Shear wave elastography as a quantitative biomarker of diabetic peripheral neuropathy: A systematic review and meta-analysis

BackgroundDiabetic peripheral neuropathy (DPN) is one of the most common chronic complications of diabetes and the strongest initiating risk factor for diabetic foot ulceration. Early diagnosis of DPN through screening measures is, therefore, of great importance for diabetic patients. Recently, shear wave elastography (SWE) has been used as a method that is complementary to neuroelectrophysiological examination in the diagnosis of DPN. We aimed to conduct a meta-analysis based on currently available data to evaluate the performance of tibial nerve stiffness on SWE for diagnosing DPN.MethodsBoth PubMed, EMBASE, the Cochrane Library, and Web of Science were searched for studies that investigated the diagnostic performance of SWE for DPN up to March 1th, 2022. Three measures of diagnostic test performance, including the summary area under receiver operating characteristics curve (AUROC), the summary sensitivity and specificity, and the summary diagnostic odds ratios were used to assess the diagnostic accuracy of SWE. All included studies were published between 2017 and 2021.ResultsSix eligible studies (with 170 DPN patients, 28 clinically defined DPN patients, 168 non-DPN patients, and 154 control participants) that evaluated tibial nerve stiffness were included for meta-analysis. The summary sensitivity and specificity of SWE for tibial nerve stiffness were 75% (95% confidence interval [CI]: 68–80%) and 86% (95% CI: 80–90%), respectively, and the summary AUROC was 0.84 (95% CI: 0.81–0.87), for diagnosing DPN. A subgroup analysis of five two-dimensional SWE studies revealed similar diagnostic performance, showing the summary sensitivity and specificity of 77% (95% CI: 69–83%) and 86% (95% CI: 79–91%), respectively, and a summary AUROC value of 0.86 (95% CI: 0.83–0.89).ConclusionsSWE is found to have good diagnostic accuracy for detecting DPN and has considerable potential as an important and noninvasive adjunctive tool in the management of patients with DPN

Prognostic nomograms for predicting overall survival and cancer-specific survival of patients with very early-onset colorectal cancer: A population‑based analysis

In contrast to the declining incidence in older populations, the incidence of very early onset colorectal cancer (VEO-CRC) patients (aged ≤40 years) has been increasing in different regions of the world. In this study, we aimed to establish nomogram models for the prognostic prediction of patients with VEO-CRC for both overall survival (OS) and cancer-specific survival (CSS). Patients diagnosed with VEO-CRC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were collected and randomly assigned to the training cohort and validation cohort at a ratio of 7:3 for model construction and internal validation. Using univariate and multivariate Cox regression analysis to screen important variables, which were then used to construct a nomogram. The nomogram was evaluated using calibration curves and the receiver operating characteristic (ROC) curves. A total of 3061 patients were included and randomly divided into the training cohort (n = 2145) and validation cohort (n = 916). Five independent prognostic factors, including race, grade, tumor size, AJCC stage, and AJCC T stage were all significantly identified in OS multivariate Cox regression analysis. Meanwhile in CSS, multivariate Cox regression analysis demonstrated that race, grade, tumor size, AJCC stage, AJCC T stage, AJCC N stage, and SEER stage were independent prognostic factors.  The calibration plots of the established nomograms indicated high correlations between the predicted and observed results. C-index and ROC analysis implied that our nomogram model has a strong predictive ability. Moreover, nomograms also showed higher C-index values compared to tumor-node-metastasis (TNM) and SEER stages. We established and validated a simple-to-use nomogram to evaluate the 1-, 3-, and 5-year OS and CSS prognosis of patients with VEO-CRC. This tool can assist clinicians to optimize individualized treatment plans

Characterization of ultrasound and postnatal pathology in fetuses with heterotaxy syndrome

BackgroundTo explore the diagnostic clues and abnormality spectrum of heterotaxy syndrome by prenatal ultrasonography and postnatal verification.MethodsThe prenatal ultrasonic data of 88 heterotaxy syndrome fetuses were analyzed retrospectively as left isomerism (LI) and right isomerism (RI). Prenatal ultrasound compared with the anatomical casting of the fetal body after labor induction, and the confirmatory postnatal diagnosis after delivery.ResultsFetal LI showed typical malformations of gastric vesicles on different sides from the heart, absence of hepatic segment of the inferior vena cava (IVC), abdominal aorta (AO) parallel with the azygos vein (AV), bilateral left bronchus, bilateral left atrial appendages, and polysplenia; intracardiac malformations of AV septal defects (AVSD), single atrium (SA), left ventricular outflow tract obstruction (LVOTO), and double-outlet right ventricle (DORV); and cardiac conduction abnormalities of sinus bradycardia and AV blockage. Fetal RI reported typical malformations of gastric vesicles on different sides from the heart, juxtaposition of the IVC with AO, anomalous pulmonary venous connection (APVC), asplenia, and bilateral right atrial appendages; intracardiac malformations of AVSD, SA, single ventricle, pulmonary atresia and stenosis, and DORV. The postnatal verification revealed 3 malformations misdiagnoses and 4 malformations missed diagnoses in LI fetuses and 10 misdiagnoses and 8 missed diagnoses in RI fetuses.ConclusionsThe proposed five-step prenatal ultrasonography has an important diagnostic value for the identification and classification of heterotaxy syndrome. The different sides of gastric vesicles and cardiac apex are important diagnostic clues for heterotaxy syndrome, featuring disconnected or hypoplastic IVC, typical complex cardiac malformation, and atrioventricular block in fetal LI, and shown APVC, juxtaposition of IVC and AO, and intracardiac malformations such as AVSD, DORV, and LVOTO in fetal RI

Maternal body fluid lncRNAs serve as biomarkers to diagnose ventricular septal defect: from amniotic fluid to plasma

Background: Maternal body fluids contain abundant cell-free fetal RNAs which have the potential to serve as indicators of fetal development and pathophysiological conditions. In this context, this study aimed to explore the potential diagnostic value of maternal circulating long non-coding RNAs (lncRNAs) in ventricular septal defect (VSD).Methods: The potential of lncRNAs as non-invasive prenatal biomarkers for VSD was evaluated using quantitative polymerase chain reaction (qPCR) and receiver operating characteristic (ROC) curve analysis. The biological processes and regulatory network of these lncRNAs were elucidated through bioinformatics analysis.Results: Three lncRNAs (LINC00598, LINC01551, and GATA3-AS1) were found to be consistent in both maternal plasma and amniotic fluid. These lncRNAs exhibited strong diagnostic performance for VSD, with AUC values of 0.852, 0.957, and 0.864, respectively. The bioinformatics analysis revealed the involvement of these lncRNAs in heart morphogenesis, actin cytoskeleton organization, cell cycle regulation, and protein binding through a competitive endogenous RNA (ceRNA) network at the post-transcriptional level.Conclusion: The cell-free lncRNAs present in the amniotic fluid have the potential to be released into the maternal circulation, making them promising candidates for investigating epigenetic regulation in VSD

The dimethadione-exposed rat fetus: an animal model for the prenatal ultrasound characterization of ventricular septal defect

Abstract Background Ventricular septal defect (VSD) is the most prevalent congenital heart disease (CHD) and is easily misdiagnosed or missed. An appropriate VSD animal model could be used to analyze the ultrasound characteristics and their related pathological bases, and provides the opportunity to further explore the pathogenesis of VSD. Currently, little is known about whether ultrahigh-frequency ultrasound biomicroscopy (UBM) is suitable to diagnose VSD of fetal rats. There is no research on whether a dimethadione (DMO)-induced fetal VSD model is suitable for the observation and analysis of imaging characteristics and the associated pathological basis. Methods We used DMO to induce VSD. UBM was used to perform the prenatal ultrasound characterization. With the pathological results used as the gold standard, the ultrasound characteristics and their related pathological bases were analyzed. Results The incidence of VSD in the DMO group was 42.05% and 39.71% (diagnosed by UBM and pathology, respectively, P > 0.05). The prenatal ultrasound findings and pathological basis of various diseases, including isolated VSD, complex CHD containing VSD, and extracardiac lesions, were detected and discussed. It was discovered that some fetuses showed features of noncompacted ventricular myocardium, and for the first time, clusters of red blood cell traversing the cardiomyocytes. Conclusions The DMO-induced VSD model is a low-cost model with a high success rate and is suitable for the observation and analysis of VSD. UBM is suitable for evaluating VSD

Lamb Waves Propagation Characteristics in Functionally Graded Sandwich Plates

Functionally graded materials (FGM) have received extensive attention in recent years due to their excellent mechanical properties. In this research, the theoretical process of calculating the propagation characteristics of Lamb waves in FGM sandwich plates is deduced by combining the FGM volume fraction curve and Legendre polynomial series expansion method. In this proposed method, the FGM plate does not have to be sliced into multiple layers. Numerical results are given in detail, and the Lamb wave dispersion curves are extracted. For comparison, the Lamb wave dispersion curve of the sliced layer model for the FGM sandwich plate is obtained by the global matrix method. Meanwhile, the FGM sandwich plate was subjected to finite element simulation, also based on the layered-plate model. The acoustic characteristics detection experiment was performed by simulation through a defocusing measurement. Thus, the Lamb wave dispersion curves were obtained by V(f, z) analysis. Finally, the influence of the change in the gradient function on the Lamb wave dispersion curves will be discussed

Dataset of mitochondrial genome variants in oncocytic tumors

This dataset presents the mitochondrial genome variants associated with oncocytic tumors. These data were obtained by Sanger sequencing of the whole mitochondrial genomes of oncocytic tumors and the adjacent normal tissues from 32 patients. The mtDNA variants are identified after compared with the revised Cambridge sequence, excluding those defining haplogroups of our patients. The pathogenic prediction for the novel missense variants found in this study was performed with the Mitimpact 2 program

Risk estimation for postoperative nausea and vomiting: development and validation of a nomogram based on point-of-care gastric ultrasound

Abstract Background We aimed to develop a nomogram that can be combined with point-of-care gastric ultrasound and utilised to predict postoperative nausea and vomiting (PONV) in adult patients after emergency surgery. Methods Imaging and clinical data of 236 adult patients undergoing emergency surgery in a university hospital between April 2022 and February 2023 were prospectively collected. Patients were divided into a training cohort (n = 177) and a verification cohort (n = 59) in a ratio of 3:1, according to a random number table. After univariate analysis and multivariate logistic regression analysis of the training cohort, independent risk factors for PONV were screened to develop the nomogram model. The receiver operating characteristic curve, calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the prediction efficiency, accuracy, and clinical practicability of the model. Results Univariate analysis and multivariate logistic regression analysis showed that female sex, history of PONV, history of migraine and gastric cross-sectional area were independent risk factors for PONV. These four independent risk factors were utilised to construct the nomogram model, which achieved significant concordance indices of 0.832 (95% confidence interval [CI], 0.771–0.893) and 0.827 (95% CI, 0.722–0.932) for predicting PONV in the training and validation cohorts, respectively. The nomogram also had well-fitted calibration curves. DCA and CIC indicated that the nomogram had great clinical practicability. Conclusions This study demonstrated the prediction efficacy, differentiation, and clinical practicability of a nomogram for predicting PONV. This nomogram may serve as an intuitive and visual guide for rapid risk assessment in patients with PONV before emergency surgery