Association between Helicobacter pylori and nonalcoholic fatty liver disease： A Meta-analysis / 临床肝胆病杂志

ObjectiveTo investigate the association between Helicobacter pylori infection and nonalcoholic fatty liver disease （NAFLD）. MethodsThis study was conducted acoording to the PRISMA guideline， with a PROSPERO registration number of CRD42023408932. Databases including PubMed， the Cochrane Library， Web of Science， Embase， CBM， Wanfang Data， CNKI， and VIP were searched for related articles published up to June 2023. This study was conducted for the case-control studies， cross-sectional studies， and cohort studies that included clear detection criteria for HP and evaluation criteria for NAFLD and performed the multivariate analysis to investigate the association between HP infection and NAFLD. Odds ratio （OR） and its 95% confidence interval （CI） were selected as the effect measures， and STATA 15.0 software was used to perform the Meta-analysis. ResultsA total of 33 primary studies were included， with 236 514 subjects in total. The Meta-analysis showed that HP was associated with the high prevalence rate of NAFLD （OR=1.25， 95%CI： 1.16‍ ‍—‍ ‍1.35， P<0.05， I2=93.7%）. Subgroup analysis was conducted in terms of sample size， the diagnostic method for HP， the quality of primary study， the health status of subjects， and the type of primary study， but no clear source of heterogeneity was found. The Meta-regression analysis was conducted with the covariates of sample size， the diagnostic method for HP， the quality of primary study， the health status of subjects， and the type of primary study， and the results showed that the health status of subjects and the type of primary study might be the sources of heterogeneity. Sensitivity analysis showed that the overall results were stable， and funnel plots and the Egger test showed no significant publication bias. ConclusionHP is associated with the high prevalence rate of NAFLD in the general population， and large-scale prospective cohort studies are still needed to specifically and comprehensively evaluate the association between HP and NAFLD.

Preoperative MRI radiomics models for predicting risk stratification of endometrial cancer / 中国医学影像技术

Objective To observe the value of preoperative MRI radiomics models for predicting risk stratification of endometrial cancer(EC).Methods Data of 219 EC patients who underwent pelvic MR examination before surgery were retrospectively analyzed.The patients were divided into high risk group(n=104)or low risk group(n=115)according to postoperative pathological findings,also assigned into training set(n=153)or test set(n=66)according to examination time and further divided into high or low risk subgroups in each set.ROI was manually sketched on MRI using 3D Slicer,and each 1 130 features were extracted from axial and sagittal fat suppression(FS)T2WI as well as axial and sagittal enhanced FS-T1WI,respectively.Then the least absolute shrinkage and selection operator(LASSO)was used to select a total of 54 merged MRI features,including 12,14,16 and 12 features,respectively.Finally,25 merged LASSO features were reduced dimensionality and selected by reusing LASSO.Extremely randomized trees algorithm was used to construct radiomics models based on each single sequence features,merged MRI features and merged LASSO features,respectively.Receiver operating characteristic curves were drawn,the area under the curve(AUC),the accuracy and F1 score were obtained to evaluate the predicting efficacy of each model.AUC was used to evaluate the predictive efficacy of the models and subjective diagnosis of test set.Results In training set,the accuracy(0.784,0.777),F1 score(0.730,0.731)and AUC(0.835,0.855)of modelmerged MRI and modelmerged LASSO were both higher than those of each single sequence model,while in test set,the sensitivity(0.794,0.882),specificity(0.909,0.969)and AUC(0.904,0.934)of modelmerged MRI and modelmerged LASSO were both higher than those of subjective diagnosis and each single sequence model.The predictive effiency of modelmerged LAsSo was better than that of modelmerged MRI,which was the best model.Conclusion Preoperative MRI radiomics model was effective for predicting risk stratification of endometrial cancer.Modelmerged LASSO had the best performance.

Perioperative nursing of 83 patients with sialolithiasis treated by sialoendoscope / 中华护理杂志

This paper introduces the perioperative nursing of 83 sialolithiasis patients undergoing sialolithectomy by sialoendoscope. The key points of successful nursing care were careful preoperative psychological nursing and equipment preparation, correct and skilled intraoperative cooperation, and early postoperative health instruction. As a result, all the patients underwent the surgery succesfully and recovered well except 3 cases who needed gland removal later.