Journal: Journal of Diabetes Investigation

Article Title: Postprandial serum C‐peptide value is the optimal index to identify patients with non‐obese type 2 diabetes who require multiple daily insulin injection: Analysis of C‐peptide values before and after short‐term intensive insulin therapy

doi: 10.1111/jdi.12103

Figure Lengend Snippet: Baseline clinical characteristics of patients enrolled in the study ( n =291)

Article Snippet: Funakoshi et al . carried out ROC analysis of CPR values as indices indicative of insulin therapy in type 2 diabetes, and found CPI to be superior among several CPR markers.

Techniques: Biomarker Discovery

Journal: Microbiology Spectrum

Article Title: Qualitative and Quantitative Detection of Multiple Sexually Transmitted Infection Pathogens Reveals Distinct Associations with Cervicitis and Vaginitis

doi: 10.1128/spectrum.01966-22

Figure Lengend Snippet: Normalized abundance of STI pathogens and Lactobacillus spp. in healthy subjects and those with cervicitis and vaginitis. (A) Box plot showing comparison of normalized abundance ratio of microbial load to human RNase P load obtained from qPCR. The bottom and top bars of the boxes represent the interquartile range (2.5th and 97.5th percentiles), and the lines within the boxes denote the median value. Circles represent data points beyond the whiskers. *, P < 0.05; **, P < 0.001; ***, P < 0.0001. (B) Heat map of 944 samples from three study groups. The normalized abundance ratio is illustrated by the color key. Each column represents a subject. Columns are clustered using normalized abundance ratio and color coded by groups: healthy, cervicitis, and vaginitis. Clustering of each microorganism was generated using unweighted pair-group method with arithmetic mean (UPGMA) clustering with Euclidean distance. (C) ROC curve showing the area under the ROC curves (AUC) of each microorganism detected in cervicitis and vaginitis. A cutoff was calculated to maximize discrimination between cases and controls: using all cases and controls in which each microorganism was detected, the maximum Youden index (YI) from the ROC curve with case-control status as the outcome and microbial normalized abundance ratio as the independent variable was determined, where YI = sensitivity + specificity − 1. LAC, Lactobacillus spp.; other abbreviations are as in Fig. 2 .

Article Snippet: The model performance was assessed by calculating the areas under the curves (AUCs) using ROC analysis (MedCalc version 19.0.4; MedCalc Software Ltd., Ostend, Belgium).

Techniques: Comparison, Generated, Control

Journal: Microbiology Spectrum

Article Title: Qualitative and Quantitative Detection of Multiple Sexually Transmitted Infection Pathogens Reveals Distinct Associations with Cervicitis and Vaginitis

doi: 10.1128/spectrum.01966-22

Figure Lengend Snippet: Classification variables selected by logistic regression models. (A) Forest plot representing the odds ratio and 95% confidence interval for the association of significant microbial agents present in cervicitis and vaginitis. Each microbial agent was analyzed using logistic regression in a multivariable model. This plot shows the significant association for combined qualitative and quantitative screening of microbial agents with cervicitis and vaginitis after adjustment for potential confounding factor. Adjusted odds ratios with 95% confidence intervals are shown in black, with odds ratios illustrated by circles. (B) Predictive value of the logistic regression models for patients and healthy subjects in the validation data set. Scatterplots showing the predictive value of the models for distinguishing cervicitis patients versus healthy controls and vaginitis patients versus healthy controls. Horizontal lines indicate the medians, and red dotted lines show the cutoff value of 0.20. ***, P < 0.0001 (Mann-Whitney U test). (C) Area under the ROC curves (AUC) of qualitative, quantitative, and simultaneous qualitative and quantitative PCR combined screening of STI pathogens discriminates women with cervicitis (left panel) and vaginitis (right panel) from healthy subjects.

Article Snippet: The model performance was assessed by calculating the areas under the curves (AUCs) using ROC analysis (MedCalc version 19.0.4; MedCalc Software Ltd., Ostend, Belgium).

Techniques: Biomarker Discovery, MANN-WHITNEY, Real-time Polymerase Chain Reaction

Journal: Microbiology Spectrum

Article Title: Qualitative and Quantitative Detection of Multiple Sexually Transmitted Infection Pathogens Reveals Distinct Associations with Cervicitis and Vaginitis

doi: 10.1128/spectrum.01966-22

Figure Lengend Snippet: The classification features selected by random forest models. (A) Random forest ranking plot of variable importance in predicting risk of cervicitis and vaginitis. The x axis shows the importance of the feature to the accuracy of the model, which was estimated by calculating the mean decrease in Gini after randomly permuting the values of each given feature. (B) Predictive value of the random forest models for distinguishing patients and healthy controls in the validation data set. Scatterplots show the predictive value of the random forest models for cervicitis and vaginitis. Horizontal lines indicate the medians, and red dotted lines show the cutoff value of 0.20. ***, P < 0.0001 (Mann-Whitney U test). (C) Area under the ROC curves (AUC) curve of the random forest classification models for cervicitis versus healthy subjects (left) and vaginitis versus healthy subjects (right).

Article Snippet: The model performance was assessed by calculating the areas under the curves (AUCs) using ROC analysis (MedCalc version 19.0.4; MedCalc Software Ltd., Ostend, Belgium).

Techniques: Biomarker Discovery, MANN-WHITNEY

Journal: Biomolecules and Biomedicine

Article Title: Ultrasonographic abdominal adipose tissue thickness for the prediction of gestational diabetes mellitus: A meta-analysis

doi: 10.17305/bb.2023.9902

Figure Lengend Snippet: Characteristics of the included studies

Article Snippet: Rocha, 2020 , Brazil , PC , 133 , 26 , NR , 11∼13 , VAT (ROC analysis-derived cutoff) , IADPSG criteria , 18 , Maternal age and BMI.

Techniques:

Journal: Journal of Personalized Medicine

Article Title: A Novel Noninvasive Technique for Intracranial Pressure Waveform Monitoring in Critical Care

doi: 10.3390/jpm11121302

Figure Lengend Snippet: Entire sample ROC analysis of ICP and B4C P2/P1 ratios for an ICP value cut-off >20 mmHg ( up ). The power of predicting intracranial hypertension was reduced because of sample heterogeneity. The B4C P2/P1 ratio cut-off 1 ( down ) was equivalent to ICP P2/P1 ratio cut-off 1 (AUC 0.9).

Article Snippet: Additionally, a linear correlation was presented using R. The ROC curve analysis was performed using the Johns Hopkins University tool (available at www.jrocfit.org ).

Techniques:

Journal: Journal of Applied Clinical Medical Physics

Article Title: Sensitivity and specificity of Varian Halcyon's portal dosimetry for plan‐specific pre‐treatment QA

doi: 10.1002/acm2.14001

Figure Lengend Snippet: ROC curves for the QA tool comparison. The investigated plan acceptance criteria include γ 2%/2 mm , γ 2%/1 mm , and γ 1%/1 mm for PD and γ 3%/3 mm , γ 3%/2 mm , and γ 2%/2 mm for ArcCHECK gamma analysis. (a) ROC analysis per treatment plan. While ArcCHECK measurements were evaluated for the entire plan, for PD the worst arc's gamma passing rate was assigned to each plan. (b) ROC analysis for PD measurements analyzed per treatment field. Higher diagnostic performance is indicated by curves with larger area under the ROC curve.

Article Snippet: Based on the dedicated ROC analysis tool, as provided by OriginPro v.9.0 (OriginLab, Northampton, MA), sensitivity and specificity for both PD and ArcCHECK QA using the aforementioned assessment at varying decision thresholds were evaluated.

Techniques: Comparison, Diagnostic Assay