Objective To systematically evaluate the effect of arm sling on shoulder subluxation in stroke patients with hemiplegia. METHODS CNKI, Wanfang, VIP, PubMed, Web of Science, Embase, Cochrane Library, OVID, EBM Reviews, Best Practice, ACP Journal Club, and Practice Guidline were searched from establishment to March 2023. The literature on randomized controlled trials of arm sling on gait or balance in post-stroke patients with hemiplegia were included. RevMan 5.4.1 software was used for meta-analysis. Results A total of 13 articles were included, including 691 subjects, 343 in the experimental group, and 348 in the control group. The meta-analysis results showed that patients wearing the boom arm were effective in improving the recovery of upper extremity function [mean difference (MD)=8.12, 95% confidence interval (CI) (2.39, 11.60), P＜0.000 01], relieving pain due to shoulder subluxation [MD=−1.13, 95%CI (−1.70, −0.56), P=0.000 1], and enhancement of patients’ quality of life in daily activities [MD=15.07, 95%CI (3.24, 26.90), P=0.01], all of which were superior to the control group. However, there was no statistically significant difference between the two groups in terms of Apnea-Hypopnea Index [MD=−1.86, 95%CI (−3.79, 0.06), P=0.06], 6 min walking test [MD=−0.51, 95%CI (−18.52, 17.49), P=0.96], 10 meter walk time [MD=0.00, 95%CI (−0.06, 0.06), P=0.91], heart rate [MD=−0.22, 95%CI (−5.10, 4.27), P=0.93], and Berg balance scale [MD=−2.53, 95%CI (−8.17, 3.10), P=0.38]. Conclusion The use of arm sling can effectively improve patients’ quality of life, functional recovery of the upper limbs and reduce pain, providing an evidence-based basis for healthcare professionals to treat patients with proven treatment modalities.
Objective To understand the quality of life of patients with acute mild to moderate ischemic stroke one year after stroke, analyze the factors affecting their quality of life, and provide a scientific basis for improving their health-related quality of life. Methods This study included patients who were diagnosed with acute mild to moderate ischemic stroke between March 2019 and March 2021 in four hospitals in Nanchang. Sociodemographic information and relevant clinical data were collected during hospitalization. The EQ-5D-5L questionnaire was administered to assess health-related quality of life one year after discharge. The Mann-Whitney U test (for two groups) and Kruskal-Wallis one-way ANOVA (for multiple groups) were used to analyze differences in utility scores among various factors. A Tobit regression model was built to investigate the factors influencing quality of life one-year post-stroke. Results A total of 1 181 patients participated in the study, including 791 males (66.98%) and 390 females (33.02%), with an average age of 63.7±10.9 years. Health-related quality of life data collected one year after the stroke revealed that 22.69% of patients experienced pain/discomfort, 17.27% suffered anxiety/depression, 15.66% had mobility issues, 10.33% had difficulties with daily activities, and 8.64% had trouble with self-care. Tobit regression results showed that age (β=−0.263, 95%CI −0.327 to −0.198), gender (β=−0.134, 95%CI −0.189 to −0.080), previous hypertension (β=−0.068, 95%CI −0.120 to −0.016), previous dyslipidemia (β=−0.068, 95%CI −0.126 to −0.011), admission NIHSS score (β=−0.158, 95%CI −0.198 to −0.118), and discharge mRS score (β=−0.193, 95%CI −0.250 to −0.136) were negatively associated with health utility values. Current employment status (β=0.141, 95%CI 0.102 to 0.181) and admission GCS score (β=0.209, 95%CI 0.142 to 0.276) were positively correlated with health utility values. Conclusion One year after an acute mild to moderate ischemic stroke, patients commonly face pain/discomfort and anxiety/depression. Factors affecting overall quality of life include age, sex, current employment status, previous hypertension, previous dyslipidemia, admission NIHSS score, admission GCS score, and discharge mRS score. Clinically, developing scientifically sound and reasonable rehabilitation plans post-discharge is crucial for improving long-term quality of life.
Objective To investigate the relationship between age-adjusted Charlson comorbidity index (aCCI) and ischemic stroke in patients with ophthalmic artery occlusion (OAO) or retinal artery occlusion (RAO). MethodsA single center retrospective cohort study. Seventy-four patients with OAO or RAO diagnosed by ophthalmology examination in Shenzhen Second People's Hospital from June 2004 to December 2020 were included in the study. The baseline information of patients were collected and aCCI was used to score the patients’ comorbidity. The outcome was ischemic stroke. The median duration of follow-up was 1 796.5 days. According to the maximum likelihood ratio of the two-piecewise COX regression model and the recursive algorithm, the aCCI inflection point value was determined to be 6, and the patients were divided into low aCCI group (＜6 points) and high aCCI group (≥6 points). A Cox regression model was used to quantify the association between baseline aCCI and ischemic stroke. ResultsAmong the 74 patients, 53 were males and 21 were females, with the mean age of (55.22±14.18) (19-84) years. There were 9 patients of OAO and 65 patients of RAO. The aCCI value ranges from 1 to 10 points, with a median of 3 points. There were 63 patients (85.14%, 63/74) in the low aCCI group and 11 patients (14.86%, 11/74) in the high aCCI group. Since 2 patients could not determine the time from baseline to the occurrence of outcome events, 72 patients were included for Cox regression analysis. The results showed that 16 patients (22.22%, 16/72) had ischemic stroke in the future. The baseline aCCI in the low aCCI group was significantly associated with ischemic stroke [hazard ratio (HR)=1.76, 95% confidence interval (CI) 1.21-2.56, P=0.003], and for every 1 point increase in baseline aCCI, the risk of future ischemic stroke increased by 76% on average. The baseline aCCI in the high aCCI group had no significant correlation with the ischemic stroke (HR=0.66, 95%CI 0.33-1.33, P=0.247). ConclusionsaCCI score is an important prognostic information for patients with OAO or RAO. A higher baseline aCCI score predicts a higher risk of ischemic stroke, and the association has a saturation effect.
Ischemic stroke (IS) is one of the important diseases threatening human health. The occurrence and development of IS can trigger a series of complex pathophysiological changes, including damage to the blood-brain barrier, ion imbalance, oxidative stress, mitochondrial damage, which ultimately lead to the apoptosis and necrosis of nerve cells in the ischemic area. Impaired blood-brain barrier is a key factor for cerebral edema, hemorrhagic transformation and poor prognosis in patients with IS, and neuroinflammatory response plays an important role in the damage and repair of the blood-brain barrier. This article mainly focuses on the neuroinflammatory response mediated by glial cells, pro-inflammatory cytokines and matrix metalloproteinases and the related mechanisms of IS blood-brain barrier damage and repair, in order to provide new directions for the treatment of IS.
As a kind of disease with high incidence rate, high mortality, high recurrence rate and high disability rate, stroke has become one of the most serious disease burdens in China. Rapid diagnosis and treatment of stroke can effectively improve the outcome of patients and reduce the psychological and economic burden of patients’ families and society. In recent years, with the rapid development of artificial intelligence technology,this technology can effectively improve daily diagnosis and treatment efficiency. This paper focuses on the application of artificial intelligence technology to the diagnosis, treatment and outcome prediction of stroke, aiming to provide ideas for further guiding precision medicine.
Diabetes mellitus patients have the characteristics of higher morbidity of ischemic stroke, severe symptoms, more recurrent stroke and higher mortality. Current studies have shown that stroke patients with or without diabetes mellitus have different pathophysiological mechanisms during stroke progress. Accordingly, treatment that is beneficial to non-diabetes mellitus patients may not be beneficial to diabetes mellitus stroke patients. This article reviews the current research status of pathophysiological mechanism of diabetes mellitus complicated with ischemic stroke, and provides reference for the relevant research of drug intervention in diabetes mellitus patients complicated with stroke.
Clinically, non-contrastive computed tomography (NCCT) is used to quickly diagnose the type and area of stroke, and the Alberta stroke program early computer tomography score (ASPECTS) is used to guide the next treatment. However, in the early stage of acute ischemic stroke (AIS), it’s difficult to distinguish the mild cerebral infarction on NCCT with the naked eye, and there is no obvious boundary between brain regions, which makes clinical ASPECTS difficult to conduct. The method based on machine learning and deep learning can help physicians quickly and accurately identify cerebral infarction areas, segment brain areas, and operate ASPECTS quantitative scoring, which is of great significance for improving the inconsistency in clinical ASPECTS. This article describes current challenges in the field of AIS ASPECTS, and then summarizes the application of computer-aided technology in ASPECTS from two aspects including machine learning and deep learning. Finally, this article summarizes and prospects the research direction of AIS-assisted assessment, and proposes that the computer-aided system based on multi-modal images is of great value to improve the comprehensiveness and accuracy of AIS assessment, which has the potential to open up a new research field for AIS-assisted assessment.
Stroke has the characteristics of high incidence rate, high mortality rate and high disability rate. Most patients may have some motor dysfunction after stroke, which greatly affects the normal life of patients. As a common sequela after stroke, foot drop seriously affects the walking gait of patients, limits the activities of patients, and reduces their quality of life. In recent years, repetitive peripheral magnetic stimulation (rPMS) has been used more and more in the rehabilitation of various diseases. Because rPMS is noninvasive, affordable and effective, it is accepted by many patients. This article reviews the research progress of rPMS for foot drop after stroke.