A meta-analysis of the accuracy of Xpert MTB/RIF in diagnosing intestinal tuberculosis.

OBJECTIVE: A detection method with high efficiency and accuracy is urgently needed in clinical work. The purpose of our study was to determine the diagnostic accuracy of the Xpert MTB/RIF assay for intestinal tuberculosis (ITB). METHODS: We searched PubMed and 4 other databases from their establishment to July 19, 2022, for published essays of diagnostic performance in which Xpert MTB/RIF was used to test patients with clinically suspected ITB. An assessment of the quality of the selected literature was conducted using QUADAS-2. We built forest plots by MetaDiSc software. RESULTS: The pooled Xpert MTB/RIF sensitivity was 48%, and the specificity was 99%. Moreover, the positive likelihood ratio for ITB diagnosis was 21.61. The negative likelihood ratio was 0.54. There were substantial variations between the study estimates of sensitivity (I2 = 87.6%) and specificity (I2 = 82.4%). CONCLUSION: Intestinal TB is detected with limited diagnostic sensitivity by Xpert MTB/RIF but with high specificity. An Xpert-positive result may facilitate the rapid identification of ITB cases. Nevertheless, a negative result has less certainty in excluding the disease.

Comparative study on risk prediction model of type 2 diabetes based on machine learning theory: a cross-sectional study.

OBJECTIVES: To compare the prediction effects of six models based on machine learning theories, which can provide a methodological reference for predicting the risk of type 2 diabetes mellitus (T2DM). SETTING AND PARTICIPANTS: This study was based on the monitoring data of chronic disease risk factors in Dongguan residents from 2016 to 2018. The multistage cluster random sampling method was adopted at each monitoring site, and 4157 people were finally selected. In the initial population, we excluded individuals with more than 20% missing data and eventually included 4106 subjects. DESIGN: K nearest neighbour algorithm and synthetic minority oversampling technique were used to process the data. Single factor analysis was used for preliminary selection of variables. The 10-fold cross-validation was used to optimise the parameters of some models. The accuracy, precision, recall and area under receiver operating characteristic curve (AUC) were used to evaluate the prediction effect of models, and Delong test was used to analyse the differences of AUC values of each model. RESULTS: After balancing data, the sample size increased to 8013, of which 4023 are patients with T2DM and 3990 in control group. The comparison results of the six models showed that back propagation neural network model has the best prediction effect with 93.7% accuracy, 94.6% accuracy, 92.8% recall and the AUC value of 0.977, followed by logistic model, support vector machine model, CART decision tree model and C4.5 decision tree model. Deep neural network has the worst prediction performance, with 84.5% accuracy, 86.1% precision, 82.9% recall and the AUC value of 0.845. CONCLUSIONS: In this study, six types of risk prediction models for T2DM were constructed, and the predictive effects of these models were compared based on various indicators. The results showed that back propagation neural network based on the selected data set had the best prediction effect.

Psychometric properties of the coronary heart disease scale of the quality-of-life instruments for chronic diseases (QLICD-CHD): an application to Cantonese patients.

The purpose of this study was to validate the applicability of our proposed disease-specific questionnaire to Cantonese coronary heart disease (CHD) patients. During the investigation from August 2010 to March 2012, 1000 Cantonese inpatients were recruited. The reliability of the scale was judged by the internal consistency, and the content and construct validity were assessed by using Pearson correlation and confirmatory factor analysis, respectively. Results showed that the Cronbach's α coefficient for the whole scale and most domains/facets were larger than .70 (.59 to .93). Most items had moderate to strong Pearson correlations with their respective facets (r > 0.50). Confirmatory factor analysis showed that the indices for goodness of fit were nearly acceptable. Overall, the QLICD-CHD scale has adequate psychometric properties when applied to Cantonese CHD patients.

[Identification of gene functional modules shared by cancers based on biclustering].

Pleiotropy is a common phenomenon in the genetics of cancers, which is rarely systematically evaluated. A novel idea for identifying shared gene functional modules using biclustering was proposed in this paper to explore the common molecular mechanisms among cancers and the relationships between different types of cancers. Gene expression datasets for 20 cancers were obtained. And genes differentially expressing in at least two types of cancers were selected using both moderated t-statistic and fold change to construct a 10417 × 20 matrix (gene-cancer matrix). 22 gene clusters shared by cancers were found by using the biclustering method. Further, Gene Ontology (GO)-based enrichment analysis identified 17 gene functional modules (Bonferroni corrected P < 0.05). The involved biological processes primarily included regulation of chromatids separation during mitosis, cell differentiation, immune and inflammatory response, and collagen fibril organization. These modules undertook molecular functions of ATP binding and microtubule motor activity, MHC class II receptor activity, endopeptidase inhibitor activity and so on. And their activity sites were mostly located in cytoskeleton, chromosome, MHC protein complex, intermediate filament, fibrillar collagen and so on. The network constructed based on these modules indicates that gastric cancer, ovarian adenocarcinoma, cervical cancer and mesothelioma were highly relevant to each other. However, the molecular mechanisms of two hematologic malignancies (acute myeloid leukemia and multiple myeloma) seem very different from other cancers. It can be seen that gene functional modules shared by cancers are associated with many biological mechanisms, and similarities among cancers are probably attributed to cellular origin and shared carcinogenic mechanisms. The proposed method for analysis of pleiotropy in this paper will help understand the common molecular mechanisms for complex human diseases.

A meta-analysis of the association between TNF-α -308G>A polymorphism and type 2 diabetes mellitus in Han Chinese population.

OBJECTIVE: A meta-analysis was applied to evaluate the associations between tumor necrosis factor-α (TNF-α) -308G>A (rs1800629) polymorphism and type 2 diabetes mellitus (T2DM). METHODS: Hardy-Weinberg equilibrium (HWE) was employed to test genetic equilibrium among the genotypes of the selected literature. Power analysis was performed with the Power and Sample Size Calculation (PS) program. A fixed or random effect model was used on the basis of heterogeneity. Publication bias was quantified and examined with the Begg's funnel plot test and Egger's linear regression test. The meta-analysis was performed with Review Manager 5.1 and Stata 11.0. RESULTS: There were 10 studies including 1425 T2DM patients and 1116 healthy control subjects involved in this meta-analysis. No significant publication bias was found in the studies. The pooled ORs (95% CIs) for TNF-α -308G>A of A vs. G allele and GA+AA vs. GG genotype were 1.63 (1.17-2.25) and 1.47 (1.17-1.85), respectively. CONCLUSION: This meta-analysis result suggested that TNF-α -308G>A polymorphism was strongly associated with T2DM risk, and A allele at this locus might be a susceptibility allele for the development of T2DM in Han Chinese population.

Laryngeal aerodynamic analysis in assisting with the diagnosis of muscle tension dysphonia.

OBJECTIVE/HYPOTHESIS: To estimate the aerodynamic multiparameters for patients with muscular tension dysphonia (MTD) and evaluate voice aerodynamic analysis for assisting the diagnosis of this disorder. STUDY DESIGN: A prospective study. METHODS: Voice aerodynamic parameters, including subglottal pressure (SGP) level, glottal resistance (GR), mean airflow rate (MFR), and maximum phonation time (MPT), for 26 MTD patients and 27 normal adults were analyzed using receiver operating characteristics (ROC) analysis and multivariate logistic regression. RESULTS: For male samples, MTD patients had higher SGP (P=0.001), higher GR (P=0.012), lower MFR (P=0.042), and shorter MPT (P=0.027), whereas for female samples, the difference between cases and controls was statistically significant only in SGP (P<0.001) and MPT (P<0.001). ROC analysis showed that the threshold of 8.175 cm H(2)O for SGP achieved a good classification for MTD, with an adequate sensitivity (76.9%) and the perfect specificity (100%). Finally, multivariate logistic regression established a credible model (with SGP and MPT as the predictors) for classifying MTD, with a 92.5% percentage correct. CONCLUSIONS: This analysis indicates that aerodynamics evaluation could help the diagnosis of MTD patients, jointly with medical history scrutiny, physical examination, fibrolaryngoscopy, and/or videoendostroboscopy.

SOD2 V16A SNP in the mitochondrial targeting sequence is associated with noise induced hearing loss in Chinese workers.

OBJECTIVE: To investigate whether single nucleotide polymorphisms (SNPs) in the Mn-superoxide dismutase gene (SOD2) underlie the susceptibility to noise-induced hearing loss (NIHL). METHODS: Audiometric data from 2400 Chinese Han workers who exposed to occupational noise were analyzed. DNA samples were collected from the 10% most susceptible and the 10% most resistant individuals, and five SNPs (SOD2 rs2842980, rs5746136, rs2758331, rs4880 and rs5746092) were genotyped by Taqman SNP Genotyping Kits. The SNP main effects and interactions between noise exposure and SNP were analyzed using logistic regression. Haplotypes were analyzed by using Haploview software. RESULTS: The CT genotype of rs4880 (SOD2 V16A SNP) was associated with a higher risk of NIHL (covariates-adjusted OR, 2.18; 95% CI, 1.34-3.54, P=0.002). Haplotype analysis revealed that the frequency of AGCCG at the five SNP loci was significantly higher in the susceptible group (P=0.020). With AGCTG as the reference, the OR (95% CI) was 2.63 (1.14, 6.06). The rs4880 polymorphisms imposed larger effects when the carriers were exposed to higher levels of noise, indicating the interaction between SNP and noise exposure. CONCLUSIONS: Our results suggest that SOD2 V16A SNP in the mitochondrial targeting sequence is associated with noise induced hearing loss in Chinese workers, and this effect was enhanced by higher levels of noise exposure.