30,4. 63] vs. 2. 18 [1. 37,2. 76],1. 52 [1. 25, 1. 99] vs. 1. 19 [1. 03,1. 51],and 1. 21 [1. 11,1. 69] vs. 1. 05 [0. 94,1. 31],all P<0. 01). The proportion of irregular morphologic aneurysms in the enhancement group was higher than that in the non-enhancement group. There was significant difference between the 2 groups (55. 9％ [19/34] vs. 17. 3％ [9/52],P<0. 01 ) . There were no significant differences in transverse length ratio and inflow angle between the 2 groups (all P>0. 05). (3) Because the ratio of height to width,volume ratio,dome-to-neck ratio,and bottleneck factor were related to the aneurysm size,the aneurysm size,inflow angle,and irregular shape were included in the multivariate logistic regression analysis. The results showed that aneurysm size ( OR,3. 727,95％CI 1. 933-6. 971,P<0. 01) and irregular shape (OR,3. 990,95％CI 1. 219-13. 065,P=0. 022) were the independent risk factors for aneurysm wall enhancement. Conclusions The size and irregular shape of unruptured intracranial aneurysms are the independent risk factors for aneurysm wall enhancement. High-resolution magnetic resonance wall imaging may become an effective and noninvasive imaging method for evaluating the ruptured risk of intracranial aneurysms.

Humans ; Medicine, Chinese Traditional ; Colitis-Associated Neoplasms ; Drugs, Chinese Herbal/adverse effects* ; Colitis/chemically induced* ; Colorectal Neoplasms/drug therapy*

Objective: To explore the patient and hospital related determinants of adherence to early antithrombotic therapy among patients with acute ischemic stroke (AIS). Methods: AIS patients aged 50 years old or above who were eligible for early antithrombotic therapy, were included from the China National Stroke Registry Ⅱ (CNSR Ⅱ) project. Characteristics related to patients and hospitals were collected. Univariate analysis method was conducted to explore the correlation between hospital or patient-related determinants and early antithrombotic therapy. A 2-level logistic regression model was set up to identify patient and hospital-related variables that were associated with the adherence to early antithrombotic therapy, with patient as level 1 and hospital as level 2. Results: A total of 16 910 patients were included in the study, with 14 332 (84.75%) of them having received early antithrombotic therapy. Results from the univariate analysis showed that the patient determinants to early antithrombotic therapy would include age, type of health insurance, average income and history of dyslipidemia. Hospital determinants would include factors as: level and region of the hospital, academic status, with/without stroke unit, quality control on single disease and the percentage of neurological beds in total beds (P<0.05). Data on multilevel model showed that the patient-related determinants on early antithrombotic therapy would include age, gender, average income, history of hypertension, National Institutes of Health Stroke Scale (NIHSS) score at admission while hospital related determinants would include percentage of neurological beds in total beds, and region of the hospital (P<0.05). Conclusions The quality of a hospital was associated with the adherence to early antithrombotic therapy. AIS patients at advanced age or with high NIHSS score at admission should be paid more attention.