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Diagnostics
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Risk Factors for Acute Ischemic Stroke
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Risk Factors for Acute Ischemic Stroke

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 7987

Special Issue Editor

Prof. Dr. Lung Chan

E-Mail Website
Guest Editor
Department of Neurology, Shuang-Ho Hospital, Taipei Medical University, New Taipei 23561, Taiwan
Interests: stroke prevention; early diagnosis; brain computer tomography; magnetic resonance image; ultrasound; emergency decision making

Special Issue Information

Dear Colleagues,

Acute ischemic stroke is one of the major causes of disability and death worldwide. Faster diagnoses and emergency interventional treatment remain the best approaches for improving the outcomes of patients. Currently, the recognized risk factors for acute ischemic stroke include age, high blood pressure, atrial fibrillation, diabetes mellitus, congestive heart failure, etc.

This Special Issue aims to collect the recent advances in the pathophysiology underlying acute ischemic stroke; the risk factors for ischemic stroke; stroke presentation; the diagnosing and monitoring protocols that are critical to patient recovery.

Prof. Dr. Lung Chan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ischemic stroke
  • outcome
  • risk factor
  • stroke prevention
  • early diagnosis
  • brain computer tomography
  • magnetic resonance image
  • ultrasound
  • emergency decision making

Published Papers (4 papers)

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Research

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16 pages, 2439 KiB  
Article
The Diagnostic Value of Gut Microbiota Analysis for Post-Stroke Sleep Disorders
by Huijia Xie, Jiaxin Chen, Qionglei Chen, Yiting Zhao, Jiaming Liu, Jing Sun and Xuezhen Hu
Diagnostics 2023, 13(18), 2970; https://doi.org/10.3390/diagnostics13182970 - 17 Sep 2023
Viewed by 1479
Abstract
Background: Gut microbiota have been associated with many psychiatric disorders. However, the changes in the composition of gut microbiota in patients with post-stroke sleep disorders (PSSDs) remain unclear. Here, we determined the gut microbial signature of PSSD patients. Methods: Fecal samples of 205 [...] Read more.
Background: Gut microbiota have been associated with many psychiatric disorders. However, the changes in the composition of gut microbiota in patients with post-stroke sleep disorders (PSSDs) remain unclear. Here, we determined the gut microbial signature of PSSD patients. Methods: Fecal samples of 205 patients with ischemic stroke were collected within 24 h of admission and were further analyzed using 16 s RNA gene sequencing followed by bioinformatic analysis. The diversity, community composition, and differential microbes of gut microbiota were assessed. The outcome of sleep disorders was determined by the Pittsburgh Sleep Quality Index (PSQI) at 3 months after admission. The diagnostic performance of microbial characteristics in predicting PSSDs was assessed by receiver operating characteristic (ROC) curves. Results: Our results showed that the composition and structure of microbiota in patients with PSSDs were different from those without sleep disorders (PSNSDs). Moreover, the linear discriminant analysis effect size (LEfSe) showed significant differences in gut-associated bacteria, such as species of Streptococcus, Granulicatella, Dielma, Blautia, Paeniclostridium, and Sutterella. We further managed to identify the optimal microbiota signature and revealed that the predictive model with eight operational-taxonomic-unit-based biomarkers achieved a high accuracy in PSSD prediction (AUC = 0.768). Blautia and Streptococcus were considered to be the key microbiome signatures for patients with PSSD. Conclusions: These findings indicated that a specific gut microbial signature was an important predictor of PSSDs, which highlighted the potential of microbiota as a promising biomarker for detecting PSSD patients. Full article
(This article belongs to the Special Issue Risk Factors for Acute Ischemic Stroke)
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13 pages, 3678 KiB  
Article
Comparative Effectiveness of Two Models of Point-of-Care Ultrasound for Detection of Post-Void Residual Urine during Acute Ischemic Stroke: Preliminary Findings of Real-World Clinical Application
by Wan-Ling Chang, Shu-Hui Lai, Chu-Fang Cheng, Valeria Chiu and Shinn-Kuang Lin
Diagnostics 2023, 13(15), 2599; https://doi.org/10.3390/diagnostics13152599 - 4 Aug 2023
Viewed by 1508
Abstract
We conducted a comparative study of two models of point-of-care ultrasound devices for measuring post-void residual urine (PVRU). We prospectively enrolled 55 stroke inpatients who underwent both real-time B-mode ultrasound (Device A) and automated three-dimensional (3D) scanning ultrasound (Device B), with a total [...] Read more.
We conducted a comparative study of two models of point-of-care ultrasound devices for measuring post-void residual urine (PVRU). We prospectively enrolled 55 stroke inpatients who underwent both real-time B-mode ultrasound (Device A) and automated three-dimensional (3D) scanning ultrasound (Device B), with a total of 108 measurements. The median PVRU volume of Device B was 40 mL larger than that of Device A. The PVRU difference between the devices was positively and linearly correlated with PVRU. The correlation of PVRU volume between the devices was strong, but the agreement level was only moderate. Measurement deviations were observed in 43 (40%) and 11 (10%) measurements with Device B and Device A, respectively. The PVRU volume was low in spherical bladder shapes but sequentially increased in triangular, undefined, ellipsoid, and cuboid bladder shapes. Further comparison of 60 sets of PVRU without measurement deviations revealed higher agreements between the devices at correction coefficients of 0.52, 0.66, and 0.81 for PVRU volumes of <100, 100–200, and >200 mL, respectively. The automated 3D scanning ultrasound is more convenient for learning and scanning, but it exhibits larger measurement deviations. Real-time B-mode ultrasound accurately visualizes the urinary bladder but tends to underestimate the urinary bladder when the PVRU volume is large. Hence, real-time B-mode ultrasound with automated PVRU-based adjustment of calculation formulas may be a better solution for estimating bladder volume. Full article
(This article belongs to the Special Issue Risk Factors for Acute Ischemic Stroke)
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13 pages, 2140 KiB  
Article
XGBoost-Based Simple Three-Item Model Accurately Predicts Outcomes of Acute Ischemic Stroke
by Chen-Chih Chung, Emily Chia-Yu Su, Jia-Hung Chen, Yi-Tui Chen and Chao-Yang Kuo
Diagnostics 2023, 13(5), 842; https://doi.org/10.3390/diagnostics13050842 - 22 Feb 2023
Cited by 6 | Viewed by 2541
Abstract
An all-inclusive and accurate prediction of outcomes for patients with acute ischemic stroke (AIS) is crucial for clinical decision-making. This study developed extreme gradient boosting (XGBoost)-based models using three simple factors—age, fasting glucose, and National Institutes of Health Stroke Scale (NIHSS) scores—to predict [...] Read more.
An all-inclusive and accurate prediction of outcomes for patients with acute ischemic stroke (AIS) is crucial for clinical decision-making. This study developed extreme gradient boosting (XGBoost)-based models using three simple factors—age, fasting glucose, and National Institutes of Health Stroke Scale (NIHSS) scores—to predict the three-month functional outcomes after AIS. We retrieved the medical records of 1848 patients diagnosed with AIS and managed at a single medical center between 2016 and 2020. We developed and validated the predictions and ranked the importance of each variable. The XGBoost model achieved notable performance, with an area under the curve of 0.8595. As predicted by the model, the patients with initial NIHSS score > 5, aged over 64 years, and fasting blood glucose > 86 mg/dL were associated with unfavorable prognoses. For patients receiving endovascular therapy, fasting glucose was the most important predictor. The NIHSS score at admission was the most significant predictor for those who received other treatments. Our proposed XGBoost model showed a reliable predictive power of AIS outcomes using readily available and simple predictors and also demonstrated the validity of the model for application in patients receiving different AIS treatments, providing clinical evidence for future optimization of AIS treatment strategies. Full article
(This article belongs to the Special Issue Risk Factors for Acute Ischemic Stroke)
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Review

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15 pages, 1106 KiB  
Review
The Pathophysiology of Collateral Circulation in Acute Ischemic Stroke
by Marilena Mangiardi, Adriano Bonura, Gianmarco Iaccarino, Michele Alessiani, Maria Cristina Bravi, Domenica Crupi, Francesca Romana Pezzella, Sebastiano Fabiano, Enrico Pampana, Francesco Stilo, Guido Alfano and Sabrina Anticoli
Diagnostics 2023, 13(14), 2425; https://doi.org/10.3390/diagnostics13142425 - 20 Jul 2023
Cited by 2 | Viewed by 1961
Abstract
Cerebral collateral circulation is a network of blood vessels which stabilizes blood flow and maintains cerebral perfusion whenever the main arteries fail to provide an adequate blood supply, as happens in ischemic stroke. These arterial networks are able to divert blood flow to [...] Read more.
Cerebral collateral circulation is a network of blood vessels which stabilizes blood flow and maintains cerebral perfusion whenever the main arteries fail to provide an adequate blood supply, as happens in ischemic stroke. These arterial networks are able to divert blood flow to hypoperfused cerebral areas. The extent of the collateral circulation determines the volume of the salvageable tissue, the so-called “penumbra”. Clinically, this is associated with greater efficacy of reperfusion therapies (thrombolysis and thrombectomy) in terms of better short- and long-term functional outcomes, lower incidence of hemorrhagic transformation and of malignant oedema, and smaller cerebral infarctions. Recent advancements in brain imaging techniques (CT and MRI) allow us to study these anastomotic networks in detail and increase the likelihood of making effective therapeutic choices. In this narrative review we will investigate the pathophysiology, the clinical aspects, and the possible diagnostic and therapeutic role of collateral circulation in acute ischemic stroke. Full article
(This article belongs to the Special Issue Risk Factors for Acute Ischemic Stroke)
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