In most of the studies, oral microbiota composition was found to be different between digestive cancer patients and controls. Particularly, oral microbiota dysbiosis and specific bacteria, such as Fusobacterium nucleatum and Porphyromonas gingivalis, appeared to be associated with colorectal cancers. Current evidence suggests that differences exist in oral microbiota composition between patients with and without digestive cancers. Further studies are required to investigate and validate oral–gut microbial transmission patterns and their role in digestive cancer carcinogenesis.The relation between the gut microbiota and human health is increasingly recognized. Recently, some evidence suggested that dysbiosis of the oral microbiota may be involved in the development of digestive cancers. A systematic review was conducted according to the PRISMA guidelines to investigate the association between the oral microbiota and digestive cancers. Several databases including Medline, Scopus, and Embase were searched by three independent reviewers, without date restriction. Over a total of 1654 records initially identified, 28 studies (2 prospective cohort studies and 26 case-controls) were selected. They investigated oral microbiota composition in patients with esophageal squamous cell carcinoma ( Digestive cancers include cancers located in the esophagus, stomach, liver, pancreas, colon, and rectum. Their incidence and related mortality are increasing worldwide, but with some characteristic geographical differences . AccordiThe oral cavity is a reservoir of more 700 species or phylotypes of bacteria, of which approximately 35% have not been cultured yet . The equFusobacterium nucleatum [Porphyromonas gingivalis [Fusobacterium nucleatum abundance by quantitative real-time polymerase chain reaction of DNA extracted from colorectal tissue biopsies and surgical resection specimens and observing that Fusobacterium nucleatum was more abundant in stool samples from CRC patients compared with adenomas or controls [Fusobacterium nucleatum could be a novel risk factor for disease progression from adenoma to cancer, possibly affecting patient survival outcomes [In particular, specific oral bacteria that are typically found in the oral cavity of individuals suffering from periodontal diseases, such as ucleatum  and Porpngivalis , have bengivalis ,19, suppngivalis ,21,22,23ngivalis ,25,26. Tcontrols ,28,29. Soutcomes .In this perspective, recent evidence suggested that certain oral bacteria and in general the characterization of the oral microbiota composition may be used as biomarkers for the detection of certain digestive cancers, with a potential role as a non-invasive screening tool ,30,31.The present systemic review aims to provide an updated appraisal of the current literature investigating the association between the oral microbiota and different types of digestive cancers, by (i) describing the observed differences in oral bacterial composition and abundance in cancer patients vs. controls and (ii) suggesting the possible impact of oral microbiota on digestive cancer risk.The present systematic review was performed according to the Cochrane collaboration-specific protocol  and was Studies that investigated the association between oral microbiota and digestive cancers were searched in the following databases without date restrictions: Medline (through PubMed), Scopus, Embase, Cochrane Library and Google Scholar.A specific research equation was used for each database, using the following keywords and MeSH terms: oral microbiome, oral microbiota, mouth microbiome, gastrointestinal neoplasms, gastrointestinal cancers, gastrointestinal carcinoma, digestive cancer, digestive neoplasms.Population: adult patients with a diagnosis of digestive cancer .Intervention: analysis of oral microbiota composition and/or oral microbiome with or without a concomitant oral/periodontal examination. No restriction was applied for the type of microbiological technique used to sample and analyze the oral microbiota/microbiome, which include culture-dependent and genome sequencing methods.Comparison(s): adult patients without cancer.Outcome(s): oral microbiota composition .Study designs: All types of descriptive  and analytic studies  estimating the magnitude of the association between oral microbiota dysbiosis and digestive cancers.According to the PICOS schema, the following criteria were used to construct the literature search and to select the pertinent articles: Results were limited to human clinical studies with review articles, with case reports being excluded. The literature review was completed by an extensive search using the “related articles” function in PubMed. The reference lists of the eligible records and of review articles were double-checked to identify potential additional pertinent articles. Articles were selected and reviewed if written in English only.The literature search and selection were performed independently and blindly by three reviewers . Records were removed from the selection if all reviewers excluded the articles at the title/abstract screening levels. Disagreements were resolved with discussion with a third reviewer (N.d.A.).The reviewers performed an independent full-text analysis and data extraction by filling an electronic database. Extracted data included first author name, country, journal, year of publication, number of patients, age of the patients, type of cancer, oral diagnosis, type of microbiota analysis, sample extraction, detection method, and main results.The reviewers also carried out a study quality assessment and risk of bias evaluation of the selected articles. According to the type of study design, the Newcastle–Ottawa scale  (NOS) waThe merged search yielded 1805 results. After removing duplicates, 1654 articles were screened for eligibility based on title and abstract. Twenty-eight articles fulfilled the inclusion criteria and were selected for the present systematic review, as shown in n = 3), USA (n = 8), China (n = 14), Japan (n = 1), Turkey (n = 1), and Iran (n = 1). The general characteristics of the studies examined are summarized in The selected studies were published between 2012 and 2021. There were 2 prospective cohort studies and 26 case-control studies (of which 6 were based on matched case-control groups). The studies were carried out in Europe n = , USA (n All studies described microbiota composition differences between cases (cancer patients) and controls, and several studies ,50,56,57Five articles investigated the association between oral microbiota and EC ,54,55,56Lautropia, Bulleidia, Catonella, Corynebacterium, Moryella, Peptococcus, and Cardiobacterium and higher relative abundance of Prevotella, Streptococcus, and Porphyromonas in the ESCC group [Actinomyces and Antopobium were related to a higher risk of ESCC, whereas the healthy group of the study was closely related to Fusobacterium and Porphyromonas. Zhao et al. [Firmicutes, Negativicutes, Selenomonadales, Prevotellaceae, Prevotella, and Veillonellaceae and with a decreased taxa of Proteobacteria, Betaproteobacteria, Neisseriales, Neisseriaceae, and Neisseria.Chen et al.  demonstrCC group . Wang etCC group  showed to et al.  showed tTannarella forsythia and a depletion of the commensal genus Neisseria and Streptococcus Pneumoniae [Kawasaky et al. and Peters et al. concluded that differences in microbiota compositions between cases and controls could be used as a possible biomarker for cancer screening ,56. OnlyOribacterium and Fusobacterium as possible biomarkers to identify LC patients, showing a significant difference in their relative abundance between healthy controls and LC patients [Haemophilus, Porphyromonas, and Filifactor.Only two articles investigated the association between oral microbiota dysbiosis, and LC. Lu et al.  identifipatients . Li et aPorphyromonas gingivalis, but contrasting findings were reported in relation to Fusobacterium, which was respectively linked to an increased and decreased risk of cancer [In the seven studies dealing with PC, the microbiota analysis was conducted on salivary samples in five studies ,43,44,47f cancer ,46. The The microbiota analysis was conducted on tongue coating in four studies ,48,51,52Fusobacterium nucleatum was found to be linked to an increased risk of CRC in five studies [Prevotella and CRC risk [Microbial samples were collected by oral swab in three studies ,16,40, o studies ,39,40,41CRC risk ,37,40, wBased on the NOS assessment , 4 studiThe present systematic review provides a synthesis of studies investigating the association between oral microbiota composition and digestive cancers with a systematic approach. The available evidence suggests that digestive cancer patients present an oral microbiota composition that differs from non-cancer controls and specific oral bacteria may be linked to increased odds for digestive cancers. The predominance and/or relative abundance of these bacteria could have a synergistic effect on digestive cancers’ etiology ,49,51,55Porphyromonas, Prevotella, and Fusobacterium, can contribute to a chronic inflammatory reaction by stimulating the production of inflammatory mediators such as interleukin-1β, interleukin-6, and matrix metalloproteinases [Prevotella and Fusobacterium have also been linked to carcinogenesis by the mechanisms of suppressing host immunological functions and promoting the malignant transformation of epithelial cells [In the digestive tract, the microbiota synthetizes essential amino acids and vitamins taking part in the digestion process. A symbiotic microbiota is normally characterized by a high diversity, and it is able to resist changes that occur during physiological stress , and to teinases ,62. Preval cells ,29,59.The potential translocation ability of the oral microbiota through the circulation system (hematogenous route) or following the flow of food and fluids into the digestive system  could explain its presence in the gut and its role in carcinogenesis . Three pFinding the exact transmission pathways between the oral and the gut microbiota might provide evidence to support new methods for non-invasive cancer screening and could lead to control specific bacteria in their source, i.e., the oral cavity . SchmidtDue to their clinical relevance, these findings need to be validated in future studies with a large population of patients and reproducible protocols for oral microbiota sampling and analysis. The available literature is characterized by a high degree of heterogeneity in the methodology used. Moreover, the role of potential confounders, such as alcohol intake and smoking, which are known to drastically influence oral health and oral microbiota homeostasis ,70, has Another relevant issue to consider is the sampling method used in the different studies . The oral cavity consists of different sites  that create specific niches for microbial colonization characterized by different oxygen levels, nutrient availability, and mechanical stress conditions. Consequently, distinct microbial communities can be found in the oral cavity according to the explored sites and the presence of diseases  . The typThe present systematic review has some limitations related to the type and quality of the pertinent literature considered. Overall, the body of evidence is of low-to-moderate quality, but the results support the need of further studies investigating the role of oral microbiota composition in digestive cancer patients. The qualitative synthesis of the literature highlights the need for standardization in study design and methods to obtain comparable results contributing to the emerging evidence and elucidating the current knowledge. Indeed, the literature is characterized by high heterogeneity related not only to methodological aspects  but also to population characteristics, lifestyle habits, and culture, which may influence oral microbiota composition. Indeed, geography, ethnicity, subsistence-specific variations in human microbiome composition , and theDespite the limited evidence available, the literature is consistent in suggesting a significant association between oral microbiota composition and digestive cancers. To date, it is not possible to identify specific bacteria species involved in digestive cancer development, but these findings support further research to characterize the oral microbiota of these patients. Indeed, future studies should analyze the possible microbiota dissemination patterns from the oral cavity and the rest of the digestive tract and the possible role of oral microbiota characterization as a screening tool for digestive cancers.


Pressure injuries are common adverse events in clinical practice, affecting the well‐being of patients and causing considerable financial burden to healthcare systems. It is therefore essential to use reliable assessment tools to identify pressure injuries for early prevention. The Braden Scale is a widely used tool to assess pressure injury risk, but the literature is currently lacking in determining its accuracy. This study aimed to evaluate the accuracy of the Braden Scale in assessing pressure injury risk.Systematic review and meta‐analysis.Articles published between 1973–2020 from periodicals indexed in the PubMed, EMBASE, CINAHL, Web of Science and the Cochrane Library were selected. Two reviewers independently selected the relevant studies for inclusion. Data were analysed by the STATA 15.0 and the RevMan 5.3 software.In total, 60 studies involving 49,326 individuals were eligible for this meta‐analysis. The pooled SEN, SPE, PLR, NLR, DOR and AUC were 0.78 (95% CI: 0.74 to 0.82), 0.72 (95% CI: 0.66 to 0.78), 2.80 (95% CI: 2.30 to 3.50), 0.30 (95% CI: 0.26 to 0.35), 9.00 (95% CI: 7.00 to 13.00) and 0.82 (95% CI: 0.79 to 0.85), respectively. Subgroup analyses indicated that the AUC was higher for prospective design , mean age <60 years , hospital  and Caucasian population . In addition, 18 was found to be the optimal cut‐off value.The evidence indicated that the Braden Scale had a moderate predictive validity. It was more suitable for mean age <60 years, hospitalized patients and the Caucasian population, and the cut‐off value of 18 might be used for the risk assessment of pressure injuries in clinical practice. However, due to the different cut‐off values used among included studies, the results had a significant heterogeneity. Future studies should explore the optimal cut‐off value in the same clinical environment. IndividSince the early 1960s, a variety of risk assessment tools have been developed with over 50 scales currently to determine the risk of PIs, such as the Norton Scale, the Waterlow Scale and the Braden Scale  were searched, from inception of each database to July 2020. In addition, we explored the bibliographies of relevant reviews in order to identify other potentially eligible studies. The literature search terms and strategies used are available in supplementary appendix 4.2The eligible studies must meet the following criteria: (a) patients were 18 years of age or older and had no PIs at time of admission; (b) the Braden Scale was used to identify the risk of PIs; (c) studies directly provided true positive (TP), false positive (FP), false negative (FN) and true negative (TN) for predicting PIs’ risk or with data available regarding these statistics; (d) the definition and classification of PIs were produced by one of the accepted standards, such as the National Pressure Ulcer Advisory Panel (NPUAP), the European Pressure Ulcer Advisory Panel (EPUAP), the Agency for Health Care Policy and Research (AHCPR), the International Classification of Diseases, Ninth Revision (ICD‐9), and the Bergstrom and others; and (e) the cross‐sectional study and the cohort study were included.Exclusion criteria were as follows: (a) studies failed to obtain a complete data; (b) letter, comment and meeting abstract; and (c) duplicate publications.4.3Two reviewers independently screened titles and abstracts for eligibility with the consistent accomplishment of a pilot literature selection. The full text was read if the abstract and title cannot be determined for inclusion. In case of disagreement, a third reviewer resolved the conflict between them.4.4Two reviewers extracted data into a spreadsheet independently and resolved any discrepancies through discussion to reach a consensus. For each study included, the following information was extracted: first author, publication year, country, study design, age, gender, sample size, cut‐off value, reference standard, TP, FP, TN and FN.4.5The Quality Assessment of Diagnostic Accuracy Studies Ⅱ (QUADAS‐Ⅱ)  and Review Manager 5.3 software . The bivariate meta‐analysis model was selected to calculate the pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and their corresponding 95% confidence intervals (95% CIs)  studies, and 39 (65%) studies were observed to have low risk in terms of the index test. Reference standard in 58 (97%) studies were judged to have a low risk of bias, and 50 (83%) studies belonged to low risk in the domain of flow and timing. In applicability, 44 (73%) studies were deemed to be low risk in the patient selection, 51 (85%) studies in the index test and 58 (97%) studies in the reference standard. Details regarding risk of bias and applicability are summarized in Figure 5.42I values in SEN and SPE reached 96.10%  and 99.17% , respectively.The pooled SEN was 0.78 (95% CI: 0.74 to 0.82), and the pooled SPE was 0.72 (95% CI: 0.66 to 0.78) Figure . The poo5.5p =.009), suggested the presence of a threshold effect to some extent. The pooled results of different cut‐off points are shown in Table Visual inspection of forest plots and SROC curves, as well as Spearman's correlation of 0.334 , mean age (<60 years vs. ≥60 years) .We carried out sensitivity analysis to assess the result reliability in Figure 6This meta‐analysis included 60 studies involving 49,326 patients. The pooled SEN, SPE, PLR, NLR, DOR and AUC were 0.78, 0.72, 2.80, 0.30, 9.00 and 0.82, respectively. Subgroup analyses indicated that the Braden Scale was more accurate in assessing the risk of PIs for mean age <60 years, hospitalized patients and Caucasian population. When the cut‐off value was 18, the Braden Scale was the most effective in identifying PIs’ risk.The results indicated that the probability of a positive result was 78% when the Braden Scale was used to assess a person who actually developed PI, and the probability of a negative result was 72% when the Braden Scale was applied to assess a person who did not actually develop PI. The pooled PLR and NLR were also calculated in order to evaluate the diagnostic accuracy in clinical level. The pooled PLR value was 2.80, suggesting that the probability of PI in a person with a positive test was 2.80‐fold higher than that in a healthy individual. By contrast, the pooled NLR indicated that the probability of not having PI in a person with a negative test was 30%. Meanwhile, DOR demonstrated a high level of overall accuracy. DOR, which is found by dividing PLR by NLR, can range from 0–infinity, and a higher DOR represents higher accuracy Deeks, . Finallyp =.009) suggested the presence of a threshold effect to some extent. Threshold effect occurs when different cut‐off values are used to define a positive test result in different studies, affecting the reported sensitivity and specificity of the test  than retrospective design (AUC: 0.78), which may be attributed to more rigorous design in the prospective studies. Although there was no significant difference in the AUC (0.87 vs. 0.81) between the young and middle‐aged population and the elderly, the pooled SEN and SPE of the young and middle‐aged population were 0.83 and 0.78, while those of the elderly were 0.77 and 071. Based on these, we found that the Braden Scale was more accurate in the young and middle‐aged population than in elderly. The possible reason was that older people developed chronic diseases due to their declined physiological reserve Jaul, , which w6.1The strengths of this meta‐analysis included the large number of patients retained in the quantitative synthesis. Furthermore, this is the first meta‐analysis on the overall accuracy of the Braden Scale for identifying PI risk. In addition, we performed threshold analyses and cut‐off‐stratified analyses, and identified the optimal cut‐off value, which played an important role in determining the risk of PIs. More importantly, sensitivity analysis was performed in order to find outlier studies. After removing the outliers and performing the same analyses for the remaining studies, we found that the overall parameters of diagnostic accuracy did not change significantly, which suggested that the random‐effects bivariate model was robust for the calculation of the pooled estimates. However, there are still several limitations. First, we have implemented a comprehensive systematic literature review, yet the language of the included studies was limited to English and Chinese, which might lead to publication bias. Second, because the cut‐off value of 16 was only found in the 4 original studies, the pooled parameters in the systematic review had a limited interpretation. Future studies should conduct more original researches to compare the effectiveness of 18 with that of 17.6.2The Braden Scale is more suitable to identify the risk of PI for mean age <60 years, hospitalized patients and the Caucasian population. It appears that 18 is the optimal cut‐off value in clinical practice.7The Braden Scale has a moderate predictive validity for PI risk assessment, and it is more suitable for mean age <60 years, hospitalized patients and Caucasian population, compared with mean age ≥60 years, long‐term care facility and Asian population. Meanwhile, the cut‐off value of 18 afforded the best choice in SEN and AUC, and could be recommended for use in clinical practice. Future studies should explore the optimal cut‐off in the specific environments.The authors declare no conflict of interest.C.H., Y.M., L.H.: Study design. C.H., Y.M., M.J.: Data collection. C.H., Y.M., C.M.: Data analysis. C.H., Y.M., M.J., C.W., L.H.: Manuscript writing and revisions for important intellectual content.Supplementary MaterialClick here for additional data file.


I2 = 76.7%, P < 0.001). Meta-regression analysis identified latitude (P = 0.02), adjustment for gender (P = 0.001), and 25(OH)D stratification (P < 0.001) as sources of heterogeneity. Furthermore, the nonlinear dose–response analysis determined the OR (95% CI) of T1DM to be 0.91  per 10 nmol/L increase in the 25(OH)D concentration. A ‘U’-shaped association was found between serum 25(OH)D concentration and risk of T1DM. The present study highlights the significant inverse association between the circulating 25(OH)D concentration and the risk of T1DM.It remains debatable whether vitamin D plays any role as a risk factor for type 1 diabetes mellitus (T1DM). We have summarized the effect of circulating 25-hydroxy vitamin D [25(OH)D] concentration on the risk of developing T1DM via a dose–response meta-analysis. We undertook a database search on PubMed, Embase, and Cochrane Library from inception to January 2020. A meta-analysis based on random-effects model was applied. Subgroup analysis and meta-regression were performed to inspect the source of heterogeneity. Dose–response data were examined using the generalized least squares trend estimation method. This study was registered with the PROSPERO (ID: CRD42020166174). In total, 16 studies including 10,605 participants (3913 case patients) were included. The pooled odds ratios (OR) and 95% confidence intervals (95% CI) for the highest versus the lowest 25(OH)D concentration was 0.39 , with a high heterogeneity ( Type 1 diabetes mellitus (T1DM) is an insulin-dependent diabetes that is characterized by immune-mediated destruction of pancreatic β cells, which leads to severe insulin deficiency . A pooleThe concentration of 25-hydroxy vitamin D [25(OH)D] in the serum reflects the status of vitamin D in the blood circulation . VitaminSeveral recent observational studies examined the relation between the serum 25(OH)D concentration and the risk of T1DM. Accordingly, we undertook the present meta-analysis to investigate the correlation between the serum 25(OH)D concentration and the risk of T1DM, while demonstrating their dose–response association.This study was registered with the PROSPERO (ID: CRD42020166174).The databases of PubMed, Embase, and Cochrane Library were searched for literatures published from inception to January 2020. Free-text terms and MeSH terms were used as follows: “type 1 diabetes” OR “type I diabetes” OR “insulin-dependent diabetes” OR “juvenile onset diabetes” OR “sudden onset diabetes” OR “autoimmune diabetes” OR “brittle diabetes” OR “Ketosis Prone diabetes” AND “vitamin D” OR “25-hydroxy vitamin D” OR “25(OH)D” OR “1,25-dihydroxy vitamin D” OR “1,25(OH)2D” OR “calcitriol” OR “calcidiol”. Potentially eligible studies were included without placing any language restriction in the search.The following inclusion criteria were set to select clinical studies for the present meta-analysis: (1) Observational studies on humans, except for cross-sectional studies; (2) All subjects met the diagnosis criteria of T1DM; (3) The serum 25(OH)D concentration was measured quantitatively; (4) Studies that evaluated the association between the 25(OH)D concentration and the risk of T1DM and were obliged to report the odds ratios (OR), relative risk or hazard ratios with the corresponding 95% confidence intervals (95% CI) or useful data for these statistics. All reviews, case reports, letters, registration of trials, and conference abstracts without full-text link were excluded from the study.All literatures collected according to the search strategy were independently assessed by two authors (YH and YJ), who were blinded to author and journal details, to identify potentially eligible studies. Any issue that presented was addressed by discussion with the third author, GS. The literature selection method flowchart is illustrated in Fig. I2 statistic, which was confirmed to be statistically significant at P < 0.05 and I2 > 50%. Pooled OR and 95% CI were evaluated using the random-effects model (DerSimonian and Laird method) [P < 0.05 for meta-regression, the heterogeneity between the subgroups was considered to be significant [P < 0.10 was for Egger’s test, indicating potential publication bias [OR and 95% CI were obtained as the summary risk estimates for T1DM from all studies, and the relative risks and the hazard ratios were esteemed to be equivalent to OR. Heterogeneity among the studies was estimated by Cochrane Q test and  method) . To scrunificant . By omition bias . In addiion bias , 18.Based on the dissimilar cut-off points for categories in individual article, we computed OR and 95% CI of T1DM for every 10 nmol/L of serum 25(OH)D concentration increase via generalized least squares for trend estimation, as suggested by Greenland and Longnecker  and OrsiIn addition, we appraised a potential curve for dose–response relationship between the 25(OH)D concentration and the summary OR and 95% CI for T1DM. A restricted cubic spline model with four knots at the 5th, 35th, 65th, and 95th percentiles of 25(OH)D concentration was used. The linear and nonlinear models were calculated by testing the null hypothesis, with the splines coefficient considered zero.All statistical analyses were performed using the Stata version 15.1.614 .Based on our initial literature research, 2591 articles were identified, of which 409 that were identified to be duplicates and 2105 that were uncorrelated, were removed. After the full-text screening, 62 articles were excluded as they did not meet all of the eligible criteria listed in Fig. The characteristics of each included studies are outlined in Table P value of Cochrane Q test was <0.001, and the I2 statistics was 76.7%, which indicated that the heterogeneity among the analyzed studies was significant.The forest plot for the pooled effects of the highest versus the lowest cut-off point of 25(OH)D concentration on the risk of T1DM is illustrated in Fig. Pbetween < 0.001; Fig. Pbetween = 0.02; Fig. Pbetween = 0.001) between the subgroups. Nevertheless, the subgroups stratified by age, ethnicity, assay method for estimating 25(OH)D concentration, duration of T1DM, and adjustment of ethnicity showed no statistical significance between the subgroups in heterogeneity.Subgroup analysis and meta-regression are summarized in Table Sensitivity analysis was conducted to investigate which individual study with extreme OR influenced the pooled OR. For instance, if the study by Hamed et al.  with theFigure P < 0.001), and the heterogeneity was insignificant  for both fixed and random models. The OR (95% CI) of T1DM was 0.91  per 10 nmol/L increase in the 25(OH)D concentration. A ‘U’-shaped association was found. The risk of T1DM significantly descended with the 25(OH)D concentration ranging from 39 to 89 nmol/L with OR (95% CI) from 0.79  to 0.31 , trended stably when the 25(OH)D concentration reached 103–113 nmol/L with OR (95% CI) around 0.28 , and slightly ascended when the 25(OH)D concentration surpassed 150 nmol/L with OR 95% CI and 0.34 .We noted an inverse nonlinear association between the serum 25(OH)D concentration and the T1DM risk  was asymmetrical and the Egger’s test revealed In this meta-analysis of 16 observational studies including 10,605 participants, a significant inverse association was recorded between the highest versus the lowest circulating 25(OH)D concentration and the T1DM risk. This analysis demonstrated the role of vitamin D as a protective factor for T1DM, albeit the heterogeneity among the pooled studies was significant. In support, Shen et al.  reportedSubgroup analysis along with meta-regression was applied to explore the source of heterogeneity. We recognized a positive association between the latitude of patient location and risk of T1DM, which suggests that individuals living in high latitude may be predisposed to T1DM. Weng et al.  also repAdjustment for gender was identified as a potential source of heterogeneity. A previous study EURODIAB found that the incidence of T1DM was nearly the same between both the genders of children . HoweverWe also identified that the association was undeviating and did not diverge appreciably after stratifying by age, ethnicity, assay method for estimating the 25(OH)D concentration, duration of T1DM, and adjustment for ethnicity. Shen et al.  found thNotably, we observed a significant inverse correlation between the circulating 25(OH)D concentration and the risk of T1DM and developed a robust database supporting the dose–response curve. To the best of our knowledge, no previous studies have addressed the quantitative association between serum 25(OH)D concentration of 100–150 nmol/L to the significantly lower risk of T1DM. Functionally, sufficient serum 25(OH)D concentration can preserve the activity of residual pancreatic β-cells and insulin secretion . MeanwhiOur meta-analysis identified contradicting results with those from past RCTs. The daily supplementation of vitamin D differs across countries and organizations. For children under 18 years, the recommendation vitamin D dose was 200–1000 IU . And it Notwithstanding, we noted some limitations in our study. For instance, most of the included articles were case-control studies, which is not a relatively robust study design toward confirming a causal relationship. As compared with studies that record data in the real time, case-control studies have a greater probability of recall bias. In addition, this meta-analysis was based on observational studies that were generally not considered to be able to demonstrate causality between serum 25(OH)D concentration and T1DM risk . HoweverIn conclusion, through our dose–response meta-analysis enlisting 16 studies, we demonstrated a significant inverse association between the 25(OH)D concentration in circulation and the risk of T1DM. The resultant dose–response relationship also provided a broad 25(OH)D spectrum. We suggest the necessity for further studies focusing on the molecular mechanism underlying this association. In clinical relevance, optimized and well-designed RCT are necessary to yield greater insights to the benefits and safety of vitamin D supplementation in preventing the risk of developing T1DM.Supplementary information is available at EJCN’s website.Supplementary Material File


Attention-deficit/hyperactivity disorder (ADHD) is the most common psychiatric disorder in childhood. Studies explored the association of maternal exposure to pesticides during pregnancy with a risk of offspring developing ADHD, but have reported inconclusive results. Here, we will perform a systematic review and meta-analysis of observational studies to assess a possible association between them.This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols. PubMed, Embase, Web of Science, the Cochrane Library, and the PsycINFO will be searched from inception to May 2021. Observational studies investigating the association of maternal exposure to pesticides during pregnancy with a risk of offspring developing ADHD will be considered. The Newcastle-Ottawa Scales or the scale of the Agency for Healthcare Research and Quality will be used to assess the methodological quality of the included studies according to their study design. A fixed or random-effect model will be used to synthesize data depend on the heterogeneity test. STATA version 12.0 will be used to conduct the meta-analysis.This study will provide a high-quality evaluation of association between maternal exposure to pesticides during pregnancy and risk for ADHD in offspring.This study will present evidence on whether maternal exposure to pesticides during pregnancy is a risk factor for ADHD in offspring. In addition, ADHD may seriously disrupt one's social life, leading to a series of negative outcomes, such as educational underachievement, unemployment, and criminality.,4 While short-term medication-based treatments for ADHD have proven to be efficacious and cost-effective, the long-term effectiveness of these treatments, regarding remains uncertain on key educational, vocational, and social outcomes. Moreover, the effectiveness of non-pharmacological approaches to treatment has proven to be lower than expected. Therefore, primary prevention targeting at risk factors for ADHD is of great importance to the prevention and management of ADHD from a public health perspective.Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset neurodevelopmental disorder characterized by developmentally inappropriate inattentiveness, hyperactivity, and increased impulsivity.,6 Environmental factors may also contribute to the development of ADHD, as is indicated by the increased prevalence of ADHD over the last few decades, during which genes are stable. Among numerous environmental factors, many prenatal risk factors, such as intrauterine exposure to tobacco, maternal stress, and obesity during pregnancy, have been demonstrated to be associated with an increased risk of ADHD. The identification of these prenatal risk factors calls for special attention and sufficient interventions for pregnant women.Although the exact etiology remains unknown, ADHD is suggested to be a highly heritable disorder, with an estimated heritability of 70% to 80%. and are intensively used worldwide during the past century. Humans can be exposed to pesticides directly through occupational, agricultural, and/or household use of pesticides, or indirectly through the circulation and accumulation of pesticides in the food chain. Studies demonstrated that maternal exposure to pesticides during pregnancy is related to an increased risk of adverse reproductive outcomes and neurodevelopmental disorders in offspring.Pesticides are a group of complex chemicals or biological agents used for destroying or mitigating pest,–12 though a similar association was not confirmed in other studies.,13–18 Therefore, the purpose of this study will be to explore whether there is an association between maternal exposure to pesticides during pregnancy with the ADHD risk in offspring.In recent years, several studies focused on the potential effects of maternal exposure to pesticides during pregnancy on the ADHD risk in offspring; however, the results of these studies were inconclusive. Some studies found that maternal exposure to chlorpyrifos, pyrethroids, and p, p’-dichlorodiphenyldichloroethylene during pregnancy was associated with an increased ADHD risk in offspring,22.1Ethical approval is not applicable, since this study will not involve individual data.2.2 to this protocol.The systematic review and meta-analysis has been registered in INPLASY . It will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses Protocols guidelines2.32.3.1Pregnant women and their offspring will be included.2.3.2The exposure factor is pesticides, including herbicides, insecticides, fungicides, bactericides, rodenticides, fumigants, and any of their subtypes. The level of maternal household and agricultural exposure will be ascertained by measurements of maternal serum or unary biomarkers, or by estimation from previous pesticide application data.2.3.3Offspring participants whose mothers were not exposed or were only exposed to a relatively low dose of pesticides during pregnancy will be used as the control group.2.3.4The outcome is the incidence of ADHD, which will be ascertained by the International Classification of Diseases or the Diagnostic and Statistical Manual of Mental Disorders, or their related diagnostic tools.2.3.51.Observational studies, including cohort, case–control, and cross-sectional studies, will be included in this study.2.These studies should have reported the relative risk (RR) or odds ratio (OR) and their corresponding 95% confidence interval (CI) of association of maternal exposure to pesticides during pregnancy with the ADHD risk in offspring, or have reported any original data to compute the aforementioned risk estimates and 95% CI.3.If more than one study is generated from the same cohort, the study that reported the largest number of ADHD cases will be included.2.3.6Duplicate studies, non-human studies, case reports or case series studies, conference abstracts, reviews, comments, and letters will be excluded.2.4Relevant studies will be identified by searching PubMed, Embase, Web of Science, the Cochrane Library, and the PsycINFO. All of the databases will be searched from inception to May 2021.2.5The main search terms will include “pregnancy,” “pesticide,” “organochlorines,” “organophosphates,” “herbicides,” “insecticides,” “fungicides,” “bactericides,” “rodenticides,” “fumigants,” “attention deficit hyperactivity disorder,” and “ADHD”. The detailed search strategy for PubMed is shown in Table 2.6Two independent researchers will perform the study selection and data extraction. Any discrepancies will be resolved by discussion with an experienced third researcher. The EndNote reference manager will be applied to store and manage the tiles and abstracts of all of the studies identified by the literature search. Titles, abstracts, or full texts of the candidate studies will be scanned to identify eligible studies. Using a standard data collection form developed prior to data extraction, the following data from the included studies will be recorded: name of the first author, publication year, country, study design, sample size, ascertainment of ADHD, measurement of pesticide exposure, indicators for quality assessment, the most fully adjusted risk estimate, the corresponding 95% CI, and confounding factors.2.7 will be used to assess the methodological quality of cohort and case-control studies. This tool evaluates the selection of study groups (maximum of 4 stars), comparability of the study populations (maximum of 2 stars), and ascertainment of outcomes (for cohort studies) or exposure (for case-control studies) (maximum of 3 stars). A high score indicates a low risk of methodological quality. The scale of the Agency for Healthcare Research and Quality will be used to assess cross-sectional studies. The Begg test and Egger test will be used to detect potential publication bias.The Newcastle-Ottawa Scales2.8The corresponding author will be contacted by email to ask for original data if missing or unclear data is identified from the included studies. Otherwise, the existing data will be used for analysis.2.9I2 statistic. The heterogeneity will be considered statistically insignificant if I2 ≤ 50%, then the fixed-effect model will be used to calculate pooled OR among the studies, otherwise, the random-effect model will be adopted. Subgroup analysis will be conducted according to study design, study location, sub-type of pesticides, ascertainment of ADHD, measurement of pesticide exposure, study quality, and adjustment for confounding factors. Sensitivity analysis will be performed by omitting the risk estimate of each study in turn to examine the robustness and stability of the pooled results.STATA version 12.0  will be used to conduct the meta-analysis. The association between maternal exposure to pesticide with ADHD risk in offspring will be quantified using OR values and the corresponding 95% CIs. Between-study heterogeneity will be evaluated by the 3I2 statistic, and P value for heterogeneity will be summarized in another table. A forest plot will be presented in a figure to show the RRs for individual studies and the pooled RR. A separate table will be presented to list the eligible studies we could not obtain raw data from after contacting the corresponding authors.The selection process will be presented in a flow chart Fig. . The cha4In this systematic review and meta-analysis, we will assess the association between maternal exposure to pesticides and the risk of developing ADHD in offspring based on existing literature according to a pre-prepared protocol. The results might help to identify some types of pesticide that may contribute to the increased risk of ADHD. It will be of great practical and theoretical significance for the primary prevention of ADHD, focusing on prenatal interventions in the future.Conceptualization: Zhixian Zhu, Liwei Cheng.Data curation: Zhixian Zhu, Huawei Tan.Formal analysis: Ying Wang, Shiming Tang.Funding acquisition: Zhixian Zhu, Cheng Liu, Liwei Cheng.Investigation: Ying Wang, Shiming Tang, Huawei Tan.Methodology: Zhixian Zhu, Cheng Liu.Project administration: Liwei Cheng.Resources: Zhixian Zhu, Cheng Liu, Liwei Cheng.Software: Ying Wang, Shiming Tang.Supervision: Zhixian Zhu, Liwei Cheng.Validation: Huawei Tan.Visualization: Zhixian Zhu, Ying Wang.Writing – original draft: Zhixian Zhu, Liwei Cheng.Writing – review & editing: Zhixian Zhu, Ying Wang, Shiming Tang, Huawei Tan, Cheng Liu, Liwei Cheng.


Venous thromboembolism (VTE) in patients with COVID-19 in intensive care units (ICU) is frequent, but risk factors (RF) remain unidentified. In this meta-analysis (CRD42020188764) we searched for observational studies from ICUs reporting the association between VTE and RF in Medline/Embase up to 15 April 2021. Reviewers independently extracted data in duplicate and assessed the certainty of the evidence using the GRADE approach. Analyses were conducted using the random-effects model and produced a non-adjusted odds ratio (OR). We analysed 83 RF from 21 studies (5296 patients). We found moderate-certainty evidence for an association between VTE and the D-dimer peak , and length of hospitalization  and intubation . We identified low-certainty evidence for an association between VTE and CRP , D-dimer , troponin T , and the requirement for inotropic drugs . Traditional VTE RF  were not found to be associated to VTE in COVID-19. Anticoagulation was not associated with a decreased VTE risk. VTE RF in severe COVID-19 correspond to individual illness severity, and inflammatory and coagulation parameters. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for an outbreak of respiratory disease called Coronavirus Infectious disease 2019 (COVID-19) . The repGiven the increased risk of VTE, several clinical trials evaluated the role of intermediate dose thromboprophylaxis and high dose anticoagulation , showingWe followed the MOOSE  guidelines; the Cochrane Prognosis Methods Group guidelines ; the Grahttps://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42020188764 (accessed on 6 December 2021).There was a Medline and Embase literature search from 1 January 2020 to 15 April 2021. We aimed to collect all published observational studies reporting VTE in COVID-19. We used the following keywords (including MeSH): coronavirus, severe acute respiratory syndrome coronavirus 2, novel coronavirus, nCoV, 2019-CoV, COVID-19, thrombosis, venous thromboembolism, and pulmonary embolism. The search string is available at Additionally, we manually searched relevant articles on the websites of major medical journals  as well as the bibliographies of each included article. We did not retain non-English papers, abstracts, and pre-print papers that were not peer-reviewed.-Demographic characteristics: age, male sex;-−2), alcohol and tobacco use, history of cancer, history of previous VTE, several medical conditions  infection, hypertension and use of angiotensin convertor enzyme (ACE) inhibitors);Patient history factors: body-mass-index (BMI) and obesity , Simplified Acute Physiology Score II (SAPS-II), Sepsis-related Organ Failure Assessment score (SOFA), Therapeutic Intervention Scoring Systemc-10 (TISS-10), arterial oxygen partial pressure/fractional inspired oxygen (PaO2/FiO2), requirement and duration of use of neuromuscular blockers and inotropic drugs, length of hospital stay and disease duration, acute kidney injury and requirement for renal replacement therapy, myocarditis, requirement for extracorporeal membrane oxygenation (ECMO), use of anticoagulant treatment ;-Inflammation biomarkers: C-reactive protein (CRP), ferritin, fibrinogen, interleukin-6 (IL-6) and procalcitonin.-Coagulation tests: activated partial thromboplastin time (APTT), D-dimers, Prothrombin Time (PT), score for disseminated intravascular coagulation (DIC) from the International Society on Thrombosis and Haemostasis (ISTH);-Haematological parameters: complete blood count ;-Biological markers of organ dysfunction: alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatine kinase serum level, creatinine level, lactate dehydrogenase (LDH), N-terminal pro-brain natriuretic peptide (NT-proBNP), troponin T, and troponin I level.The inclusion criteria were: (i) cohort studies of at least 10 patients in ICU, (ii) patients with positive reverse transcriptase polymerase chain reaction COVID-19 sample or with suggestive radiologic findings on computed chest tomography, (iii) available rate of documented VTE as defined by the investigators, and (iv) available rate of exposures as tested by investigators, including:Two reviewers (H. L. and J-C. L.) independently applied these criteria to the titles and abstracts of all citations obtained. If pertinent, each reviewer retrieved and explored the complete articles to make a final decision about their inclusion in the meta-analysis. In case of disagreement, a third reviewer (S. M.) was consulted to reach a consensus. Throughout this process, reviewers were blinded to author and journal names. In case of cohorts reported in multiple papers, the analysis was limited to the largest cohort, unless the necessary data had appeared only in another paper. A log of reasons for rejection of citations identified from the searches was kept. In case of doubt or apparent inconsistency, a reviewer (H. L.) would contact the corresponding author to remove any ambiguity.p < 0.05). We assumed that the effect of publication bias should be minor if the plot of the magnitude of the effect size in each study versus its precision estimate  showed a roughly symmetrical funnel shape (if number of studies >10).The quality and risk of bias were assessed using the Quality In Prognostic Studies (QUIPS) tool as recommended by the Cochrane Prognosis Methods . Two revThe main outcomes were VTE, as defined by the investigators, including deep vein thrombosis (DVT) or pulmonary embolism (PE). We investigated all the prognostic factors tested in individual studies, including the clinical characteristics, biological testing, disease severity markers, and the drug or procedure exposures.We standardized the units of measurement for each prognostic factor, unifying the direction of the predictors, adjusting the weights of the studies, and calculating crude-effect estimates when not provided. When possible, we performed meta-analysis of all the risk factors to assess their association with VTE occurrence, when reported by more than one study. For a dichotomous outcome, we presented the effect estimate as an OR and the corresponding 95% confidence interval (CI). We conducted a meta-analysis of associations using the generic inverse variance-based method and random-effects model to produce an overall measure of association. For a continuous outcome, we estimated the standardized mean difference. The standardized mean difference was re-expressed as an OR using the method of Chinn et al. . The meaNo funding was received to perform this meta-analysis. All authors had full access to all the data and the final responsibility to submit for publication. The authors declare no conflict of interest related to this study.All data relevant to the study are included in the article; raw data will be made available upon reasonable request.This section may be divided by subheadings. It should provide a concise and precise description of the experimental results and their interpretation, as well as the experimental conclusions that can be drawn.A total of 5690 articles were retrieved using the search terms. After reviewing titles and abstracts, 75 articles were selected for full text eligibility. Overall, 12 retrospective and 9 prospective studies (5296 patients) ,33,34,35The main characteristics of the included studies are described in n = 3), DVT (n = 5), or both (n = 13) were assessed. In 10 studies, VTE incidence was evaluated as routine care, whereas in 11 studies VTE was evaluated only in case of clinical suspicion. The median number of patients was 81 (range 16–3239). The median follow-up duration was 23 days (range 14–28). The included studies took place in France (n = 6), the United States of America (n = 5), the United Kingdom (n = 3), China (n = 2), and other various counties (n = 5). Six studies were multicentric.Risk factors for PE (As shown in p > 0.05) test were not in favour of publication bias for the variables reported in >10 studies  ,31,32,35We identified an association between VTE risk and requirement for intubation ,25,29,31The requirements for ECMO ,28,29,31We found no association between the use of anticoagulation regardless of the dosage used and risk of VTE ,28,30,32We identified low-certainty evidence for an association between VTE risk and CRP ,30,32,35We found moderate to low-certainty evidence for an association between VTE and the D-dimer levels  ,32,34,35In a single study, an association was found between the platelets peak count and a decreased risk of VTE with low certainty-evidence . We found no association between the risk of VTE and the haemoglobin levels ,27,30,35We found no association between VTE and the creatinine levels ,27,29,35Levels of evidence and the estimated OR are summarized in p < 0.0001), peak of D-dimer (p < 0.0001), D-dimer (p < 0.0001), troponin T (p < 0.0001), and mechanical ventilation (p < 0.0001) remained statistically significant.We performed 92 statistical tests. Using the Bonferonni correction, only the hospital stay duration  and biological parameters . Some risk factors previously reported were not confirmed by our analysis, including an older age, female sex, obesity ,37, and Taken together, the present meta-analysis provides more precise estimates of the association between individual risk factors and the risk of VTE, which may help identifying ICU patients at lower and higher risk of VTE. Three randomized trials in ICU patients reported the absence of efficacy of therapeutic anticoagulation or intermediate-dose thromboprophylaxis compared to the standard dose thromboprophylaxis ,7,40, whThese trials included patients irrespective of their D-dimer levels or inflammatory parameters. Our study identified the candidate risk factors for VTE in ICU patients with COVID-19, which is crucial for VTE screening and prevention. Indeed, the stratifications of VTE risk may increase the benefit–risk ratio of primary prevention of thrombosis using intermediate or therapeutic anticoagulant dose. This concept is supported by a retrospective monocentric study including critically ill COVID-19 patients, suggesting that this subgroup of patients with elevated D-dimer levels requiring mechanical ventilation—two risk factors identified in the present meta-analysis—may benefit from therapeutic anticoagulation . AlthougInterestingly, we confirmed the increased risk of VTE amongst patients with high inflammation biomarkers, whereas “traditional risk factors” for thrombosis  were noA potential limitation of the present meta-analysis was the variability in the study sample, study design, patients’ characteristics and management, and the definition of VTE events. In addition, many estimates were associated with large confidence intervals despite the increased statistical power provided by the meta-analysis. Conversely, because of the multiple statistical tests, we could not exclude fortuitous association . This may explain the protective effect of the presence of cardiovascular disease, or the effect of IL-6 levels and cardiovascular disease on VTE risk. These factors were non-significant after the Bonferroni correction. Nonetheless, this study is unique in many aspects, including its comprehensiveness, the novelty of its findings, and its rigorous methods. Finally, we produced a crude estimate of the risk factors, with a high probability of collinearity between variables between the inflammatory and coagulation parameters . MulticeThe present meta-analysis identified the relevant risk factors of VTE in patients admitted to the ICU for severe COVID-19, mainly inflammation profile and illness severity. These findings may help identify individual patients at higher risk of VTE, inform experts developing risk assessment models to risk-stratify patients, and ultimately, improve patients’ outcomes through optimal screening and management strategies.


Objective: We conducted a meta-analysis to explore all the potential risk factors for non-arteritic anterior ischemic optic neuropathy (NAION) based on the published literature.Methods: A comprehensive literature search through the online databases was performed to obtain studies concerning the risk factors of NAION up to June 2020. Pooled unadjusted odds ratios (ORs) or rate ratios (RRs) were calculated to evaluate the weight of risk factors. This study was registered in PROSPERO under the number CRD42018084960.Results: Our meta-analysis included 49 original studies comprising of more than 10 million patients. The following risk factors were proved to be significantly associated with NAION: male gender , hypertension , hyperlipidemia , diabetes mellitus (DM) , coronary heart disease (CHD) , sleep apnea , factor V Leiden heterozygous , and medication history of cardiovascular drugs.Conclusion: We concluded that the above risk factors were significantly related to NAION. Better understanding of these risk factors in NAION can help the direct therapeutic approaches. Non-arteritic anterior ischemic optic neuropathy (NAION) is the most common ischemic optic neuropathy. The incidence rate is 2.5–11.8 per 100,000 cases in men elder than 50 . AlthougThe elder men were susceptible to NAION , 3. NAIOThe two published meta-analyses reported influences of DM or sleep apnea on NAION, respectively , 14. Howhttps://www.crd.york.ac.uk/prospero/) was CRD42018084960.We conducted this systematic review and meta-analysis in accordance with the meta-analysis of observational studies in epidemiology (MOOSE) guidelines. The protocol registration number of PROSPERO (http://graylit.osti.gov/). The language of included studies was restricted to English. The last search was on June 6, 2020. The search terms were applied as follows: “non-arteritic anterior ischemic optic neuropathy” OR “non-arteritic anterior ischaemic optic neuropathy” OR “NAION” OR “NA-AION” in combination with “risk” OR “factor” OR “risk factor.” These terms were searched in all the fields of articles, not restricted to their abstracts.Original literature was searched comprehensively through electronic Pubmed, Medline, Embase, and Cochrane Library databases. The related references were also screened, including gray literature (in the website ORs) or rate ratios (RRs) of risk factors were reported with 95% CIs. Accordingly, we excluded the animal experiments, case reports/series, abstracts, conference proceedings, repeated publications, non-published materials, reviews, and editorials.The inclusion criteria were listed as follows. First, the clinical studies concerning the comparisons of risk factors between NAION and controls were taken into further consideration. Second, the risk factors should exist before the diagnosis of NAION, which was judged by carefully screening the abstracts and/or full texts. Third, the samples of case and control groups were provided directly, or odds ratios (via an open discussion.Two investigators (B. L. and Y. Y.) did the literature search, study screening, data extraction, and eligible study quality assessment independently. The inconsistency was resolved by a third reviewer or ORs or RRs with 95% CIs) in both the NAION and the control groups. The Newcastle-Ottawa Scale (NOS)   was applORs or RRs on dichotomous variables to identify the association between the risk factors and NAION. Accordingly, the mean differences (MDs) were used on the continuous variables. Heterogeneity was determined through the chi-square test based on Q and I2 values  and STATA .We calculated the pooled unadjusted 2 values . No signWe included a total of 49 studies containing more than 10 million patients. The process of verifying the studies was in accordance with a PRISMA flow diagram . The basCI: −6.50 to 7.78, P = 0.86) with heterogeneity   without heterogeneity . In the subgroups, five studies in Europeans also demonstrated the higher susceptibility in men . Two studies in mixed ethnicities reached similar results  . There were no obvious publication biases detected through the inverted funnel plots of these factors.0.00001) . In eigh0.00001) , 52, 55 0.00001) . No heteRR = 1.00, 95% CI: 0.72–1.39, P = 0.99) with slight heterogeneity . In the subgroup analysis based on the ethnicities, results in all the three groups  pointed out no significant association .Twelve studies –56, 59 rociation . The shaRR = 1.28, 95% CI: 1.20–1.37, P < 0.00001) with no heterogeneity . In five of the studies on Asians, a significant higher incidence of NAION was found in hypertensive patients  and 11 European studies achieved similar results . Both the cases did not demonstrate heterogeneity .Hypertension was studied in the 16 original articles , 56, 59.ogeneity . No signRR = 1.43, 95% CI: 1.26–1.62, P < 0.00001), and heterogeneity was detected . According to the subgroup analysis, more NAION cases were found in the hyperlipidemia patients among the studies on Asian , European , and mixed populations . Heterogeneity appeared in the European and mixed groups, while in Asians no heterogeneity was found .We extracted and pooled data from the 19 original studies , 58, 59 as found . NeitherRR = 1.53, 95% CI: 1.36–1.73, P < 0.00001) and results had heterogeneity . The subgroup analysis was shown as below: RR was 2.12  in Asians, 1.49  in Europeans, and 1.52  in mixed populations. Heterogeneity was shown together with the forest plot .Twenty-three studies , 58, 59 est plot . The invRR = 1.68 . Heterogeneity was also significant . In the subgroups, one Asian study  and six studies on mixed ethnicities  found significant association, while no such relationship was detected in four of the Europeans studies . Heterogeneity was obvious in the European and mixed groups, while not applicable in the Asian group .The data from 11 original studies , 58, 59 an group . No signRR = 3.28, 95% CI: 2.08–5.17, P < 0.00001) bearing heterogeneity . Four studies on the mixed ethnicities observed positive association  without heterogeneity , while three of the European studies demonstrated no influence of sleep apnea on NAION . Heterogeneity was found significantly   . No publRR = 1.78, 95% CI: 1.26–2.52, P = 0.001), hyperhomocysteinemia , and high level of lipoprotein(a)   with apparent heterogeneity . There were no publication biases detected through the inverted funnel plot for all the above factors.The laboratory biochemical markers measuring coagulative status were examined and studied , 53, 56.= 0.007) . All theOR = 2.30, 95% CI: 1.86–2.84, P < 0.00001) with no heterogeneity . In detail, a significant increase in the NAION cases was found in patients taking statins . Beta-blockers (β-blockers) were also investigated in the two studies with significant correlation to NAION   .RR = 2.21, 95% CI: 1.19–4.09, P = 0.01), while five genotypes were not significant: MTHFR 677T heterozygous , MTHFR 677T homozygous , ACE DD , ACE II , and ACE ID . Inverted funnel plots did not show the publication biases.We analyzed the six genotypes and gained pooled results from the nine included studies , 49, 59.RR = 1.16, 95% CI = 0.98–1.39, P = 0.09) with obvious heterogeneity   . No obviOR = 0.74, 95% CI: 0.11–5.00, P = 0.76) with heterogeneity . Microaneurysm/retinal hemorrhage, small optic cup, high intraocular pressure , and factor V Leiden heterozygous were risk factors of NAION. Several diseases and biomarkers were identified in <3 studies, which are listed in P = 0.06). We expected more valid original studies on different ethnicities, in case, a high-quality meta-analysis could be conducted.Diabetes and sleep apnea were proved to be important risk factors in the previously published meta-analyses , 14. We We found no apparent association between the occurrence of NAION and 1-month use of PDE5-Is, which was published by us in 2018 , their iORs or RRs of small CDR on NAION could not be extracted from these studies, so they did not meet our inclusion criteria. A meta-analysis studying this topic can be conducted in our future work, specifically collecting the continuous variables from these original articles.A crowded optic disc was often observed in NAION because hypoperfusion or ischemia of the optic nerve head is apparent in a tight optic disc structure . An optiSome other factors were researched in <3 studies. Johnson and colleagues  researchAlthough our meta-analysis was conducted comprehensively and included multiple potential risk factors of NAION, it still has several limitations. First, all the included original articles were case-control or retrospective cohort studies. No RCTs or prospective cohort studies have been published yet. Recalled data might be incomplete and inaccurate, bringing biases to these studies. Second, most NAION possible factors have similar mechanisms and act as confounders. Independence of these factors may probably be examined by RCTs; however, no RCTs can be conducted on studying the risk factors. Third, the time span of the included studies lasts from 1991 to 2019, during which the changes in lifestyles and medical techniques influence the type of risk factors. Finally, some risk factors were examined in <3 studies and it was hard to confirm their association with NAION. The above limitations reduced the quality of our meta-analysis partly and restricted our results to be applied.Consequently, our study concluded that the following risk factors were associated with NAION: male gender, hypertension, hyperlipidemia, DM, CHD, sleep apnea, medication history of cardiovascular drugs, and factor V Leiden heterozygous. Better understanding of these risk factors in NAION can direct future research and therapeutic approaches.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.BL, TD, and DX: conceptualization and project administration. BL and YY: literature search and screening, formal analysis, data curation, and writing—original draft preparation. BL and TD: methodology and software. BL, YY, and TD: validation. WL, TD, and DX: writing—review and editing. TD and DX: supervision. All authors contributed to the article and approved the submitted version.This study was supported by a grant from the Natural Science Foundation of Guangdong Province, China (No. 2020A1515110113) and the Science and Technology Planning Project of Guangzhou, China (No. 202102020113).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Although several studies have shown that each of the metabolic syndrome (MetS) components can be a risk factor for erosive esophagitis (EE), the association between MetS and EE is still a challenging subject, as studies about this association have shown inconsistent results. Therefore, this study was conducted to evaluate the association between MetS and EE. In this study, we followed the MOOSE protocol and the PRISMA guidelines for reporting the results. Web of Science (ISI), Cochrane Library (Cochrane Database of Systematic Reviews - CDSR), EMBASE, Scopus, Science Direct, PubMed/Medline, EBSCO, CINAHL, and Google Scholar search engine were searched for articles published until January 2021. Heterogeneity between studies was estimated by I2 index and Q test. All analyses were performed using Comprehensive Meta-Analysis Software. Finally, 12 studies entered the meta-analysis process after qualitative assessment. MetS was significantly associated with increased risk of EE  in 12 studies with a sample size of 45285 (12825 cases and 29377 controls). In subgroup analysis based on types of studies (P=0.832), MetS diagnostic criteria (P=0.083) and quality of studies (P=0.612), no significant association was found. Sensitivity analysis showed that the overall estimation of effect size is still robust after omission of individual studies from the meta-analysis. Publication bias based on the Begg's test (P=0.945) and Egger's test (P=0.753) were not significant. MetS increases the risk of EE compared to control groups. Future studies should examine if MetS treatment reduces the risk of EE. Gastroesophageal reflux disease (GERD), also known as acid reflux, is a long-term condition in which stomach contents rise into the esophagus, resulting in either symptoms or complications. This uncommon flow of gastroesophageal contents, which is caused by chronic exposure to esophageal epithelium with esophagitis, may cause esophageal mucosal damage, bleeding, or ulcers  is a complex disorder that includes central obesity, hyperglycemia, hypertension, high-density lipoprotein cholesterol (HDL-C) and hypertriglyceridemia. In addition to being associated with cardiovascular disease and diabetes, MetS and its components are also associated with various gastrointestinal diseases, abnormal liver function, and polycystic ovary syndrome . Most sMeta-analysis is a statistical method for combining data of several studies with similar goals. When the effect size is consistent between two studies, meta-analysis can be used to identify this common effect. When the effect is different between two studies, meta-analysis may be used to identify the cause of the inconsistency. Finally, meta-analysis results may include a more accurate estimate of the impact of treatment or risk factors for the disease or other outcomes by combining different studies . This sIn this study, we followed the Meta-analyses Of Observational Studies in Epidemiology (MOOSE)  protocoEight online databases were searched for articles published until January 2021: Web of Science (ISI), Cochrane Library (Cochrane Database of Systematic Reviews - CDSR), EMBASE, Scopus, Science Direct, PubMed/Medline, EBSCO, CINAHL, and Google Scholar search engine.The search was done using the following MeSH keywords: "Metabolic Syndrome"[Mesh], "Gastroesophageal Reflux"[Mesh], "Esophagus"[Mesh], "Esophagitis"[Mesh]. Combined search in PubMed was done as follows: ((("Esophagus"[Mesh]) OR "Gastroesophageal Reflux"[Mesh]) OR "Esophagitis"[Mesh]) AND "Metabolic Syndrome"[Mesh]. Potential articles were also obtained by manual search in the reference list from a review article published in 2016  and manInclusion criteria were: published articles, with abstract, English language studies that examined the relationship between MS and EE. Exclusion criteria were: duplicate studies, studies that did not present a correct definition of MetS, studies that did not differentiate the effect of EE from GERD, studies not relevant to our subject, congress, letters to the editor, studies lacking qualitative data and theses.Titles and abstracts of all identified reports were reviewed. The full text of articles was evaluated according to the inclusion and exclusion criteria. Eventually, the disagreements were discussed and resolved in the presence of all authors.The following data were extracted from each study: first author, year of publication, type of study, country/continent, setting, mean age and standard deviation, population size of studies , the number of patients with MetS in case group and control group, odds ratio (OR), or relative risk (RR), and 95 % confidence interval (CI), MetS diagnosis criteria, EE diagnostic criteria and the qualitative assessment score of the studies.For this purpose, the Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of nonrandomized studies (case-control and cohort) . In addAll analyses were performed using Comprehensive Meta-Analysis Software (CMA). We used ORs index and 95 % confidence interval to combine the initial studies and finally reported the results as OR and 95 % CI. In studies that did not report ORs and 95 % confidence intervals, we found them based on the total sample size of each group as well as the number of MetS positive patients in case (EE) and control (Non-EE) groups. We performed the meta-analysis using random and fixed effects model. Heterogeneity between studies was estimated by I2 index and Q test  in 12 studies with a sample size of 45285 (12825 cases and 29377 controls)  and case-control  studies, MetS was significantly associated with an increased risk of EE, but no significant difference was found between the types of studies (P = 0.832) , Japanese criteria , NCEP ATP III , and WHO , MetS was significantly associated with an increased risk of EE, but no significant difference was found between the MetS diagnostic criteria (P=0.083) Figure 4B.In studies with moderate quality  and high quality , MetS was significantly associated with an increased risk of EE, but no significant difference was found (P=0.612) Figure 4C.Meta-regression for the association between MetS and EE based on year of publication was not significant  Figure 5.Publication bias is shown as a funnel diagram in Figure 5The present study is the first meta-analysis that combined 12 primary studies to show that MetS was significantly associated with increased risk of EE. Subgroup analysis based on study design, MetS criteria and quality of studies was used to find the potential sources of heterogeneity, which showed no significant effect of the mentioned variables. In the included studies, the studies of Lee et al. in 2017 and Tai Many other studies have reported a significant association between EE and risk factors, including MetS components, male gender, BMI=25, smoking, alcohol consumption, fasting blood sugar levels=126 mg/dl, and hiatal hernia . Impairal., 2012; Hosseinal., 2012; Hung etal., 2012; Tsukadaal., 2012) and chral., 2002; Hunt etal., 2002). ElevatIn other studies, the association between hypertension and dyslipidemia (as MetS component) has also been demonstrated . In preThe present study has some limitations deserving acknowledgment. One of the limitations of the present study is the high heterogeneity of the studies, though we attempted to discover the cause of heterogeneity through subgroup analysis. Furthermore, most studies were conducted in Asian countries, which may influence the generalizability of the results. Finally the observational and prospective nature of the included studies precludes conclusion as to the causal nature of the observed association.MetS increases the risk of EE compared to control groups. Future studies should examine if MetS treatment reduces the risk of EE.Reza Ranjbar and Amirhossein Sahebkar  contributed equally as corresponding author.Not applicable.There is no conflict of interest between the authors.The authors would like to thank the Clinical Research Development Unit of Baqiyatallah Hospital, Tehran, Iran, for guidance and advice. We also would like to thank Ilam University of Medical Sciences for their financial support.None.


Further TSMR analysis of 12 dichotomous items for assessing neuroticism suggested that mood swings genetically increased the risk of CAD . Conclusions: This study reported no genetically causal association of neuroticism with CAD. The present study also found that mood swings may genetically increase the risk of CAD. These findings may highlight the potential of mood control as a preventive measure for CAD.Background: Observational studies on the association between neuroticism and coronary artery disease (CAD) are still rare, and the results of existing studies are not consistent. The present study aimed to explore causal associations of neuroticism with CAD. Methods: The summary-level data of GWAS for neuroticism and 12 items used to assess neuroticism were extracted from the UK Biobank, and included up to 380,506 participants. The general data for CAD were obtained from the CARDIoGRAMplusC4D consortium, which assembled 60,801 CAD patients and 123,504 non-cases. Single-nucleotide polymorphisms associated with neuroticism and 12 items at genome-wide significance were explored as instrumental variables. Two-sample Mendelian randomization (TSMR) analyses were performed to evaluate causal associations amongst the genetically predicted neuroticism and 12 items with CAD. Results: The present TSMR study did not reveal the genetic association of neuroticism with CAD. The calculated ORs for CAD using inverse-variance weighted, weighted median, and MR-Egger analysis were 1.12 ( Neuroticism involves a pattern of irritability, anger, sadness, anxiety, worry, hostility, self-consciousness, and vulnerability ,2, whichCoronary artery disease (CAD) is one of the most common cardiovascular diseases in the clinic, greatly increasing the burden on both patients and public health . PatientMendelian randomization (MR) is an alternative method for potential causal inference , and useIn the present study, given the uncertainties about the causal role of neuroticism for CAD, we aimed to evaluate the potential causal association of neuroticism with CAD using two-sample Mendelian randomization (TSMR) analysis.The Eysenck Personality Questionnaire, Revised Short Form (EPQ-R-S) , which ip-value < 5 × 10−8) were explored as instrumental variables, which were then extracted from GWAS data for CAD. If a particular instrumental variable requested was not available in the CAD GWAS, a proxy SNP was searched instead using the 1000 Genomes European reference population. The two-sample Mendelian randomization analysis was conducted using the “TwoSampleMR” package in R language (version 4.1.2). The inverse-variance weighted (IVW) approach was utilized to evaluate the causal association between exposure and outcome through weighting and summing the influence of each instrumental variable, assuming that all the instruments are valid [p-value > 0.05, it indicates that no horizontal pleiotropic pathway exists. The leave-one-out sensitivity analysis, leaving out each SNP in turn, was then utilized to determine the impact of a single SNP on the analysis [SNPs associated with neuroticism at genome-wide significance , 0.99 , and 0.82 , respectively. The TSMR estimate was not statistically significant, which revealed no evidence of the causal effect of neuroticism on CAD genetically  indicated that no horizontal pleiotropic pathway existed in the analysis. Moreover, the leave-one-out sensitivity analysis demonstrated that no single SNP drove these results  and “Irritableness”  have genetic pleiotropy, and the causal estimate may be biased due to the influence of the horizontal pleiotropic pathway. The other 10 items showed no horizontal pleiotropy (Instrumental variables for 12 dichotomous items are presented in eiotropy .In the present study, we conducted a TSMR analysis assessing the causal effect of neuroticism in the development of CAD. In line with several previous observational studies ,18, no aNeuroticism is manifested as a negative emotional tendency, which describes the stable individual differences in experiencing negative emotions . GrowingOn the other hand, when focusing on a more detailed pattern of neuroticism, previous studies have shown that anxiety and depression were identified as etiologic and prognostic factors in CAD patients ,20. We fThe present study has several strengths. First, TSMR is an alternative method for potential causal inference. The association between genotype and outcome can represent the effect of the exposure on the outcome. Since alleles follow the principle of random allocation, genetic variation will not be affected by potential confounding factors. In addition, genetic variation is established just before the onset of disease, which can avoid the possibility of a reverse causal association. The utilization of TSMR analysis in the present study could reduce the potential confounding and reverse causality in observational research. Second, we included a large-scale population in the present study. Summary-level data of GWAS for neuroticism and 12 items were used to assess neuroticism and were extracted from the UK Biobank, and included up to 380,506 participants. The general data for CAD were obtained from the CARDIoGRAMplusC4D consortium, which assembled 60,801 CAD patients and 123,504 non-cases. The large study samples allowed our statistical analyses to have high power.There are also several limitations in our study. First, although we determined instrumental variables of neuroticism and 12 dichotomous items of EPQ-R-S used for MR analysis through the huge sample size of the UK Biobank, it is impossible to completely rule out the possibility that SNPs related to neuroticism affect the risk of CAD through other causal pathways rather than neuroticism exposure, which is known as horizontal pleiotropy. In the present study, we conducted sensitivity analyses to eliminate horizontal pleiotropy as much as possible. Our sensitivity analysis results showed strong robustness, indicating that the bias from horizontal pleiotropy could almost be ignored. Second, since what we have obtained are summary-level data, it is impossible to conduct a more detailed stratified analysis of CAD patients. Third, our study mainly included individuals of European ancestry, and thus, cannot be generalized to other ethnicities. More analyses need to be conducted to assess the reliability of our findings in other ancestral populations.Despite these limitations, we provided novel insights into causal associations between neuroticism and CAD using TSMR analysis. Our research reduced the unmeasured confounding factors and reverse causality that may exist in observational analysis. We found that mood swings were associated with an increased risk of CAD. We can conduct some large-scale observational studies or prospective studies in the future to verify the results, based on the present study. Furthermore, conducting more in-depth studies of molecular mechanisms may help us better understand the relationship between mood swings and CAD. If controlling mood swings can really reduce the risk of suffering from CAD, it will greatly reduce medical burdens.In conclusion, the present study evaluated causal associations of neuroticism with CAD using TSMR analysis. Our findings showed no causal effect of neuroticism on CAD, whereas mood swings were associated with an increased risk of CAD. Controlling mood swings may help to reduce the risk of CAD.


Our study aimed to evaluate the association between eNOS rs1799983 polymorphism and hypertension, and to provide evidence for the etiology of hypertension.Essential hypertension is a complex disease determined by the interaction of genetic and environmental factors, eNOS rs1799983 polymorphism and hypertension were included by searching PubMed, Embase, Web of Science, Medline, Scopus, WanFang datebase, Vip datebase, and CNKI database according to PRISMA guideline. Eligible data were extracted and pooled, and were analyzed using R software based on five different genetic models.Case–control studies of eNOS rs1799983 polymorphism and hypertension under any genetic model .A total of 60 eligible articles involving 14,185 cases and 13,407 controls were finally selected. We found significant association between eNOS rs1799983 polymorphism is associated with the increased risk of hypertension under any genetic model. Moreover, investigations of gene–gene and gene-environment interactions are needed to give more insight into the association between eNOS rs1799983 polymorphism and hypertension.We found that The online version contains supplementary material available at 10.1186/s12872-021-02192-2. So far,gulation .eNOS plays a critical role in regulating vascular tone and blood pressure. For example, overexpression of eNOS gene in transgenic mice leads to a significant decrease in blood pressure [eNOS gene in healthy individuals is associated with decreased levels of NO release and increased blood pressure [Previous studies have shown that pressure . In addipressure .eNOS gene at 7q35-36 spans 21 kb, with 26 exons and 25 introns. There are about 10 polymorphic loci distributed in the promoter, exon, and intron of the eNOS gene. In these loci, the common mutation that leads to amino acid substitutions in mature proteins is G894T or Glu298Asp (rs1799983) mutations, in which base substitution of G to T will result in glutamic acid (Glu) being replaced at exon 7 by aspartic acid (Asp) at position 298 of the corresponding amino acid [The eNOS rs1799983 polymorphism and hypertension; however, these results are still inconsistent. Recently, it is noted that new studies [eNOS rs1799983 polymorphism is associated with hypertension.A large number of articles have studied the association between  studies  on this  studies . TherefoeNOS” OR “NOS3”) AND (“polymorphism” OR ‘‘variant” OR “mutation”) AND (“hypertension” OR “high blood pressure”). Moreover, we also retrieved and scrutinized related articles from the reference lists of literatures to replenish literatures that had not been identified in the initial search. A detailed form of the search strategy used in datebases was displayed in Additional file This meta-analysis was performed according to the statements in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting standard . SystemaeNOS rs1799983 polymorphism and hypertension. The exclusion criteria satisfied the followings: (1) case reports, review articles or cross-sectional studies; (2) duplicate articles; (3) secondary hypertension or gestational hypertension; (4) lack of sufficient information on genotype or allele frequencies.Studies included had to meet the following criteria: (1) case–control studies; (2) patients with essential hypertension were defined as cases, healthy subjects without hypertension were defined as controls; (3) evaluation of the association between eNOS genotype or allele in cases and controls. Hardy–Weinberg equilibrium (HWE) among the controls was calculated.For each eligible study, the following data were extracted: name of first author, year of publication, region and ethnicity of study population, sample size, and numbers of Quality of the included studies was evaluated using the Newcastle–Ottawa scale (NOS)  that hasP < 0.05 was considered as a significant deviation from HWE. The associations between eNOS rs1799983 polymorphisms and hypertension in this meta-analysis were measured based on five different genetic models including six comparisons: allelic model (T vs G), codominant model (GT vs GG and TT vs GG), dominant model (GT + TT vs GG), recessive model (TT vs GG + GT), overdominant model (GT vs GG + TT). Odds ratios (OR) and 95% confidence intervals (95% CI) were used to assess the strength of association between eNOS rs1799983 polymorphisms and hypertension. Q-statistic and I2-statistic were used to evaluate heterogeneity, random-effect models (DerSimonian and Laird methods) were used when heterogeneity existed ; otherwise, fixed-effect models (Mantel and Haenszel methods) were used. Subgroup analyses were performed by region, ethnicity, and HWE to detect main sources of heterogeneity and observe differences of the association in different groups. Sensitivity analysis was conducted to evaluate stability of our results by omitting each study at each time. Publication bias was estimated using funnel plots, and quantified by the Egger’s tests  [HWE was evaluated for control groups of each study using Goodness of fit Chi-square test, and on bias) . All datThe risk of random error in traditional meta-analysis may increase because of the dispersed data and repeated significance testing , 18. TSAA total of 60 eligible articles involving 14,185 cases and 13,407 controls were finally selected after strict screening on the basis of the inclusion and exclusion criteria, the protocol of literature search and selection is shown in Fig. eNOS rs1799983 polymorphism and hypertension in the five different genetic models, and thus random-effects model was used for all analyses. We found significant association between eNOS rs1799983 polymorphism and the risk of hypertension under any genetic model  , and the association between eNOS rs1799983 polymorphism with risk of hypertension was found in any region under other genetic models. With regard to ethnicity, we found the association between eNOS rs1799983 polymorphism with risk of hypertension was significant in Asian population under all genetic models ; however, with respect to contrast of TT versus GG and TT versus GG + GT, the genotype TT was associated with the increased risk of hypertension not only in Asian population but also in other population  ; however, the funnel plots were asymmetrical in other genetic models for the association between eNOS rs1799983 polymorphism with hypertension, and the results of Egger’s tests showed that there were publication bias   seemed symmetrical, and the results of Egger’s tests showed that there was no publication bias (eNOS rs1799983 polymorphism with hypertension under codominant model (GT vs GG), codominant model (TT vs GG), and dominant model (GT + TT vs GG), the Z-curve crossed trial sequential monitoring boundary, although the sample size did not reach the RIS , recessive model (TT vs GG + GT), and overdominant model (GT vs GG + TT), the Z-curve crossed trial sequential monitoring boundary, and the sample sizes were also more than the RIS , especially among Asian population. Moreover, with respect to contrast of TT versus GG and TT versus GG + GT, the TT genotype is associated with the increased risk of hypertension not only in Asian population but also in other population.In the meta-analysis, we collected related articles comprehensively to investigate the association between eNOS rs1799983 polymorphism and hypertension have been published, four of them  studied the Chinese populations [eNOS rs1799983 polymorphism and hypertension, and Liu et al. studied the association between GT + TT genotype of eNOS rs1799983 polymorphism and hypertension, and their results are also consistent with our results.Nine meta-analyses on association between ulations –23. CheneNOS rs1799983 polymorphism and hypertension, and consistent with the discoveries of Pereira et al., we also identified the heterogeneity and publication bias in the meta-analysis, they may exist owing to the gene–environment interactions. Niu et al. [eNOS rs1799983 polymorphism and hypertension, we all found the T allele of eNOS rs1799983 polymorphism was a risk factor of hypertension, especially among Asian population. Moreover, of the nine meta-analyses, the results of Takeuchi [eNOS rs1799983 polymorphism and hypertension, the reason they had this negative results may be a small size, or interaction of polymorphisms within haplotypes, which is a major determinant of disease susceptibility, not the individual polymorphism [Pereira et al.  studied u et al.  only stuTakeuchi  and ZintTakeuchi  were negmorphism .For the meta-analysis of Xie et al. , the laseNOS rs1799983 polymorphism and hypertension.The meta-analysis may report false positive results for the risk of type I errors, and these results are usually caused by publication bias, heterogeneity between studies, or poor study quality. However, a limited number of trials may not provide enough information, resulting in incorrect estimates . Thus, weNOS rs1799983 polymorphism and hypertension.The vasodilator effect of NO that is produced by eNOS is very important for maintenance of vascular function , and theeNOS rs1799983 polymorphism and hypertension under any genetic model except the recessive model, because negative articles are unpublished. Third, our research cannot prove the existence of causality, but only an association because of the design of case–control.Our study has some limitations. First, there is heterogeneity in our article, and the main sources of heterogeneity remain unclear. Second, publication bias was found in the association between eNOS rs1799983 polymorphism and hypertension, which further offers reliable evidence to reach the conclusion.Despite the above limitations, our research also has some advantages. First of all, we have collected the latest articles extensively, which provides more statistical power to draw effective conclusions on this issue. Secondly, the results of sensitivity analysis show that our conclusion is stable and reliable. Third, to our knowledge, this is the first TSA to evaluate the association between eNOS rs1799983 polymorphism is associated with increased risk of hypertension under any genetic model. Moreover, investigations of gene–gene and gene–environment interactions are needed to give more insight into the association between eNOS rs1799983 polymorphism and hypertension.In conclusion, Additional file 1. Table S1 Search strategies of databases.Additional file 2. Figure S1 Sensitivity analysis of association between eNOS rs1799983 polymorphism and hypertension. (A) allelic model: T vs G; (B) codominant model: GT vs GG; (C) codominant model: TT vs GG; (D) dominant model: GT + TT vs GG; (E) recessive model: TT vs GG + GT; (F) overdominant model: GT vs GG + TT.Additional file 3. Figure S2 Funnel plot for the result of association between eNOS rs1799983 polymorphism and hypertension. (A) allelic model: T vs G; (B) codominant model: GT vs GG; (C) codominant model: TT vs GG; (D) dominant model: GT+TT vs GG; (E) recessive model: TT vs GG + GT; (F) overdominant model: GT vs GG + TT