Comparison Of Receiver Operating Characteristic Curves Research Articles

Predicting new-onset persistent conduction disturbance following transcatheter aortic valve replacement: the usefulness of FEOPS finite element analysis

BackgroundDespite the frequency of persistent new-onset conduction disturbances after transcatheter aortic valve replacement (TAVR), few preoperative methods of prediction exist.MethodsPatients who underwent TAVR in the Department of Cardiology of the Second Affiliated Hospital of the Army Medical University from December 2020 to September 2021 and postoperative aortic root modeling via the FEOPS finite element analysis were included in this single-center case–control study, divided into persistent conduction disturbances (PCD) and non-PCD groups according to their pre- and postoperative electrocardiograms in the first month. Risk factors affecting PCD were identified by comparing the baseline data of these two groups, including echocardiograms, computed tomography angiography of the aortic root, surgical decision-making, and FEOPS data. Independent risk factors were screened using logistic regression modeling, and the receiver operating characteristic (ROC) curve was used to test the predictive ability.ResultsA total of 56 patients were included in this study, 37 with bicuspid aortic valve (BAV) and 19 with trileaflet aortic valve (TAV), with 17 cases of PCD. The contact pressure index (CPI) of FEOPS, valve oversize ratio, differences between membranous interventricular septum length and implantation depth (ΔMSID) and valve implantation depth were statistically different (P < 0.05). CPI could be used as an independent risk factor for PCD (P < 0.05), and the ROC curve comparison showed that the CPI was more predictive (AUC = 0.806, 95% CI: 0.684–0.928, P = 0.001).ConclusionsThe CPI of FEOPS has better predictive value for new-onset conduction disturbance after TAVR compared to other known predictors.

Differentiation between high-grade gliomas and solitary brain metastases based on multidiffusion MRI model quantitative analysis.

Differentiating high-grade gliomas (HGGs) from solitary brain metastases (SBMs) using conventional magnetic resonance imaging (MRI) remains challenging due to their similar imaging features. This study aimed to evaluate the diagnostic performance of advanced diffusion models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator magnetic resonance imaging (MAP-MRI), incomparison to traditional techniques like diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) for distinguishing HGGs from SBMs. In total, 17 patients with HGGs and 26 patients with SBMs were prospectively recruited based on the established inclusion and exclusion criteria. Structural MRI sequences and diffusion spectrum imaging (DSI) were utilized to assess quantitative parameter models, including NODDI, MAP-MRI, DWI, DTI, and DKI. Quantitative parameters were measured for both the tumor parenchymal area and the peritumoral edema area. The quantitative parameters of the two patient groups were compared using either the independent Student's t-test or the Mann-Whitney U test. The effectiveness of each model was evaluated using receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Finally, the DeLong test was employed to compare the diagnostic performance of each model through pairwise comparisons of ROC curves. Isotropic volume fraction (Viso) based on NODDI; mean squared displacement (MSD) and the return to plane probabilities (RTPP) based on MAP-MRI; radial diffusivity (RDk) and mean diffusivity (MDk) based on DKI; and axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) based on DTI of the peritumoral edema tumor were significantly different between HGGs and SBMs (p < 0.05). The optimal single discriminant parameters for each model are NODDI_Viso, MAP-MRI_MSD, DKI_MDk, and DTI_AD. Among these, the AUC of Viso (0.809) exceeds that of MSD (0.733), MDk (0.718), and AD (0.779). The combined model, which incorporates DTI_AD, DKI_RD, and NODDI_Viso, demonstrated superior diagnostic performance (0.897). Advanced diffusion MRI quantitative parameters derived from NODDI, such as Viso, have the potential to enhance the differentiation between HGGs and SBMs. The integrated utilization of these models is anticipated to enhance diagnostic accuracy and refine MRI protocols for brain tumor assessment.

Clinical features and predictors of early neurological deterioration in patients with Trousseau syndrome-related cerebral infarction

Objective: This study aimed to explore the clinical features of Trousseau syndrome (TS)-related cerebral infarction and determine predictors of early neurological deterioration (END). Methods: A retrospective study was conducted on patients with TS-related cerebral infarction admitted to the Zhongshan Hospital Affiliated with Xiamen University, from December 2015 to December 2023. Patients were categorized into groups with and without END. The laboratory findings and imaging data were compared, and receiver operating characteristic (ROC) curves were constructed to determine the best predictors of END. Results: The study included 30 patients with TS-related cerebral infarction, comprising 17 males and 13 females with an average age of 70.93 ± 8.7 years. Five patients experienced END. Lung cancer was the most common primary malignancy (n=13, 43.33%), with most patients (n=22, 73.33%) having stage IV disease with extensive metastasis. The primary neurological symptom was hemiplegia (n=17, 56.67%). The mean NIHSS score at admission was 9.33 ± 5.83. Imaging revealed varying stages of cerebral infarction in 10 patients (38.46%). Within three months, 25 patients (83.33%) died, 8 of whom (32%) succumbed to tumor-related complications. The incidence of END in TS-related cerebral infarction patients was 16.67% (5/30). Patients in the END group had significantly greater D-dimer levels and lower fibrinogen (Fib) levels upon admission (P &lt; 0.001, P = 0.042). Comparisons of ROC curves revealed that D-dimer (AUC 0.916, optimal cutoff 17.86, sensitivity 1.000, specificity 0.840) and Fib (AUC 0.788, optimal cutoff 2.54, sensitivity 1.000, specificity 0.740) significantly predicted END (P = 0.004, P = 0.045). The combined use of these markers improved the AUC to 0.952, with a sensitivity of 1.00 and specificity of 0.920, surpassing those of the individual markers (P = 0.002). Conclusion: TS-related cerebral infarction most commonly occurs in patients with advanced-stage lung cancer with widespread metastasis and is associated with poor long-term prognosis. Elevated D-dimer and decreased fibrinogen levels are significant predictors of END in patients with TS-related cerebral infarction.

Observed-to-expected lung-area-to-head-circumference ratio on ultrasound examination vs total fetal lung volume on magnetic resonance imaging in prediction of survival in fetuses with left-sided diaphragmatic hernia.

To assess and compare the value of antenatally determined observed-to-expected (O/E) lung-area-to-head-circumference ratio (LHR) on ultrasound examination vs O/E total fetal lung volume (TFLV) on magnetic resonance imaging (MRI) examination to predict postnatal survival of fetuses with isolated, expectantly managed left-sided congenital diaphragmatic hernia (CDH). This was a multicenter retrospective study including all consecutive fetuses with isolated CDH that were managed expectantly in Mannheim, Germany, and in five other European centers, that underwent at least one ultrasound examination for measurement of O/E-LHR and one MRI scan for measurement of O/E-TFLV during pregnancy. All MRI data were centralized, and lung volumes were measured by two experienced operators blinded to the pre- and postnatal data. Multiple logistic regression analyses were performed to examine the effect on survival at hospital discharge of various perinatal variables, including the center of management. In left-sided CDH with intrathoracic herniation of the liver, receiver-operating-characteristics (ROC) curves were constructed separately for cases from Mannheim and the other five European centers and were used to compare O/E-TFLV and O/E-LHR in the prediction of postnatal survival. From Mannheim, 309 patients were included with a median gestational age (GA) at ultrasound examination of 29.6 (range, 19.7-39.1) weeks and median GA at MRI examination of 31.1 (range, 18.0-39.9) weeks. From the other five European centers, 116 patients were included with a median GA at ultrasound examination of 26.7 (range, 20.6-37.6) weeks and median GA at MRI examination of 27.7 (range, 21.3-37.9) weeks. Regression analysis demonstrated that the survival rates at discharge were lower in left-sided CDH (odds ratio (OR), 0.349 (95% CI, 0.133-0.918), P = 0.033) and those with intrathoracic liver (OR, 0.297 (95% CI, 0.141-0.628), P = 0.001), and higher with increasing O/E-TFLV (OR, 1.123 (95% CI, 1.079-1.170), P < 0.001), advanced GA at birth (OR, 1.294 (95% CI, 1.055-1.588), P = 0.013) and when birth occurred in Mannheim (OR, 7.560 (95% CI, 3.368-16.967), P < 0.001). Given the difference in survival rate between Mannheim and the five other European centers, ROC curve comparisons between the two imaging modalities were presented separately. For cases of left-sided CDH with intrathoracic herniation of the liver, pairwise comparison showed no significant difference between the area under the ROC curves for the prediction of postnatal survival between O/E-TFLV and O/E-LHR in Mannheim (mean difference = 0.025, P = 0.610, standard error = 0.050), whereas there was a significant difference in the other European centers studied (mean difference = 0.056, P = 0.033, standard error = 0.056). In fetuses with left-sided CDH and intrathoracic herniation of the liver, the predictive value for postnatal survival of O/E-TFLV on MRI examination and O/E-LHR on ultrasound examination was similar in one center (Mannheim), but O/E-TFLV had better predictive value compared to O/E-LHR in the five other European centers. Hence, in these five European centers, MRI should be included in the diagnostic process for left-sided CDH. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Increasing the accuracy and reproducibility of positron emission tomography radiomics for predicting pelvic lymph node metastasis in patients with cervical cancer using 3D local binary pattern-based texture features

BackgroundThe reproducibility of positron emission tomography (PET) radiomics features is affected by several factors, such as scanning equipment, drug metabolism time and reconstruction algorithm. We aimed to explore the role of 3D local binary pattern (LBP)-based texture in increasing the accuracy and reproducibility of PET radiomics for predicting pelvic lymph node metastasis (PLNM) in patients with cervical cancer. MethodsWe retrospectively analysed data from 177 patients with cervical squamous cell carcinoma. They underwent 18F-fluorodeoxyglucose (18F-FDG)whole-body PET/computed tomography (PET/CT), followed by pelvic 18F-FDG PET/magnetic resonance imaging (PET/MR). We selected reproducible and informative PET radiomics features using Lin's concordance correlation coefficient, least absolute shrinkage and selection operator algorithm, and established 4 models, PET/CT, PET/CT-fusion, PET/MR and PET/MR-fusion, using the logistic regression algorithm. We performed receiver operating characteristic (ROC) curve analysis to evaluate the models in the training data set (65 patients who underwent radical hysterectomy and pelvic lymph node dissection) and test data set (112 patients who received concurrent chemoradiotherapy or no treatment). The DeLong test was used for pairwise comparison of the ROC curves among the models. ResultsThe distribution of age, squamous cell carcinoma (SCC), International Federation of Gynaecology and Obstetrics stage and PLNM between the training and test data sets were different (P < 0.05). The LBP-transformed radiomics features (50/379) had higher reproducibility than the original radiomics features (9/107). Accuracy of each model in predicting PLNM was as follows: training data set: PET/CT = PET/CT-fusion = PET/MR-fusion (0.848) and test data set: PET/CT = PET/CT-fusion (0.985) > PET/MR = PET/MR-fusion (0.954). There was no statistical difference between the ROC curve of PET/CT and PET/MR models in both data sets (P > 0.05). ConclusionsThe LBP-transformed radiomics features based on PET images could increase the accuracy and reproducibility of PET radiomics in predicting pelvic lymph node metastasis in cervical cancer to allow the model to be generalised for clinical use across multiple centres.

Paraspinal muscle endurance and morphology (PMEM) score: a new method for prediction of postoperative mechanical complications after lumbar fusion

BACKGROUND CONTEXTAlthough the relationships between paraspinal muscles and lumbar degenerative disorders have been acknowledged, paraspinal muscle evaluation has not been incorporated into clinical therapies. PURPOSEWe aimed to establish a novel paraspinal muscle endurance and morphology (PMEM) score to better predict mechanical complications after lumbar fusion. STUDY DESIGNProspective cohort study. PATIENT SAMPLEA total of 212 patients undergoing posterior lumbar interbody fusion with at least 1 year of follow-up were finally included. OUTCOME MEASURESMechanical complications including screw loosening, pseudarthrosis and other complications like cage subsidence, and patient-reported outcomes were evaluated at last follow-up. METHODSThe PMEM score comprised 1 functional muscular parameter (the performance time of the endurance test) and 2 imaging muscular parameters (relative functional cross-sectional area [rFCSA] of paraspinal extensor muscles [PEM] and psoas major [PS] on magnetic resonance imaging). The score was established based on a weighted scoring system created by rounding β regression coefficients to the nearest integer in univariate logistic regression. The diagnostic performance of the PMEM score was determined by binary logistic regression model and receiver operating characteristic (ROC) curve with the area under the curve (AUC). Additionally, pairwise comparisons of ROC curves were conducted to compare the diagnostic performance of the PMEM score with conventional methods based on a single muscular parameter. Moreover, differences of mechanical complications and patient-reported outcomes among the PMEM categories were analyzed using Chi-square test with Bonferroni correction. RESULTSThe PMEM score, calculated by adding the scores for each parameter, ranges from 0 to 5 points. Patients with higher PMEM scores exhibited higher rates of mechanical complications (p<.001). Binary logistic regression revealed that the PMEM score was an independent factor of mechanical complications (p<.001, OR=2.002). Moreover, the AUC of the PMEM score (AUC=0.756) was significantly greater than those of the conventional methods including the endurance test (AUC=0.691, Z=2.036, p<.05), PEM rFCSA (AUC=.690, Z=2.016, p<.05) and PS rFCSA (AUC=0.640, Z=2.771, p<.01). In terms of the PMEM categories, a score of 0–1 was categorized as low-risk muscular state of mechanical complications; 2–3, as moderate; and 4–5, as high-risk state. Moving from the low-risk state to the high-risk state, there was a progressive increase in the rates of mechanical complications (13.8% vs 32.1% vs 72.7%; p<.001), and a decrease in the rates of clinically significant improvement of patient-reported outcomes (all p<.05). CONCLUSIONSThe PMEM score might comprehensively evaluate paraspinal muscle degeneration and exhibit greater ability in predicting mechanical complications than the conventional evaluations after lumbar fusion. Surgeons might develop individualized treatment strategy tailored to different muscle degeneration statuses reflected by the PMEM score for decreasing the risk of mechanical complications.

Computed tomography-based body composition parameters can predict short-term prognosis in ulcerative colitis patients.

Emerging evidence suggests a potential relationship between body composition and short-term prognosis of ulcerative colitis (UC). Early and accurate assessment of rapid remission based on conventional therapy via abdominal computed tomography (CT) images has rarely been investigated. This study aimed to build a prediction model using CT-based body composition parameters for UC risk stratification. In total, 138 patients with abdominal CT images were enrolled. Eleven quantitative parameters related to body composition involving skeletal muscle mass, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were measured and calculated using a semi-automated segmentation method. A prediction model was established with significant parameters using a multivariable logistic regression. The receiver operating characteristic (ROC) curve was plotted to evaluate prediction performance. Subgroup analyses were implemented to evaluate the diagnostic efficiency of the prediction model between different disease locations, centers, and CT scanners. The Delong test was used for statistical comparison of ROC curves. VAT density, SAT density, gender, and visceral obesity were significantly statistically different between remission and invalidation groups (all p < 0.05). The accuracy, sensitivity, specificity, and area under the ROC curve (AUC) of the prediction model were 82.61%, 95.45%, 69.89%, and 0.855 (0.792-0.917), respectively. The positive predictive value and negative predictive value were 70.79% and 93.88%, respectively. No significant differences in the AUC of the prediction model were found in different subgroups (all p > 0.05). The predicting model constructed with CT-based body composition parameters is a potential non-invasive approach for short-term prognosis identification and risk stratification. Additionally, VAT density was an independent predictor for escalating therapeutic regimens in UC cohorts. The CT images were used for evaluating body composition and risk stratification of ulcerative colitis patients, and a potential non-invasive prediction model was constructed to identify non-responders with conventional therapy for making therapeutic regimens timely and accurately. • CT-based prediction models help divide patients into invalidation and remission groups in UC. • Results of the subgroup analysis confirmed the stability of the prediction model with a high AUC (all > 0.820). • The visceral adipose tissue density was an independent predictor of bad short-term prognosis in UC.

Comparison of the diagnostic performance of three ultrasound thyroid nodule risk stratification systems for follicular thyroid neoplasm: K-TIRADS, ACR -TIRADS and C-TIRADS.

To explore the diagnostic performance of the currently used ultrasound-based thyroid nodule risk stratification systems (K-TIRADS, ACR -TIRADS, and C-TIRADS) in differentiating follicular thyroid adenoma (FTA) from follicular thyroid carcinoma (FTC). Clinical data and preoperative ultrasonographic images of 269 follicular thyroid neoplasms were retrospectively analyzed. All of them were detected by Color Doppler ultrasound instruments equipped with high-frequency liner array probes (e.g. Toshiba Apoli500 with L5-14MHZ; Philips IU22 with L5-12MHZ; GE LOGIQ E9 with L9-12MHZ and MyLab Class C with L9-14MHZ). The diagnostic performance of three TIRADS classifications for differentiating FTA from FTC was evaluated by drawing the receiver operating characteristic (ROC) curves and calculating the cut-off values. Of the 269 follicular neoplasms (mean size, 3.67±1.53 cm), 209 were FTAs (mean size, 3.56±1.38 cm) and 60 were FTCs (mean size, 4.07±1.93 cm). There were significant differences in ultrasound features such as margins, calcifications, and vascularity of thyroid nodules between the FTA and FTC groups (P < 0.05). According to the ROC curve comparison analysis, the diagnostic cut-off values of K-TIRADS, ACR-TIRADS, and C-TIRADS for identifying FTA and FTC were K-TR4, ACR-TR4, and C-TR4B, respectively, and the areas under the curves were 0.676, 0.728, and 0.719, respectively. The difference between ACR-TIRADS and K-TIRADS classification was statistically significant (P = 0.0241), whereas the differences between ACR-TIRADS and C-TIRADS classification and between K-TIRADS and C-TIRADS classification were not statistically significant (P > 0.05). The three TIRADS classifications were not conducive to distinguishing FTA from FTC. It is necessary to develop a novel malignant risk stratification system specifically for the identification of follicular thyroid neoplasms.

High correlation of hepatic shear wave velocity with esophageal varices complication rate in patients with chronic liver diseases

BackgroundHistological evaluation by liver biopsy is considered the gold standard for assessing liver disease; however, it is highly invasive. Non-invasive liver stiffness measurement by shear wave elastography (SWE) is effective for evaluating the hepatic fibrosis stage and related diseases. In this study, we investigated the correlations of liver stiffness with hepatic inflammation/fibrosis, functional hepatic reserve, and related diseases in patients with chronic liver disease (CLD).MethodsShear wave velocity (Vs) values were measured using point SWE in 71 patients with liver disease from 2017 to 2019. Liver biopsy specimens and serum biomarkers were collected at the same time, and splenic volume was measured using computed tomography images with the software Ziostation2. Esophageal varices (EV) were evaluated by upper gastrointestinal endoscopy.ResultsAmong CLD-related function and complications, Vs values were highly correlated with liver fibrosis and EV complication rates. The median Vs values for liver fibrosis grades F0, F1, F2, F3, and F4 were 1.18, 1.34, 1.39, 1.80, and 2.12 m/s, respectively. Comparison of receiver operating characteristic (ROC) curves to predict cirrhosis showed that area under the ROC (AUROC) curve for Vs values was 0.902, which was not significantly different from the AUROCs for the FIB-4 index, platelet count, hyaluronic acid, or type IV collagen 7S, while it was significantly different from the AUROC for mac-2 binding protein glycosylation isomer (M2BPGi) (P < 0.01). Comparison of ROC curves to predict EV showed that the AUROC for Vs values was 0.901, which was significantly higher than the AUROCs for FIB-4 index (P < 0.05), platelet count (P < 0.05), M2BPGi (P < 0.01), hyaluronic acid (P < 0.05), and splenic volume (P < 0.05). In patients with advanced liver fibrosis (F3 + F4), there was no difference in blood markers and splenic volume, while Vs value was significantly higher in patients with EV (P < 0.01).ConclusionsHepatic shear wave velocity was highly correlated with EV complication rates in chronic liver diseases as compared to blood markers and splenic volume. In advanced CLD patients, Vs values of SWE are suggested to be effective in predicting the appearance of EV noninvasively.

Sensitivity to change of generic preference-based instruments (EQ-5D-3L, EQ-5D-5L, and HUI3) in the context of treatment for people with prescription-type opioid use disorder in Canada

PurposeUsing data from a randomized controlled trial for treatment of prescription-type opioid use disorder in Canada, this study examines sensitivity to change in three preference-based instruments [EQ-5D-3L, EQ-5D-5L, and the Health Utilities Index Mark 3 (HUI3)] and explores an oft-overlooked consideration when working with contemporaneous responses for similar questions—data quality.MethodsAnalyses focused on the relative abilities of three instruments to capture change in health status. Distributional methods were used to categorize individuals as ‘improved’ or ‘not improved’ for eight anchors (seven clinical, one generic). Sensitivity to change was assessed using area under the ROC (receiver operating characteristics) curve (AUC) analysis and comparisons of mean change scores for three time periods. A ‘strict’ data quality criteria, defined a priori, was applied. Analyses were replicated using ‘soft’ and ‘no’ criteria.ResultsData from 160 individuals were used in the analysis; 30% had at least one data quality violation at baseline. Despite mean index scores being significantly lower for the HUI3 compared with EQ-5D instruments at each time point, the magnitudes of change scores were similar. No instrument demonstrated superior sensitivity to change. While six of the 10 highest AUC estimates were for the HUI3, ‘moderate’ classifications of discriminative ability were identified in 12 (of 22) analyses for each EQ-5D instrument, compared with eight for the HUI3.ConclusionNegligible differences were observed between the EQ-5D-3L, EQ-5D-5L, and HUI3 regarding the ability to measure change. The prevalence of data quality violations—which differed by ethnicity—requires further investigation.

Frailty measured by risk analysis index and adverse discharge outcomes after adult spine deformity surgery: analysis of 3104 patients from a prospective surgical registry (2011–2020)

Background ContextMeasurement of frailty with the Risk Analysis Index (RAI) has demonstrated improved outcome prediction compared to other frailty indices across the surgical literature. However, the generalizability and clinical utility of preoperative RAI scoring for prediction of postoperative morbidity after adult spinal deformity surgery is presently unknown. Thus, recent studies have called for an RAI analysis of spine deformity outcomes. PurposeThe present study sought to evaluate the discriminatory accuracy of preoperative frailty, as measured by RAI, for predicting postoperative morbidity among adult spine deformity surgery patients using data queried from a large prospective surgical registry representing over 700 hospitals from 49 US states and 11 countries. Study Design/SettingSecondary analysis of a prospective surgical registry. Patient SampleAmerican College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (2011–2020). Outcome MeasuresThe primary endpoint was “adverse discharge outcome” (ADO) defined as discharge to a non-home, non-rehabilitation nursing/chronic care facility. MethodsAdult spine deformity surgeries were queried from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (2011–2020) using diagnosis and procedure codes. The relationship between increasing preoperative RAI frailty score and increasing rate of primary endpoint (ADO) was assessed with Cochran-Armitage linear trend tests. Discriminatory accuracy was tested by computation of concordance statistics (with 95% confidence interval [CI]) in receiver operating characteristic (ROC) curve analysis. ResultsA total of 3104 patients underwent spine deformity surgery and were stratified by RAI score: 0–10: 22%, 11–15: 11%, 16–20: 29%, 21–25: 26%, 26–30: 8.0%, 31–35: 2.4%, and 36+: 1.4%. The rate of ADO was 14% (N=439/3094). The rate of ADO increased significantly with increasing RAI score (p<.0001). RAI demonstrated robust discriminatory accuracy for prediction of ADO in ROC analysis (C-statistic: 0.71, 95% CI: 0.69–0.74, p<.001). In pairwise comparison of ROC curves (DeLong test), RAI demonstrates superior discriminatory accuracy compared to the 5-factor modified frailty index (mFI-5; p<.001). ConclusionPreoperative frailty, as measured by RAI, is a robust predictor of postoperative morbidity (measured by ADO) after adult spine deformity surgery. The frailty score may be translated directly to the bedside with a user-friendly risk calculator, deployed here: https://nsgyfrailtyoutcomeslab.shinyapps.io/spineDeformity

Routine chest CT combined with the osteoporosis self-assessment tool for Asians (OSTA): a screening tool for patients with osteoporosis.

The osteoporosis self-assessment tool for Asians (OSTA) is a common screening tool for osteoporosis. The seventh thoracic CT (CT-T7) Hounsfield unit (HU) measured by chest CT correlates with osteoporosis. This study aimed to investigate the diagnostic value of OSTA alone, CT-T7 alone, or the combination of OSTA and CT-T7 in osteoporosis. In this study, 1268 participants were grouped into 586 men and 682 women. We established multiple linear regression models by combining CT-T7 and OSTA. Receiver operating characteristic (ROC) curves were used to evaluate the ability to diagnose osteoporosis. In the male group, the mean age was 59.02years, and 108 patients (18.4%) had osteoporosis. In the female group, the mean age was 63.23years, and 308 patients (45.2%) had osteoporosis. By ROC curve comparison, the CT-T7 (male, AUC = 0.789, 95% CI 0.745-0.832; female, AUC = 0.835, 95% CI 0.805-0.864) in the diagnosis of osteoporosis was greater than the OSTA (male, AUC = 0.673, 95% CI 0.620-0.726; female, AUC = 0.775, 95% CI 0.741-0.810) in both the male and female groups (p < 0.001). When OSTA was combined with CT, the equation of multiple linear regression (MLR) was obtained as follows: female = 3.020-0.028*OSTA-0.004*CT-T7. In the female group, it was found that the AUC of MLR (AUC = 0.853, 95% CI 0.825-0.880) in the diagnosis of osteoporosis was larger than that of CT-T7 (p < 0.01). When the MLR was 2.65, the sensitivity and specificity were 53.9% and 90%, respectively. For a patient who has completed chest CT, CT-T7 (HU) combined with OSTA is recommended to identify the high-risk population of osteoporosis, and it has a higher diagnostic value than OSTA alone or CT-T7 alone, especially among females. For a female with MLR greater than 2.65, further DXA examination is needed.

Assessment of the Diagnostic Value of Novel Biomarkers in Adult Patients With Acute Appendicitis: A Cross-Sectional Study.

Background Acute appendicitis (AA) is one of the most frequent causes of abdominal pain requiring emergency intervention in adults. Approximately one-third of cases present with atypical clinical symptoms. This study aims to compare the monocyte-to-lymphocyte ratio (MLR), red cell distribution width (RDW) to lymphocyte ratio (RLR), and systemic immune inflammation index (SII) with other biomarkers in distinguishing patients with and without AA. Methodology A total of 347 patients (AA 125, nonspecific abdominal pain 90, and control group 132) were enrolled in the study according to the cross-sectional study design. Receiver operating characteristic (ROC) analysis was used to determine the cutoff in diagnostic value measurements. Statistical significance was determined by the statistics of sensitivity, specificity, positive predictive value, and negative predictive value. Comparison of ROC curves of C-reactive protein (CRP), white blood cell (WBC), neutrophil count (NEU), neutrophil-to-lymphocyte ratio (NLR), MLR, and SII was evaluated with the pairwise comparison of ROC curves and 95% confidence interval. Results In detecting AA, CRP, WBC, NEU, NLR, MLR, and SII have excellent diagnostic power (area under the curve [AUC] 0.80-0.88), while RDW, lymphocyte count, monocyte (MON) count, and RLR had acceptable diagnostic power (AUC 0.70-0.77). When the power in the diagnosis of AA was compared, a significant difference was found between CRP and NEU, CRP and SII, WBC and NEU, and WBC and SII. Conclusions The diagnosis of AA remains dependent on many factors. Inflammatory biomarkers assist this process. MLR and SII may be recommended to use in diagnosing AA in adults, along with other clinical findings. RLR is adequate but not superior.

Deep learning for real-time auxiliary diagnosis of pancreatic cancer in endoscopic ultrasonography.

In recent year, many deep learning have been playing an important role in the detection of cancers. This study aimed to real-timely differentiate a pancreatic cancer (PC) or a non-pancreatic cancer (NPC) lesion via endoscopic ultrasonography (EUS) image. A total of 1213 EUS images from 157 patients (99 male, 58 female) with pancreatic disease were used for training, validation and test groups. Before model training, regions of interest (ROIs) were manually drawn to mark the PC and NPC lesions using Labelimage software. Yolov5m was used as the algorithm model to automatically distinguish the presence of pancreatic lesion. After training the model based on EUS images using YOLOv5, the parameters achieved convergence within 300 rounds (GIoU Loss: 0.01532, Objectness Loss: 0.01247, precision: 0.713 and recall: 0.825). For the validation group, the mAP0.5 was 0.831, and mAP@.5:.95 was 0.512. In addition, the receiver operating characteristic (ROC) curve analysis showed this model seemed to have a trend of more AUC of 0.85 (0.665 to 0.956) than the area under the curve (AUC) of 0.838 (0.65 to 0.949) generated by physicians using EUS detection without puncture, although pairwise comparison of ROC curves showed that the AUC between the two groups was not significant (z= 0.15, p = 0.8804). This study suggested that the YOLOv5m would generate attractive results and allow for the real-time decision support for distinction of a PC or a NPC lesion.

Nomograms for predicting overall and cancer-specific survival of patients with chromophobe renal cell carcinoma after nephrectomy: a retrospective SEER-based study

ObjectiveWe aimed to construct and validate nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for patients with chromophobe renal cell carcinoma (chRCC) after nephrectomy.DesignThis study is a retrospective...

Iron quantitative analysis of motor combined with bulbar region in M1 cortex may improve diagnosis performance in ALS.

To explore whether the combined analysis of motor and bulbar region of M1 on susceptibility-weighted imaging (SWI) can be a valid biomarker for amyotrophic lateral sclerosis (ALS). Thirty-two non-demented ALS patients and 35 age- and gender-matched healthy controls (HC) were retrospectively recruited. SWI and 3D-T1-MPRAGE images were obtained from all individuals using a 3.0-T MRI scan. The bilateral posterior band of M1 was manually delineated by three neuroradiologists on phase images and subdivided into the motor and bulbar regions. We compared the phase values in two groups and performed a stratification analysis (ALSFRS-R score, duration, disease progression rate, and onset). Receiver operating characteristic (ROC) curves were also constructed. ALS group showed significantly increased phase values in M1 and the two subregions than the HC group, on the all and elderly level (p < 0.001, respectively). On all-age level comparison, negative correlations were found between phase values of M1 and clinical score and duration (p < 0.05, respectively). Similar associations were found in the motor region (p < 0.05, respectively). On both the total (p < 0.01) and elderly (p < 0.05) levels, there were positive relationships between disease progression rate and M1 phase values. In comparing ROC curves, the entire M1 showed the best diagnostic performance. Combining motor and bulbar analyses as an integral M1 region on SWI can improve ALS diagnosis performance, especially in the elderly. The phase value could be a valuable biomarker for ALS evaluation. • Integrated analysis of the motor and bulbar as an entire M1 region on SWI can improve the diagnosis performance in ALS. • Quantitative analysis of iron deposition by SWI measurement helps the clinical evaluation, especially for the elderly patients. • Phase value, when combined with the disease progression rate, could be a valuable biomarker for ALS.

PD21-05 EVALUATION OF EARLY SCORING PREDICTORS FOR EXPEDITED CARE IN A LARGE PROSPECTIVE PATIENTS’ COHORT WITH EMPHYSEMATOUS PYELONEPHRITIS

You have accessJournal of UrologyCME1 May 2022PD21-05 EVALUATION OF EARLY SCORING PREDICTORS FOR EXPEDITED CARE IN A LARGE PROSPECTIVE PATIENTS’ COHORT WITH EMPHYSEMATOUS PYELONEPHRITIS Arun Chawla, Sunil Pillai, Ravi Taori, and Arun Chawla Arun ChawlaArun Chawla More articles by this author , Sunil PillaiSunil Pillai More articles by this author , Ravi TaoriRavi Taori More articles by this author , and Arun ChawlaArun Chawla More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002559.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: To evaluate and position existing critical care scoring systems to predict the need for ICU (Intensive Care Unit) management for patients with Emphysematous Pyelonephritis (EPN). To also analyze if CT-imaging further enhances the predictive systems. METHODS: Analysis of prospectively maintained database of consecutive patients diagnosed clinico-radiologically with EPN from January 2011 to September 2020. Five scoring systems were evaluated for their predictive ability for the need for ICU management and mortality risk: National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), ‘quick’ Sequential Organ Failure Assessment score (qSOFA), Systemic Inflammatory Response Syndrome score (SIRS), and Sequential Organ Failure Assessment score (SOFA). CT images were graded and evaluated as stand-alone or added to the different predictive models. Receiver operating characteristic (ROC) curves were plotted for each critical care score and CT-grade using logistic regression, to obtain the area under curve (AUC) value for comparison of ICU admission predictability. RESULTS: 90 patients were diagnosed with EPN. Twenty-six patients required ICU management and nine patients died. The best scoring system to predict the need of early ICU management is NEWS (AUC 0.884). CT imaging does further improve, though not statistically significant, the predictive model of NEWS from 0.884 to 0.894. Supplement Table 2: Comparison of ROC curves of the various scores. CONCLUSIONS: In patients with EPN, the NEWS scoring system predicts best the requirement of ICU care. It aids in triage of patients with EPN to appropriate early management and reduce mortality risk. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e362 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Arun Chawla More articles by this author Sunil Pillai More articles by this author Ravi Taori More articles by this author Arun Chawla More articles by this author Expand All Advertisement PDF DownloadLoading ...

Comparative study of conventional ROI-based and volumetric histogram analysis derived from CT enhancement in differentiating malignant and benign renal tumors.

To quantitatively compare the diagnostic values of conventional region of interest (ROI)-based and volumetric histogram analysis derived from CT enhancement in differentiating malignant and benign renal tumors. A total of 230 patients with pathologically confirmed renal tumors who had undergone CT enhancement were classified into clear cell renal cell carcinoma (ccRCC) (n = 133), non-ccRCC (n = 56), and benign renal tumor(n = 41) group. Parametric CT enhancement of each tumor from volumetric histogram were obtained using in-house software, including 10th percentile, 25th percentile, median, 75th percentile, 90th percentile, mean, standard deviation, as well as skewness, kurtosis and entropy, and histogram metrics among these groups were analyzed. ROI-based enhancement density was also analyzed. The entropy and SD values of ccRCCs were higher than those of non-ccRCCs and benign renal tumors (p < 0.05). The 10th percentile, 25th percentile, median, 75th percentile, 90th percentile and mean values of ccRCCs were lower than those of benign renal tumors, however, higher than those of non-ccRCCs (p < 0.05). The ROI-based enhancement density of non-ccRCCs were lower than those of ccRCCs and benign renal tumors(p < 0.05). Receiver operating characteristic (ROC) curve analyses showed that entropy and mean values had the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs and benign renal tumors. ROC curve analyses showed that mean values had the highest diagnostic efficacy in differentiating ccRCCs and non-ccRCCs. In terms of pairwise comparisons of ROC curves and diagnostic efficacy, ROI-based CT enhancement density was worse than volumetric histogram analysis (p < 0.05). Volumetric histogram analysis parameters can effectively distinguish malignant and benign renal tumors. 1. Entropy and mean values had the highest diagnostic efficacy in differentiating ccRCCs/ non-ccRCCs and benign renal tumors.2. Mean values had the highest diagnostic efficacy in differentiating ccRCCs and non-ccRCCs.3.Volumetric histogram analysis had better performance than ROI-based enhancement density.

The Prognostic Value of C-Reactive Protein/Albumin Ratio in Acute Mesenteric Ischemia.

Diagnosis of acute mesenteric ischemia (AMI) in its early stages is important for reversing ischemic damage. The CRP to albumin (CRP/Alb) ratio has been defined as an inflammatory indicator and is associated with the severity of inflammation and mortality rates. However, the prognostic value of CRP/Alb has not been evaluated in patients with AMI. Here, we aimed to examine the prognostic significance of CRP/Alb and compare it with other inflammatory markers. In this retrospective, case-control study, we included patients diagnosed with AMI at the emergency department between January 1, 2016, and December 31, 2020. In addition to demographic characteristics, lactate, D-dimer, white blood cell (WBC), CRP/Alb, and neutrophil/lymphocyte ratio (NLR) were recorded. Testing characteristics of CRP/Alb in predicting in-hospital mortality were studied. The mean age of 132 patients was 66.48 ± 15.95years and 71 (53.8%) of them were male. The cut-off value obtained using the receiver operating characteristic (ROC) curve for in-hospital mortality was a CRP/Alb ratio of >1.32 (sensitivity, 93.65%; specificity, 69.57%; +LR, 3.08; -LR, .091; AUC, .782; 95% CI, .70-.85; P < .0001). The comparison of ROC curves between CRP/Alb and WBC, NLR, and lactate revealed a statistically significant difference (P < .05), whereas there was not any statistically significant difference between the ROC curves of CRP/Alb and D-dimer (P = .47). C-reactive protein/albumin ratio is a powerful predictor of in-hospital mortality for AMI patients. It was superior to WBC, NLR, and lactate. It could be used to determine low-risk patients and help clinicians with treatment options.

Diagnostic Value of Immunoglobulin G Anti-Deamidated Gliadin Peptide Antibody for Diagnosis of Pediatric Celiac Disease: A Study from Shiraz, Iran.

PurposeScreening serologic tests are important tools for the diagnosis of celiac disease (CD). Immunoglobulin (Ig)G anti-deamidated gliadin peptide (anti-DGP) is a relatively new autoantibody thought to have good diagnostic accuracy, comparable to that of anti-tissue transglutaminase (anti-tTG) antibody.MethodsPediatric patients (n=86) with a clinical suspicion of CD were included. Duodenal biopsy, anti-tTG, and IgG anti-DGP antibody tests were performed. The patients were divided into CD and control groups based on the pathological evaluation of duodenal biopsies. The diagnostic accuracy of serological tests was determined.ResultsIgA anti-tTG and IgG anti-DGP antibodies were positive in 86.3% and 95.4% of patients, respectively. The sensitivity, specificity, and diagnostic accuracy of the IgA anti-tTG test were 86.3%, 50.0%, and 68.6%, respectively, and those of the IgG anti-DGP test were 95.4%, 85.7%, and 90.7%, respectively. The area under the receiver operating characteristic (ROC) curve was 0.84 (95% confidence interval [CI], 0.74–0.91) for IgA anti-tTG test and 0.93 (95% CI, 0.86–0.97) for IgG anti-DGP test. The comparison of IgA anti-tTG and IgG anti-DGP ROC curves showed a higher sensitivity and specificity of the IgG anti-DGP test.ConclusionIgG anti-DGP is a reliable serological test for CD diagnosis in children. High tTG and DGP titers in the serum are suggestive of severe duodenal atrophy. The combined use of IgA anti-tTG and IgG anti-DGP tests for the initial screening of CD can improve diagnostic sensitivity.