Genetic causal relationship between immune diseases and migraine: a Mendelian randomization study.

Background: Migraine has an increased prevalence in several immune disorders, but genetic cause-effect relationships remain unclear. Mendelian randomization (MR) was used in this study to explore whether immune diseases are causally associated with migraine and its subtypes. Methods: We conducted a two-sample bidirectional multivariate Mendelian randomization study. Single-nucleotide polymorphisms (SNP) for six immune diseases, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes mellitus (T1D), allergic rhinitis (AR), asthma and psoriasis, were used as genetic instrumental variables. Summary statistics for migraine were obtained from 3 databases: the International Headache Genetics Consortium (IHGC), UK Biobank, and FinnGen study. MR analyses were performed per outcome database for each exposure and subsequently meta-analyzed. Reverse MR analysis was performed to determine whether migraine were risk factors for immune diseases. In addition, we conducted a genetic correlation to identify shared genetic variants for these two associations. Results: No significant causal relationship was found between immune diseases and migraine and its subtypes. These results were robust with a series of sensitivity analyses. Using the linkage disequilibrium score regression method (LDSC), we detected no genetic correlation between migraine and immune diseases. Conclusion: The evidence from our study does not support a causal relationship between immune diseases and migraine. The mechanisms underlying the frequent comorbidity of migraine and several immune diseases need to be further elucidated.

Noninvasive Diagnostic Technique for Nonalcoholic Fatty Liver Disease Based on Features of Tongue Images.

OBJECTIVE: To investigate a new noninvasive diagnostic model for nonalcoholic fatty liver disease (NAFLD) based on features of tongue images. METHODS: Healthy controls and volunteers confirmed to have NAFLD by liver ultrasound were recruited from China-Japan Friendship Hospital between September 2018 and May 2019, then the anthropometric indexes and sampled tongue images were measured. The tongue images were labeled by features, based on a brief protocol, without knowing any other clinical data, after a series of corrections and data cleaning. The algorithm was trained on images using labels and several anthropometric indexes for inputs, utilizing machine learning technology. Finally, a logistic regression algorithm and a decision tree model were constructed as 2 diagnostic models for NAFLD. RESULTS: A total of 720 subjects were enrolled in this study, including 432 patients with NAFLD and 288 healthy volunteers. Of them, 482 were randomly allocated into the training set and 238 into the validation set. The diagnostic model based on logistic regression exhibited excellent performance: in validation set, it achieved an accuracy of 86.98%, sensitivity of 91.43%, and specificity of 80.61%; with an area under the curve (AUC) of 0.93 [95% confidence interval (CI) 0.68-0.98]. The decision tree model achieved an accuracy of 81.09%, sensitivity of 91.43%, and specificity of 66.33%; with an AUC of 0.89 (95% CI 0.66-0.92) in validation set. CONCLUSIONS: The features of tongue images were associated with NAFLD. Both the 2 diagnostic models, which would be convenient, noninvasive, lightweight, rapid, and inexpensive technical references for early screening, can accurately distinguish NAFLD and are worth further study.

Development and validation of non-invasive prediction models for migraine in Chinese adults.

BACKGROUND: Migraine is a common disabling neurological disorder with severe physical and psychological damage, but there is a lack of convenient and effective non-invasive early prediction methods. This study aimed to develop a new series of non-invasive prediction models for migraine with external validation. METHODS: A total of 188 and 94 subjects were included in the training and validation sets, respectively. A standardized professional questionnaire was used to collect the subjects' 9-item traditional Chinese medicine constitution (TCMC) scores, Pittsburgh Sleep Quality Index (PSQI) score, Zung's Self-rating Anxiety Scale and Self-rating Depression Scale scores. Logistic regression was used to analyze the risk predictors of migraine, and a series of prediction models for migraine were developed. Receiver operating characteristic (ROC) curve and calibration curve were used to assess the discrimination and calibration of the models. The predictive performance of the models were further validated using external datasets and subgroup analyses were conducted. RESULTS: PSQI score and Qi-depression score were significantly and positively associated with the risk of migraine, with the area of the ROC curves (AUCs) predicting migraine of 0.83 (95% CI:0.77-0.89) and 0.76 (95% CI:0.68-0.84), respectively. Eight non-invasive predictive models for migraine containing one to eight variables were developed using logistic regression, with AUCs ranging from 0.83 (95% CI: 0.77-0.89) to 0.92 (95% CI: 0.89-0.96) for the training set and from 0.76 (95% CI: 0.66-0.85) to 0.83 (95% CI: 0.75-0.91) for the validation set. Subgroup analyses showed that the AUCs of the eight prediction models for predicting migraine in the training and validation sets of different gender and age subgroups ranged from 0.80 (95% CI: 0.63-0.97) to 0.95 (95% CI: 0.91-1.00) and 0.73 (95% CI: 0.64-0.84) to 0.93 (95% CI: 0.82-1.00), respectively. CONCLUSIONS: This study developed and validated a series of convenient and novel non-invasive prediction models for migraine, which have good predictive ability for migraine in Chinese adults of different genders and ages. It is of great significance for the early prevention, screening, and diagnosis of migraine.

Efficacy and safety of intranasal agents for the acute treatment of migraine: a systematic review and network meta-analysis.

BACKGROUND: Intranasal agents may be ideal for the treatment of migraine patients. Many new acute intranasal-specific therapies have been developed, but few of them have been directly compared. The aim of this network meta-analysis (NMA) was to compare the efficacy and safety of various intranasal agents for the treatment of acute migraine in adult patients. METHODS: The Cochrane Register of Controlled Trials, Embase, and PubMed were searched from inception to 15 August 2023. Randomized controlled trials (RCTs) using intranasal agents (no restrictions on dose, formulation, dosing regimen or timing of the first dose) to treat adult patients with acute migraine were included. The primary efficacy endpoint was pain freedom at 2 h, and the primary safety endpoint was adverse events (AEs). The analysis process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. RESULTS: Nineteen studies (21 RCTs, 9738 participants) were included. Compared to the placebo, 5 mg of zolmitriptan using a conventional liquid nasal spray device was the most effective for pain freedom at 2 h [odds ratio (OR): 4.67, 95% confidence interval (CI): 3.43 to 6.43] and 24 h (OR: 5.49, 95% CI: 3.58 to 8.42) among all the interventions. Butorphanol nasal spray 1 mg was the most effective (OR: 8.62, 95% CI: 1.11 to 66.92) for pain freedom at 1 h, but with low-quality evidence. DFN-02 presented the highest freedom from nausea (OR: 4.95, 95% CI: 1.29 to 19.01) and phonophobia (OR: 5.36, 95% CI: 1.67 to 17.22) at 2 h, albeit with lower odds of achieving complete pain freedom. ROX-828 showed the highest improvement in freedom from photophobia at 2 h (OR: 4.03, 95% CI: 1.66 to 9.81). Dihydroergotamine nasal spray was significantly associated with the highest risk of AEs (OR: 9.65, 95% CI: 4.39 to 21.22) and was not recommended for routine use. Zavegepant nasal spray demonstrated the lowest risk of AEs (OR: 2.04, 95% CI: 1.37 to 3.03). The results of sensitivity analyses for the primary endpoints (pain freedom at 2 h and AEs) were generally consistent with those of the base case model. CONCLUSIONS: Compared with other new intranasal-specific therapies in treating migraine attacks, zolmitriptan nasal spray 5 mg was the most effective agent for pain freedom at 2 h. Zavegepant nasal spray 10 mg had the fewest adverse side effects.

Associations between anxiety, depression with migraine, and migraine-related burdens.

Background: Anxiety and depression are the most common psychiatric comorbidities in migraine, but their impact on the risk of developing migraine and their gender and age differences are unclear, and research on their associations with migraine-related burdens are limited. Objective: To systematically explore the association between anxiety and depression with migraine and migraine-related burdens, including the risk of developing migraine, as well as migraine frequency, severity, disability, headache impact, quality of life and sleep quality. Methods: A total of 170 migraineurs and 85 sex-and age-matched healthy control subjects were recruited consecutively for this study. Anxiety and depression were assessed using Zung's Self-rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS), respectively. Logistic regression and linear regression analyses were used to explore the associations between anxiety and depression with migraine and its burdens. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of SAS score and SDS score on migraine and its severe burdens. Results: After adjusting for confounders, anxiety and depression remained significantly associated with an increased risk of developing migraine, with odds ratios of 5.186 (95% CI:1.755-15.322) and 3.147 (95% CI:1.387-7.141), respectively. Meanwhile, there were significant additive interactions between the association of anxiety and depression with the risk of developing migraine in gender and age (P for interaction <0.05), and the stronger correlations were found in participants with an age ≤ 36 years old and females. In addition, anxiety and depression were significantly independently associated with the migraine frequency, severity, disability, headache impact, quality of life, and sleep quality in migraine patients (P trend <0.05). The area under the ROC curve (AUC) of SAS score in predicting developing migraine was significantly higher than that of SDS score [0.749 (95% CI: 0.691-0.801) vs. 0.633 (95% CI: 0.571-0.692), p < 0.0001]. Conclusion: Anxiety and depression were significantly independently associated with the increased risk of migraine and migraine-related burdens. Enhanced assessment of SAS score and SDS score is of great clinical value for the early prevention and treatment of migraine and its burdens.

Development and validation of machine learning models for nonalcoholic fatty liver disease.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) had become the most prevalent liver disease worldwide. Early diagnosis could effectively reduce NAFLD-related morbidity and mortality. This study aimed to combine the risk factors to develop and validate a novel model for predicting NAFLD. METHODS: We enrolled 578 participants completing abdominal ultrasound into the training set. The least absolute shrinkage and selection operator (LASSO) regression combined with random forest (RF) was conducted to screen significant predictors for NAFLD risk. Five machine learning models including logistic regression (LR), RF, extreme gradient boosting (XGBoost), gradient boosting machine (GBM), and support vector machine (SVM) were developed. To further improve model performance, we conducted hyperparameter tuning with train function in Python package 'sklearn'. We included 131 participants completing magnetic resonance imaging into the testing set for external validation. RESULTS: There were 329 participants with NAFLD and 249 without in the training set, while 96 with NAFLD and 35 without were in the testing set. Visceral adiposity index, abdominal circumference, body mass index, alanine aminotransferase (ALT), ALT/AST (aspartate aminotransferase), age, high-density lipoprotein cholesterol (HDL-C) and elevated triglyceride (TG) were important predictors for NAFLD risk. The area under curve (AUC) of LR, RF, XGBoost, GBM, SVM were 0.915 [95% confidence interval (CI): 0.886-0.937], 0.907 (95% CI: 0.856-0.938), 0.928 (95% CI: 0.873-0.944), 0.924 (95% CI: 0.875-0.939), and 0.900 (95% CI: 0.883-0.913), respectively. XGBoost model presented the best predictive performance, and its AUC was enhanced to 0.938 (95% CI: 0.870-0.950) with further parameter tuning. CONCLUSIONS: This study developed and validated five novel machine learning models for NAFLD prediction, among which XGBoost presented the best performance and was considered a reliable reference for early identification of high-risk patients with NAFLD in clinical practice.

Nonlinear correlation between fatty liver index and carotid intima media thickness among individuals undergoing health examination.

Background: Fatty liver index (FLI) is a predictor of non-alcohol fatty liver disease (NAFLD). This study aimed to assess the association between FLI and carotid intima media thickness (CIMT). Methods: In this cross-sectional study, we enrolled 277 individuals for health examination from the China-Japan Friendship Hospital. Blood sampling and ultrasound examinations were conducted. Multivariate logistic regression and restricted cubic spline analyses were performed to evaluate the association between FLI and CIMT. Results: Overall, 175 (63.2%) and 105 (37.9%) individuals had NAFLD and CIMT, respectively. The multivariate logistic regression analyses results showed that high FLI was independently associated with a high risk of increased CIMT, T2 vs. T1 (odds ratio [OR], 95% confidence interval [CI]): 2.41, 1.10-5.25, p = 0.027; T3 vs. T1 (OR, 95% CI): 1.58, 0.68-3.64, p = 0.285. The association between FLI and increased CIMT exhibited a J-shaped curve (nonlinear, p = 0.019). In the threshold analysis, the OR for developing increased CIMT was 1.031 (95% CI: 1.011-1.051, p = 0.0023) in participants with FLI < 64.247. Conclusion: The relationship between FLI and increased CIMT in the health examination population is J-shaped, with an inflection point of 64.247.

Studying the imaging features and infarction mechanism of vertebrobasilar dolichoectasia with high-resolution magnetic resonance imaging.

The mechanisms underlying ischemic infarction in patients with vertebrobasilar dolichoectasia (VBD) remain unclear. In this study, we retrospectively analyzed the imaging characteristics of high-resolution magnetic resonance imaging (HR-MRI) in patients with VBD to explore the possible mechanisms of ischemic stroke (IS) in patients with VBD. Patients with VBD were recruited from the HR-MRI database between July 2017 and June 2021. HR-MRI was used to evaluate the diameter, bifurcation height, laterality, arterial dissection, and atherosclerotic plaques of the basilar artery (BA). Transcranial Doppler was used to measure the vertebrobasilar mean velocity (Vm), peak systolic velocity (Vs), end-diastolic velocity (Vd), and pulsatile index. Twenty-six patients with VBD were enrolled, of which 15 had IS and 11 did not. The incidence of classical vascular risk factors, including age, sex, hypertension, diabetes, and hypercholesterolemia, did not differ significantly between the two groups. The BA diameters of the stroke group were significantly higher than that of the nonstroke group (6.57 ± 1.00 mm vs. 5.06 ± 0.50 mm, p = 0.000). The height of the BA bifurcation in the stroke and nonstroke groups was statistically significant (p = 0.002). Compared with the nonstroke group, the Vm, Vs, and Vd of the BA in the stroke group were lower, but the difference was not significant. In the 16 patients with atherosclerotic stenosis, 30 atherosclerotic plaques were found in the BA, 18 (60%) in the greater curvature, and 12 (40%) in the lesser curvature. In addition, one artery dissection (on the lesser curvature) and two dissecting aneurysms (on the greater curvature) were found in the BA of three patients, respectively. The BA diameter and bifurcation height are factors related to IS in patients with VBD. The mechanism of stroke in patients with VBD may involve abnormal hemodynamics, artery dissection, and atherosclerosis. HR-MRI is a useful method for evaluating the risk and underlying mechanism of stroke in patients with VBD.

Optimum non-invasive predictive indicators for metabolic dysfunction-associated fatty liver disease and its subgroups in the Chinese population: A retrospective case-control study.

Objective: Metabolic dysfunction-associated fatty liver disease (MAFLD) affects 25% of the population without approved drug therapy. According to the latest consensus, MAFLD is divided into three subgroups based on different diagnostic modalities, including Obesity, Lean, and Type 2 diabetes mellitus (T2DM) MAFLD subgroups. This study aimed to find out the optimum non-invasive metabolism-related indicators to respectively predict MAFLD and its subgroups. Design: 1058 Chinese participants were enrolled in this study. Anthropometric measurements, laboratory data, and ultrasonography features were collected. 22 metabolism-related indexes were calculated, including fatty liver index (FLI), lipid accumulation product (LAP), waist circumference-triglyceride index (WTI), etc. Logistic regression analyzed the correlation between indexes and MAFLD. Receiver operating characteristics were conducted to compare predictive values among 22 indicators for screening the best indicators to predict MAFLD in different subgroups. Results: FLI was the best predictor with the maximum odds ratio (OR) values of overall MAFLD (OR: 6.712, 95%CI: 4.766-9.452, area under the curve (AUC): 0.879, P < 0.05) and T2DM MAFLD subgroup (OR: 14.725, 95%CI: 3.712-58.420, AUC: 0.958, P < 0.05). LAP was the best predictor with the maximum OR value of Obesity MAFLD subgroup (OR: 2.689, 95%CI: 2.182-3.313, AUC: 0.796, P < 0.05). WTI was the best predictor with the maximum OR values of Lean MAFLD subgroup (OR: 3.512, 95%CI: 2.286-5.395, AUC: 0.920, P < 0.05). Conclusion: The best predictors of overall MAFLD, Obesity, Lean, and T2DM MAFLD subgroups were respectively FLI, LAP, WTI, and FLI.

Atherogenic index of plasma combined with waist circumference and body mass index to predict metabolic-associated fatty liver disease.

BACKGROUND: Early identification of metabolic-associated fatty liver disease (MAFLD) is urgent. Atherogenic index of plasma (AIP) is a reference predictor of obesity-related diseases, but its predictive value for MAFLD remains unclear. No studies have reported whether its combination with waist circumference (WC) and body mass index (BMI) can improve the predictive performance for MAFLD. AIM: To systematically explore the relationship between AIP and MAFLD and evaluate its predictive value for MAFLD and to pioneer a novel noninvasive predictive model combining AIP, WC, and BMI while validating its predictive performance for MAFLD. METHODS: This cross-sectional study consecutively enrolled 864 participants. Multivariate logistic regression analysis and receiver operating characteristic curve were used to evaluate the relationship between AIP and MAFLD and its predictive power for MAFLD. The novel prediction model A-W-B combining AIP, WC, and BMI to predict MAFLD was established, and internal verification was completed by magnetic resonance imaging diagnosis. RESULTS: Subjects with higher AIP exhibited a significantly increased risk of MAFLD, with an odds ratio of 12.420 (6.008-25.675) for AIP after adjusting for various confounding factors. The area under receiver operating characteristic curve of the A-W-B model was 0.833 (0.807-0.858), which was significantly higher than that of AIP, WC, and BMI (all P < 0.05). Subgroup analysis illustrated that the A-W-B model had significantly higher area under receiver operating characteristic curves in female, young and nonobese subgroups (all P < 0.05). The best cutoff values for the A-W-B model to predict MAFLD in males and females were 0.5932 and 0.4105, respectively. Additionally, in the validation set, the area under receiver operating characteristic curve of the A-W-B model to predict MAFLD was 0.862 (0.791-0.916). The A-W-B level was strongly and positively associated with the liver proton density fat fraction (r = 0.630, P < 0.001) and significantly increased with the severity of MAFLD (P < 0.05). CONCLUSION: AIP was strongly and positively associated with the risk of MAFLD and can be a reference predictor for MAFLD. The novel prediction model A-W-B combining AIP, WC, and BMI can significantly improve the predictive ability of MAFLD and provide better services for clinical prediction and screening of MAFLD.

Cardiometabolic index: A new predictor for metabolic associated fatty liver disease in Chinese adults.

Objective: Cardiometabolic index (CMI) is a well promising indicator for predicting obesity-related diseases, but its predictive value for metabolic associated fatty liver disease (MAFLD) is unclear. This study aimed to investigate the relationship between CMI and MAFLD and to evaluate the predictive value of CMI for MAFLD. Methods: A total of 943 subjects were enrolled in this cross-sectional study. CMI was calculated by multiplying the ratio of triglycerides and high-density lipoprotein cholesterol (TG/HDL-C) by waist-to-height ratio (WHtR). Multivariate logistic regression analysis was used to systematically evaluate the relationship between CMI and MAFLD. Receiver operating characteristic (ROC) curves were used to assess the predictive power of CMI for MAFLD and to determine the optimal cutoff value. The diagnostic performance of high CMI for MAFLD was validated in 131 subjects with magnetic resonance imaging diagnosis. Results: Subjects with higher CMI exhibited a significantly increased risk of MAFLD. The odds ratio for a 1-standard-deviation increase in CMI was 3.180 (2.102-4.809) after adjusting for various confounding factors. Further subgroup analysis showed that there were significant additive interactions between CMI and MAFLD risk in gender, age, and BMI (P for interaction < 0.05), and the area under the ROC curve(AUC) of CMI for predicting MAFLD were significantly higher in female, young, and nonobese subgroups than that in male, middle-aged and elderly, and obese subgroups (all P < 0.05). Moreover, among nonobese subjects, the AUC of CMI was significantly higher than that of waist circumference, BMI, TG/HDL-C, and TG (all P < 0.05). The best cutoff values of CMI to diagnose MAFLD in males and females were 0.6085 and 0.4319, respectively, and the accuracy, sensitivity, and specificity of high CMI for diagnosing MAFLD in the validation set were 85.5%, 87.5%, and 80%, respectively. Conclusions: CMI was strongly and positively associated with the risk of MAFLD and can be a reference predictor for MAFLD. High CMI had excellent diagnostic performance for MALFD, which can enable important clinical value for early identification and screening of MAFLD.

Association between sleep quality, migraine and migraine burden.

Background: The relationship between sleep and migraine is well known to be bidirectional. However, few studies have systematically assessed the association between sleep quality and the risk of developing migraine, and its gender and age differences are unclear. And there is currently limited evidence on the associations between sleep quality and migraine-related burdens. Objective: The objectives of this study were to: (1) explore the association between sleep quality and the risk of developing migraine, and its gender and age differences; (2) investigate the associations between sleep quality and the total pain burden, severity, disability, headache impact, quality of life, anxiety, and depression of migraine patients. Methods: This study consecutively enrolled 134 migraine patients and 70 sex- and age-matched healthy control subjects. Sleep quality was assessed through the Pittsburgh Sleep Quality Index (PSQI). Logistic regression and linear regression analyses were used to explore the associations between sleep quality with the risk of developing migraine and the migraine-related burdens. Results: The prevalence of poor sleep quality in migraine patients was significantly higher than that in subjects without migraine (P < 0.001). After adjusting for various confounding factors, the risk of migraine with poor sleep quality remained 3.981 times that of those with good sleep quality. The subgroup analysis showed that there were significant additive interactions between poor sleep quality and the risk of migraine in gender, age, and education level (P for interaction < 0.05), and the stronger correlations were found in females, populations with ages more than 35 years old, and with lower education levels. In addition, multivariate linear regression analysis showed that poor sleep quality was significantly and independently associated with the total pain burden, severity, headache impact, quality of life, anxiety, and depression in migraine patients (P trend < 0.05). Conclusion: Poor sleep quality was significantly independently associated with an increased risk of developing migraine and the migraine-related burdens. Strengthening PSQI assessment is valuable for the early prevention and treatment of migraine patients.

Efficacy and safety of underwater endoscopic mucosal resection for ≤20 mm superficial non-ampullary duodenal epithelial tumors: Systematic review and meta-analysis.

Background and aims: Superficial non-ampullary duodenal epithelial tumors (SNADETs) as a rare disease have gradually increased in recent years. Underwater endoscopic mucosal resection (UEMR) has emerged as a newly available option for the endoscopic resection of SNADETs. This study aimed to evaluate the efficacy and safety of UEMR for ≤20 mm SNADETs. Methods: A literature search was performed across multiple databases, including PubMed, Embase, Scopus, and Clinical trials for studies containing tumors ≤20 mm published from January 1, 2012, to August 8, 2022. Outcomes examined were the pooled rates of en bloc resection, R0 resection, adverse events, and recurrence. Subgroup analyses of the resection rate were conducted stratified by sample size and polyp size. Results: A total of 10 studies with UEMR performed in a total of 648 tumors were included for analysis. The pooled rate of en bloc resection and R0 resection was 88.2% (95% confidence interval (CI): 82.1-93.2) and 69.1% (95% CI: 62.2-76.1), respectively. The results showed pooled rate of intraoperative bleeding rate was 2.9% (95% CI: 0-9.0), delayed bleeding rate was 0.9% (95% CI: 0.1-2), recurrence rate was 1.5% (95% CI: 0-4.9). In the subgroup analysis, R0 and en-bloc resection rates were significantly higher in <10 mm than 10-20 mm SNADETs subgroups (R0 resection rate 83.1 vs. 48.6%; en bloc resection rate 100.0 vs. 84.0%, P < 0.05). Conclusion: Underwater endoscopic mucosal resection was an effective and safe technique for the optional treatment for ≤20 mm SNADETs, especially of <10 mm. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022340578.

MRI-determined liver fat correlates with risk of metabolic syndrome in patients with nonalcoholic fatty liver disease.

BACKGROUND AND AIM: Little is known about that the relationship between hepatic fat content (HFC) and metabolic syndrome (MetS). We aimed to determine whether HFC correlated with MetS in patients with nonalcoholic fatty liver disease (NAFLD). METHODS: HFC was measured by MRI-determined proton density fat fraction (MRI-PDFF) for 131 suspected NAFLD subjects. Patients with NAFLD defined as MRI-PDFF ≥5% were stratified into two groups based on whether they were above or below the median MRI-PDFF value; the MRI-PDFF value for the control group was <5%. The primary outcome was the presence of MetS. Logistic regression models were used to obtain the associations between the severity of liver fat and MetS, and the corresponding odds ratios (ORs) and 95% confidence intervals (CIs) were recorded. RESULTS: Compared to NAFLD patients with low-HFC (n = 48) and the control group (n = 35), NAFLD patients with high-HFC (n = 48) had significantly greater prevalence of central obesity, hypertension, hyperglycemia, and hypertriglyceridemia (all P < 0.05). NAFLD patients with high-HFC had a higher prevalence of MetS than NAFLD patients with low-HFC (79.2% vs. 56.2%, P < 0.05). The multivariate-adjusted OR for the prevalence of MetS comparing NAFLD patient with low-HFC and high-HFC to the control group were 4.56 (95% CI: 0.54-38.79, P = 0.165) and 22.91 (95% CI: 1.80-292.21, P = 0.016), respectively (Ptrend = 0.014). CONCLUSION: Increased hepatic fat quantitatively measured by MRI-PDFF had a significant dose-relationship with the presence of MetS, and the amount of liver fat may affect cardiovascular risk.

The association between Helicobacter pylori infection with overweight/obesity: A protocol for a systematic review and meta-analysis of observational studies.

BACKGROUND: Obesity has become a serious public health issue. The role of Helicobacter pylori (H. pylori) infection in overweight or obesity is inconsistent and controversial. It is very necessary to conduct a systematic review and meta-analysis for determining whether H. pylori infection was associated with risk of overweight/obesity. METHODS: Four databases (PubMed, Web of Science, The Cochrane Library, and EMBASE) will be searched from the inception to January 15, 2019. All observational studies (including cross-sectional, case-control or longitudinal studies) reporting the association between H. pylori infection and overweight/obesity will be included. The primary outcome was the presence and incidence of overweight/obesity in conjunction with H. pylori infection. Study selection, data extraction, and assessment of quality will be conducted independently by 2 reviewers. RevMan 5.3 and STATA 14.0 software will be used for data synthesis. RESULTS: The results of this study will provide a better understanding of the role of H. pylori infection in overweight/obesity among overall population. CONCLUSION: This systematic review and meta-analysis will generate evidence of the association between H. pylori infection and overweight/obesity, and the findings of this study will be published in a peer-reviewed journal.PROSPERO registration number: CRD42019121939.