scholarly journals Potential Fluid Biomarkers and a Prediction Model for Better Recognition Between Multiple System Atrophy-Cerebellar Type and Spinocerebellar Ataxia

2021 ◽  
Vol 13 ◽  
Author(s):  
Shuo Guo ◽  
Bi Zhao ◽  
Yunfei An ◽  
Yu Zhang ◽  
Zirui Meng ◽  
...  
Keyword(s):  
Multiple System Atrophy ◽  
Prediction Model ◽  
Spinocerebellar Ataxia ◽  
Web Application ◽  
Age Of Onset ◽  
External Validation ◽  
Lasso Regression ◽  
Net Benefit ◽  
Cerebellar Type ◽  
Potential Fluid

ObjectiveThis study screened potential fluid biomarkers and developed a prediction model based on the easily obtained information at initial inspection to identify ataxia patients more likely to have multiple system atrophy-cerebellar type (MSA-C).MethodsWe established a retrospective cohort with 125 ataxia patients from southwest China between April 2018 and June 2020. Demographic and laboratory variables obtained at the time of hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) regression and logistic regression to construct a diagnosis score. The receiver operating characteristic (ROC) and decision curve analyses were performed to assess the accuracy and net benefit of the model. Also, independent validation using 25 additional ataxia patients was carried out to verify the model efficiency. Then the model was translated into a visual and operable web application using the R studio and Shiny package.ResultsFrom 47 indicators, five variables were selected and integrated into the prediction model, including the age of onset (AO), direct bilirubin (DBIL), aspartate aminotransferase (AST), eGFR, and synuclein-alpha. The prediction model exhibited an area under the curve (AUC) of 0.929 for the training cohort and an AUC of 0.917 for the testing cohort. The decision curve analysis (DCA) plot displayed a good net benefit for this model, and external validation confirmed its reliability. The model also was translated into a web application that is freely available to the public.ConclusionThe prediction model that was developed based on laboratory and demographic variables obtained from ataxia patients at admission to the hospital might help improve the ability to differentiate MSA-C from spinocerebellar ataxia clinically.

scholarly journals Clinical prediction of thrombectomy eligibility: A systematic review and 4-item decision tree

2018 ◽  
Vol 14 (5) ◽  
pp. 530-539 ◽  
Author(s):  
Gaia T Koster ◽  
T Truc My Nguyen ◽  
Erik W van Zwet ◽  
Bjarty L Garcia ◽  
Hannah R Rowling ◽  
...  
Keyword(s):  
Decision Tree ◽  
Prediction Model ◽  
External Validation ◽  
Facial Asymmetry ◽  
Decision Support Tool ◽  
Patient Characteristics ◽  
Group Lasso ◽  
Lasso Regression ◽  
Vessel Occlusion ◽  
Support Tool

Background A clinical large anterior vessel occlusion (LAVO)-prediction scale could reduce treatment delays by allocating intra-arterial thrombectomy (IAT)-eligible patients directly to a comprehensive stroke center. Aim To subtract, validate and compare existing LAVO-prediction scales, and develop a straightforward decision support tool to assess IAT-eligibility. Methods We performed a systematic literature search to identify LAVO-prediction scales. Performance was compared in a prospective, multicenter validation cohort of the Dutch acute Stroke study (DUST) by calculating area under the receiver operating curves (AUROC). With group lasso regression analysis, we constructed a prediction model, incorporating patient characteristics next to National Institutes of Health Stroke Scale (NIHSS) items. Finally, we developed a decision tree algorithm based on dichotomized NIHSS items. Results We identified seven LAVO-prediction scales. From DUST, 1316 patients (35.8% LAVO-rate) from 14 centers were available for validation. FAST-ED and RACE had the highest AUROC (both >0.81, p < 0.01 for comparison with other scales). Group lasso analysis revealed a LAVO-prediction model containing seven NIHSS items (AUROC 0.84). With the GACE (Gaze, facial Asymmetry, level of Consciousness, Extinction/inattention) decision tree, LAVO is predicted (AUROC 0.76) for 61% of patients with assessment of only two dichotomized NIHSS items, and for all patients with four items. Conclusion External validation of seven LAVO-prediction scales showed AUROCs between 0.75 and 0.83. Most scales, however, appear too complex for Emergency Medical Services use with prehospital validation generally lacking. GACE is the first LAVO-prediction scale using a simple decision tree as such increasing feasibility, while maintaining high accuracy. Prehospital prospective validation is planned.

scholarly journals Vertical pons hyperintensity and hot cross bun sign in cerebellar-type multiple system atrophy and spinocerebellar ataxia type 3

2020 ◽  
Author(s):  
Atsuhiko Sugiyama ◽  
Hajime Yokota ◽  
Yoshitaka Yamanaka ◽  
Hiroki Mukai ◽  
Tatsuya Yamamoto ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Multiple System Atrophy ◽  
Spinocerebellar Ataxia ◽  
High Intensity ◽  
Spinocerebellar Ataxia Type ◽  
Motor Symptoms ◽  
Spinocerebellar Ataxia Type 3 ◽  
Early Stages ◽  
Cerebellar Type ◽  
Type 3

Abstract Background The “hot cross bun” (HCB) sign, a cruciform hyperintensity in the pons on magnetic resonance imaging (MRI), has gradually been identified as a typical finding in multiple system atrophy, cerebellar-type (MSA-C). Few reports have evaluated the sensitivity of an HCB, including a cruciform hyperintensity and vertical line in the pons, which precedes a cruciform hyperintensity, in the early stages of MSA-C. Moreover, the difference in frequency and timing of appearance of an HCB between MSA-C and spinocerebellar ataxia type 3 (SCA3) has not been fully investigated.Methods This study investigated the time at which an HCB and orthostatic hypotension (OH) appeared in 41 patients with MSA-C, based on brain MRI and head-up tilt test. The MRI findings were compared with those of 26 patients with SCA3. The pontine signal findings on T2-weighted MRI were graded as 0 (no change), 1 (a vertical T2 high-intensity line), or 2 (a cruciform T2 high-intensity line), with grades 1 or 2 considered as an HCB. OH 30/15 was defined as a decrease in systolic blood pressure of > 30 mmHg or diastolic blood pressure of > 15 mmHg.Results Among the 24 patients with MSA-C within 2 years from the onset of motor symptoms, an HCB was detected in 91.7%, whereas OH 30/15 was present in 60.0%. Among the 36 patients with MSA-C within 3 years from the onset of motor symptoms, a grade 2 HCB was detected in 66.7% of those with MSA-C but in none of those with SCA-3.Conclusions HCB is a highly sensitive finding for MSA-C, even in the early stages of the disease. A grade 2 HCB in the early stage is an extremely specific finding for differentiating MSA-C from SCA-3.

scholarly journals The vertical pons hyperintensity and hot cross bun sign in cerebellar-type multiple system atrophy and spinocerebellar ataxia type 3

2020 ◽  
Author(s):  
Atsuhiko Sugiyama ◽  
Hajime Yokota ◽  
Yoshitaka Yamanaka ◽  
Hiroki Mukai ◽  
Tatsuya Yamamoto ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Multiple System Atrophy ◽  
Spinocerebellar Ataxia ◽  
High Intensity ◽  
Spinocerebellar Ataxia Type ◽  
Motor Symptoms ◽  
Spinocerebellar Ataxia Type 3 ◽  
Early Stages ◽  
Cerebellar Type ◽  
Type 3

Abstract Background The “hot cross bun” (HCB) sign, a cruciform hyperintensity in the pons on magnetic resonance imaging (MRI), has gradually been identified as a typical finding in multiple system atrophy, cerebellar-type (MSA-C). Few reports have evaluated the sensitivity of an HCB including a cruciform hyperintensity and vertical line in the pons, which precedes a cruciform hyperintensity, in the early stages of MSA-C. Moreover, the difference in frequency and timing of appearance of an HCB between MSA-C and spinocerebellar ataxia type 3 (SCA3) has not been fully investigated. Methods This study investigated the time at which an HCB and orthostatic hypotension (OH) appeared in 41 patients with MSA-C, based on brain MRI and head-up tilt test. The MRI findings were compared with those of 26 patients with SCA3. The pontine signal findings on T2-weighted MRI were graded as 0 (no change), 1 (a vertical T2 high-intensity line), or 2 (a cruciform T2 high-intensity line), with grades 1 or 2 considered as an HCB. OH 30/15 was defined as a decrease in systolic blood pressure of > 30 mmHg or diastolic blood pressure of > 15 mmHg. Results Among the 24 patients with MSA-C within 2 years from the onset of motor symptoms, an HCB was detected in 91.7%, whereas OH 30/15 was present in 60.0%. Among the 36 patients with MSA-C within 3 years from the onset of motor symptoms, a grade 2 HCB was detected in 66.7% of those with MSA-C but in none of those with SCA-3. Conclusions HCB is a highly sensitive finding for MSA-C, even in the early stages of the disease. A grade 2 HCB in the early stage is an extremely specific finding for differentiating MSA-C from SCA-3.

scholarly journals Diffusion Tensor Magnetic Resonance Imaging for Differentiating Multiple System Atrophy Cerebellar Type and Spinocerebellar Ataxia Type 3

2019 ◽  
Vol 9 (12) ◽  
pp. 354 ◽  
Author(s):  
Chi-Wen Jao ◽  
Bing-Wen Soong ◽  
Chao-Wen Huang ◽  
Chien-An Duan ◽  
Chih-Chun Wu ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Multiple System Atrophy ◽  
Spinocerebellar Ataxia ◽  
Diffusion Tensor ◽  
Spinocerebellar Ataxia Type ◽  
Resonance Imaging ◽  
Spinocerebellar Ataxia Type 3 ◽  
Cerebellar Type ◽  
Type 3

Multiple system atrophy cerebellar type (MSA-C) and spinocerebellar ataxia type 3 (SCA3) demonstrate similar manifestations, including ataxia, pyramidal and extrapyramidal signs, as well as atrophy and signal intensity changes in the cerebellum and brainstem. MSA-C and SCA3 cannot be clinically differentiated through T1-weighted magnetic resonance imaging (MRI) alone; therefore, clinical consensus criteria and genetic testing are also required. Here, we used diffusion tensor imaging (DTI) to measure water molecular diffusion of white matter and investigate the difference between MSA-C and SCA3. Four measurements were calculated from DTI images, including fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). Fifteen patients with MSA-C, 15 patients with SCA3, and 30 healthy individuals participated in this study. Both patient groups demonstrated a significantly decreased FA but a significantly increased AD, RD, and MD in the cerebello-ponto-cerebral tracts. Moreover, patients with SCA3 demonstrated a significant decrease in FA but more significant increases in AD, RD, and MD in the cerebello-cerebral tracts than patients with MSAC. Our results may suggest that FA and MD can be effectively used for differentiating SCA3 and MSA-C, both of which are cerebellar ataxias and have many common atrophied regions in the cerebral and cerebellar cortex.

scholarly journals Prediction Model for COVID-19 Vaccination Intention among the Mobile Population in China: Validation and Stability

Vaccines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1221
Author(s):  
Fan Hu ◽  
Ruijie Gong ◽  
Yexin Chen ◽  
Jinxin Zhang ◽  
Tian Hu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Prediction Model ◽  
External Validation ◽  
Multivariate Logistic Regression Analysis ◽  
Stability Index ◽  
Lasso Regression ◽  
Mobile Population ◽  
Leading Position ◽  
The Government ◽  
Selection Operator

Since China’s launch of the COVID-19 vaccination, the situation of the public, especially the mobile population, has not been optimistic. We investigated 782 factory workers for whether they would get a COVID-19 vaccine within the next 6 months. The participants were divided into a training set and a testing set for external validation conformed to a ratio of 3:1 with R software. The variables were screened by the Lead Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Then, the prediction model, including important variables, used a multivariate logistic regression analysis and presented as a nomogram. The Receiver Operating Characteristic (ROC) curve, Kolmogorov–Smirnov (K-S) test, Lift test and Population Stability Index (PSI) were performed to test the validity and stability of the model and summarize the validation results. Only 45.54% of the participants had vaccination intentions, while 339 (43.35%) were unsure. Four of the 16 screened variables—self-efficacy, risk perception, perceived support and capability—were included in the prediction model. The results indicated that the model has a high predictive power and is highly stable. The government should be in the leading position, and the whole society should be mobilized and also make full use of peer education during vaccination initiatives.

scholarly journals Vertical pons hyperintensity and hot cross bun sign in cerebellar-type multiple system atrophy and spinocerebellar ataxia type 3

2020 ◽  
Author(s):  
Atsuhiko Sugiyama ◽  
Hajime Yokota ◽  
Yoshitaka Yamanaka ◽  
Hiroki Mukai ◽  
Tatsuya Yamamoto ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Multiple System Atrophy ◽  
Spinocerebellar Ataxia ◽  
High Intensity ◽  
Spinocerebellar Ataxia Type ◽  
Motor Symptoms ◽  
Spinocerebellar Ataxia Type 3 ◽  
Early Stages ◽  
Cerebellar Type ◽  
Type 3

Abstract Background The “hot cross bun” (HCB) sign, a cruciform hyperintensity in the pons on magnetic resonance imaging (MRI), has gradually been identified as a typical finding in multiple system atrophy, cerebellar-type (MSA-C). Few reports have evaluated the sensitivity of an HCB, including a cruciform hyperintensity and vertical line in the pons, which precedes a cruciform hyperintensity, in the early stages of MSA-C. Moreover, the difference in frequency and timing of appearance of an HCB between MSA-C and spinocerebellar ataxia type 3 (SCA3) has not been fully investigated.Methods This study investigated the time at which an HCB and orthostatic hypotension (OH) appeared in 41 patients with MSA-C, based on brain MRI and head-up tilt test. The MRI findings were compared with those of 26 patients with SCA3. The pontine signal findings on T2-weighted MRI were graded as 0 (no change), 1 (a vertical T2 high-intensity line), or 2 (a cruciform T2 high-intensity line), with grades 1 or 2 considered as an HCB. OH 30/15 was defined as a decrease in systolic blood pressure of > 30 mmHg or diastolic blood pressure of > 15 mmHg.Results Among the 24 patients with MSA-C within 2 years from the onset of motor symptoms, an HCB was detected in 91.7%, whereas OH 30/15 was present in 60.0%. Among the 36 patients with MSA-C within 3 years from the onset of motor symptoms, a grade 2 HCB was detected in 66.7% of those with MSA-C but in none of those with SCA-3.Conclusions HCB is a highly sensitive finding for MSA-C, even in the early stages of the disease. A grade 2 HCB in the early stage is an extremely specific finding for differentiating MSA-C from SCA-3.

1575: External Validation of Outcome Prediction Model for Ureteral/Renal Calculi

2005 ◽  
Vol 173 (4S) ◽  
pp. 427-427
Author(s):  
Sijo J. Parekattil ◽  
Udaya Kumar ◽  
Nicholas J. Hegarty ◽  
Clay Williams ◽  
Tara Allen ◽  
...  
Keyword(s):  
Prediction Model ◽  
Outcome Prediction ◽  
External Validation ◽  
Renal Calculi

scholarly journals The landscape of gene co-expression modules correlating with prognostic genetic abnormalities in AML

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Chao Guo ◽  
Ya-yue Gao ◽  
Qian-qian Ju ◽  
Chun-xia Zhang ◽  
Ming Gong ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Prediction Model ◽  
Hox Genes ◽  
Expression Profiles ◽  
Penalized Regression ◽  
Diagnostic Utility ◽  
Lasso Regression ◽  
Hub Genes ◽  
Npm1 Mutation ◽  
Genetic Abnormalities

Abstract Background The heterogenous cytogenetic and molecular variations were harbored by AML patients, some of which are related with AML pathogenesis and clinical outcomes. We aimed to uncover the intrinsic expression profiles correlating with prognostic genetic abnormalities by WGCNA. Methods We downloaded the clinical and expression dataset from BeatAML, TCGA and GEO database. Using R (version 4.0.2) and ‘WGCNA’ package, the co-expression modules correlating with the ELN2017 prognostic markers were identified (R2 ≥ 0.4, p < 0.01). ORA detected the enriched pathways for the key co-expression modules. The patients in TCGA cohort were randomly assigned into the training set (50%) and testing set (50%). The LASSO penalized regression analysis was employed to build the prediction model, fitting OS to the expression level of hub genes by ‘glmnet’ package. Then the testing and 2 independent validation sets (GSE12417 and GSE37642) were used to validate the diagnostic utility and accuracy of the model. Results A total of 37 gene co-expression modules and 973 hub genes were identified for the BeatAML cohort. We found that 3 modules were significantly correlated with genetic markers (the ‘lightyellow’ module for NPM1 mutation, the ‘saddlebrown’ module for RUNX1 mutation, the ‘lightgreen’ module for TP53 mutation). ORA revealed that the ‘lightyellow’ module was mainly enriched in DNA-binding transcription factor activity and activation of HOX genes. The ‘saddlebrown’ module was enriched in immune response process. And the ‘lightgreen’ module was predominantly enriched in mitosis cell cycle process. The LASSO- regression analysis identified 6 genes (NFKB2, NEK9, HOXA7, APRC5L, FAM30A and LOC105371592) with non-zero coefficients. The risk score generated from the 6-gene model, was associated with ELN2017 risk stratification, relapsed disease, and prior MDS history. The 5-year AUC for the model was 0.822 and 0.824 in the training and testing sets, respectively. Moreover, the diagnostic utility of the model was robust when it was employed in 2 validation sets (5-year AUC 0.743–0.79). Conclusions We established the co-expression network signature correlated with the ELN2017 recommended prognostic genetic abnormalities in AML. The 6-gene prediction model for AML survival was developed and validated by multiple datasets.

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