A Nomogram Prediction Model Based on Tissue Window for the Prognosis of Patients with Acute Ischemic Stroke Undergoing Thrombectomy.

OBJECTIVE: Thrombectomy greatly improves the clinical prognosis of patients with acute ischemic stroke (AIS). The aim of this study is to develop a nomogram model that can predict the prognosis of patients with acute ischemic stroke undergoing thrombectomy. METHODS: We retrospectively collected information of patients with acute ischemic stroke who were admitted to the stroke Green Channel of the First Affiliated Hospital of Soochow University from September 2018 to May 2022. The main outcome was defined as a three-month unfavorable outcome (modified Rankin Scale 3-6). Based on the results of multivariate regression analysis, a nomogram was established. We tested the accuracy and discrimination of our nomogram by calculating the consistency index (C-index) and plotting the calibration curve. RESULTS: National Institutes of Health Stroke Scale (NIHSS) score (OR, 1.418; 95% CI, 1.177-1.707; P＜0.001), low density lipoprotein cholesterol (LDL-C) (OR, 2.705; 95% CI, 1.203-6.080; P = 0.016), Alberta Stroke Program Early Computed Tomography Score (ASPECTS) (OR, 0.633; 95% CI, 0.421-0.952; P = 0.028), infarct core volume (OR, 1.115; 95% CI, 1.043-1.192; P = 0.001) and ischemic penumbra volume (OR, 1.028; 95% CI, 1.006-1.050; P = 0.012) were independent risk factors for poor clinical prognosis of AIS patients treated with thrombectomy. The C-index of our nomogram was 0.967 and the calibration plot revealed a generally fit in predicting three-month unfavorable outcomes. Based on this nomogram, we stratified the risk of thrombectomy population. We found that low-risk population is less than or equal to 65 points, and patients of more than 65 points tend to have a poor clinical prognosis. CONCLUSION: The nomogram, composed of NIHSS, LDL-C, ASPECTS, infarct core volume and ischemic penumbra volume, may predict the clinical prognosis of cerebral infarction patients treated with thrombectomy.

Gadolinium enhancement of atherosclerotic plaque in the intracranial artery.

Background: Gadolinium enhancement on high resolution magnetic resonance imaging (HR-MRI) has been considered a sign of instability and inflammation of intracranial atherosclerotic plaques. Our research objective was to explore the relationship between the extent of plaque enhancement (PE), the degree of intracranial artery stenosis, and acute ischemic stroke events.Methods: HR-MRI was performed in 91 patients with intracranial vascular stenosis to determine the existence and intensity of PE.Results: Among 91 patients enrolled in the trial, there were 43 patients in the acute/subacute group (≤1 month from ischemic stroke event), 15 patients in the chronic group (>1 month from ischemic stroke event), and 33 patients in the non-culprit plaques group (no ischemic stroke event). A total of 105 intracranial atherosclerotic plaques were detected in 91 patients. 14 (13.3%) were mild-stenosis plaques, 22 (21.0%) were moderate-stenosis plaques, and 69 (65.7%) were severe-stenosis plaques. There were 12 (11.4%), 18 (17.1%), and 75 (71.4%) plaques in the non-enhanced plaque group, the mild-enhancement group, and the significant-enhancement group, respectively. The degree of PE among the acute/subacute group, the chronic group, and the non-culprit plaque group had a significant difference (P = 0.005). Enhanced plaques were more often observed in culprit plaques (acute/subacute group and chronic group) than non-culprit plaques (96.7% vs 77.3%). Non-enhanced plaques were more often observed in non-culprit plaques than culprit plaques (acute/subacute group and chronic group) (22.7% vs 3.3%). And 36.6% of the enhanced plaques were non-culprit plaques. After performing univariate and multivariate logistic regression analysis, the results showed that strong plaque enhancement (P = 0.025, odds ratio [OR] 3.700, 95% confidence interval [95% CI] 1.182-11.583) and severe stenosis (P = 0.008, OR 4.393, 95%CI 1.481-13.030) were significantly associated with acute ischemic events.Conclusion: Enhanced plaques were more often observed in culprit plaques, and non-enhanced plaques were more often observed in non-culprit plaques. Moreover, significant plaque enhancement and severe ICAS were closely associated with acute ischemic events.

The relationship between COVID-19's severity and ischemic stroke: a systematic review and meta-analysis.

OBJECTIVE: We aim to determine the risk of acute ischemic stroke in patients with severe and non-severe coronavirus disease 2019 (COVID-19). METHODS: A literature search was conducted in the PubMed, Embase, Web of Science, and Cochrane Library databases until October 28, 2020. Studies covering COVID-19's severity classification data and COVID-19 patients with acute ischemic stroke were included. Two independent evaluators extracted data, and the random effects model was used to calculate the risk ratios (RR) and 95% confidence interval (95% CI) of acute ischemic stroke associated with COVID-19's severity. RESULTS: A total of 8 studies were included, involving 5266 patients. Among all COVID-19 patients, the total incidence of ischemic stroke was 1.76% (95% CI: 0.82-3.01). Severe patients have an increased risk of acute ischemic stroke compared with non-severe patients (RR = 3.53, 95% CI: 2.06-6.07, P < 0.0001; I2 = 12%). This association was also observed when COVID-19's severity was defined by clinical parameters (RR 2.91, 95% CI: 1.17-7.26, P = 0.02; I2 = 29%) and the need for intensive care (RR 4.47, 95% CI: 2.40-8.31, P < 0.0001; I2 = 0%). CONCLUSIONS: This meta-analysis shows that the severe course of COVID-19 is associated with an increased risk of acute ischemic stroke.

Insertable cardiac monitors for detection of atrial fibrillation after cryptogenic stroke: a meta-analysis.

BACKGROUND: In recent years, the implantable cardiac monitors (ICM) have enhanced the recognition ability of atrial fibrillation (AF), which makes ICM have a new application in AF detection. We conducted a meta-analysis to determine the total incidence of newly found AF detected by ICM after cryptogenic stroke and to evaluate the factors related to the detection of AF. METHODS: A literature search was conducted in the PubMed, EMBASE, Web of Science, and Cochrane library databases until March 1, 2020. Studies that reported the detection rate of AF using ICM in cryptogenic stroke patients with negative initial AF screening were analyzed. RESULTS: A total of 23 studies were included. The overall proportion of AF detected by ICM in cryptogenic stroke patients was 25% (95% confidence interval [CI], 22-29%). The rate of AF detected by ICM was independently related to both cardiac monitoring time (coefficient = 0.0003; 95% CI, 0.0001-0.0005; P = 0.0001) and CHA2DS2-VASc score (coefficient = 0.0834; 95% CI, 0.0339-0.1329; P = 0.001). In subgroup analysis, we found a significant difference in the detection rate of AF for monitoring duration (< 6 months: 9.6% [95% CI, 4.4-16.4%]; ≥ 6 and ≤ 12 months: 19.3% [95% CI, 15.9-23.0%]; > 12 and ≤ 24 months: 23.6% [95% CI, 19.9-27.5%]; > 24 months and ≤ 36 months: 36.5% [95% CI, 24.2-49.9%]; P < 0.001), and continent (Europe: 26.5% [95% CI, 22.2-31.0%]; North America: 16.0% [95% CI, 10.3-22.6%]; Asia: 17.4% [95% CI, 12.4-23.0%]; P = 0.005). CONCLUSIONS: The longer the time of ICM monitoring after cryptogenic stroke, the higher the detection rate of AF. Further research is still needed to determine the optimal duration of long-term cardiac monitoring.