Sedentary behaviour is an emerging risk factor for several site-specific cancers. Ovarian cancers are often detected at late disease stages and the role of sedentary behaviour as a modifiable risk factor potentially contributing to ovarian cancer risk has not been extensively examined. We systematically searched relevant databases from inception to February 2020 for eligible publications dealing with sedentary behaviour in relation to ovarian cancer risk. We conducted a systematic review and meta-analysis, calculating summary relative risks (RR) and 95% confidence intervals (CI) using a random-effects model. We calculated the E-Value, a sensitivity analysis for unmeasured confounding. We tested for publication bias and heterogeneity. Seven studies (three prospective cohort studies and four case–control studies) including 2060 ovarian cancer cases were analysed. Comparing highest versus lowest levels of sedentary behaviour, the data indicated a statistically significant increase in the risk of ovarian cancer in relation to prolonged sitting time . Sub-analyses of prospective cohort studies  and case–control studies  showed statistically non-significant results. Sensitivity analysis showed that an unmeasured confounder would need to be related to sedentary behaviour and ovarian cancer with a RR of 1.90 to fully explain away the observed RR of 1.29. Our analyses showed a statistically significant positive association between sedentary behaviour and ovarian cancer risk.The online version of this article (10.1007/s10654-020-00712-6). Ovarian cancer is the eighth most common cancer in women worldwide, with 295,414 incident cases and 184,799 deaths in 2018 .Sedentary behaviour is a modifiable risk factor for several chronic diseases including different tumour entities . SedentaSeveral epidemiologic studies have investigated the association between sedentary behaviour and ovarian cancer risk. Previous meta-analyses generated inconsistent findings , 8–10. WThe present study was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) . The PRITo qualify for our analysis, studies had to fulfil the following inclusion criteria: studies 1) represented a cohort or case–control design, 2) were conducted in adult women, 3) defined total sitting time, leisure-time sitting, TV-viewing time or occupational sitting time as an exposure variable and considered ovarian cancer risk as the primary outcome, 4) provided a relative risk (RR), odds ratio (OR) or hazard ratio (HR) and 95% confidence intervals (CI) for highest versus lowest levels of sedentary behaviour and 5) were published in English language.We excluded studies assessing physical inactivity, as physical inactivity cannot be equated with sedentary behaviour . FurtherWe systematically searched the PubMed and Web of Science databases from inception to February 2020. Weekly updates provided by both databases were used and we reiterated our search on a monthly basis. Additionally, we manually reviewed the reference lists of suitable articles and consulted with experts in the field to obtain further relevant publications. Two authors (VB and CJ) developed the search term (Online Resource 2), which entailed sedentary behaviour and appropriate synonyms, as well as terms related to sedentary behaviours , combined with keywords for ovarian neoplasms or site-specific cancer.The first author (VB) screened titles and abstracts and retrieved full-text articles that met the inclusion criteria for further reading. The final decision about inclusion in the meta-analysis was made by two authors (VB and CJ) and disagreements were resolved by discussion with ML. If several reports regarding the same cohort study were found, we included the most recent publication.The following data of each study was extracted by the first author (VB) and re-examined by the second author (CJ): first author’s name, publication year, study design and name, size and age of study population, geographic region, follow-up time, number of incident cases, number of controls (if case–control design), histologic cancer type , case ascertainment , sedentary behaviour domain ), exposure ascertainment , unit of measurement , and adjustment factors, risk estimates  with corresponding 95% CIs.i). We computed the natural logarithms of relative risks (log(RRi)) with their corresponding standard errors (si = di / 1.96), where di was defined as maximum of (log(upper bound 95% CI of RRi) – log(RRi)) and (log(RRi) – (log(lower bound 95% CI of RRi)). The logarithmic relative risks were weighted by ωi = 1/(si2 + τi2) using a random-effects model, where si describes the standard error of log(RRi) and τI the restricted maximum likelihood estimate of the overall variance allowing for effect measure heterogeneity [Risk estimates were interpreted as relative risks , geographic region , sedentary behaviour domain , exposure ascertainment  and adjustments for body mass index (BMI), family history of breast or ovarian cancer, parity, age at menarche, age at menopause, use of oral contraceptives, hormone therapy, education, alcohol use and smoking status.Publication bias was evaluated using a funnel plot , Begg’s We calculated the E-Value to estimate how strong an unmeasured confounder would need to be to fully resolve a reported exposure-outcome association, above and beyond measured covariates . As partAll risk estimates were calculated with the corresponding 95% CIs. P-values < 0.05 were considered statistically significant. All statistical analyses were performed with the software R (version 3.5.1) , using tThe systematic literature search identified 6074 publications, of which 6055 were found through electronic literature search  and 19 through hand search or other sources . The summary risk estimates were almost identical in cohort  and case–control  studies, although the stratum-specific risk estimates were statistically non-significant and heterogeneity was modest in both cohort  and case–control  studies.Our primary random-effects meta-analysis of seven risk estimates revealed a statistically significant positive association between high versus low level of sedentary behaviour and risk of ovarian cancer   Table .Table 2SVisual inspection of the funnel plot yielded no evidence for publication bias (Online Resource 4), as indicated by Egger’s regression test (P = 0.97) and Begg’s correlation test (P = 1.00).Leave-one-out diagnostics and influence diagnostics of the seven included studies showed no relevant changes in summary risk estimates, spanning a range from RR = 1.24 (95% CI = 1.02–1.51) to RR = 1.38 (95% CI = 1.12–1.70). For example, when the case–control study that used job title assignment and occupational sitting time as exposure variable  was omitThe sensitivity analysis for unmeasured confounding showed that an unobserved confounder needed to be associated with both sedentary behaviour and ovarian cancer with a risk ratio of at least 1.90 to fully explain away the mean RR of 1.29, above and beyond the measured confounders, yet weaker confounding could not do so. To render the estimated risk ratio statistically non-significant, unobserved confounding strength associated with sedentary behaviour and ovarian cancer risk with a risk ratio of 1.34 would be necessary to move the lower confidence limit of 1.07 to include the null. Unobserved confounder strengths with RRs of 2.14, 1.96, 1.84, 1.73 and 1.63 in each meta-analysed study, respectively, would be necessary to reduce to less than 10%, 20%, 30%, 40%, and 50%, respectively, the percentage of studies with true causal RRs above the meaningful scientific threshold of 1.10 (Online Resource 5).The results of our primary meta-analysis, including 2060 ovarian cancer cases from seven studies, showed a 29% increase in ovarian cancer risk with high versus low levels of sedentary behaviour. The association between sedentary behaviour and ovarian cancer risk was not modified by study design, geographic region, sedentary behaviour domain, exposure ascertainment, or adjustment for several confounders, including reproductive, hormonal, and lifestyle factors.Our results update and expand the existing evidence on sedentary behaviour and ovarian cancer risk. Results from previous meta-analyses differed. Whereas some studies , 10 founTo our knowledge, the current study is the first meta-analysis on the association between sedentary behaviour and ovarian cancer risk that considered the E-Value as a parameter for unmeasured confounding, representing a novel methodological contribution to the existing evidence. The E-Value, a sensitivity analysis for unmeasured confounding, is a relatively new way to test the robustness of an association between exposure and outcome and to evaluate evidence for causation. Even though most of our included studies reduced confounding by adjusting the risk estimates for relevant factors, there is still concern about possible bias caused by uncontrolled confounding. Our results show that an unobserved confounder would have needed to be related to both the exposure and the outcome with a risk ratio of 1.90 to fully explain away the mean RR of 1.29. Also, a confounder would have needed a risk ratio of 1.34 to render the risk estimate statistically non-significant. Although the observed E-value implies a true exposure-outcome association, we cannot fully rule out the existence of an unmeasured confounder associated with sedentary behaviour and ovarian cancer .We were unable to examine whether prolonged sedentary behaviour affects ovarian cancer risk through an etiologic pathway involving obesity because none of the included studies provided risk estimates for different adiposity groups. However, several plausible hypotheses exist regarding obesity as a potential underlying biological mechanism. For example, time spent sedentary replaces time spent with physical activity, and high amounts of sedentary behaviour may coexist with increased energy supply , subsequOne challenge in interpreting the positive association between sedentary behaviour and ovarian cancer observed in our study is that there is currently limited evidence of an inverse relation of physical activity to ovarian cancer . NumerouOur meta-analysis has numerous important strengths. We used unified and a priori defined criteria for our comprehensive literature search and extraction of relevant information from included studies. We conducted stratified analyses to identify potential sources of heterogeneity and provided precise and valid risk estimates throughout. Notably, we excluded studies that assessed physical inactivity instead of sedentary behaviour as the exposure variable. Importantly, sensitivity analysis for unmeasured cofounding, the E-Value has not yet been conducted in other meta-analyses covering the association between sedentary behaviour and ovarian cancer.However, there are some limitations to our meta-analysis. Firstly, study designs were heterogenous (prospective cohort and case–control studies). As the number of existing prospective cohort studies on this topic is still small, more high-quality research is required to confirm our results. In addition, almost all studies used self-administered questionnaires , 16, 18 In conclusion, this quantitative analysis of all available studies indicates that sedentary behaviour increases the risk of ovarian cancer. Our results represent an important step towards considering sedentary behaviour as a modifiable risk factor for ovarian cancer. Therefore, endeavours to reduce time spent sedentary throughout our everyday lives are to be encouraged on an individual and public health level.Supplementary file 1 (PDF 122 kb)Supplementary file 2 (PDF 133 kb)Below is the link to the electronic supplementary material.


VDR) BsmI, FokI, ApaI, and TaqI polymorphisms and type 2 diabetes mellitus (T2DM) risk. However, the results were inconsistent. Therefore, an updated meta-analysis was performed to further explore these issues.Numerous original studies and 4 published meta-analyses have reported the association between the Vitamin D receptor  AND (polymorphism OR variant OR mutation) AND (diabetes OR mellitus OR diabetes mellitus). Pooled crude odds ratios with 95% confidence intervals were applied to evaluate the strength of association in 5 genetic models. Statistical heterogeneity, the test of publication bias, and sensitivity analysis were carried out using the STATA software (Version 12.0). To evaluate the credibility of statistically significant associations, we applied the false-positive report probabilities (FPRP) and Bayesian false discovery probability (BFDP) test.PubMed, EMBASE, Scopus, and Wanfang databases were searched. The following search strategy were used:  in any significant association.On the In summary, this study strongly indicates that all significant associations were less credible positive results, rather than from true associations. The pathogenesis of T2DM is complex, many factors such as geography, obesity, diet and exercise, genetic susceptibility, and other possible factors have been discovered, among them, genetic predisposition plays a crucial role in the development of T2DM, although its manifestation is highly dependent on environmental factors.Type 2 diabetes mellitus (T2DM) is a progressive chronic disease that is marked by the inability of tissues such as the liver and skeletal muscles to respond to insulin, it has become a significant global healthcare problem and its reported incidence is increasing at an alarming rate. Based on the recent International Diabetes Federation Diabetes Atlas (9th edition) an estimated 463 million global citizens are suffering from diabetes, costing around 10% of global health spending ($760 billion). Projections based on current trends predict that 700.2 million people will be living with diabetes by 2045; which means that 1 in 11 people will be affected, with an excessive amount of funding required globally to treat diabetes and manage diabetic complications.VDR) was the most extensively reported, which is a member of the nuclear receptor superfamily of transcriptional regulators and located on chromosome 12q13, through binding to vitamin D responsive elements (VDREs and nVDREs), respectively, which is located in the promoter region of target genes to regulates gene transcription positively or negatively. The VDR is expressed in many different cell types such as pancreatic b-cells, vascular smooth muscle cells, osteoblasts and chondrocytes, liver, adipose tissue, muscle, dendritic cells, and lymphocytes. Therefore, the VDR protein regulates the expression of genes involved in diverse biological functions, and it has also been shown to play a significant role in T2DM.,12Vitamin D receptor  and T2DM risk, this study systematically reviewed the literature again and conducted an updated meta-analysis. this study included more studies and reliable results than previously published meta-analysis.–17Over the past several years, more than 25 22.1 We searched databases including PubMed, EMBASE, Scopus, and the Chinese Wanfang Data Knowledge Service Platform. In addition, we also searched the Catalog of Published Genome-Wide Association Studies (www.genome.gov/gwastudies) of the US National Human Genome Research Institute. The following search strategy were used: (VDR OR vitamin D receptor) AND (polymorphism OR variant OR mutation) AND (diabetes OR mellitus OR diabetes mellitus). The search deadline is September 12, 2020. In addition, the reference lists of previously published meta-analysis–17 were also checked.We performed the current study according to the guidelines of the PRISMA group.2.2VDR BsmI, FokI, ApaI, and TaqI polymorphisms with T2DM risk; and (3) provided sufficient genotype data or the odds ratio (OR) with their 95% confidence intervals (CI) in the selected literature. The exclusion criteria were: (1) duplicated studies or data; (2) studies with no available data; and (3) case reports, reviews, and letters.The inclusion criteria were as follows: (1) case-control or cohort studies; (2) described the association on the 2.3Data were extracted and checked by 2 investigators independently. Disagreement was settled through discussion and consensus. The extracted information was as follows: (1) first author, (2) year of publication, (3) country, (4) geographic region, (5) ethnicity, (6) sample size of cases and controls, (7) source of controls, (8) type of controls, (9) matching, and (10) genotype distributions in cases and controls.The quality score assessment of selected studies was also independently conducted by 2 authors. Table 1, Supplemental Digital Content lists the scale for quality assessment of molecular association studies of T2DM. The total score was 18 points, studies scoring >11 were high, those scoring <8 were low, and those scoring between 8 and 11 were moderate.2.4VDR genetic polymorphisms  and T2DM risk. P < .05 was considered as statistically significant results. Five genetic models were used: (1) an allele model; (2) an additive model; (3) a dominant model; (4) a recessive model; and (5) an over-dominant model. Heterogeneity among studies applied Chi-square-based Q test and I2 value. There was no obvious heterogeneity among studies if P > .10 and/or I2 ≤ 50% and the ORs were pooled to apply a fixed-effects model. Otherwise, a random-effects model was conducted. Furthermore, a meta-regression analysis was applied to explore sources of heterogeneity. Subgroup analyses were performed by geographic region and ethnicity. We assessed sensitivity analysis by including high-quality and Hardy–Weinberg equilibrium (HWE) in control studies. HWE was examined using Chi-square goodness-of-fit test and it was regarded as HWE in controls if P > .05. The publication bias was estimated using the Begg funnel plot and Egger test. A nonparametric “trim and fill” method will be employed to add missing studies if an obvious publication bias was found. Finally, the false-positive report probabilities (FPRP) and the Bayesian False Discovery Probability (BFDP) test were applied to assess the credibility of statistically significant associations. We preset a noteworthy value (FPRP < 0.2 and BFDP < 0.8) and set a prior probability of 0.01 to detect risk.,23 All statistical analyses were conducted using Stata 12.0 software .The crude ORs with their corresponding 95% CIs were employed to evaluate the strength of association between the 33.1,19,35–80 of which 37 studies reported the VDR BsmI (5586 cases and 6484 controls), 31 studies examined the VDR FokI (6525 cases and 7464 controls), 19 studies investigated the VDR ApaI (2593 cases and 3557 controls), and 24 studies explored the VDR TaqI (3221 cases and 4027 controls) with T2DM risk, as shown in Figure VDR BsmI, 13 high-quality studies, 15 medium-quality studies, and 2 low-quality studies on the VDR FokI, 10 high-quality studies, 9 medium-quality studies on the VDR ApaI, and 13 high-quality studies and 11 medium-quality studies on the VDR TaqI. The detailed characteristics and scoring of each study are displayed in Table 4, Supplemental Digital Content. The genotype frequencies of VDR BsmI, FokI, ApaI, and TaqI polymorphisms with T2DM risk and HWE test results were shown in Table 4, Supplemental Digital Content.Figure 3.2VDR BsmI and T2DM risk. No significant association was observed in the overall analysis. Subgroups were conducted by ethnicity and geographic region, the VDR BsmI was associated with a significantly decreased T2DM risk in Asians (BB vs (Bb + bb): OR = 0.77, 95% CI = 0.60–0.99). Unfortunately, after FPRP and BFDP correction, less-credible results were found in Asians, as shown in Table Table VDR FokI and T2DM risk. Overall, a significantly decreased T2DM risk was observed in overall analysis  vs ff: OR = 0.98, 95% CI = 0.96–1.00), Asians  vs ff: OR = 0.97, 95% CI = 0.94–0.99; FF vs (Ff + ff): OR = 0.79, 95% CI = 0.69–0.90; F vs f: OR = 0.93, 95% CI = 0.90–0.96), African countries , and Asian countries  vs ff: OR = 0.97, 95% CI = 0.95–1.00; FF vs (Ff + ff): OR = 0.84, 95% CI = 0.75–0.95, F vs f: OR = 0.94, 95% CI = 0.89–0.99). After FPRP and BFDP correction, associations remained significant in the overall population, Asians, and African countries, as shown in Table Table VDR ApaI with T2DM risk are shown in Table The results of the association on the VDR TaqI polymorphism with T2DM risk.As lists in Table 3.3VDR BsmI and ApaI. However, we found that ethnicity (FF vs (Ff + ff): P = .004; F vs f: P < .001), sample size (F vs f: P = .016), quality score (FF vs (Ff + ff): P = .006; F vs f: P = .001), and HWE (FF vs (Ff + ff): P = .018; F vs f: P = .002) were the source of heterogeneity in the overall analysis for the VDR FokI polymorphism. Concerning the VDR TaqI polymorphism, the quality of selected studies was the source of heterogeneity in the overall population (Tt vs tt: P = .033).Heterogeneity was shown in Tables VDR BsmI, ApaI, and TaqI polymorphisms, as also shown in Tables Sensitivity analyses were estimated by applying 2 methods in this meta-analysis. First, results did not change removing a single study each time. Second, when we excluded studies of low quality and Hardy–Weinberg disequilibrium (HWD) in controls, no significantly decreased or increased T2DM risk was observed for the VDR FokI polymorphism and T2DM risk, as also shown in Table A significant association was observed in the overall analysis ): OR = 0.89, 95% CI = 0.81–0.97), Asians : OR = 0.85, 95% CI = 0.74–0.98; F vs f: OR = 0.94, 95% CI = 0.88–1.00), African countries , Asian countries , and mixed populations  vs ff: OR = 1.15, 95% CI = 1.01–1.31) between the 3.4VDR BsmI polymorphism and T2DM risk by Begg funnel plot and Egger test ((BB + Bb) vs Bb: P = .041; B vs b: P = .044). Then, A nonparametric “trim and fill” method was used to adjust publication bias, We need to add 6 articles and 4 articles in the future for (BB + Bb) vs Bb and B vs b models, respectively, as shown in Figure Publication bias was only observed between the 4VDR gene polymorphisms  have been considered as potential genetic factors for T2DM. However, the results from published studies are still inconsistent. Moreover, 4 previously published meta-analyses–17 also have yielded obvious disagreement results, as lists in Table 3, Supplemental Digital Content. Thus, further evidence needs to clarify their associations with T2DM risk, and as far as we know that this is the first meta-analysis to explore the positive results by FPRP and BFDP test to avoid confounding factors.T2DM is a chronic, complex, and life-long disease with a strong genetic component, which has a significant impact on quality of life, and increases the morbidity and mortality of other diseases, the etiology of T2DM is not elucidated till now. There were a lot of significant evidence indicating that the 4 VDR BsmI polymorphism was associated with a significantly decreased T2DM risk in Asians; the VDR FokI polymorphism was associated with a significantly decreased T2DM risk in Asians, African countries, and Asian countries; the VDR ApaI polymorphism was associated with a significantly decreased T2DM risk in Caucasians and North American countries. On the VDR ApaI polymorphism, a significantly increased T2DM risk was found in a mixed population. The current study was performed by applying multiple subgroups and different genetic models, at the cost of multiple comparisons, in which case the pooled P value must be adjusted. FPRP was considered as an appropriate approach to evaluate the probability of significant results on the multiple hypothesis testing of gene polymorphism and disease susceptibility studies. In addition, Ioannidis JP et al provided a more precise Bayesian measure of false discovery in genetic epidemiology studies. Therefore, we employed FPRP and BFDP test to evaluate the false significant associations in this manuscript. Results of meta-regression analysis suggested that studies of ethnicity, sample size, quality score, and HWD were the source of heterogeneity. Deviation from HWE in controls may indicate selection bias, population stratification, or genotyping errors. In addition, random error and bias may be common in some small samples, low quality, and HWD in control studies, so that the results of these original researches can not be credible, especially in the studies of gene polymorphism and disease susceptibility. Moreover, as we know, small sample studies with significant results may be easier to accept than those with negative reports. However, when they tend to come positive results, their studies maybe not rigorous and often of low-quality. Hence, we assessed sensitivity analysis by including high-quality and HWE in control studies. However, when we further performed a sensitivity analysis, FPRP, and BFDP test, less-credible positive results were identified .Overall, the VDR FokI polymorphism is located within the 5′ end of the gene near the promoter region. FokI polymorphism not only affects the function of the Vitamin D3 but also interrupts the binding efficiency of vitamin D and VDR, impairing insulin function and leading to T2DM finally. However, the single SNP role was much weak, this study indicates that significant association is less-credible positive results, we thought the VDR FokI polymorphism maybe not associated with T2DM risk. In addition. It has been indicated that the VDR TaqI polymorphism is a silent mutation despite being located in exon 9, and both BsmI and ApaI are located in the intron between exons 8 and 9 and do not alter the amount of the VDR protein, structure, or function. These biological functions supported our findings.The VDR  polymorphisms and T2DM risk. Yu et al in 2016 found that the VDR BsmI polymorphism significantly increased T2DM risk only in overall analysis; Zhu et al in 2014 and Li et al in 2013 reported that the VDR BsmI polymorphism was not associated with T2DM risk in overall populations, Asians and Caucasians; Wang et al in 2012 observed that the VDR BsmI polymorphism was associated with an increased T2DM risk in overall populations and Asians, as shown in Table 3, Supplemental Digital Content. Yu et al in 2016 reported that the FokI polymorphism significantly decreased T2DM risk in the overall analysis and Chinese population; Wang et al in 2012 observed that the VDR FokI polymorphism was associated with a decreased T2DM risk in overall populations and Asians; Li et al in 2013 found that the VDR FokI polymorphism was not consistently associated with either increased or decreased risk of T2DM in the overall analysis, as shown in Table 3, Supplemental Digital Content. Previously published meta-analyses did not found any significant association between the VDR (ApaI and TaqI) polymorphisms and T2DM risk, as shown in Table 3, Supplemental Digital Content. An obvious inconsistency was found in the classification of ethnic groups between these previously published meta-analyses and the present meta-analysis. Furthermore, all previously published meta-analyses did not adjusted ORs and their 95% CI. In addition, the sample size of this study was much larger. In the present study, 37 studies reported the VDR BsmI (5586 cases and 6484 controls), 31 studies examined the VDR FokI (6525 cases and 7464 controls), 19 studies investigated the VDR ApaI (2593 cases and 3557 controls), and 24 studies explored the VDR TaqI (3221 cases and 4027 controls) with T2DM risk. Previously meta-analyses reported the largest sample size only including 18 studies (2757 cases and 3517 controls) for the VDR BsmI, 12 studies (2218 cases and 1859 controls) for the VDR FokI, and 10 studies for the ApaI (1430 cases and 2441 controls), as shown also in Table 3, Supplemental Digital Content. In addition, Yu et al used 4 genetic models, Zhu et al applied 3 genetic models, and Li et al and Wang et al only employed 1 genetic model. Therefore, their results may be not credible.Table 3, Supplemental Digital Content shows the results of previously published meta-analyses on the association between the The current meta-analysis, there has some advantages: (1) we assessed the quality of included studies; (2) we applied FPRP and BFDP test to evaluate the significant associations; (3) we explored sources of heterogeneity by meta-regression analysis; and (4) the sample size was larger over the previous meta-analysis. However, some potential limitations should be considered in the current meta-analysis. First, some potential covariates were not controlled, for example, age, gender, and so on. Second, in the subgroup analyses, the number of studies was small in Indians, North America, South America, and Africa, and there was not enough statistical power to explore their real associations. Third, T2DM is a complicated multi-genetic disease, the association was very weak between the single SNP and T2DM risk, unfortunately, no data were extracted on exploring the combined effects between gene and gene or gene and environment. Therefore, the study with a large sample size and a large enough subgroup will help to verify our findings.In summary, this study strongly indicates that all significant associations were less credible positive results, rather than from true associations. Future larger-scale epidemiological investigations of this topic should be conducted to confirm or refute our findings.Conceptualization: Yao Liu, Hu-Wei Shen.Data curation: Yao Liu, Xin Guo, Shao-Yan Huang.Formal analysis: Yao Liu.Funding acquisition: Yao Liu.Investigation: Yao Liu.Methodology: Yao Liu, Xiang-Hua Ye, Xiao-Feng He.Project administration: Yao Liu, Xiao-Feng He.Resources: Yao Liu.Software: Yao Liu, Xiao-Feng He.Supervision: Yao Liu, Luan Gong, Jin-Hui Cui, Hu-Wei Shen, Xiang-Hua Ye, Xiao-Feng He.Validation: Yao Liu, Xiang-Hua Ye, Xiao-Feng He.Visualization: Yao Liu.Writing – original draft: Yao Liu, Hu-Wei Shen.Writing – review & editing: Yao Liu, Hu-Wei Shen, Xiang-Hua Ye, Xiao-Feng He.This study was designed by Xiao-Feng He, Hu-Wei Shen, and Xiang-Hua Ye. Yao Liu, Xin Guo, Shao-Yan Huang,Luan Gong, and Jin-Hui Cui did the literature search, study quality assessment, and data extraction. Yao Liu performed the statistical analysis, drafted the tables and figures, and wrote the first draft of this analysis, and Xiao-Feng He helped to finish the final version. All authors approved the conclusions of our study.


Candida infection. However, many different risk factors have been derived from multiple studies. These risk factors lack specificity, and broad application would render most ICU patients eligible for empirical antifungal therapy.Current guidelines recommend empirical antifungal therapy in patients with sepsis with high risk of invasive Candida infection can be identified by a systematic review and meta-analysis?What risk factors for invasive Candida infection. We calculated pooled ORs for risk factors present in more than one study.We searched PubMed, Web of Science, ScienceDirect, Biomed Central, and Cochrane and extracted the raw and adjusted OR for each risk factor associated with invasive Candida infection included demographic factors, comorbid conditions, and medical interventions. Although demographic factors do not play a role for the development of invasive Candida infection, comorbid conditions  and medical interventions have a significant impact. The risk factors associated with the highest risk for invasive Candida infection were broad-spectrum antibiotics , blood transfusion , Candida colonization , central venous catheter , and total parenteral nutrition . However, dependence between the various risk factors is probably high.We included 34 studies in our meta-analysis resulting in the assessment of 29 possible risk factors. Risk factors for invasive Candida infection in the ICU. Most of the factors identified were either related to medical interventions during intensive care or to comorbid conditions.Our systematic review and meta-analysis identified patient- and treatment-related factors that were associated with the risk for the development of invasive   Study Question: What risk factors for invasive Candida infection can be identified by a systematic review and meta-analysis?Results: We identified 29 risk factors from 34 studies mostly related to medical interventions during intensive care or to comorbid conditions, but most ORs were small.Interpretation: There are multiple correlated risk factors for invasive Candida infection in the intensive care setting.Candida species cause approximately 80% of those infections.Candida infection (ICI) is associated with a high risk of death with an attributable mortality of 49%,,The burden of invasive fungal infections on ICUs is increasing,The reporting of this study follows the recommendations for Meta-analysis Of Observational Studies in Epidemiology,An internet search of relevant publications was performed on five databases  on June 23, 2014. A search algorithm was applied which has been modified from a previous systematic review.Candida species from urine or tracheal aspirates in their case definition were excluded because this mainly reflects colonization and not invasive infection. Control groups had to come from the same ICU population as the cases. Abstracts were included if they contained analyzable results, and no full paper with those data was available. Only publications in English, German, or French were included. If two or more publications were based on the same patient cohort, only one publication was included in the analyses, but all papers were used to extract all available information.We included cohort and case-control studies on adult patients (≥ 18 years of age) admitted to an ICU, which assessed risk factors for the occurrence of ICI either retrospectively or which prospectively followed patients for the development of ICI. The study-specific definition of ICI could be either bloodstream infection (candidemia) or using the European Organization of the Research and Treatment of Cancer/Mycoses Study Group criteriaInitially, all duplicates from the searches were removed. All titles and in a second step all remaining abstracts were screened by one author (D. T.-R.) for possible eligibility. The full texts of all potentially eligible publications were then rescreened by two authors (F. B. and D. T.-R.); conflicting opinions about eligibility could be resolved in all cases by discussion. Potentially eligible publications identified by the updated PubMed search, personal files, or reference lists were screened the same way.All reported risk factors and their definition were extracted from the selected publications and thematically grouped by one author (D. T.-R.). Two authors (F. B. and D. T.-R.) decided to collapse identical or nearly identical risk factors into one category and to omit risk factors only assessed by single publications and without reasonable association with ICI from further data extraction. Zero counts in a two-by-two table were replaced by 0.5 to avoid infinite ORs . Univariate and, if reported, multivariable ORs and 95% CIs of the applicable risk factors for developing ICI were independently extracted by two authors (F. B. and D. T.-R.) onto standardized data extraction sheets. ORs and CIs were independently calculated by both authors if only frequency data were reported. If a publication reported several cohorts, only data from the cohorts fulfilling inclusion criteria were extracted. Discrepancies were resolved by repeat extraction by both authors, discussion between the data extractors, and if still unresolved discussion with a third author (M. P. and O. K.). The corresponding author was contacted for all articles where data of interest were found to be missing.Two authors (F. B. and D. T.-R.) independently assessed the risk of bias for each included study by adapting the Scottish Intercollegiate Guidelines Network quality checklists for cohort studies and case-control studies. The checklists provided measures for assessing internal validity  and overall study quality. Because of the specifics of epidemiologic research in the ICU setting, not all items were applicable, and the checklists were accordingly modified. The modification of the Scottish Intercollegiate Guidelines Network checklist resulted in seven checklist items each for the case-control studies and the cohort studies . One poiI2 and the heterogeneity variance τ2. Calculations were performed with R  and the metagen-function from the meta-package.Pooled-adjusted univariate and multivariable ORs for each risk factor were calculated using a general inverse variance method with a random effects model. Heterogeneity between studies was investigated using Through the literature search in MEDLINE and Embase, we identified 4,877 references. Duplicate references were identified and removed , resulting in 3,272 articles. After screening of titles and abstracts and search updates, 104 articles were selected for full-text review, resulting in 34 studies included in this meta-analysis .Figure 1,,A list of the 34 included studies with their characteristics is presented in Candida colonization , central venous catheter , and total parenteral nutrition . ICU length of stay, assessed by four studies, was an outlier with an extremely high risk . Meta-analyses, differing definitions, funnel plots, and cumulative meta-analyses for individual risk factors are presented in Twenty-nine risk factors were extracted from the selected publications. The results for all risk factors except ICU length of stay  are pres,,,,,,,,,I2 showed a wide range (0%-96%), resulting in significant heterogeneity in 12 of 29 of the observed risk factors. Egger test showed a significant asymmetry of funnel plots only for central venous catheter , our meta-analysis also identified renal replacement therapy, mechanical ventilation, blood transfusion, and diabetes as important risk factors.We identified 34 articles that investigated risk factors for ICI in critically ill adults. Apart from confirming the widely recognized risk factors . Therefore, implanted medical devices or Candida colonization per se obviously provide a potential source for ICI. Surgery or chemotherapyCandida species.Candida colonizationCandida species.Candida species are capable of multiplying in several parenteral nutrition solutions even in preparations where bacteria cannot grow.,C albicans.Candida species.Candida biofilm formation and pathogenicity.,There is biological plausibility for almost all risk factors significantly associated with ICI acquired in the ICU. In health, the immune system is capable in avoiding invasive fungal infections despite presence of these pathogens in primary unsterile body fluids or surfaces. Therefore, immunosuppression, including patients after transplantation or with HIV infections, solid and hematologic malignancies,Candida colonization.Length of stay in the ICU is the risk factor with the highest OR in the unadjusted analyses. However, there was significant heterogeneity between the studies, likely caused by different cutoffs, and we could not observe an e-table OR in the cumulative meta-analysis. ICU length of stay was extensively analyzed in a recent meta-analyses using wider inclusion criteria than ours but reaching similar results.Our wide meta-analysis approach has several limitations. Most of the included studies have only a limited number of ICI cases while assessing a large number of risk factors. Such an approach may result in chance findings. On the other hand, the large number of small studies published together with funnel plot inspection makes relevant publication bias unlikely. The assessed patient populations are very heterogeneous. Inclusion and exclusion criteria of the studies, their definitions of ICI, and their matching algorithms for case-control studies differ among the included studies. Some results from special populations might not be generalizable to less selected populations and vice versa. In addition, risk factor definitions or cutoffs differ between studies; most studies do not report definitions at all. Sometimes the wording for a risk factor changes within the same article. Because of these imprecisions in the underlying studies, we might in some cases have calculated common ORs of incongruous risk factors. To help readers with interpretation, we transparently report cutoffs and definitions in the supplement. Many of the assessed risk factors are highly correlated with each other. Therefore, multivariable analyses are of great importance to elucidate the real independent importance of each risk factor. However, only about one-half of the studies performed such an analysis, and the limited number of studies reporting each risk factor limits interpretability. Calculation of reliable common ORs was further hampered by the fact that most studies only reported statistically significant variables in their multivariable analysis. Model building for multivariable analysis including variable selection differed considerably between the studies. Ideally, all studies on such a topic should be consistent in their definitions and report complete multivariable models. A wider use of data repositories for epidemiologic studies in the ICU setting would enable individual patient data meta-analyses. Some studies were excluded because of language restrictions. They were published in six different languages not available in the study team and tended to be smaller studies. Because cumulative meta-analysis showed ,Our central finding is that a large number of risk factors are associated with ICU-acquired ICI, but the risk increase by each factor is relatively small or moderate at best. Future very large epidemiologic studies or individual patient data meta-analyses could only result in more precise estimators for this multitude of risk factors. The success of a risk-driven antifungal therapyOur systematic review and meta-analysis identified acute and chronic factors that were associated with the risk for the development of ICI in the ICU. Most of the factors identified were either related to medical interventions during intensive care or to comorbid conditions. However, dependence between the various risk factors is probably high. The underlying studies do not sufficiently allow to identify those risk factors independently associated with ICI.


Objective and Methods. In order to explore the relationship between AGT p.Thr174Met polymorphism and MI risk, the current meta-analysis involving 7657 subjects from 11 individual studies was conducted.  It has been suggested that the aAGT p.Thr174Met polymorphism and MI was found under recessive , dominant , codominant , and additive  genetic models. In the Asian subgroup, significantly increased MI risk was found under all genetic models (P < 0.05). No significant association between AGT p.Thr174Met polymorphism and MI was found under all genetic models in the Caucasian subgroup (P > 0.05).  A significant association between AGT p.Thr174Met variant might increase MI risk, especially within the Asian population. The Met174 allele of AGT p.Thr174Met might confer the risk for MI. Myocardial infarction (MI) is a serious type of coronary artery disease (CAD) that has high morbidity and mortality rates , 2. MI mAGT, located at 1q42-43, is 13 kb in length and contains five exons and four introns. In 1992, Corvol et al. [AGT p.Thr174Met might increase the plasma levels of AGT and Ang II, thereby increasing vasoconstriction, VSMC proliferation, and lipid deposition; this allele participates in the pathogenesis of atherosclerosis, hypertension, and MI and increases the MI risk [Angiotensinogen (AGT) is the main member of the RAS system. Human AGT is produced in the liver, digested by renin enzyme to produce angiotensin I (Ang I), and then converted to angiotensin II (Ang II) by angiotensin-converting enzyme (ACE). Ang II induces the proliferation and hypertrophy of human vascular smooth muscle cells (VSMCs), increases the expression of platelet-derived growth factor, inhibits fibrinolytic activity, and promotes blood thrombogenesis, low-density lipoprotein (LDL) deposition, oxidation, and endocytosis in the vascular wall . As a sal et al.  discover MI risk , 13–15.AGT p.Thr174Met polymorphism and MI were widely performed, their results varied widely. In 2006, Ning et al. [AGT Met174 allele increased MI risk in the Chinese population. In 2008, Xie et al. [AGT p.Thr174Met might be a risk factor for MI in an Uigur ethnic population in Xinjiang of China. By contrast, in 1995, Tiret et al. [AGT locus had no significant impact on the risk of nonfatal MI in the French population.Although studies on the relationship between g et al.  found tht et al.  reportedAGT p.Thr174Met polymorphism and MI.This meta-analysis including 3944 patients with MI and 3713 controls was conducted to confirm the relationship between The terms “myocardial infarction”, “angiotensinogen”, and “polymorphism” were used to search the China Biological Medicine Database China National Knowledge Infrastructure, Embase, PubMed, and Web of Science. Studies were retrieved within the publication year ranging from 1995 to 2018 .AGT p.Thr174Met polymorphism and MI and (b) diagnosis of MI in accordance with the diagnosis criteria promulgated by the World Health Organization in 1979 or the global universal definition of MI by the European Society of Cardiology, American College of Cardiology Foundation, American Heart Association, and World Heart Federation in 2012. MI was diagnosed if the patient had a conclusive positive history of MI or presented with ST elevation or non-ST elevation.The inclusion criteria for the studies were as follows: (a) evaluation of the P value for Hardy-Weinberg equilibrium (HWE), and NOS score.Data were obtained according to a standard protocol. Repeated literature, studies that did not meet the inclusion criteria, and studies with limited data were removed. Overlapping portions of data were used only once. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of all eligible studies. The abstracted data were composed of the following items: the first author's name, publication year, region, number of genotypes, genotyping, study design, matching criteria, total number of cases and controls, P value was set at <0.05 for most of the statistical tests.All of the statistical analysis would be performed by using the STATA 12.0 software  and review manager 5.0, and AGT p.Thr174Met polymorphism and MI, the pooled odds ratio (OR) corresponding to 95% confidence interval (CI) was used. In the present meta-analysis, four genetic models as the recessive , dominant , codominant , and additive genetic models  were used. The chi-square test was used to evaluate the HWE of the genotype distribution.In order to assess the association between Q-test was used with significance set at P < 0.10 [I2 was calculated to assess the heterogeneity variation. The pooled OR was determined using Z test, and the random-effects model was applied when there was heterogeneity among the studies (DerSimonian and Laird method) [In order to calculate the heterogeneity between studies, the chi-square-based P < 0.10 . The inc method) . Otherwi method) .The potential publication bias would be estimated by using a funnel plot. The funnel plot asymmetry would be assessed by using Egger's linear regression test on the natural logarithm scale of the OR .AGT p.Thr174Met polymorphism. No study was excluded for the reason of deviating from HWE.Of the 20 papers produced by our initial search of literature, 11 studies met the inclusion criteria. Of the 9 dropped studies, four papers were double publications, two papers were reviews, and three papers were not associated with the Total data were extracted from 3944 patients with MI and 3713 controls  16–18, –30. PatiThe NOS scores in all of the included studies were no less than 6 stars, which implied that all of the eligible studies were of high quality.AGT p.Thr174Met polymorphism and MI were found for recessive , dominant , codominant , and additive  genetic models (1Significant associations between Pheterogeneity < 0.10), but no heterogeneity existed in the Asian subgroup for all genetic models (Pheterogeneity > 0.10) (1Pheterogeneity < 0.10) (Pheterogeneity > 0.10)  1. In the  < 0.10)  and 4, a0 1. In t > 0.10) . Hence, AGT p.Thr174Met polymorphism significantly increased MI risk for recessive , dominant , codominant , and additive  genetic models , dominant , codominant , or additive  genetic models . In 2006, after the study by Sun et al. was added in the current meta-analysis, a significant association between them was detected .A cumulative analysis over time was performed using the recessive genetic model . No signT = 2.16, P = 0.059; Funnel plot and Egger's test were used to assess the publication bias of the individual studies. No visual publication bias was found according to the funnel plot of the overall studies using a recessive genetic model . FurtherIn this meta-analysis, the controls comprised hospitalized individuals who matched the case group by age, sex, BMI, or ethnicity. The controls were not diagnosed with CAD by coronary angiography and had no history of cardiovascular disease in their families. Case-control study design was used in all of the included studies. The abstracted data quality was high because the NOS score in all of the included studies, including manuscript selection, comparability, and exposure, was no less than 6 stars.AGT p.Thr174Met polymorphism and MI for recessive (OR: 2.26), dominant (OR: 1.131), codominant (OR: 2.198), and additive (OR: 1.363) genetic models.In the entire sample population, a significant association was found between AGT p.Thr174Met polymorphism and MI. Furthermore, the allelic frequencies between these ethnic groups and the differences in the matching criteria could also influence the results. In addition, the negative results in the Caucasian population were possibly influenced by the small number of included studies. Only six studies were included in the Caucasian subgroup, indicating that more studies should be conducted in the future to verify the result within this population.The different results in the two subgroups suggested that ethnicity might influence the association between AGT p.Thr174Met variant was found after 2006. It was suggested that the significant association between them was confirmed after 2006 which might be related with more individual included studies. The bias diagnostics showed that no publication bias was detected which suggested that no obvious systemic error existed in the current meta-analysis.The cumulative analysis over time also showed that the significant association between MI and AGT p.Thr174Met mutation is not in the range of conserved sequences of the AGT protein core serpin domain [MI is a multifactorial disease that varies among race, ethnicity, and geographic region. Different morbidity rates were found among different races and ethnicities. Although the n domain , 32, thin domain .AGT p.Thr174Met polymorphism and CAD risk and found no significant overall association  in the Asian and Caucasian population. Their meta-analysis included 16 individual studies. CAD includes angina pectoris, MI, silent myocardial ischemia, ischemic cardiomyopathy, and sudden death. The different results between all types of CAD, single MI risk, and AGT p.Thr174Met polymorphism were probably associated with different genetic variants among the five different types of CAD diseases.In 2012, Xu et al.  performeAGT p.Thr174Met polymorphism with MI risk [A further meta-analysis found association of the  MI risk  in both AGT p.Thr174Met polymorphism remains insufficient. Other AGT genetic polymorphisms such as -217G>A (rs5049), -532C>T (rs5046), 12775G>A (rs943580), -6T>C (rs5051), 4072C>T orMet235Thr (rs699), 11535C>A (rs7079), and 6309C>T (rs2493132) might also influence the AGT activity. Additionally, environmental factors, such as race, region, smoking status, hyperlipidemia, and diabetes mellitus, were not accounted for in this study.This meta-analysis has some limitations. The sample size is relatively small, and large-scale research on the relationship between MI and AGT p.Thr174Met variant increases MI risk, especially in the Asian population. This finding needs to be further confirmed by further research in the future.


To evaluate the association between serum galectin-3 and all-cause death (ACD) and cardiovascular death (CVD) in patients with chronic heart failure (CHF).www.clinicaltrials.gov) were searched for studies with data on serum galectin-3 and ACD and CVD in CHF patients. The hazard ratios (HRs) of ACD and CVD were calculated and presented with 95% CIs. HRs were pooled using fixed effects or random effects models when appropriate. Sensitivity analysis, meta-regression and subgroup analysis were applied to find the origin of heterogeneity. Visual inspection of Begg's funnel plot and Egger's test were performed to assess the possibility publication bias.The PubMed and Embase databases and Clinical Trials Registry  and CVD  in CHF patients. In the subgroup analyses, higher serum galectin-3 was associated with an increased risk of ACD in all subgroups. The pooled HR of the shorter follow-up group  was significantly higher than the pooled HR of the longer follow-up group . Sensitivity analysis of eliminating one study in each turn indicated that Koukoui et al.'s study had the largest influence on the risk of all-cause death. All-cause death publication bias was not detected (Pr>|z| = 0.35 for Begg's test and P>|t| = 0.15 for Egger's test).Serum galectin-3 has prognostic value of both all-cause death and cardiovascular death in CHF. Serum galectin-3 could be useful for risk classification in patients with CHF.https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=193399. Chronic heart failure (CHF) is a common clinical syndrome in cardiology with high morbidity and mortality worldwide . DespiteMyocardial fibrosis is a major determinant of clinical outcomes in patients with CHF. Fibrosis markers, such as galectin-3, soluble suppression of tumorigenicity 2 (sST2), human epididymis protein 4 (HE4), metalloproteinases (TIMP)-1, and matrix metallopeptidase (MMP)-9 have been evaluated in HF . GalectiOur meta-analysis was performed followed the Preferred Reporting Items of PRISMA statement. We registered this meta-analysis in the PROSPERO database (CRD42020193399).www.Clinicaltrials.gov) up to April 10, 2020. Two search themes were combined using the Boolean operator “and.” The first theme was heart failure, combined exploded versions of medical subject headings (MeSH) heart failure, cardiac failure, heart decompensation, myocardial failure, congestive heart failure. The second theme, galectin 3, combined exploded versions of MeSH terms galectin 3, galectin-3, or Gal-3. The exact search string was used for pubmed and modified to suit Embase database: (((“Heart Failure”[Mesh]) OR ((((Cardiac Failure) OR Heart Decompensation) OR Myocardial Failure) OR Congestive Heart Failure))) AND  OR  OR Gal-3)).We conducted the meta-analysis according to the Meta-analysis of Observational Studies in Epidemiology Group . We perfStudies that met the following criteria were included in the analysis: (1) enrollment of outpatients with CHF (either HFrEF or HFpEF); (2) follow-up studies with adult participants (aged ≥ 18 years); (3) serum galectin-3 was measured; (4) the relationship between galectin-3 and all-cause death (ACD) was reported, possibly, also for cardiovascular death (CVD); (5) multivariable adjusted hazard ratio (HR) and the corresponding 95% confidence interval (CI) were available; (6) English language. Exclusion criteria: (1) studies on patients with end-stage HF; (2) studies that cannot provide valid data for estimating HR and 95% CI; (3) only unadjusted risks were provided for associated outcomes; (4) duplicate data or analyses.On the basis of the predefined criteria, two independent authors (Zhendong Cheng and Kefeng Cai) evaluated and screened the candidate studies. When a disagreement arised, two authors reached a consensus by discussing it with the third author (Chaoxiang Xu). The following basic information were recorded each study: first author, country, year of publication, sample size, percentage of males, mean age, follow-up time, LVEF of the participants, and plasma galectin-3 levels. The quality of each included study was assessed using the Newcastle-Ottawa Scale (NOS) by two independent authors (Zhendong Cheng and Kefeng Cai) . The NOSP < 0.10 or I2 >50% indicated existence of significant heterogeneity.The primary end point measure was the risk of all-cause death (ACD) associated with serum galectin-3. The secondary end point measure was the risk of cardiovascular death (CVD) associated with serum galectin-3. From each study, multivariate adjusted outcome data (hazard ratios (HRs) and 95%CIs) for all-cause death (ACD) and cardiovascular death (CVD) were recorded for analysis . The hetThe pooled HRs and 95% CIs were calculated by using both the random-effects and fixed-effects model. If there was no or low heterogeneity, the fixed effects model was used, Otherwise a random effects model was adopted. To explore the origin of heterogeneity, we conducted subgroup analysis of the primary end point according to mean age (<65 vs. ≥65 years); sample size (<300 vs. ≥300); follow-up period (<40 vs. ≥40 months); publication year (<2015 vs. ≥2015). Meta-regression analysis was applied to explore the potential impact of population characteristics on primary outcome. In addition, a sensitivity analysis was conducted to explore the heterogeneity of different studies. The pooled HR was recalculated by omitting 1 study at a time. We evaluated publication bias for all cause death (ACD) by using Begg's funnel plot and Egger's test .p values were two tailed with a statistical significance level of 0.05.All the statistical analyses were conducted using STATA version 12.0 . The graphic displays of Newcastle-Ottawa Scale (NOS) assessment were performed by RevMan 5.2 . All The search process is summarized in I2 = 77.9%, P < 0.1), a random effects model was adopted. Our results showed that elevated serum galectin-3 was associated with a higher risk of ACD in CHF ; therefore, a fixed effects model was adopted. Our results showed that elevated serum galectin-3 was associated with a higher risk of CVD in CHF .In 11 studies that reported the risk of ACD, meta-regression analysis showed no significant associations among study characteristics  and risk of ACD , no further analyses were performed. Compared with this meta-analyses, our study provides significant strengths. We evaluated the predictive role of serum galectin-3 for ACD and CVD in CHF patients. Moreover, sensitivity analyses, meta-regression analyses and subgroup analyses were applied to search for the origin of heterogeneity.The result of ACD is consistent with a previous meta-analysis published in 2015 , which iBNP and NT-proBNP are the most well-established biomarkers used in evaluating prognosis of patients with heart failure, which are included in the current guideline and widely used in clinical practice , 17. NovGalectin-3, a chimeara-type β-galactoside binding lectin, is a crucial molecule in cardiac fibrosis , 35. GalI2 = 77.9%, P < 0.1), which may result from differences in follow-up time and participant characteristics. While there was moderate to high heterogeneity in many subgroups, the pooled HRs revealed consistent positive correlations in different subgroups. A sensitivity analysis of eliminating one study at a time revealed that Koukoui et al.'s study may be the origin of heterogeneity. Second, most of the included studies in the meta-analysis were of high quality. However, some of the involved studies were post hoc analyses in designing, which might affect the quality of the meta-analysis. Third, the involved studies in this meta-analysis were all from Western countries, and most of the participants had HF with reduced left ventricular ejection fraction. Thus, further well-designed studies in a wide range of regions and populations are needed to confirm our conclusions. Finally, this study was limited to English publications only, so publication bias may exist.Some limitations of our meta-analysis should be mentioned. First, there was a high heterogeneity across the included studies in HR for ACD ; the Science and Technology Program of Guangdong Province (2021A0505030031); the Frontier Research Program of Guangzhou Regenerative Medicine and Health Guangdong Laboratory (2018GZR110105001); and the Youth Science and Technology Innovation Talent Program of Guangdong TeZhi plan (2019TQ05Y136).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.


Congenital cytomegalovirus (cCMV) infection is the most common cause of childhood hearing loss (HL), although the strength of this association remains limited and inconclusive. Thus, the purpose of this study was to summarize evidence regarding the strength of the relationship between cCMV and childhood HL and to determine whether this relationship differs according to patient characteristics.The PubMed, EmBase, and Cochrane Library databases were searched for studies evaluating the relationship between cCMV and HL from inception to September 2019. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were used to calculate the investigated outcomes in a random-effects model. Sensitivity, subgroup, and publication bias analyses were also performed.P < .001), irrespective of whether studies reported sensorineural HL , or did not evaluate HL types among their patients . However, in studies conducted in the United States (P < 0.001) and published in or after 2000 (P = 0.026), the study populations included <60% males (P < 0.001). Moreover, studies of high quality (P < .001) demonstrated a significantly greater risk of HL with cCMV infection than that in the corresponding subgroups.A total of 15 studies involving 235,026 children met the inclusion criteria and were included in the final analysis. The summary results indicated that cCMV infection was associated with an increased risk of HL (odds ratio [OR]: 8.45; 95% confidence interval [CI]: 3.95–18.10; The study results suggest that cCMV infection increases the risk of HL. Further studies are required to investigate the association of cCMV infection with the risk of specific subtypes of HL. Notably, around 90% of cCMV-positive infants have been reported to be asymptomatic at birth; however, 6% to 23% infants later develop sensorineural HL (SNHL).,11 Furthermore, the majority of children with cCMV infection remain undiagnosed due to the lack of symptoms at birth and the lack of universal screening for CMV infection at birth and during pregnancy. Given these circumstances, the strength of the relationship between cCMV and SNHL may be underestimated, resulting in the development of late sequelae associated with cCMV.–15 Therefore, cCMV and hearing screenings should be assessed concurrently in neonates to identify early-onset HL, and infants who pass initial hearing screening should be regularly monitored to detect late-onset HL.Congenital cytomegalovirus (cCMV) infection is the most frequently occurring congenital viral infection in children, affecting approximately 0.64% to 0.7% of neonates worldwide.,17 Clarifying the association between cCMV and HL is especially important in children. Therefore, in this study, we comprehensively examined the available studies to explore the association between cCMV infection and the risk of HL in children, and compared this relationship between patients with different characteristics.Two systematic reviews have summarized the importance of cCMV as a cause of childhood SNHL, although the strength of the relationship between cCMV and childhood HL was not reported in both studies.22.1This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement issued in 2009 (Checklist S1).Any observational study that investigated the association between cCMV and the risk of HL was eligible for inclusion in the present study, without restrictions on publication language or status. In brief, a literature search was conducted across the PubMed, Embase, and Cochrane library databases with keywords, including ‘cytomegalovirus, “hearing loss," and “congenital," from their inception up to September 2019. A manual search of each study's reference list was performed to identify additional potentially eligible studies. Furthermore, the study topic, design, status of children, exposure, and incidence of HL in each potential study was assessed to identify studies suitable for inclusion.Following a standardized approach, two independent reviewers conducted the literature search and study selection, and conflicts between them were resolved by discussions until a consensus was reached. The inclusion criteria for studies in this meta-analysis were as follows: participants, children with or without cCMV infection; exposure, cCMV infection; control, no cCMV infection; outcome, incidence of HL; and study design, observational studies regardless of design. In contrast, the exclusion criteria consisted of reviews, editorials, non-human studies, letters, and conference articles without sufficient data.2.2 As mentioned previously, data extraction and quality assessment were conducted independently by 2 authors, and any disagreement was settled with a review of the original article by the corresponding author of this meta-analysis.The following items were extracted from the included articles: first author's name, publication year, country, study design, sample size, mean age of participants, proportion of male participants, birth weight of participants, and incidence of HL. The methodological quality of each study was then assessed using the Newcastle-Ottawa Scale (NOS), which is based on three subscales, namely selection (4 items), comparability (1 item), and outcome (3 items), and uses a “star system” (range: 0–9) for quality assessment.2.3,21 A heterogeneity test for the investigated outcome was conducted across the included studies using I2 and Q statistics, and P < .10 was considered significantly heterogeneous.,23 Sensitivity analysis was used to explore the source of heterogeneity and to evaluate the influence of a single study on the pooled conclusion. In addition, subgroup analyses were conducted according to publication year, country, study design, sample size, proportion of male participants, HL types, and study quality. Based on the ORs and 95% CIs in each subset, the ratios of ORs with 95% CIs were calculated between subgroups, and P values for the heterogeneity between subgroups were calculated using the χ2 test. Furthermore, publication bias was assessed using funnel plots, Egger test, and Begg test.,27 Two-tailed P values were obtained, and P < .05 was considered statistically significant. The STATA software  was used to conduct all analyses in this study.The association between cCMV infection and HL risk was examined based on the abstracted incidence of HL and number of cCMV patients in each study, and the pooled odds ratio (OR) and its corresponding 95% confidence interval (CI) were used to calculate the pooled results using a random-effects model.2.4Ethics committee approval and informed consent of patients were not required, as this study did not involve confidential patient information.33.1–45 No additional study was identified through a review of the reference lists of these studies , and the sensitivity analysis showed that the conclusion was not altered by excluding any individual study , country (P < .001), proportion of male participants (P < .001), and study quality (P < .001) was statistically significant. Moreover, cCMV-positive participants were found to have a significantly increased risk of developing HL as compared to cCMV-negative participants in all subgroups. Furthermore, studies published in or after 2000 reported a significantly greater risk of HL than those published before 2000 . Furthermore, studies conducted in the United States; retrospective studies; high-quality studies; and studies with a sample size ≥100, a proportion of male participants <60%, or HL as the outcome reported a greater risk of HL than that in corresponding subgroups, although these differences were not statistically significant.Subgroup analyses of HL risk, including publication year, country, study design, sample size, proportion of male participants, reported outcomes, and study quality, were performed to explore the source of heterogeneity and evaluate the relationship between cCMV infection and HL risk in patients with specific characteristics Table . Notably3.5P = .206; Begg, P = .762).Publication bias could not be ruled out by reviewing the funnel plot Fig. . The res4Since the characteristics of cCMV infection may affect the incidence of HL in children, the correlation between cCMV infection and HL risk was evaluated according to publication year, country, study design, sample size, proportion of male participants, reported outcomes, and study quality. This meta-analysis included a total of 235,026 participants from 12 prospective and 6 retrospective studies, and the results indicated that cCMV infection was associated with an increased risk of HL. Furthermore, the conclusions of subgroup analyses were consistent with those of the overall analysis for the most part; however, publication year, country, proportion of male participants, and study quality could have possibly biased the association between cCMV and HL risk. Moreover, Korver et al (2011) suggested that the causes of childhood hearing impairment were either hereditary (38.9%), acquired (29.7%), miscellaneous (7.1%), or unknown (24.3%) in origin; however, the relationship between cCMV infection and HL risk in children with different characteristics was not illustrated. The major strength of the present study was the comprehensive inclusion of observational studies with a large sample size and broad participant characteristics. The large sample size ensured the reliability of our conclusions, and the broad participant characteristics ensured the applicability of our results.A previous systematic review of 37 studies concluded that the prevalence of cCMV in developed countries was 0.58% . The report also indicated that 12.6%  of cCMV-positive children developed HL, of which 33.3% were symptomatic, and 10% were asymptomatic. Similarly, Saigal et al (1982) found that the prevalence of SNHL was similar in cCMV-positive and cCMV-negative groups. Kumar et al (1984) found that asymptomatic CMV infection could result in audiologic sequelae, although this relationship was not statistically significant, whereas Boppana et al (1992) reported that cCMV infection was associated with multi-system disease in newborns, but this did not affect the incidence of HL. Peckham et al (1987) reported that the prevalence of CMV infection was similar in children with and without SNHL. Diener et al (2017) indicated that CMV testing could be used as an adjunct to the newborn hearing screening program to attain timely audiological diagnostics within 90 days, although the risk of HL was not statistically significant. Lastly, Hicks et al (1993) indicated that cCMV infection may be a principal cause of hearing impairment; however, this association was not statistically significant. This study had a smaller sample size and a lower incidence of HL, which may have contributed to its low statistical power and broader 95% CI. Furthermore, the prevalence of asymptomatic cCMV infection across studies was variable, which could have affected subsequent HL risk, although the pooled analysis was not stratified according to asymptomatic or symptomatic cCMV infection. The potential pathogenesis of HL in children with cCMV infection could be attributed to injuries to the endolymphatic structures and stria vascularis, consequently inducing the degeneration of sensory structures.,47 Additionally, the occurrence of HL could also be attributed to the cytopathic effect of CMV and host immune responses in the inner ear.The pooled results indicated that cCMV-positive individuals had a significantly increased risk of developing HL, although the results were inconsistent between included studies. Harris et al (1984) suggested that cCMV screening in newborns could identify high-risk infants and facilitate the implementation of early intervention strategies. However, they found that the relationship between cCMV infection and SNHL risk was not statistically significant.For the most part of this study, the results of the stratified analysis were consistent with those of the overall analysis. However, five breakthroughs should be highlighted. First, studies published in or after 2000 reported a higher risk of HL than that in studies published before 2000. This discrepancy may be due to the use of different screening methods, which may have affected the accuracy of the reported incidence of cCMV infection and HL risk. Second, the incidence of HL in relation to cCMV infection was affected by country, which was possibly due to the variations in cCMV prevalence and presentation. Third, a sex difference in the prevalence of HL may exist due to infection with other viruses. Fourth, the study quality may have affected the reported risk of HL due to the accuracy of intrinsic relationships. Lastly, the different number of studies included in each subset may have been correlated with statistical power, and thus summary results may have varied.This study had certain limitations. First, the ascertainment of cCMV infection rate in each study was inconsistent, which may have introduced confounders to the representative study cohort. Second, recall and selection biases are inevitable in retrospective studies. Third, the majority of the results were calculated with crude data, and numerous factors were not adjusted for correlation with HL risk. Fourth, the substantial heterogeneity observed could not be fully interpreted due to the lack of several important factors. Finally, publication bias and the availability of individual data sets are inherent limitations of all study-level meta-analyses.In conclusion, cCMV infection increased the risk of HL. Furthermore, in this meta-analysis, study publication year, gender, and study quality affected the apparent risk of developing HL. Further studies should be conducted to clarify the associations between cCMV infection and different subtypes of HL, and to assess the symptoms, diagnosis, and treatments of HL related to cCMV.PHL and GQD were involved in the literature search, study design, data collection, data analysis, data interpretation, and preparation of the manuscript. JDH, WYL, JT, JZ, and YMZ conducted the data collection and analysis, and critically revised the manuscript. All authors read and approved the final manuscript.Conceptualization: Pei-Hui Liu, Guo-Qing Dong.Data curation: Pei-Hui Liu, Jin-Dou Hao.Formal analysis: Pei-Hui Liu.Investigation: Jin-Dou Hao, Wei-Yan Li, Jia Tian, Jie Zhao, Yong-Mei Zeng.Methodology: Wei-Yan Li, Jia Tian, Jie Zhao, Yong-Mei Zeng.Software: Guo-Qing Dong.Supervision: Guo-Qing Dong.Writing – original draft: Pei-Hui Liu.Writing – review & editing: Guo-Qing Dong.


Emerging evidence has indicated that interleukin-8 (IL-8) gene-251A/T polymorphism may affect individual susceptibility to sepsis. However, the results of published studies are inconclusive. The aim of this meta-analysis was to elucidate the association between this polymorphism and the risk and mortality of sepsis.Relevant publications were searched from PubMed, EmBase, and Web of Science databases up to January 31, 2021, with studies only in English. The reference lists of the retrieved studies were investigated as well. Pooled odds ratio (OR) with 95% confidence interval (CI) was calculated to figure out the relationship between IL-8-251 A/T polymorphisms and the risk and mortality of sepsis. All of the data were analyzed with Stata 16.0.The results of this meta-analysis will be submitted to a peer-reviewed journal for publication.This meta-analysis will summarize the relationship between IL-8-251 A/T polymorphism and the risk and mortality of sepsis. The causes of sepsis include severe infections of lung, abdomen, blood, and urethra.–6 Among them, pulmonary infection accounts for about 64% of all cases of septicemia. Multiple organ dysfunction syndrome is the most common and serious complication secondary to sepsis, and it is one of the main factors of sepsis death in the world.,9 The mortality rate of hospitalized patients with sepsis is 25% to 30%. Early identification could improve the prognosis of sepsis.,12 Therefore, the treatment of patients with sepsis mainly depends on early identification and timely treatment.Sepsis is a life-threatening organ disorder in which the host fails to control severe infection. The host immune system generates a series of substances such as cytokines in response to infection or injury. Interleukin (IL)-8 is a pro-inflammatory cytokine that is involved in the inflammatory reaction at the early stage of sepsis. Inflammation is one of the most important clinical manifestations of sepsis.–16 During inflammation, mononuclear macrophages secrete IL-8 from the blood in tissues. The upregulation of IL-8 in vitro indicates the deterioration of the disease and the higher tendency to death.,19 In addition, it has been reported that IL-8 is associated with the progression of sepsis.,21 IL-8 blocking therapy is beneficial to the prognosis of septicemia by blocking systemic inflammatory response.The change of immune function is considered as a key factor in the pathogenesis of sepsis.–27 However, the results were conflicting. Thus, this study was aimed to investigate the association between the IL-8-251 A/T polymorphism and the risk and mortality of sepsis by meta-analysis.As the most common genetic variation, single nucleotide polymorphism (SNP) has attracted more and more attentions in the research on sepsis. According to previous studies, it has been obvious that single nucleotide polymorphism can predict the risk and prognosis of sepsis. It was reported that a functional SNP, -251A/T, in the promoter region of IL-8 gene can influence the expression of IL-8. Several recent studies have been carried out to explore the correlation between the SNP of IL-8–251 A/T (rs4073) polymorphism and sepsis susceptibility.22.1 on the basis of reports.The protocol of this review was registered in OSF (OSF registration number: DOI 10.17605/OSF.IO/EPR3Y), and followed the statement guidelines of preferred reporting items for systematic reviews and meta-analyses protocol2.2The publications fulfilling the following criteria were included: an original study evaluating the association between IL-8-251 A/T polymorphism and the risk and/or mortality of sepsis; objects in each study were from the same epoch; including a case group of sepsis; including a control group; including precise sample size of IL-8-251 A/T polymorphism of case and control groups that could be directly extracted or calculated based on the information available.2.3The exclusion criteria are as follows: repetition of the published studies; a meta-analysis or a review; study with insufficient or incorrect data.2.4Two investigators independently performed a systematically computerized search for English studies through PubMed, EmBase, and Web of Science databases up to January 31, 2021. The keywords for searching were the combination of “IL-8, interleukin-8, polymorphism, sepsis, septicemia, and septic shock.” Meanwhile, references of relevant literature reviews were screened to identify potentially relevant publications. The search strategy for PubMed is illustrated in Table 2.52.5.1The 2 reviewers complete the screening process independently, and any differences are decided by a third reviewer. The screening process of the article includes reading the title, the abstract, and the full text, so as to determine whether it meets the inclusion criteria. The researchers record the reasons to exclude each study in light of the preferred reporting items for systematic reviews and meta-analysis guidelines and report the screening results. The flowchart is demonstrated in Figure 2.5.2P value for Hardy–Weinberg equilibrium (HWE) of controls. In some studies, the risk and mortality of sepsis are discussed. In this case, the information was collected.All data were extracted by 2 independent investigators from included studies. Divergence was solved after discussion on every item. The following information was extracted from studies: first author, year of publication, country of the study and features of case and control groups such as ethnicity, age group, type of case and controls, genotype frequencies, genotyping method, and 2.5.3 Available data were extracted by 2 authors independently. Disagreements were dealt with by a third reviewer. The NOS values arrange from 0 to 9. Studies with the score of 6 are considered to be of high quality.According to Newcastle-Ottawa Scale (NOS) by 2 researchers, the quality of included studies was evaluated.2.5.4The reason for the loss of data in the period of data screening and extraction is identified here. We would attempt to contact the authors if the data of potential studies are insufficient, missing, or vague. These studies would be excluded only if the data are not available through the method described above.2.5.5P < .05 was seen as significant disequilibrium. Odds ratios (ORs) and the 95% confidence intervals (95% CIs) were calculated to evaluate the association between IL-8-251 A/T polymorphism and the risk or mortality of sepsis. The pooled ORs were executed for homozygote comparison, dominant and recessive models, allele comparison and heterozygote comparison. The heterogeneity was calculated by performing the χ2-based I2 test and the Q test. The fixed-effect model (the Mantel-Haenszel method) was chosen when the I2 value is <50%. Although the I2 is >50%, a random-effects model (DerSimonian and Laird method) was adopted. All of the statistical analyses were conducted by the STATA 16.0 , and the P values were 2-sided.2.5.6. Subgroup analysisThe HWE for control subjects of each studies was evaluated by conducting a chi-square test, and In the analysis on sepsis risk, subgroup analyses based on age group, ethnicity, restricted healthy controls were performed. Subgroup analysis on age and ethnicity in the mortality analysis was also made.2.5.6The eligible study was sequentially removed to perform the sensitivity analysis.2.5.7P < .05.,32Publication bias was assessed by Begg rank correlation and Egger linear regression. The publication bias was regarded as statistically significance when 2.5.8The content of this article does not involve moral approval or ethical review and would be presented in print or at relevant conferences.3 Studies have revealed that the promoter of IL-8 gene-251 A/T allele can upregulate the expression of IL-8 through transcriptional regulation. Therefore, it plays an important role in the pathogenesis and progression of sepsisIL-8 belongs to the COX2C subfamily of inflammatory mediators and participates in the regulation of inflammatory acute phase.–27 Because of the controversial findings, a meta-analysis is necessary to bring some new insights into this topic. This study has the largest sample so far to address this issue.The association between IL-8-251 A/T polymorphism and the risk or mortality of sepsis has been widely investigated.This study has the following shortcomings. First, due to a change in the definition of sepsis, the selected study is unlikely to have the same definition, as our analysis includes studies over a longer period of time. Second, most of the subjects of the study are whites, and more researches are needed to further study other races. Sepsis is a complex disease, and its pathogenic factors include genetic and environmental factors. The results of this study did not adjust other confounding factors, so the interpretation of the results should be cautious. In spite of this, this study still ensures the truthfulness and reliability of the research results from the following points. On the one hand, this paper includes a large number of cases and controls from different studies, which significantly increases the testing efficiency of statistics. On the other hand, for the same population source or repeatedly published literature, only the larger or recent data results are included in the study to ensure that there is no obvious selection bias.In summary, this meta-analysis will summarize the relationship between the IL-8-251 A/T polymorphism and the risk and mortality of sepsis. However, considering the limitations of this study, better design and larger sample size are needed to confirm this conclusion.Data curation: Shiqiao Zhao and Junzuo Gong.Formal analysis: Junzuo Gong.Methodology: Junzuo Gong.Project administration: Shu Luo.Supervision: Songlin Yin.Validation: Xiaofeng Li and Tianyi Mou.Visualization and software: Shuangquan Zhao.Writing – original draft: Shiqiao Zhao, Junzuo Gong and Shu Luo.Writing – review & editing: Shiqiao Zhao, Junzuo Gong and Shu Luo.Conceptualization: Shu Luo, Shiqiao Zhao.Funding acquisition: Shu Luo.Project administration: Shu Luo, Shiqiao Zhao.Writing – original draft: Shu Luo, Shiqiao Zhao, Junzuo Gong.Writing – review & editing: Shu Luo, Shiqiao Zhao, Junzuo Gong.Data curation: Shiqiao Zhao.Investigation: Junzuo Gong.Resources: Songlin Yin.Software: Songlin Yin.Supervision: Songlin Yin.Validation: Xiaofeng Li.Visualization: Shuangquan Zhao, Tianyi Mou.


Whether overweight increases the risk of postoperative atrial fibrillation (POAF) is unclear, and whether adiposity independently contributes to POAF has not been comprehensively studied. Thus, we conducted a meta-analysis to clarify the strength and shape of the exposure-effect relationship between adiposity and POAF.The PubMed, Cochrane Library, and EMBASE databases were searched for revelant studies , cohort studies, and nest-case control studies) reporting data regarding the relationship between adiposity and the risk of POAF.P < 0.001), but not being underweight  or being overweight  was associated with an increased risk of POAF. In the exposure-effect analysis (BMI) was 1.09  for the risk of POAF. There was a significant linear relationship between BMI and POAF (Pnonlinearity = 0.44); the curve was flat and began to rise steeply at a BMI of approximately 30. Notably, BMI levels below 30 (overweight) were not associated with a higher risk of POAF. Additionally, waist obesity or visceral adiposity index was associated with the risk of POAF.Thirty-five publications involving 33,271 cases/141,442 patients were included. Analysis of categorical variables showed that obesity (RR: 1.39, 95% CI [1.21–1.61]; Based on the current evidence, our findings showed that high body mass index or abdominal adiposity was independently associated with an increased risk of POAF, while underweight or overweight might not significantly increase the POAF risk. The prevalence of overweight and obesity has rapidly increased in recent decades in both developing and developed counties . This in2) and POAF in patients undergoing cardiac surgery, whether being overweight (BMI of 25–29.9 kg/m2) increases the risk remains unclear as some studies found a positive association  is among the most common complications arising from cardiac surgery, affecting between 20% and 40% of patients undergoing cardiac operation , and is ociation , while oociation . Severalociation . Furtherociation . Second,ociation , BMI wasociation  or literociation . Third, ociation . ClarifyThus, we conducted a dose–response meta-analysis to quantify the association among body mass index, abdominal adiposity and the incidence of POAF.P < 0.05 was considered statistically significant. The full details of the literature search strategy, study selection criteria, quality assessment, and statistical analysis are reported in the This study was performed according to Preferred Reporting Items for Systematic reviews and Meta-Analyses Statement (PRISMA) guidelines  Table S. All stuAs shown in The overall reporting quality of the included studies was acceptable. All included studies obtained an NOS ≥ 6 points .2 = 29%; P = 0.14) or overweight  was not associated with an increased risk of POAF. In contrast, obesity significantly increased the risk of POAF . Interestingly, the risk of POAF seemed to gradually increase with the obesity stage .Fourteen studies grouped the BMI categories according to the World Health Organization criteria; however, only six articles (seven cohorts)  reported2 = 82%)  to 1.10 . Additionally, the pooled results were not significantly changed when omitting one study at a time (P = 0.44) in the relationship between BMI and POAF (Thirty-three (34 cohorts) studies  involvin2 = 82%)  was fount a time  . There and POAF . The nonand POAF . Table SP = 0.001; I2 = 82%), 1.34 , and 1.13 , respectively (nonlinearity = 0.12); notably, the risk of POAF significantly increased at a BMI of 30 and rose more steeply at higher BMI levels. However, the curve was somewhat steep in the combined cardiac surgery group .We further performed a subgroup analysis by type of cardiac operation. Nineteen articles (20 cohorts) reported the association in coronary artery bypass graft (CABG), three articles reported the association in valve surgery, and eleven articles reported the association in combined types of cardiac surgery. The summary RRs for a 5-unit increment in BMI in the CABG group, valve surgery group, and combined cardiac surgery group were 1.07  rather than BMI in a younger population   . A combiFinally, our findings have important clinical implications for the prevention of POAF. Since previous meta-analysis analyzed BMI but did not include other measures of fat in relation to the risk of POAF, and did not assess the dose–response relationship between BMI and POAF in as great detail as the present analysis. In addition, our results show that obesity was associated with an increased risk of POAF in studies from Europe, North America, and Oceania, suggesting that the prevention of obesity is essential across populations. The current analysis suggests that both general and abdominal adiposity (waist circumference) measures are related to an increased risk of POAF and that being relatively slim, as assessed by BMI and other adiposity measures, may confer the lowest risk of POAF.Our meta-analysis has several strengths. First, all included studies were designed as cohort studies, largely reducing the possibility of selection bias. Second, this meta-analysis included a large number of cohort studies (33 studies) with BMI reported as either a categorical or continuous variable, providing strong statistical power to detect moderate associations. The detailed exposure–effect analyses clarified the shape of the exposure–effect relationship. Third, the positive association between BMI and POAF persisted in different subgroups  and after adjusting for confounding factors, confirming the robustness of our findings.2 =82%) was observed across the included studies, which might have been derived from between-study differences, such as differences in study design, basic patient characteristics, and analytical strategies. Third, we did not analyze the long-term POAF incidence since most studies only reported the incidence of POAF during the length of hospitalization. However, most POAF has a peak incidence between days 2 and 4 after surgery (Our study inevitably has several limitations. First, this meta-analysis included observational studies, and bias was not entirely avoided. Measured and unmeasured confounding variables might have influenced our results. However, this limitation cannot be mitigated by the large number of studies and adjustments for coexistent confounding factors in all included studies. Second, significant heterogeneity (I surgery , especia surgery .Based on the current evidence, Our results showed that high body mass index or abdominal adiposity was independently associated with an increased risk of POAF, while being underweight or overweight might not significantly increase the POAF risk.10.7717/peerj.11855/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.11855/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.11855/supp-3Supplemental Information 3Click here for additional data file.