scholarly journals DIAGNOSTIC ACCURACY OF INTERLIMB DIFFERENCES OF ULTRASONOGRAPHIC SUBCUTANEOUS TISSUE THICKNESS MEASUREMENTS IN BREAST CANCER-RELATED ARM LYMPHEDEMA

Lymphology ◽  
2019 ◽  
Vol 52 (1) ◽  
Author(s):  
E Giray ◽  
I Yagcl
Keyword(s):  
Breast Cancer ◽  
Diagnostic Accuracy ◽  
Subcutaneous Tissue ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Tissue Thickness ◽  
Assessment And Treatment ◽  
Arm Lymphedema ◽  
Sensitivity Specificity ◽  
Thickness Measurements

Use of ultrasound as an assessment technique for lymphedema has been increasing with measurement of subcutaneous tissue thickness used for both assessment and treatment outcome. Reliability of ultrasound examination of the thickness of the skin and subcutaneous tissue have been studied. However, interlimb differences of ultrasonographic subcutaneous tissue thickness have not been explored. This study aimed to establish diagnostic accuracy of interlimb differences of ultrasonographic subcutaneous tissue thickness measurements in breast cancer-related arm lymphedema. We compared the truncated cone method by using circumference measurements and interlimb differences of ultrasonographic subcutaneous tissue thickness measurements to evaluate the diagnostic accuracy of interlimb differences of ultrasonographic subcutaneous tissue thickness measurements. Sensitivity, specificity, receiver-operating characteristic (ROC) curve, and area under the curve (AUC) were used. Analysis of ROC curves yielded area under the curve (AUC) of 0.804 (p=0.002). ROC analysis identified 0.17cm as the cut-point for differentiating between tissue with and without lymphedema resulting in a sensitivity of 79.3% and specificity of 69.2%.

scholarly journals Inflammatory Breast Carcinoma: Elevated microRNA miR-181b-5p and Reduced miR-200b-3p, miR-200c-3p, and miR-203a-3p Expression as Potential Biomarkers with Diagnostic Value

Biomolecules ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1059
Author(s):  
Sarah Atef Fahim ◽  
Mahmoud Salah Abdullah ◽  
Nancy A. Espinoza-Sánchez ◽  
Hebatallah Hassan ◽  
Ayman M. Ibrahim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Diagnostic Accuracy ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Diagnostic Value ◽  
Differentially Expressed Mirnas ◽  
E Box ◽  
Aggressive Breast Cancer ◽  
Potential Biomarkers

Inflammatory breast cancer (IBC) is a rare yet aggressive breast cancer variant, associated with a poor prognosis. The major challenge for IBC is misdiagnosis due to the lack of molecular biomarkers. We profiled dysregulated expression of microRNAs (miRNAs) in primary samples of IBC and non-IBC tumors using human breast cancer miRNA PCR array. We discovered that 28 miRNAs were dysregulated (10 were upregulated, while 18 were underexpressed) in IBC vs. non-IBC tumors. We identified 128 hub genes, which are putative targets of the differentially expressed miRNAs and modulate important cancer biological processes. Furthermore, our qPCR analysis independently verified a significantly upregulated expression of miR-181b-5p, whereas a significant downregulation of miR-200b-3p, miR-200c-3p, and miR-203a-3p was detected in IBC tumors. Receiver operating characteristic (ROC) curves implied that the four miRNAs individually had a diagnostic accuracy in discriminating patients with IBC from non-IBC and that miR-203a-3p had the highest diagnostic value with an AUC of 0.821. Interestingly, a combination of miR-181b-5p, miR-200b-3p, and miR-200c-3p robustly improved the diagnostic accuracy, with an area under the curve (AUC) of 0.897. Intriguingly, qPCR revealed that the expression of zinc finger E box-binding homeobox 2 (ZEB2) mRNA, the putative target of miR-200b-3p, miR-200c-3p, and miR-203a-3p, was upregulated in IBC tumors. Overall, this study identified a set of miRNAs serving as potential biomarkers with diagnostic relevance for IBC.

scholarly journals Comparison of biparametric and multiparametric MRI in the diagnosis of prostate cancer

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Lili Xu ◽  
Gumuyang Zhang ◽  
Bing Shi ◽  
Yanhan Liu ◽  
Tingting Zou ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Multiparametric Mri ◽  
Dce Mri ◽  
Prostate Imaging ◽  
The Difference ◽  
Sensitivity Specificity

Abstract Purpose To compare the diagnostic accuracy of biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) for prostate cancer (PCa) and clinically significant prostate cancer (csPCa) and to explore the application value of dynamic contrast-enhanced (DCE) MRI in prostate imaging. Methods and materials This study retrospectively enrolled 235 patients with suspected PCa in our hospital from January 2016 to December 2017, and all lesions were histopathologically confirmed. The lesions were scored according to the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2). The bpMRI (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI]/apparent diffusion coefficient [ADC]) and mpMRI (T2WI, DWI/ADC and DCE) scores were recorded to plot the receiver operating characteristic (ROC) curves. The area under the curve (AUC), accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) for each method were calculated and compared. The patients were further stratified according to bpMRI scores (bpMRI ≥3, and bpMRI = 3, 4, 5) to analyse the difference in DCE MRI between PCa and non-PCa lesions (as well as between csPCa and non-csPCa). Results The AUC values for the bpMRI and mpMRI protocols for PCa were comparable (0.790 [0.732–0.840] and 0.791 [0.733–0.841], respectively). The accuracy, sensitivity, specificity, PPV and NPV of bpMRI for PCa were 76.2, 79.5, 72.6, 75.8, and 76.6%, respectively, and the values for mpMRI were 77.4, 84.4, 69.9, 75.2, and 80.6%, respectively. The AUC values for the bpMRI and mpMRI protocols for the diagnosis of csPCa were similar (0.781 [0.722–0.832] and 0.779 [0.721–0.831], respectively). The accuracy, sensitivity, specificity, PPV and NPV of bpMRI for csPCa were 74.0, 83.8, 66.9, 64.8, and 85.0%, respectively; and 73.6, 87.9, 63.2, 63.2, and 87.8%, respectively, for mpMRI. For patients with bpMRI scores ≥3, positive DCE results were more common in PCa and csPCa lesions (both P = 0.001). Further stratification analysis showed that for patients with a bpMRI score = 4, PCa and csPCa lesions were more likely to have positive DCE results (P = 0.003 and P < 0.001, respectively). Conclusion The diagnostic accuracy of bpMRI is comparable with that of mpMRI in the detection of PCa and the identification of csPCa. DCE MRI is helpful in further identifying PCa and csPCa lesions in patients with bpMRI ≥3, especially bpMRI = 4, which may be conducive to achieving a more accurate PCa risk stratification. Rather than omitting DCE, we think further comprehensive studies are required for prostate MRI.

scholarly journals The Potential Diagnostic Accuracy of Circulating MicroRNAs for Leukemia: A Meta-Analysis

2021 ◽  
Vol 20 ◽  
pp. 153303382110119
Author(s):  
Wen-Ting Zhang ◽  
Guo-Xun Zhang ◽  
Shuai-Shuai Gao
Keyword(s):  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Subgroup Analysis ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Circulating Micrornas ◽  
Sensitivity Specificity

Background: Leukemia is a common malignant disease in the human blood system. Many researchers have proposed circulating microRNAs as biomarkers for the diagnosis of leukemia. We conducted a meta-analysis to evaluate the diagnostic accuracy of circulating miRNAs in the diagnosis of leukemia. Methods: A comprehensive literature search (updated to October 13, 2020) in PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang database and China National Knowledge Infrastructure (CNKI) was performed to identify eligible studies. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) for diagnosing leukemia were pooled for both overall and subgroup analysis. The meta-regression and subgroup analysis were performed to explore heterogeneity and Deeks’ funnel plot was used to assess publication bias. Results: 49 studies from 22 publications with a total of 3,489 leukemia patients and 2,756 healthy controls were included in this meta-analysis. The overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the curve were 0.83, 0.92, 10.8, 0.18, 59 and 0.94, respectively. Subgroup analysis shows that the microRNA clusters of plasma type could carry out a better diagnostic accuracy of leukemia patients. In addition, publication bias was not found. Conclusions: Circulating microRNAs can be used as a promising noninvasive biomarker in the early diagnosis of leukemia.

Diagnostic accuracy of enthesis ultrasound in the diagnosis of early spondyloarthritis

2010 ◽  
Vol 70 (3) ◽  
pp. 434-439 ◽  
Author(s):  
Eugenio de Miguel ◽  
Santiago Muñoz-Fernández ◽  
Concepción Castillo ◽  
Tatiana Cobo-Ibáñez ◽  
Emilio Martín-Mola
Keyword(s):  
New York ◽  
Diagnostic Accuracy ◽  
Statistical Significance ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Controlled Study ◽  
Diagnostic Classification ◽  
Hla B27 ◽  
Cross Sectional ◽  
Ultrasound Score

ObjectiveTo determine the sensitivity and specificity of enthesis ultrasound for the diagnostic classification of early spondyloarthritis.MethodsA cross-sectional, blinded and controlled study. Standardised bilateral ultrasound of six entheses (Madrid sonography enthesitis index (MASEI)) was performed. Accepted diagnostic classification criteria were used as the gold standard. Validity was analysed by receiver operating characteristic (ROC) curves. Values of p<0.05 were considered significant.Results113 early spondyloarthritis patients were included (58 women/55 men), 57 non-inflammatory control individuals (29 women/28 men) and 24 inflammatory control individuals (11 women/13 men). The evolution time of spondyloarthritis was 10.9±7.1 months. At least some grade of sacroiliitis on x-ray was present in 59 patients, but only five fulfilled the radiographic sacroiliitis New York criteria. Human leucocyte antigen B27 (HLA-B27) was positive in 42% of patients. No statistical differences were found for the enthesis score among diagnostic spondyloarthritis subtypes form of presentation (axial, peripheral or mixed) or HLA-B27 positivity. The MASEI score achieved statistical significance for gender. The ultrasound score was 23.36±11.40 (mean±SD) in spondyloarthritis patients and 12.26±6.85 and 16.04±9.94 in the non-inflammatory and inflammatory control groups (p<0.001), respectively. The ROC area under the curve was 0.82, and a cut-off point of ≥20 points achieved a likelihood ratio of 5.30 and a specificity of 89.47%.ConclusionsEntheses are affected early in spondyloarthritis, and the incidence of involvement is higher in men and independent of the spondyloarthritis diagnostic subtype, HLA-B27 status or presentation pattern. The enthesis ultrasound score seems to have diagnostic accuracy and may be useful for improving the diagnostic accuracy of early spondyloarthritis.

scholarly journals Identification of the most specific markers to differentiate primary pulmonary carcinoma from metastatic gastrointestinal carcinoma to the lung

2022 ◽  
Vol 17 (1) ◽  
Author(s):  
Bachar Alabdullah ◽  
Amir Hadji-Ashrafy
Keyword(s):  
Gastrointestinal Tract ◽  
Predictive Value ◽  
Regression Models ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Multivariate Models ◽  
Gastrointestinal Carcinoma ◽  
Lung Tumours ◽  
Napsin A ◽  
Sensitivity Specificity

Abstract Background A number of biomarkers have the potential of differentiating between primary lung tumours and secondary lung tumours from the gastrointestinal tract, however, a standardised panel for that purpose does not exist yet. We aimed to identify the smallest panel that is most sensitive and specific at differentiating between primary lung tumours and secondary lung tumours from the gastrointestinal tract. Methods A total of 170 samples were collected, including 140 primary and 30 non-primary lung tumours and staining for CK7, Napsin-A, TTF1, CK20, CDX2, and SATB2 was performed via tissue microarray. The data was then analysed using univariate regression models and a combination of multivariate regression models and Receiver Operating Characteristic (ROC) curves. Results Univariate regression models confirmed the 6 biomarkers’ ability to independently predict the primary outcome (p < 0.001). Multivariate models of 2-biomarker combinations identified 11 combinations with statistically significant odds ratios (ORs) (p < 0.05), of which TTF1/CDX2 had the highest area under the curve (AUC) (0.983, 0.960–1.000 95% CI). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 75.7, 100, 100, and 37.5% respectively. Multivariate models of 3-biomarker combinations identified 4 combinations with statistically significant ORs (p < 0.05), of which CK7/CK20/SATB2 had the highest AUC (0.965, 0.930–1.000 95% CI). The sensitivity, specificity, PPV, and NPV were 85.1, 100, 100, and 41.7% respectively. Multivariate models of 4-biomarker combinations did not identify any combinations with statistically significant ORs (p < 0.05). Conclusions The analysis identified the combination of CK7/CK20/SATB2 to be the smallest panel with the highest sensitivity (85.1%) and specificity (100%) for predicting tumour origin with an ROC AUC of 0.965 (p < 0.001; SE: 0.018, 0.930–1.000 95% CI).

scholarly journals Arm lymphedema after treatment of breast cancer: Etiology, diagnosis, and management

2015 ◽  
Vol 01 (02) ◽  
pp. 077-083 ◽  
Author(s):  
Ashish Goel ◽  
Juhi Agarwal ◽  
Sandeep Mehta ◽  
Kapil Kumar
Keyword(s):  
Breast Cancer ◽  
Solid Phase ◽  
Subcutaneous Tissue ◽  
Fluid Phase ◽  
Team Work ◽  
Treatment Modalities ◽  
Cancer Etiology ◽  
Complete Decongestive Therapy ◽  
Arm Lymphedema ◽  
Decongestive Therapy

ABSTRACTBreast cancer related lymphedema (BCRL) is a chronic debilitating condition seen after treatment of breast cancer. The overall incidence varies from 20% to 56% in all patients treated for breast cancer. Every patient is at a lifelong risk for BCRL and the risk goes on increasing as the followup period increases. Locoregional treatment including surgery or radiotherapy is the most common risk factor for development of arm lymphedema. There are two phases of arm lymphedema. There is increased fluid accumulation in the fluid phase of lymphedema which later on goes into the solid phase where fat and fibrotic tissue is deposited in the subcutaneous tissue. The treatment of BCRL is a challenge both for the patient and the treating surgeon and it needs multidisciplinary team work to be successful. Non-surgical treatment modalities include complete decongestive therapy (CDT) and pneumatic compression therapy. Surgery for BCRL is usually undertaken as a salvage modality after failure of conservative approaches. The surgical spectrum for BCRL varies from extensive excisional operations which were commonly done in the past to newer methods like suction assisted protein lipectomy, lymphatic reconstruction and vascular lymph node transfer (VLNT) using super-microsurgical techniques. There is no consensus regarding the preference of one procedure over other due to lack of randomised control trials. It is however suggested to do lymphovenous anastomosis and complete decongestive therapy for early cases in fluid phase; while patients in the solid phase may be treated with a combination of liposuction with CDT or VLNT alone.

scholarly journals The role of red cell distribution width in the differential diagnosis of iron deficiency anemia and non-transfusion dependent thalassemia patients

2018 ◽  
Vol 10 (3) ◽  
Author(s):  
Pokpong Piriyakhuntorn ◽  
Adisak Tantiworawit ◽  
Thanawat Rattanathammethee ◽  
Chatree Chai-Adisaksopha ◽  
Ekarat Rattarittamrong ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Microcytic Anemia ◽  
Deficiency Anemia ◽  
Operating Characteristics ◽  
Training Set ◽  
Distribution Width ◽  
Validation Set ◽  
Sensitivity Specificity

This study aims to find the cut-off value and diagnostic accuracy of the use of RDW as initial investigation in enabling the differentiation between IDA and NTDT patients. Patients with microcytic anemia were enrolled in the training set and used to plot a receiving operating characteristics (ROC) curve to obtain the cut-off value of RDW. A second set of patients were included in the validation set and used to analyze the diagnostic accuracy. We recruited 94 IDA and 64 NTDT patients into the training set. The area under the curve of the ROC in the training set was 0.803. The best cut-off value of RDW in the diagnosis of NTDT was 21.0% with a sensitivity and specificity of 81.3% and 55.3% respectively. In the validation set, there were 34 IDA and 58 NTDT patients using the cut-off value of >21.0% to validate. The sensitivity, specificity, positive predictive value and negative predictive value were 84.5%, 70.6%, 83.1% and 72.7% respectively. We can therefore conclude that RDW >21.0% is useful in differentiating between IDA and NTDT patients with high diagnostic accuracy

scholarly journals The diagnostic utility of the “Thwaites’ system” and “lancet consensus scoring system” in tuberculous vs. non-tuberculous subacute and chronic meningitis: multicenter analysis of 395 adult patients

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Tarek Sulaiman ◽  
Sai Medi ◽  
Hakan Erdem ◽  
Seniha Senbayrak ◽  
Derya Ozturk-Engin ◽  
...  
Keyword(s):  
Bacterial Meningitis ◽  
Diagnostic Accuracy ◽  
Scoring System ◽  
Area Under The Curve ◽  
Receiver Operating Curve ◽  
Chronic Meningitis ◽  
Multicenter Analysis ◽  
Consensus Scoring ◽  
Sensitivity Specificity ◽  
Management Challenge

Abstract Background Tuberculous meningitis (TBM) represents a diagnostic and management challenge to clinicians. The “Thwaites’ system” and “Lancet consensus scoring system” are utilized to differentiate TBM from bacterial meningitis but their utility in subacute and chronic meningitis where TBM is an important consideration is unknown. Methods A multicenter retrospective study of adults with subacute and chronic meningitis, defined by symptoms greater than 5 days and less than 30 days for subacute meningitis (SAM) and greater than 30 days for chronic meningitis (CM). The “Thwaites’ system” and “Lancet consensus scoring system” scores and the diagnostic accuracy by sensitivity, specificity, and area under the curve of receiver operating curve (AUC-ROC) were calculated. The “Thwaites’ system” and “Lancet consensus scoring system” suggest a high probability of TBM with scores ≤4, and with scores of ≥12, respectively. Results A total of 395 patients were identified; 313 (79.2%) had subacute and 82 (20.8%) with chronic meningitis. Patients with chronic meningitis were more likely caused by tuberculosis and had higher rates of HIV infection (P < 0.001). A total of 162 patients with TBM and 233 patients with non-TBM had unknown (140, 60.1%), fungal (41, 17.6%), viral (29, 12.4%), miscellaneous (16, 6.7%), and bacterial (7, 3.0%) etiologies. TMB patients were older and presented with lower Glasgow coma scores, lower CSF glucose and higher CSF protein (P < 0.001). Both criteria were able to distinguish TBM from bacterial meningitis; only the Lancet score was able to differentiate TBM from fungal, viral, and unknown etiologies even though significant overlap occurred between the etiologies (P < .001). Both criteria showed poor diagnostic accuracy to distinguish TBM from non-TBM etiologies (AUC-ROC was <. 5), but Lancet consensus scoring system was fair in diagnosing TBM (AUC-ROC was .738), sensitivity of 50%, and specificity of 89.3%. Conclusion Both criteria can be helpful in distinguishing TBM from bacterial meningitis, but only the Lancet consensus scoring system can help differentiate TBM from meningitis caused by fungal, viral and unknown etiologies even though significant overlap occurs and the overall diagnostic accuracy of both criteria were either poor or fair.

Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs

2021 ◽  
pp. 20200513
Author(s):  
Su-Jin Jeon ◽  
Jong-Pil Yun ◽  
Han-Gyeol Yeom ◽  
Woo-Sang Shin ◽  
Jong-Hyun Lee ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cone Beam Ct ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Learning System ◽  
Operating Characteristics ◽  
Panoramic Radiographs ◽  
Test Sets ◽  
Sensitivity Specificity ◽  
Deep Learning Model

Objective: The aim of this study was to evaluate the use of a convolutional neural network (CNN) system for predicting C-shaped canals in mandibular second molars on panoramic radiographs. Methods: Panoramic and cone beam CT (CBCT) images obtained from June 2018 to May 2020 were screened and 1020 patients were selected. Our dataset of 2040 sound mandibular second molars comprised 887 C-shaped canals and 1153 non-C-shaped canals. To confirm the presence of a C-shaped canal, CBCT images were analyzed by a radiologist and set as the gold standard. A CNN-based deep-learning model for predicting C-shaped canals was built using Xception. The training and test sets were set to 80 to 20%, respectively. Diagnostic performance was evaluated using accuracy, sensitivity, specificity, and precision. Receiver-operating characteristics (ROC) curves were drawn, and the area under the curve (AUC) values were calculated. Further, gradient-weighted class activation maps (Grad-CAM) were generated to localize the anatomy that contributed to the predictions. Results: The accuracy, sensitivity, specificity, and precision of the CNN model were 95.1, 92.7, 97.0, and 95.9%, respectively. Grad-CAM analysis showed that the CNN model mainly identified root canal shapes converging into the apex to predict the C-shaped canals, while the root furcation was predominantly used for predicting the non-C-shaped canals. Conclusions: The deep-learning system had significant accuracy in predicting C-shaped canals of mandibular second molars on panoramic radiographs.

scholarly journals Circular RNA FUNDC1 improves prediction of stroke associated infection in acute ischemic stroke patients with high risk

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Lei Zuo ◽  
Cai Li ◽  
Juan Zu ◽  
Honghong Yao ◽  
Fuling Yan
Keyword(s):  
Ischemic Stroke ◽  
High Risk ◽  
Acute Ischemic Stroke ◽  
Risk Model ◽  
Area Under The Curve ◽  
Preventive Treatment ◽  
Roc Curves ◽  
Circular Rna ◽  
Diagnosis And Prognosis ◽  
Sensitivity Specificity

Abstract Identifying those patients who were at high risk of stroke associated infection (SAI) for preventive antibiotic therapy was imperative for patients’ benefits, thus improving prediction of SAI was critical for all acute ischemic stroke (AIS) patients. Circular RNA FUNDC1 (circFUNDC1) has been reported to be the diagnosis and prognosis biomarker of AIS. Therefore, the present study aimed to figure out whether circFUNDC1 could be the potential predictor of SAI that could help to guide preventive treatment. In total, 68 patients were included in the study, 26 of which had infection and 42 without. Copy number of circFUNDC1 in plasma were quantified by quantitative real-time polymerase chain reaction (qPCR). Platelet spike-in experiment and correlation analysis were conducted to explore possible origins of circFUNDC1 in plasma. A significantly elevated level of circFUNDC1 was found in SAI patients compared with not infected AIS patients (P=0.0258). Receiver operating characteristic (ROC) curves demonstrated the prediction significance of circFUNDC1, with the area under the curve (AUC) at 0.6612 and sensitivity, specificity at 69.23%, 61.90% respectively in predicting SAI. Then, when adding circFUNDC1 in the risk model, the AUC increased from 0.7971 in model A to 0.8038 in model B. Additionally, positive correlation was observed between circFUNDC1 level and neutrophils counts. WBC and neutrophil ratios were significantly elevated in SAI patients compared with non-SAI patients. Therefore, circFUNDC1 could be used to construct a risk model for the prediction of SAI that is beneficial for AIS patients’ preventive treatment.

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