Nomogram to predict 3-month unfavorable outcome after thrombectomy for stroke.

BACKGROUND: Mechanical thrombectomy (MT) is an effective treatment for large-vessel occlusion in acute ischemic stroke, however, only some revascularized patients have a good prognosis. For stroke patients undergoing MT, predicting the risk of unfavorable outcomes and adjusting the treatment strategies accordingly can greatly improve prognosis. Therefore, we aimed to develop and validate a nomogram that can predict 3-month unfavorable outcomes for individual stroke patient treated with MT. METHODS: We analyzed 258 patients with acute ischemic stroke who underwent MT from January 2018 to February 2021. The primary outcome was a 3-month unfavorable outcome, assessed using the modified Rankin Scale (mRS), 3-6. A nomogram was generated based on a multivariable logistic model. We used the area under the receiver-operating characteristic curve to evaluate the discriminative performance and used the calibration curve and Spiegelhalter's Z-test to assess the calibration performance of the risk prediction model. RESULTS: In our visual nomogram, gender (odds ratio [OR], 3.40; 95%CI, 1.54-7.54), collateral circulation (OR, 0.46; 95%CI, 0.28-0.76), postoperative mTICI (OR, 0.06; 95%CI, 0.01-0.50), stroke-associated pneumonia (OR, 5.76; 95%CI, 2.79-11.87), preoperative Na (OR, 0.82; 95%CI, 0.72-0.92) and creatinine (OR, 1.02; 95%CI, 1.01-1.03) remained independent predictors of 3-month unfavorable outcomes in stroke patients treated with MT. The area under the nomogram curve was 0.8791 with good calibration performance (P = 0.873 for the Spiegelhalter's Z-test). CONCLUSIONS: A novel nomogram consisting of gender, collateral circulation, postoperative mTICI, stroke-associated pneumonia, preoperative Na and creatinine can predict the 3-month unfavorable outcomes in stroke patients treated with MT.

Left Atrial Enlargement is Associated with Stroke Severity with Cardioembolic and Cryptogenic Subtypes in a Chinese Population.

BACKGROUND: Left atrial enlargement is associated with increased risk for stroke. However, few studies that evaluated the correlation between left atrial size and ischemic stroke severity. In this study, we aim to evaluate the association between left atrial size and stroke severity, especially with cardioembolic and cryptogenic stroke in the Chinese population. METHODS: A total of 1271 patients with acute ischemic stroke were included in this study. Echocardiographic left atrial diameter was measured and indexed to height. Stroke severity was assessed at admission with the National Institutes of Health Stroke Scale (NIHSS). Moderate-to-severe neurologic deficit was defined as NIHSS greater than or equal to 5. Patients were divided into mild, moderate, or severe abnormal left atrial size by tertile distribution. Binary logistic regression analysis was used to identify independent predictors of severe stroke after adjustment. RESULTS: Among all enrolled patients, 328 (25.8%) were classified into moderate-to severe stroke severity (NIHSS ≥ 5). In the multivariable model, compared with the lowest tertile of left atrial size, the odds ratio for moderate-to-severe neurologic deficit was 0.902 (95% CI, 0.644-1.264, P = .550) when left atrial size was the highest tertile. Of all patients, 190 patients were further categorized as cardioembolic and cryptogenic subtypes, and 70 (36.8%) were classified into moderate-to-severe stroke severity. After adjusting for confounders, compared with the lowest tertile, the top tertile of left atrial size was significantly associated with moderate-to-severe stroke (3.156, 95% CI, 1.143-8.711, P = .027). CONCLUSION: Left atrial enlargement was associated with more severe initial neurologic deficits of embolic subtypes (cardioembolic and cryptogenic stroke) in patients with acute ischemic stroke.

Predictors of Very Poor Outcome After Mechanical Thrombectomy in Older Patients with Acute Ischemic Stroke.

BACKGROUND: Mechanical thrombectomy (MT) is an effective treatment for patients with acute ischemic stroke due to large vessel occlusion. However, some elderly patients with recanalization have a very poor outcome, including vegetative state and mortality. This study evaluated predictors of very poor outcome at 3 months in older patients with stroke undergoing MT treatment. METHODS: We retrospectively collected data from consecutive stroke patients ≥80 years old undergoing MT between April 2018 and January 2021. A very poor outcome was defined as a modified Rankin Scale (mRS) score of 5 or 6 at 3-month follow-up. Multiple logistic regression analysis was performed to identify the predictors of very poor outcome at 3 months. RESULTS: The study enrolled 62 patients with a median age of 85.5 years (interquartile range: 82.0-89.0). Of patients, 35 (56.5%) had a very poor outcome at 3-month follow-up. Multiple logistic regression analysis identified female sex (odds ratio = 3.592, 95% confidence interval 1.047-12.319, P = 0.042) and stroke-associated pneumonia (odds ratio = 6.103, 95% CI 1.541-24.174, P = 0.010) as independent predictors of very poor outcome. CONCLUSIONS: In elderly stroke patients undergoing MT treatment, female sex and stroke-associated pneumonia were independent predictors of very poor outcome at 3 months.

Red cell distribution width is associated with stroke severity and unfavorable functional outcomes in ischemic stroke.

Background: Red blood cell distribution width (RDW) is considered to be related to coronary heart disease and heart failure and all-cause mortality, but its relationship with acute ischemic stroke is still unclear. In this study, we aimed to explore the relationship between RDW and the stroke severity and functional outcomes of ischemic stroke. Methods: We retrospectively reviewed patients with acute ischemic stroke between September 2016 and January 2020. Demographic, clinical, stroke complications, laboratory data, and treatment were collected for all patients. Stroke severity and functional outcomes were evaluated by NIHSS score, modified Rankin Scale (mRS), and Barthel Index (BI) at 3 months. Furthermore, multiple logistic regression analysis was used to assess the relationship between RDW and stroke severity and functional outcomes. Results: A total of 629 patients with acute ischemic stroke were included and were categorized into four groups according to the quartiles of RDW (< 12.4, 12.4-12.9, 13.0-13.4, > 13.4). After multivariable analysis, higher RDW was directly associated with moderate to severe stroke (OR 2.21, 95% CI, 1.30-3.75, P = 0.003), mRS score of 3-6 at 3 months (OR 1.86, 95% CI, 1.02-3.41, P = 0.044), and BI score below 85 at 3 months (OR 2.27, 95% CI, 1.25-4.12, P = 0.007) in patients with ischemic stroke. Conclusion: Our results demonstrate that RDW is associated with stroke severity and unfavorable functional outcomes at 3 months in patients with ischemic stroke.

Inflammatory markers as independent predictors for stroke outcomes.

BACKGROUND: Inflammation plays an important role in the pathophysiology of stroke. The aim of the present study was to investigate the association between various inflammatory risk markers and ischemic stroke outcome and subtype. METHODS: A total of 3,013 ischemic stroke patients who were admitted to our hospital from 01/01/2016 to 12/30/2018 were retrospectively studied. Stroke subtypes were defined by the Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification. Levels of five common inflammatory markers including white blood cell (WBC) count, neutrophil, lymphocyte, serum C-reactive protein (CRP), and interleukin-6 (IL-6) were measured, and eleven conventional risk factors were further evaluated in the prediction of overall mortality as well as three functional outcomes defined by the National Institute of Health Stroke Scale (NIHSS), the modified Rankin Scale (mRS), and the Barthel Index (BI). Independent predictors of outcome were identified by multivariate logistic regression, and an importance score measured by the area under the receiver operating characteristics curve for each predictor using a Naive Bayes model was reported. RESULTS: Neutrophil and WBC were significantly higher in large-artery atherosclerosis (LAA) and cardioembolism (CE) subtype. In contrast, lymphocyte was significantly higher in small-artery occlusion (SAO). Neutrophil-lymphocyte ratio and CRP level were the best independent predictors, after adjustment for traditional risk factors and TOAST subtype for all four types of outcomes. CONCLUSION: Inflammatory risk markers including neutrophil, lymphocyte, and CRP may have strong independent prediction values for stroke outcome.

Clinical characteristics and risk score for poor clinical outcome of acute ischemic stroke patients treated with intravenous thrombolysis therapy.

BACKGROUND: Tissue plasminogen activator (t-PA) is an effective therapy for acute ischemic stroke, but some patients still have poor clinical outcome. In this study, we investigated clinical characteristics of stroke patients and determined predictors for poor clinical outcome in response to t-PA treatment. METHODS: Clinical data from 247 patients were retrospectively reviewed. Clinical parameters that were associated with survival of patients were analyzed. Areas under receiver operating characteristic curves (ROC) were used to determine the feasibility of using various combinations of the clinical parameters to predict poor clinical response. The clinical outcome was defined according to the changes in Modified Rankin Scale. RESULTS: Overall, 145 patients had improved/complete recovery, 73 had no change, and 29 had worsening conditions or died during the in-clinic period. A univariate analysis showed that baseline characteristics including age, CRP, blood glucose level, systolic blood pressure, and admission NIHSS were significantly different (p < 0.05) among patients with different clinical outcome. A further multivariate analysis was then performed. Variables associated with poor clinical outcome (worsening/death) (p < 0.1) were included in the logistic regression model. Four parameters were retained in the model: Age, CRP, Blood glucose level, and Systolic blood pressure (ACBS). To allow a convenient usage of the ACBS classifier, the parameters were put into a scoring system, and the score at 7.7 was chosen as a cut-off. The ROC curve of this ACBS classifier has an area under the curve (AUC) of 0.7788, higher than other individual parameters. The ACBS classifier provided enhanced sensitivity of 69.2% and specificity of 74.3%. CONCLUSION: The ACBS classifier provided a satisfactory power in estimating the patients' clinical outcome. After further validating, the classifier may provide important information to clinicians for making clinical decisions.