Several studies have assessed the relationship between type 2 diabetes (T2D) and tooth loss; however, results have been inconsistent. Therefore, the present systematic review and meta-analysis of observational studies was designed to examine the association between T2D and tooth loss.2 index. Measure of effect and 95% confidence interval (CI) were extracted from each study. The results of the study were analyzed using the random effects model.This systematic review and meta-analysis was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guideline. We searched all the relevant studies in international databases of Scopus, PubMed, ProQuest, Web of Science, Cochrane Library, and Google scholar search engine until February 2022. The heterogeneity of the studies was calculated using the Ip < 0.001), and OR adjusted was 1.20 , respectively. Subgroup analysis based on study design for adjusted OR indicated that in the cohort study , in the cross-sectional study , and in the case-control study  there was a significant association between T2D and tooth loss. Other subgroups analyses showed consistent results and no publication bias existed.In the present study, 22 eligible studies were included. Meta-analysis of unadjusted and adjusted results showed that T2D significantly increased the risk of tooth loss, and Odds Ratio (OR) unadjusted was 1.87 (95% CI: 1.62–2.13, The findings suggest that T2D is associated with increased risk of tooth loss. This conclusion may provide useful evidence for correlated clinical researches.The online version contains supplementary material available at 10.1186/s12902-022-01012-8. Diabetes mellitus is a chronic metabolic disease characterized by hyperglycemia caused by defects in insulin secretion, insulin function, or both. It is divided into two types: type 1 and type 2 diabetes . The estOral health is a very important factor in increasing the quality of life despite increasing attention and dental care, various risk factors such as: age, socioeconomic status , 18, 21,This systematic review and meta-analysis was reported in according to referred reporting items for systematic reviews and meta-analyses (PRISMA) guideline . This reLiterature search were conducted for English evidences in PubMed/Medline, Scopus, ProQuest and Web of Sciences up to February 2022. The following keywords were used: ‘Tooth’ OR ‘teeth’ AND ‘Loss’ AND ‘diabet*’ OR ‘Prediabet*’ OR ‘Glucose Intolerance’. No restriction for publication date was applied. Full search strategies for all sources are listed in Appendix Each title and abstract were reviewed to identify relevant studies by two individual researchers (M.GH and MM). The full texts of publications were reviewed if the abstract suggested that diabetics had been examined in relation to tooth loss. Studies met the inclusion criteria if: a) had observational design, b) reported odds ratio (OR), prevalence ratio (PR), risk ratio (RR) or hazard ratio (HR) with 95% confidence interval (95% CI) for the category of diabetic or provided number of tooth loss subjects and without tooth loss subjects in each category of diabetic or without diabetic to calculate OR and 95% CI. Studies were excluded if: a) had randomized clinical trial (RCT) design, b) insufficient data studies, animal experiments, letters, case reports and review b) reporting mean (SD), correlation, or regression coefficient as the effect size, and c) were conducted on the same population.The following data were extracted from each study: first author’s last name, date of publication, country, study design, duration of follow-up for cohort studies, sex, age, definition of diabetics, type of outcome and its definition, number of total subjects and cases in each category of diabetics, OR, RR, and HR (95% CI) in each category of exposure diabetics and adjusted variables.Risk of bias of included observational studies were assessed using the Newcastle-Ottawa Scale (NOS) , 35. NOSStata software version 16  was used to conduct meta-analysis. The ORs (95% CI) were used to calculate summary effect size. Pooled odds ratios were summarized using the Der Simonian and Laird method for random effects models. The reported HRs or RRs and PRs by cohort studies were considered the same as OR. For studies that did not report ORs, HRs, or PRs, we calculated ORs and 95% CIs using relevant formula: OR = (odds of being tooth loss if diabetics / odds of being tooth loss if not diabetics) and 95% CI = exp. [ln (OR) ± 1.96 SE (ln (OR))] . HeterogIn the first step of our search, a total of 3121 articles were retrieved using PubMed/Medline, Scopus, Web of Science, ProQuest, and Cochrane library, Google and Google Scholar. Of these articles, 494 articles were removed due to duplication and other 2175 articles were excluded after their title and abstract evaluation. The remaining 121 primary studies were considered for further eligibility assessment through careful reading of their full texts. After full-text evaluation, a further 99 articles were excluded due to inability to calculate effect sizes, study settings, and outcome interest  were not reported, therefore, we calculated ORs (95% CI) based on relevant formula. In addition, 16 studies have considered the any tooth loss for calculation of the effect sizes, and in six studies tooth loss at least 5 and more considered for calculation of the effect sizes. There were 677,532 participants in the included studies, with the number of participants per study ranging from 60 to 379,021. The characteristics of the included studies are summarized in Table % CI werep < 0.001), and OR adjusted was 1.20 , respectively. The forest plot is displayed in Fig. In the overall summary, in unadjusted and adjusted results indicated that T2D significantly increased the risk of tooth loss, and OR unadjusted was 1.87 , but in the case-control study  and cohort study  T2D not significantly was associated with tooth loss. Also, Subgroup analysis based on study design for adjusted OR indicated that in the cohort study , in the cross-sectional study , and in the case-control study  there was a significant association between T2D and tooth loss , in South America , and in Europe , but in Asia, T2D was not significantly associated with tooth loss . Also, Subgroup analysis based on the continent for adjusted OR indicated that in North America , in South America , and in Asia  there was a significant association between T2D and tooth loss , an OR of 1.70 with a 95% CI (1.31–2.09) for those with moderate quality and an OR of 2.32 at a 95% CI (1.34–3.29) for those with high quality. Also, subgroup analysis based on quality of studies for adjusted OR indicated that in the low quality , and high quality  there was a significant association between T2D and tooth loss, but in moderate quality, T2D was not significantly associated with tooth loss  , and any tooth loss OR: 1.77 at a 95% CI (1.50–2.04) Also, subgroup analysis based on the number of tooth loss for adjusted OR indicated that in the category of tooth loss at least 5 teeth and more , and for any tooth loss category  there was a significant association between T2D and tooth loss  and vice versa . The findings of this study are consistent with previous evidence that there is a significant association between T2D and tooth loss.Previous observational studies investigating the association between T2D and tooth loss have reported conflicting results. In a cohort study of 15,113 participants, Greenblatt et al.  showed tThe relationship between diabetes and oral diseases such as tooth loss, gingivitis, periodontal disease, and soft tissue damage has been investigated in various studies , 17. PerTooth loss as a proxy for severe periodontitis might play an epidemiologically confusing role in the evaluation of a systemic disease hypothesis , 55. HowBetween-study heterogeneity is common in meta-analyses, and different characteristics between studies such as year of publication, study location, diagnostic testing, design, and quality of original articles may be sources of between-study heterogeneity , 57. OurAssessment of risk of bias is a key step in conducting SRs and informs many other steps and decisions within the review. It also plays an important role in the final assessment of the strength of the evidence . Based oThe current systematic reviews and meta-analyses have some strengths and limitations. The study advantages; firstly, our study is the first comprehensive meta-analysis about the association between T2D and tooth loss. Second, in the current study, there was no publication bias between studies, and we performed several subgroup analyses. Third, in the diagnosis of diabetes, the self-report method and the blood sample diagnosis method were evaluated, and the results were reported separately.There are limitations in our present meta-analysis. First, our study only included articles published in English and the limited number of studies included in this study may lead to false or unstable results. Second, most of the studies included were cross-sectional, so it is difficult to determine the causal relationship between T2D and tooth loss. The results of this study should be interpreted with caution.In conclusion, the results of our study showed a positive association between T2D and tooth loss in cross-sectional studies. No significant association between T2D and tooth loss was found in cohort studies. Undoubtedly, large-scale prospective studies are needed to validate the current results in the future.Additional file 1.


RR) showed teratogens the most likely microcephaly-associated risk factor , while the statistical significance of the ZIKV–microcephaly association was marginal . Other congenital infections showed strong but variable associations with microcephaly . Microcephaly cases were associated with impoverished socioeconomic settings, but this association was statistically non-significant . The marginal ZIKV–microcephaly association and statistical significance of the competing hypotheses suggest maternal ZIKV infection might not be a cause of microcephaly alone.Congenital microcephaly is caused by a multitude of drivers affecting maternal–fetal health during pregnancy. It is a rare outcome in high-income industrial countries where microcephaly rates are in the range of 0.3–0.9 per 1000 newborns. Prevalence of microcephaly varies considerably across developing countries and can go as high as 58 cases per 1000 live births in pregnancies exposed to infection by Zika virus (ZIKV). Not only ZIKV-infected pregnancies, but other drivers can modulate the occurrence and severity of this outcome. Here, we sought to test the ZIKV–microcephaly association vs. competing hypotheses using a meta-analysis with 8341 microcephaly cases pooled from 10,250,994 newborns in the Americas, Africa, and Asia. Analysis of risk ratios ( Microcephaly is a congenital anomaly of multifactorial origin, possibly related to genetic and chromosomal changes or environmental exposures, including infectious diseases—toxoplasmosis, rubella, cytomegalovirus, and herpes (TORCH)—detrimental substances , and severe malnutrition ,2. The aFlaviviridae, Genus Flavivirus) [The risk of microcephaly was not much relevant in the Brazilian epidemiological scenario until recently . Accordivivirus) ,6. ZIKV vivirus) . Previouvivirus) . Notwithvivirus) .t = 18.36; df = 3, p-value = 0.0004). In the Information System for Reporting Diseases (SINAN), the number of reported cases of ZIKV infection in pregnant women in Brazil was 281,464 in 2016, 32,684 in 2017, 19,551 in 2018, 30,500 in 2019, 20,867 in 2020, and 18,680 in 2021 [The association between maternal ZIKV infection during pregnancy and a microcephaly case was primarily formulated based on spatio-temporal and clinical epidemiological studies . The hyp in 2021 ,13.The ZIKV–microcephaly association became disputed by competing hypotheses. One of the reasonings was that microcephaly annually occurred in Brazil with an average of 170 cases per year before the onset of the ZIKV outbreak in 2015 . The comThe research questions here were the following:Question 1: Is maternal ZIKV infection associated with the risk of microcephaly?Question 2: Can exposures other than ZIKV confer further risk to microcephaly?The research questions’ assumptions were: (1) microcephaly has a multifactorial etiology and (2) the risk of microcephaly increases when pregnant women are exposed to a multitude of associated factors. The study’s impact is to provide decision-makers with basic knowledge for the adoption of preventive measures by public health agencies in Brazil. Finally, this study aims to analyze risk factors associated with microcephaly and assess the ZIKV–microcephaly association vs. competing hypotheses in a specific hypothesis-testing framework.A literature search of the PubMed, Scopus, and Web of Science databases was carried out from the earliest database date to December 2021. The retrieval method was based on the Medical Subject Headings (MeSH) terms “microcephaly” and “risk factors” plus free words. The search strategy is displayed in The inclusion criteria were: (1) mothers and their newborns; (2) the case group was exposed to ZIKV, other congenital infections, teratogens, or poor socioeconomic background, and the control group was non-exposed to these risk factors; (3) outcome was microcephaly; and (4) observational studies. The exclusion criteria were: (1) animal or in vitro experiments; (2) studies having low samples sizes; and (3) grey literature.The data extracted from the reports and included in the syntheses  were tabulated according to the information needed for the analytical process and extracted using the Rayyan tool . Among tTwo reviewers  working independently screened each record and each report retrieved to decide whether a study met the eligibility of this review.The outcome analyzed was microcephaly and its association with covariates as risk factors. Risk factors considered were: (1) socioeconomic background; (2) teratogen; (3) TORCH; and (4) ZIKV. No other outcomes or variables were analyzed.The quality of the selected observational studies was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool ,19,20 wiR Software v. 4.0.4 with the meta package v. 5.5 [RR) with 95% confidence intervals (95%-CI) in the meta-analysis. A pooled estimate of the risk of microcephaly per risk factors was computed using a random effects model [metabin function [Data were imported and analyzed in e v. 5.5 . The rists model  with thefunction  and the function .Q and I2 statistics. The random effects model was used if heterogeneity was high, as indicated by a p-value < 0.1 and I2 ≥ 50%. A common effect model was utilized instead when a low heterogeneity was identified by a p-value ≥ 0.1 and I2 < 50%.Statistical heterogeneity between the studies was assessed using the The research found 1424 studies from the three databases PubMed, Scopus, and Web of Science using “microcephaly” and “risk factors” as MeSH terms in the search strategy . After tn) Case Group—presented with microcephaly and exposed to risk factor; (2) Newborns Total (N) Case Group—exposed to risk factor; (3) Microcephaly (n) Control Group—presented with microcephaly and unexposed to risk factor, and (4) Newborns Total (N) Control Group—unexposed to risk factor. These data were utilized in the meta-analysis for estimating risk ratio (RR) of microcephaly per risk factor. Specific information on data extracted from each study was detailed in the table’s footnotes (ootnotes .RR) and CI-95% of microcephaly between exposed  and non-exposed (control) groups of newborns per risk factor  socioeconomic RR = 2.75 , (2) TORCH RR = 15.24 , and (2) ZIKV RR = 2.12 .High statistical heterogeneity was observed in the meta-analysis of socioeconomic, TORCH, and ZIKV risk factors A,C,D—theRR = 3.43 .Low statistical heterogeneity is shown in the meta-analysis of teratogen B, the coOur statistical results highlighted associations between risk factors and microcephaly. The quality of evidence was variable among risk factors. The most reliable analysis that with teratogen as a risk factor, followed by analysis of ZIKV, and then TORCH or Socioeconomic. Nevertheless, the effects from any risk factors considered here were reciprocally associated with microcephaly. Stronger or longer exposures to these factors can be linked to a higher or an increased risk of microcephaly. According to this view, the discussion follows with specific interpretations per risk factor.Aedes. Populations—vectors of dengue and other arboviral diseases [The northeast region of Brazil has the highest poverty rates in the country, with lower socioeconomic indices and poor environmental management . This undiseases . Povertydiseases . Socioecdiseases .To better understand the pathogenesis of microcephaly related to poverty, comprehensive large-scale cohort studies carried out in Brazil in 2010, previous to the arrival of ZIKV, were re-analyzed . These aImmunization rates against infectious diseases are generally high in the Brazilian population . HoweverIn Canada and China, maternal exposure to teratogens—alcohol and/or drug abuse—will likely induce fatal underdevelopment ,27. FromRR. Maternal infection during pregnancy was the strongest risk factor in the Canadian cohort study 1989–2012, with a 32-fold risk of microcephaly compared with no infection, whereas it was the second most important risk factor (after teratogen) in the Chinese birth cohort 2009–2017 [RR = 1.62) is lower than the risks from maternal infection by TORCH (RR = 4.29–31.17), as shown by [Meta-analysis of TORCH showed high heterogeneity and large 95% confidence interval of 009–2017 ,27. The 009–2017 ,27. A se009–2017 . The aut009–2017 . Althoug009–2017 , the strshown by ,27.RR = 15) indicates that maternal exposure to any of the TORCH agents  or others (hepatitis B virus) during pregnancy will likely result in a greater risk of microcephaly.One of the studies that increased variance in the analysis of TORCH was a population-based pooled cohort study of 2,338,580 pregnancies in the USA between 2000–2013 and 2011–2015 . In thisIt has long been hypothesized that congenital infections beyond TORCH can also contribute to microcephaly ,39. AbnoRR = 2.12), which means it was statistically significant by a very small margin (1%). This further indicates that ZIKV infection during pregnancy is not acting alone in the causation of microcephaly in newborns.Lastly, we compared studies assessing specific effects from ZIKV to microcephaly and obtained two contrasting situations: (1) ZIKV effect as an emerging arboviral disease in Brazil ,31, (2) Pooling different types of observational studies in epidemiology  can increase heterogeneity in the model estimates due to sampling variation. When heterogeneity was high, our interpretation relied on the random model estimates. Additionally, the use of observational studies for meta-analysis has been encouraged and the selected studies were carried out using standard methodologies .Other databases not included in our analyses, including Embase, have been expanding their coverage in the last years. Notwithstanding, the selected databases  can still cover the most comprehensive studies on the topic.Quality assessment using the GRADE tool is the standard recommendation by the Cochrane Library. The quality of evidence may depend on the type of study design. Randomized trials have higher quality of evidence than observational studies. Here observational studies were used—thus the overall quality of evidence is low. However, in respect to the nature of research questions, the meta-analysis here was the only approach possible.n = 6454 and newborns N = 5,893,238 in socioeconomic analysis, microcephaly n = 923 and newborns N = 1,989,069 in teratogen analysis, microcephaly n = 1731 and newborns N = 4,356,752 in TORCH analysis, and microcephaly n = 156 and newborns N = 1004 in ZIKV analysis.The recommended number of studies per meta-analysis is 10. Here, meta-analysis was carried out with 2–4 studies. However, the sample sizes analyzed were large: microcephaly Considering the first research question, we first conclude that maternal ZIKV infection is associated with the risk of microcephaly, but the statistical significance of this association was marginal. In addition, ZIKV infection showed association with microcephaly in Brazil, but not in Africa. Moreover, the ZIKV–microcephaly association in Brazil could have been modulated by other factors .In relation to the second research question, it is highly possible that exposures other than ZIKV confer further risk for microcephaly. Teratogenic factors, including maternal alcohol and/or drug abuse, are the most likely to increase the risk of microcephaly. TORCH showed strong but heterogenous effects on microcephaly, which indicates other modulating factors, such as socioeconomic background, underlying TORCH effects.It is finally concluded that the risk factors associated with microcephaly in newborns are more likely related to the additive contribution of competing hypotheses  than ZIKV alone.


Random-effects meta-analysis was used to generate summary estimates. Subgroup analysis and meta-regression models were used to address the issue of high heterogeneity. Two authors independently identified eligible articles, collected data, and performed a risk of bias analysis. Twelve studies were included in the meta-analysis , of which 7 were of “high” quality. The pooled prevalence of diabetic foot ulcers was 12.16% (95% CI: 5.91–20.23%). We found significant between-study heterogeneity  but no statistical evidence of publication bias (p = 0.8544). Subgroup meta-analysis found significant differences in foot ulcer prevalence by publication year and by the duration of diabetes. An increasing trend was observed during the last two decades, with the prevalence of diabetic foot ulcers being the highest in the latest period from 2011 to 2022 (19.54%) than in the early 2000 s (4.55%). This study suggests that the prevalence of diabetic foot ulcers in Pakistan is relatively high, with significant variation between provinces. Further study is required to identify ways for early detection, prevention, and treatment in the population.We aimed to determine the pooled prevalence of diabetic foot ulcers in Pakistan. MEDLINE (PubMed), Web of Science, Google scholars, and local databases were systematically searched for studies published up to August 10, 2022, on the prevalence of foot  A diabetic foot ulcer is a chronic consequence of diabetes characterized by lesions in the deep tissues. It causes neurological problems and peripheral vascular diseases in the lower extremities , 2. It pThe prevalence of diabetes and associated complications in Pakistan is steadily rising –9. AccorThe PRISMA Guidelines  were folFor this study, articles were included if they met the following criteria: (1) based on a population-based survey or hospital-based study published in English up to August 10, 2022; (2) participants must be Pakistan residents. The following articles were excluded if they were: (1) letters to the editor, reviews, case series, case studies, conference abstracts, qualitative studies, and intervention studies; (2) based on the Pakistani community living outside Pakistan; (3) did not report sufficient data; (4) were irrelevant to a diabetic foot ulcer, and (5) were based on duplicated information (data). Using a two-step procedure, the selection of articles was conducted. Two authors (S.A. and F.H.) separately examined the titles and abstracts of all identified articles. Second, the full texts of the pre-selected publications were independently evaluated based on the previously established inclusion criteria. When necessary, a third reviewer (A.A.) resolved conflicts.A prepiloted data collection form was used by two independent investigators (S.A. and A.A.) to collect data on the following variables: author first, publication year, survey year, study design, the geographical location where the study was performed, the average age of diabetic patients, total sample size, the proportion of men, the number of participants with foot ulcers, sampling strategy, and setting . Discrepancies and uncertainties were explored and resolved through cross-checking of the data.Two investigators (A.A. and F.H.) independently evaluated the risk of bias in the selected studies by adapting items from the JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data . DispariP value of 0.05 was considered statistically significant. For the statistical pooling of the prevalence of foot ulcers among diabetic patients, random effects (Der Simonian-Laird) models were used  and a forest plot. Heterogeneity was defined as I2 >50%  was used to conduct all analyses, and a ere used , 21. The I2 >50% , 23. Pub I2 >50% , 25. SubSubgroup meta-analyses were performed according to different extracted variables . To further explore heterogeneity, meta-regression analyses were performed to determine the association between the prevalence of foot ulcers and study characteristics. The covariates in the meta-regression considered were: year of publication, setting , sample size, year of investigation, mean age of diabetic patients, methodological quality, and gender . To examine the impact of individual studies on the pooled prevalence estimates, sensitivity analyses were carried out by excluding each study. The agreement between the investigators was evaluated by the Kappa statistic .n = 432), 197 studies were found ineligible after their titles and abstracts were thoroughly screened. The remaining 28 studies were subjected to a full-text evaluation to determine their eligibility; they were eliminated because they did not match the inclusion criteria. In the end, 12 papers were included in the analysis. The authors' inter-rater agreement for study inclusion was very good .p = 0.001).2 value  indicated high between-study heterogeneity across the findings of different studies. The funnel plot  and Egger's test  suggested no publication bias in the meta-analysis. The sensitivity analysis showed that the pooled prevalence of diabetic foot ulcers varied from 9.67% (95% CI: 5.23–15.28%) to 13.44% (95% CI: 6.68–22.06%) by excluding each study individually. The analysis found that no single study substantially affected the pooled prevalence of foot ulcers in diabetic patients.The pooled prevalence and subgroup meta-analysis for diabetic foot ulcers are summarized in nel plot , Begg's n = 7], followed by Azad Kashmir and 6.92% , and was lowest in Sindh . When stratified by publication year, the pooled prevalence for diabetic foot ulcers estimates were 4.55%  from 1999 to 2010 and 19.54%  during 2011–2022. The highest prevalence of diabetic foot ulcers has been detected in recent years. When stratified by gender, the pooled prevalence of foot ulcers in male diabetic patients  was higher than in female diabetic patients .To analyze the substantial sources of statistical heterogeneity, subgroup meta-analyses were conducted using age group, gender, geographical location, and time period. The subgroup meta-analysis based on geographical location showed that the prevalence of foot ulcers in diabetic patients was highest in studies conducted in Punjab province [16.13% (95% CI: 5.57–30.79%); p = 0.0007; R2 = 49.07%), as well as the year of investigation . The findings also showed that neither the percentage of men in the sample, the sample size, nor the methodological quality of the studies was significantly associated with the prevalence of foot ulcers in diabetic patients.The meta-regression analysis  revealedOver the last few decades, diabetes and its associated consequences have become more widespread. Diabetes-related hospitalizations are disproportionately impacted by foot ulcers, which account for half of the hospitalizations . The devMeta-analysis estimates were higher than those from Iran  and SaudAccording to our data, male diabetic patients 12.04%) had more significant diabetic foot ulcers than female diabetic patients (7.29%). Males' harder physical labor could be one explanation for this gender discrepancy . The fin2.04% hadThe study has several benefits and drawbacks. We deployed exhaustive search procedures, rigorous selection criteria, and a dual review procedure. We could generate reliable prevalence estimates since the included studies provided sufficient data. Our analysis identified no evidence of publication bias, indicating that we did not overlook any papers that could have altered the results of our meta-analysis. Furthermore, due to their superior methodological quality, all included studies exhibited a low or moderate risk of bias. According to the meta-regression analysis, the methodological quality of the studies did not affect the assessment of the overall prevalence.There are some limitations to this study. The meta-analysis revealed significant variation in the estimated pooled prevalence, as expected. To address the issue of substantial heterogeneity, subgroup analysis and meta-regression with components added to the univariate model were used. The outcomes of this study should be regarded with caution due to the significant degree of heterogeneity. Second, we could not discover any research article published on Khyber Pakhtunkhwa or Baluchistan. As a result, the findings should be regarded with caution. Thirdly, the aim of the study was to estimate the foot ulcers prevalence in diabetic patients which is the reason it excluded the studies which did not provide prevalence estimates. Fourthly, in the subgroup meta-analyses and meta-regression models, the choice of important covariates  was limited, on the basis of the restricted availability of primary data in the eligible studies. Finally, because the number of papers included in this review is limited, a univariate meta-regression analysis rather than a multivariable meta-regression model is employed to assess the importance of each covariate.This study concludes with pooled estimates of foot ulcers among diabetic patients in Pakistan, indicating that diabetic foot is a substantial public health issue in Pakistan. The frequency of foot ulcers in the general population has increased over the past three decades, and this trend may continue in the future. Foot ulcer among diabetic patients is on the rise in Pakistan. Therefore, diabetic foot clinical centers are required for foot ulcer screening, identification, and management in urban as well as rural areas.The original contributions presented in the study are included in the article/All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.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.


Early hospital readmission (EHR) within 30 days after kidney transplantation is a significant quality indicator of transplant centers and patient care. This meta-analysis aims to evaluate the incidence, predictors, and outcomes of EHR after kidney transplantation.We comprehensively searched the databases, including PubMed, Cochrane CENTRAL, and Embase, from inception until December 2021 to identify studies that assessed incidence, risk factors, and outcome of EHR. The outcomes included death-censored graft failure and mortality. Data from each study were combined using the random effect to calculate the pooled incidence, mean difference (MD), odds ratio (OR), and hazard ratio (HR) with 95% confidence interval (CI).A total of 17 studies were included. The pooled EHR incidence after kidney transplant was 24.4% (95% CI 21.7–27.3). Meta-analysis showed that recipient characteristics, including older recipient age , Black race , diabetes , and longer dialysis duration , donor characteristics, including older donor age , and transplant characteristics, including delayed graft function  and longer length of hospital stay during transplantation , were significantly associated with the increased risk of EHR. EHR was significantly associated with the increased risk of death-censored graft failure  and mortality  within the first year after transplantation.Almost one-fourth of kidney transplant recipients had EHR within 30 days after transplant, and they had worse post-transplant outcomes. Several risk factors for EHR were identified. This calls for future research to develop and implement for management strategies to reduce EHR in high-risk patients. Kidney transplantation is the best renal replacement therapy option for end-stage kidney disease patients. Kidney transplant recipients have a higher long-term survival and quality of life than those who remains on dialysis , 2. DespEarly hospital readmission (EHR), defined as any hospitalization within 30 days of discharge following kidney transplantation, is a significant quality indicator of transplant centers and patient care . EHR is The objective of this meta-analysis was to determine the incidence of EHR, identify the risks factors for EHR, and assess the impact of EHR on post-transplant outcomes in kidney transplant recipients.This article has been reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines .We conducted a systematic literature search for relevant articles in the databases, including Pubmed, Embase, and Cochrane CENTRAL, using a comprehensive search strategy from inception until December 20th, 2021. The combination of the following MeSH keywords was used: “renal transplant,” “kidney transplant,” “readmission,” “early hospital readmission,” “30-day readmission,” “incidence,” “rate,” “predictor,” “risk factors,” and “association.” The detailed search strategy is presented in We included studies that reported the incidence, predictors, or outcomes of EHR after kidney transplantation. EHR was defined as 30-day readmission to any institution, due to any cause, after kidney transplantation. We excluded studies with  readmissThe potential of sample dependence arises when multiple papers included in the review report findings from analyses on the same cohort of patients. When the studies had overlapping periods, the potential for sample dependence was minimized by the selection of studies with the longest period of data collection as the representative study for that cohort, for each variable. However, when two or more studies had the same period of data collection, the study with higher methodological quality was selected as the representative study.Two independent researchers (KI and AI) extracted data from the eligible articles. The following information was extracted: name of the first author, year of publication, study design, country of origin, sample size, subject demographics, comorbidities, and incidence of EHR. Data regarding the risk factors for EHR included the following recipient characteristics: age, gender, black race, body mass index (BMI), diabetes, prior dialysis, and dialysis duration; donor characteristics: age, donor type, and expanded donor criteria; and transplant characteristics: delayed graft function (DGF) and length of hospital stay during transplantation. The outcomes of EHR included death-censored graft failure and mortality within 1 year after kidney transplant. Raw data and adjusted estimates were extracted.For studies that provided medians and ranges instead of means and standard deviations or provided only means in the absence of standard deviations, the means and/or standard deviations were calculated using the formula described by Hozo et al. . Some stp-value < 0.05 was considered significant in all cases. We examined the correlation between the risk factors and EHR; risk factors reported in 3 or more studies were statistically analyzed. When available, risk factors based on multivariate analysis were also collected. To rule out the possibility of any single study disproportionately affecting the results, a leave-one-out sensitivity analysis was carried out by removing one study at a time. The quality appraisal of the included studies was performed by using the Newcastle–Ottawa Quality Assessment Scale  and MedCalc v 20.027 to perform all the analyses. A random-effects model was used to calculate the Mantel Haenszel odds ratios (OR) for dichotomous variables and mean difference (MD) for continuous variables. Adjusted estimates were reported using inverse variance adjusted Hazard ratios (aHR). All estimates were reported with a confidence interval (CI) of 95% and a nt Scale . Each stThe initial search strategy identified a total of 700 potentially relevant articles. After excluding the duplicates, 408 articles were screened for relevance based on their titles and abstracts. Out of these, 52 full-text articles that aligned with the objective of the manuscript were reviewed. Ultimately, 17 studies were included in the final analysis, out of which twelve were cohort studies  and one was a case-control study –25. Suppp-values of Begg-Mazumdar's rank correlation test and Egger's regression test are presented in The methodological quality assessment of included studies  showed tI2 = 98.26%; A total of 16 studies reported the incidence of EHR after kidney transplantation in 26,285 out of total 87,124 transplant recipients. The pooled incidence of EHR in kidney transplant recipients was 24.4% [95% CI = 21.7–27.3 %; p = 0.0005; I2 = 97%), black race , diabetes , and longer dialysis duration  were significantly associated with increased EHR , body mass index , and prior dialysis   .p = 0.05; I2 = 89%) and longer dialysis duration  remained significantly associated with EHR   and expanded donor criteria  were not significantly associated with EHR  . Howeverwith EHR .p < 0.00001; I2 = 82%) and longer length of hospital stay during transplantation , were significantly associated with increased EHR  and longer length of hospital stay  and remained significantly associated with increased EHR  and expanded donor criteria  became significant predictors of EHR on performing leave-one-out sensitivity analysis.The results of leave-one-out sensitivity analysis and studies that caused a significant drop in heterogeneity are shown in p < 0.00001; I2 = 2%)   . EHR wasI2 = 0%) .In the current meta-analysis, we have summarized pertinent evidence on the incidence, risk factors, and outcomes of EHR in kidney transplantation. Significant recipient-related risk factors of EHR after kidney transplantation included age, gender, black race, BMI, diabetes, and a higher number of years on dialysis. Similarly, older donor age and deceased donor were significant donor-related predictors of EHR. Delayed graft function (DGF) and a longer length of hospital stay during transplantation were significant transplant characteristics that increased the odds of EHR. Moreover, EHR was significantly associated with incident death-censored graft failure and mortality within the first year of transplantation.Our study showed a pooled incidence of 30-day readmission of 24.4% [95% CI = 21.7–27.3 %). This is higher than the incidence of readmission previously reported in patients undergoing orthopedic procedures (5.4%), colectomy (14.7%), and pancreatic resection (19.1%) . Howeverp < 0.001). Dialysis treatment of 6–12, 12, and 12–24 months was associated with a 37, 55, and 68% greater risk for death-censored graft loss, respectively  compared to non-diabetics. Factors associated with readmissions included infections (9.4 vs. 7.7%), heart failure (6.0 vs. 3.1%), and chest pain/myocardial infarction (5.5 vs. 3.3%)  .DGF leads to an increased risk of EHR and short-term as well as long-term graft loss . DialysiOur systematic review suggests patients at high risk of EHR can be identified through relevant risk factors. Patients are likely to have more than one of the above-mentioned risk factors and, therefore, predictive models should be developed to identify patients at high risk of EHR at the time of discharge. It may provide the basis of a robust risk predictive model given the number of studies included. Such patients could be selected in clinical trials to experiment with interventions to prevent early readmissions. A systematic review by Leppin et al. observed that tested interventions prevented 30-day readmissions in patients admitted to an inpatient ward for a minimum of 24 h for any medical or surgical reason. They reported that multidisciplinary strategies which increase patients' easy access to post-discharge care were the most successful . QualityThere are several limitations in our meta-analysis. First, most of the included articles were single-center observational studies, which limits cohort size and generalization of data. Most studies were retrospective in nature; therefore, the inherent confounding of the study type was inevitable. Second, some included articles defined EHR as readmission within 30 days from the date of the transplant procedure, while others measured EHR from the date of discharge after transplantation. Third, our study reported significant heterogeneity across various risk factors. Heterogeneity in our meta-analysis could be due to various factors that lead to effect size variability. The high I-squared values in the incidence of EHR and other risk factors in our study could be attributed to differences in sex, age, surgeon training, and time from enrollment in the included studies. Last, there was insufficient data to assess the role of type of immunosuppression on EHR after kidney transplantation.This meta-analysis reported a high incidence of EHR in kidney transplant patients and summarized the evidence available on the risk factors associated with it. The most prominent risk factors include recipient's black race, diabetes, a higher number of years on dialysis, delayed graft function (DGF), and a longer length of hospital stay during transplantation. EHR is associated with death censored graft failure and mortality within the first year of transplantation. Hence, future research should aim to develop and implement predictive models for patient identification and novel management strategies to reduce EHR in patients at risk.Publicly available datasets were analyzed in this study. This data can be found here: Data is available upon reasonable request from the authors.KI and SSR: concept/design. AI and SKK: data analysis/interpretation. MH, KI, AI, and SKK: drafting article. FY, TK, CT, and SS: critical revision of the article. TK, CT, and SS: approval of the article. FY: statistics. AI and SSR: data collection. All authors contributed to the article and approved the submitted version.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.


The subgroup analysis demonstrated consistent results by showing a significantly positive association between them, irrespective of WMC category. We also found that cultural environments could moderate this association, and we identified a strong correlation in participants from an Asian cultural context. In conclusion, this study provides the evidence to clarify the positive association between WMC and creativity, and implies that the Asian cultural context may boost such an association.Creativity serves as a fountain for social and scientific development. As one of the most crucial human capabilities, creativity has been believed to be supported by the core component of higher cognitive functions—working memory capacity (WMC). However, the evidence supporting the association between WMC and creativity remains contradictory. Here, we conducted a meta-analysis using random-effects models to investigate the linear association between WMC and creativity by pooling the individual effect size from the previous literature. Further, a subgroup analysis was performed to examine whether such association is specific for different WMC categories . The main meta-analytic results showed a significantly positive association between WMC and creativity ( Creativity refers to the ability to produce novel and suitable ideas in a specific environment . Based oGrowing evidence suggests that executive functions (EFs) play an important role in creativity . HoweverIt has long been acknowledged that creativity is one of the most crucial factors associated with the development of multifarious cognitive components . HoweverIn contrast to the above results, another theory, known as the controlled attention theory, posits that individuals with a higher WMC are more easily confined within a single domain, which is detrimental to the implementation of creativity . RelatedTo make things more complicated, a portion of studies argued that WMC does not show any impact on creativity, by finding that WMC is not a robust predictor for creativity ability . TheoretTo address these conflicting results, meta-analysis has been widely used as a potent tool by providing evidence, based on the extensive previous literature . By syntTherefore, the current study aimed to provide evidence to clarify the association between WMC and creativity. We conducted a meta-analysis with a random-effects model to pool the individual effect size from each study concerning the association between WMC and creativity. The systematic retrieval of the literature was conducted by following 2020 PRISMA pipeline in PsycINFO, Web of Science, PubMed, EMBASE, CNKI (Chinese database) and PsycARTICLES datasets on 17 June 2022. Further, to probe into the potential hierarchical factors affecting this association, we conducted an exploratory, subgroup meta-analysis by dividing comprehensive WMC into verbal WMC, visual–spatial WMC and dual-task coordination WMC. Finally, to further probe into the impact of potential confounding factors for the meta-analytic effects, we conducted a moderation analysis to examine whether the association between WMC and creativity is moderated by cultural background and age group.To improve reproducibility and transparency as recommended, this study adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and CHARMS pipelines  see Fig. FurtherFor completeness and accuracy of the literature search, we used a keyword-based retrieval strategy to search in Boolean logic in PsycINFO, Web of Science, PubMed, EMBASE, CNKI and PsycARTICLES datasets. Specific Boolean expressions were as follows:  AND  NOT . To ensure data pooling completeness, reference lists of included articles, published in the last two years, were hand-reviewed.According to the research objectives we predefined, the inclusion criteria were defined was as follows: (1) WMC and creativity should be measured by using standardized scales or board-certified behavioral tasks; (2) fundamental statistics  for examining the association between WMC and creativity should be presented clearly; (3) peer-reviewed journal articles and dissertations are allowed; (4) analytic data should be self-recruited ; (5) a sample or control group would be qualified; (6) creativity and/or WMC would be assessed without intervention; and (7) studies should be in English/Chinese language only. On the other hand, the exclusion criteria were as follows: (1) systematic reviews  or preprints were not be accepted; (2) non-standardized measures were used to estimate WMC or creativity; and (3) statistics were reported vaguely.Meta-information was extracted from these included studies, including the author’s name, publication date, sample size, age, and sample populations (nations and identity). Further, tasks for measuring WMC were extracted and coded into three domains: verbal WMC task, visual–spatial WMC task and dual WMC task. In addition, measures for quantifying creativity were extracted and coded into the following categories: Torrance Tests of Creative Thinking (TTCT), Test of Creative Thinking–Drawing Production(TCT-DP), Abbreviated Torrance Test for Adults (ATTA), Divergent thinking tests (DT), Convergent thinking tests (CT), Williams Prefer Measurement Forms (WPMF), Williams Creativity Assessment Packet (WCAP), Unusual uses task (UUT), Alternative Uses Task (AUT), Consensual Assessment Technique (CAT), Creative Achievement Questionnaire (CAQ), Associative fluency tasks (AF) and the Remote Association Test (RAT). Finally, for pooling the individual effect size into the meta-analytic model, the statistics  and sample size for each included study were extracted.To ensure the data quality, all the data that were extracted and coded from included studies were cross-validated by two independent researchers . Any disagreements of data extraction and coding were solved by the third IR (CZY). Furthermore, two additional assessors (LXR and LMJ) were recruited to evaluate evidence-based quality by using a modified Newcastle–Ottawa Scale (mNOS) . The mNO2 test . In addition to this main analysis, the sub-group meta-analysis was deployed to validate the individual meta-analytic effect for this association by three WMC tasks, including verbal, visual–spatial, and dual-task coordination. Furthermore, to examine whether the meta-analytic effect is biased by confounding factors, we built the moderation-effect models by taking the cultural background and age group into account. Finally, for quality control, publication bias was inspected by producing funnel plots and was calculated by using Egger’s test and Kendall’s test  was used to implement all the data analysis as we mentioned above . To dete2 test  and Cochl’s test .Here, a total of twenty-eight papers  were screened and deemed eligible for generating the final data pool in the following meta-analysis. Fundamental information for all the included studies is tabulated in 2 value . Thus, the random-effects models were built for the following meta-analysis.The results of the heterogeneity tests revealed high between-study heterogeneity in this meta-analytic model, by showing a significantly high Ir = .083, 95% confidence interval (CI): .050–.115, SE = .003, p < .001, n = 3104)  see .2 = 39%, p = .069). Thus, the meta-analysis, using the random-effects model for investigating the association between verbal WMC and creativity, revealed that the meta-analytic effect for the positive correlation between verbal WMC and creativity reached statistical significance   see .2 = 0%, p = .58). Thus, the fix-effect model for meta-analysis was built; this demonstrated the statistically significant correlation between WMC and creativity   see .2 = 70%, p < .001), the results of the meta-analysis with the random-effects model showed the statistically significant correlation between dual-task WMC and creativity  (see Given the high between-study heterogeneity (I602) see .Given the high heterogeneity in the meta-analytic model, the moderation-effect analyses were performed to identify factors that may moderate the meta-analytic main effect. Here, the age and cultural contexts of the samples were reported in all the included studies and were modeled as potential moderators separately.r = .126, 95% CI: .091–.160, SE = .004, p = .000, n = 1282) than that from Western culture ; the Q-value was significant   and age groups  and schoolchildren (age < 18)). Results showed the moderating roles of cultural contexts in the meta-analytic effect, with a stronger correlation for participants from Asian cultural backgrounds (= 0.039) .r = .078, 95% CI: .048–.109, SE = .005, p = .000, n = 1831) and schoolchildren . The Q-value was not significant   .p = 0.507)  .e = .449, p = .350). Finally, the evidence quality for the included studies was validated to be acceptable .A funnel plot for standard Fisher-Z scores for the included studies can be used to explore the publication bias. The scattered points showed a symmetric distribution see , which iThe main purpose of this study was to clarify the association between WMC and creativity by synthesizing meta-analytic evidence. We found that WMC is significantly positively correlated with creativity by pooling individual effects, indicating that an increased WMC indeed supports human creativity. Furthermore, subgroup meta-analysis was conducted by dividing WMC into three categories, including verbal WMC, visual–spatial WMC and dual-task coordination WMC. The results demonstrated that such associations are robust in different WMC tasks. Lastly, we conducted moderation analysis, which revealed that the correlation between WMC and creativity was moderated by cultural background, with a higher correlation for participants from Asian cultural contexts. On balance, the current study may provide weak evidence to clarify the positive correlation of WMC with creativity. In addition, such associations were found to be robust for the potential impacts of the WMC categories, and the moderating role of cultural background was revealed in this association.One of the most crucial findings in this study is that there is a statistically significant (but weak) correlation between WMC and creativity. Both theoretical and empirical evidence supports that WMC could positively predict one’s creative ability. As the most important indicator of WM, the WMC is typically described as being the limited capacity for the temporary storage and processing of information . On the By using subgroup analysis, this study also found that the positive correlations between WMC and creativity were consistent, irrespective of the WMC category . This finding attempted to answer whether the conflicting results, derived from previous studies, were attributed to a heterogenous WMC category. Supporting this, measuring WMC performance was argued to be comparable across different sensory pathways  . In addiTo clarify the impact of potential confounding factors on the meta-analytic effects, moderation analyses were drawn for the cultural background of participants  and age groups , respectively. Interestingly, the meta-analytic effect for the association between WMC and creativity was significantly moderated by cultural background. Specifically, compared to participants with Western cultural background, participants in the Asian cultural environment reported a stronger correlation between WMC and creativity. This finding could be explained partly by the relativity of the creativity theory . This thAlthough this study clarifies the association between WMC and creativity, several limitations should be acknowledged. Due to the strict inclusion and exclusion criteria, the total sample size (n < 3500) and evidence  seem to be inadequate. Therefore, the nuance of these variations in task types of WM or creativity cannot be examined currently. Thus, future studies are needed to provide neuroimaging evidence to further confirm the association between them. Additionally, extending the main conclusion of the current study is prudent, because the total effect size for such an association is relatively small .This study provides evidence to clarify the statistically significant positive association between WMC and creativity, though it has a weak strength. Further, the present study revealed that such associations exist across different types of WMC measurement , indicating that the conflicting results for the association between them are not biased by measure heterogeneity. This study also demonstrates that the cultural gap may confound the association between WMC and creativity.


However, whether ctDNA could be an accurate diagnostic biomarker in colorectal cancer (CRC) remains to be clarified. The aim of this study was to evaluate the diagnostic accuracy of ctDNA in CRC. (2) Methods: PubMed, Web of Science, and Cochrane databases were searched to identify studies reporting the use of ctDNA to screen and diagnose CRC, and all relevant studies published until October 2022 were enrolled for our analysis. These studies were divided into three primer subgroups: the subgroup of quantitative or qualitative analysis of ctDNA and the subgroup of septin9 (SEPT9) methylation assay. (3) Results: A total of 79 qualified articles with 25,240 subjects were incorporated into our meta-analysis. For quantitative studies, the combined sensitivity (SEN), specificity (SPE), and diagnostic odds ratio (DOR) were 0.723 (95% CI: 0.623–0.803), 0.920 (95% CI: 0.827–0.966), and 23.305 (95% CI: 9.378–57.906), respectively, yielding an AUC of 0.860. The corresponding values for qualitative studies were 0.610 (95% CI: 0.566–0.651), 0.891 (95% CI: 0.878–0.909), 12.569 (95% CI: 9.969–15.848), and 0.823, respectively. Detection of SEPT9 methylation depicted an AUC of 0.879, with an SEN of 0.679 (95% CI: 0.622–0.732), an SPE of 0.903 (95% CI: 0.878–0.923), and a DOR of 20.121 (95% CI:14.404–28.106), respectively. (4) Conclusion: Blood-based ctDNA assay would be a potential novel biomarker for CRC screening and diagnosis. Specifically, quantitative analysis of ctDNA or qualitative analysis of SEPT9 methylation exhibited satisfying diagnostic efficiency. Larger sample studies are needed to further confirm our conclusions and to make the ctDNA approach more sensitive and specific. Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second most common cause of cancer death worldwide, which accounts for nearly 10% of cancer cases and 9% of cancer deaths . Since tSince the detection of higher levels of circulating free DNA (cfDNA), which consists of fragments of extracellular, in the blood of patients with various types of cancer , accumulAlteration of ctDNA has been detected in CRC patients by the quantitative method, which measures the quantity of ctDNA , and theThis systematic review and meta-analysis were performed according to the Preferred Items for Systematic Review and Meta-Analysis (PRISMA)  and MetaPubMed, Web of Science and The Cochrane Library were searched with query term: “(circulating tumor DNA OR circulating DNA OR ctDNA OR Cell Free Tumor DNA OR Plasma DNA OR Serum DNA) AND  AND (Diagnosis OR Detection OR Screen OR Sensitivity OR Specificity)”. The language was limited to English. All potentially relevant articles published until October 2022 were retrieved and independently queried by two authors. We also manually screened the reference from the included studies and relevant reviews for enlarged retrieval.The articles that conformed to the following criteria were included: (a) ctDNA was used for first-diagnosed CRC patients rather than the recurrent patients; (b) the numerical value of SEN and SPE of each detection method could be calculated in each study; (c) specimens were extracted from peripheral blood. The exclusion criteria were as follows: (a) review, case report or case series, comments, letter, or conference abstract; (b) sample size of studies was less than 10; (c) duplicated or overlapping publications that utilized the same patient specimens and identical gene modification; (d) publications with no full-text available. Two authors independently evaluated the eligibility of all publications. A third author would assess studies when there was a discrepancy.Data from eligible publications were extracted and compiled by two independent authors. The information extracted from included studies was as follows: the first author’s name, publication year, region/country, study design, sample size, control type, source of specimens, sampling time, detection method, reference gene, cut-off values, diagnostic performance (including SEN and SPE), true positive (TP), true negative (TN), false positive (FP), false negative (FN), positive likelihood ratio (PLR) and negative likelihood ratio (NLR), and diagnostic concordance.The quality of all included studies was evaluated by two independent authors according to Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), which assesses the studies on four key domains, including patient selection, index test, reference standard, and flow timing . Two autp-value were used to identify the presence of the threshold effect [2 tests. p < 0.10 or I2 > 50% indicated a significant heterogeneity, and the random effect model should be used [We utilized Revman Manager 5.4 and R program  with “meta” , “mada” d effect . Heterog be used . Subgrou be used . Potenti be used .n = 11) [n = 67) [n = 1) [n = 11) ,48,49,50[n = 67) ,117,118  [n = 1) . Among t [n = 1) ,115,116 n= 13,841). There were 18 prospective studies and 8 retrospective studies, while 53 studies did not clarify the study design. Among 50 studies with known sample collecting time, all samples were collected before surgery or treatment. While the majority of studies collected plasma for ctDNA analysis (n = 55), serum specimens were also analyzed in some research (n = 24). The methods applied to measure the concentration of ctDNA include real-time quantitative polymerase chain reaction (RT-qPCR) (n = 8), droplet digital polymerase chain reaction (ddPCR) (n = 2), branched DNA assay (bDNA) (n = 1) and florescent dye assay (n = 1). For qualitative analysis of ctDNA, methylation-specific polymerase chain reaction (MSP) was the most common method applied (n = 64).In our meta-analysis, a total population of 8076 CRC patients and 17164 control subjects were included. The primary characteristics of all studies are summarized in The quality assessment was based on QUADAS-2, and the outcome of eligible studies is depicted in 2 = 87.5%, p = 0.000; SPE: I2 = 77.0%, p = 0.000; DOR: I2 = 82.3%, p = 0.000). The Spearman correlation coefficient was 0.008 (p = 0.983), indicating that heterogeneity among quantitative studies was derived from other factors rather than the threshold effect.The quantitative analysis group, including 12 studies, yields an SEN of 0.723 (95% CI: 0.623–0.803) and an SPE of 0.920 (95% CI: 0.827–0.966) a,b. The 2 = 93.9%, p = 0.000; SPE: I2 = 93.5%, p = 0.000; DOR: I2 = 89.6%, p = 0.000). The Spearman correlation analysis was 0.149 (p = 0.118), depicting that heterogeneity among quantitative studies was derived from a non-threshold effect.In the qualitative analysis group, an SEN of 0.609 (95% CI: 0.563–0.650), an SPE of 0.891 (95% CI: 0.864–0.910) a,b, and 2 = 91.8%, p = 0.000; SPE: I2 = 89.8%, p = 0.000; DOR: I2 = 82.3%, p = 0.000). The result of Spearman correlation analysis was 0.02 (p = 0.993), indicating that heterogeneity among quantitative studies was derived from the non-threshold effect , 0.904 (95% CI: 0.881–0.923) a,b, and d effect .Different covariates including region (Asia vs. non-Asia), sample size (≥100 vs. <100), control type , sample source (plasma vs. serum), assay methods , and methylation gene  were applied in the subgroup analysis .Subgroup analysis based on sample size revealed an improved diagnostic accuracy in quantitative studies with sample size ≥ 100 since the SEP, SEN, and AUC for quantitative studies with sample size ≥100 were 0.771 (95% CI: 0.681–0.842), 0.924 (95% CI: 0.815–0.971) and 0.878, whereas corresponding values were 0.545 (95% CI: 0.417–0.667), 0.904 (95% CI: 0.604–0.983), and 0.694 for quantitative studies with sample size < 100. Similarly, qualitative analysis of ctDNA with a large sample size also had a more robust diagnostic accuracy (SEN: 0.598 (95% CI: 0.552–0.643), SPE: 0.903 (95% CI: 0.884–0.919), AUC: 0.849) compared to qualitative studies with sample size < 100 (SEN: 0.662 (95% CI: 0.544–0.762), SPE: 0.819 (95% CI: 0.694–0.900), AUC: 0.759).p = 0.01), which was consistent with the primary outcome of a clinical trial of SEPT9 methylation for CRC detection, indicating SEPT9 as a promising CRC diagnostic biomarker.For the quantitative analysis of ctDNA, subgroup analysis associated with control type showed that the SEN, SPE, and AUC for quantitative analysis of ctDNA to discriminate CRC from healthy control were 0.723 (95% CI: 0.626–0.803), 0.927 (95% CI: 0.833–0.967) and 0.861, while the corresponding values for quantitative analysis of ctDNA to discriminate CRC form non-CRC disease were 0.647 (95% CI: 0.508–0.765), 0.878 (95% CI: 0.563–0.976), and 0.641, respectively. While subgroup analysis in qualitative studies depicted an SEN of 0.601 (95% CI: 0.554–0.647), an SPE of 0.915 (95% CI: 0.895–0.932), and an AUC of 0.844 in qualitative studies with healthy people as control, and an SEN of 0.672 (95% CI: 0.617–0.723), an SPE of 0.809 (95% CI: 0.737–0.865) and an AUC of 0.774 in qualitative studies used non-CRC disease as control. These results indicated that studies utilizing healthy people as control provided a more satisfactory diagnostic efficiency compared to studies that used non-CRC patients as a control in both quantitative and qualitative analysis of ctDNA, which highlighted a more robust capability of ctDNA assay to distinguish CRC from healthy individuals than from non-CRC disease patients. Multiple levels of meta-regression also revealed that the parameter “control type” could contribute to the heterogeneity . Moreovep-value less than 0.05 indicated significance. No significant publication bias was observed in the quantitative analysis of ctDNA (p = 0.307). Nevertheless, our results revealed a significant publication bias in the qualitative analysis of ctDNA (p = 0.000). In addition, among these qualitative analysis studies, our analysis demonstrated that no significant publication bias existed in the SEPT9 methylation group (p = 0.731), while a significant publication bias was found in the non-SEPT9 methylation group (p = 0.000).Deek’s funnel plot asymmetry test  was usedCRC is one of the most common malignancies with poor prognosis and high mortality, which is highly correlated with the low early diagnostic rate . When deIn our meta-analysis, quantitative analysis of ctDNA exhibited a higher SEN (0.723 vs. 0.609) and a comparable SPE (0.920 vs. 0.891) compared to qualitative analysis, which is consistent with a higher AUC (0.860 vs. 0.828). This might be explained by the fact that some genetic loci selected for the test were not commonly expressed in CRC, which might generate a false negative in the test. Various septins have been associated with tumorigenesis, and SEPT9 hypermethylation has been detected in CRC . FurtherDOR was also applied to evaluate the diagnostic accuracy, and the discriminatory test performance would be classified as satisfactory when the value of DOR was over 10 . Both quIn this study, the value of PLR of quantitative analysis and SEPT9 methylation were 6.820 and 6.420, respectively, indicating that CRC subjects have an approximately six to seven folds higher chance of being positive in quantitative analysis and SEPT9 methylation analysis of ctDNA. However, qualitative analysis of ctDNA depicted a PLR of 4.920, which is lower than the value of quantitative analysis and SEPT9 methylation. Moreover, the qualitative analysis of ctDNA yielded an NLR of 0.496, implying that the probability for cases with negative qualitative assay results to have CRC is 49.6%, whereas the value of NLR of quantitative analysis and SEPT9 methylation detection of ctDNA were 0.326 and 0.367, respectively. These results might be explained that some gene locus methylation might not exist in all CRC cases, and using single gene methylation as a biomarker might lead to false negatives. However, SEPT9 methylation demonstrated a comparable PLR and NLR with quantitative analysis of ctDNA, depicting the robust diagnostic performance of SEPT9 methylation assay. Additionally, the SEPT9 assay demonstrated better compliance than FIT and colonoscopy in CRC screening [p = 0.307). However, it was highly possible that publication bias was presented in the qualitative analysis group (p = 0.000). As previous analysis demonstrated the disparity between the SEPT9 methylation assay and other gene methylation assays within the qualitative analysis, we further evaluated the publication bias based on gene loci. The Deek’s funnel plot asymmetry test revealed that publication biases were likely to exist in the non-SEPT9 methylation assay (p = 0.000) but not in the SEPT9 methylation assay (p = 0.731). Furthermore, a meta-regression analysis was adapted to explore the potential source of heterogeneity. In the quantitative analysis of ctDNA, none of the parameters of region, control types, sample size, ample source, and assay methods represented a primary source of heterogeneity; thus, heterogeneity might be generated from subjects’ ages, TMN stages, tumor size, tumor metastasis, or different protocol, which failed to be evaluated in this meta-analysis due to the lack of complete information. In the qualitative analysis of ctDNA, among parameters of region, control types, sample size, ample source, assay methods, and gene loci methylation, “control type”  and “gene loci methylation”  were potential primary sources of heterogeneity. We further analyzed the heterogeneity in SEPT9 methylation studies and revealed that “region”  and “control type”  could be the primary sources of heterogeneity. Thus, further large clinical trials should reasonably select the control subjects and various ethnicities or be performed in multiple regions to boost the diagnostic performance of ctDNA of CRC.Publication bias was evaluated by Deek’s funnel plot asymmetry test, and no publication bias was revealed in the quantitative analysis of ctDNA (Remarkably, there were several limitations that should be discussed in this meta-analysis. Firstly, even though we searched various databases, there were several publications we did not include in our meta-analysis as we failed to access the full texts. Moreover, there were only a small number of studies that described quantitative analysis of ctDNA, which might diminish the statistical significance. Thirdly, we failed to include some parameters, such as TMN stages, as incomplete information in included articles. Additionally, potential publication bias within the qualitative analysis that detects non-SEPT9 methylation, which might diminish the confidence of the analysis. Eventually, single gene loci were analyzed in qualitative analysis, while the combination of different gene alterations or other detection techniques might help to improve the diagnostic performance . TherefoIn summary, this is the first integrated meta-analysis on the overall diagnostic accuracy of circulating tumor DNA assays in CRC. Both quantitative and qualitative analyses of ctDNA exhibited excellent diagnostic efficiency. Specifically, quantitative analysis of ctDNA or qualitative analysis of SEPT9 methylation could potentially serve as effective diagnostic methods for CRC. Larger sample studies are needed to further confirm our conclusions and to make the ctDNA approach more sensitive and specific.


Obesity, especially severe obesity, is associated with a higher risk of atherosclerotic cardiovascular disease (ASCVD) morbidity and mortality. Bariatric surgery is a durable and effective weight loss therapy for patients with severe obesity and weight-related comorbidities. Elevated plasma levels of lipoprotein (a) (Lp(a)) are causally associated with ASCVD. The aim of this meta-analysis was to analyze whether bariatric surgery is associated with Lp(a) concentrations.  A literature search in PubMed, Scopus, Embase, and Web of Science was performed from inception to May 1st, 2021. A random-effects model and the generic inverse variance weighting method were used to compensate for the heterogeneity of studies in terms of study design, treatment duration, and the characteristics of the studied populations. A random-effects metaregression model was used to explore the association with an estimated effect size. Evaluation of funnel plot, Begg's rank correlation, and Egger's weighted regression tests were used to assess the presence of publication bias in the meta-analysis. p < 0.001, I2: 94.05%). The results of the metaregression did not indicate any significant association between the changes in Lp(a) and duration of follow-up after surgery, reduction in body mass index, or baseline Lp(a) concentration. The reduction in circulating Lp(a) was robust in the leave-one-out sensitivity analysis.  Meta-analysis of 13 studies including 1551 patients showed a significant decrease of circulating Lp(a) after bariatric surgery  concentrations. This decrease may have a positive effect on ASCVD in obese patients. It is well known that obesity, especially severe obesity, is associated with a higher risk of atherosclerotic cardiovascular disease (ASCVD) morbidity and mortality . ObesityThe most widely performed bariatric procedures are sleeve gastrectomy (SG), Roux-en-Y gastric bypass (RYGB), laparoscopic adjustable gastric band (LAGB), biliopancreatic diversion/duodenal switch (BPD/DS), and one anastomosis gastric bypass/minigastric bypass (OAGB/MGB) .Weight loss, no matter how achieved, decreases the risk of ASCVD, cardiovascular events, and total mortality. Weight loss has beneficial effects on the main risk factors for ASCVD including elevated total and LDL-cholesterol (LDL-C), triglycerides, and decreased HDL-cholesterol (HDL-C) . BariatrLPA gene determine 30-40% of the variance [LPA gene expression may be increased by inflammation, while diseases like hypothyroidism and chronic kidney disease may affect Lp(a) removal.Lipoprotein (a) (Lp(a)) is a cholesterol-rich LDL moiety that is covalently linked to a glycoprotein-apolipoprotein (a) ((apo (a)) by a disulfide bond . ElevateConsidering the profound metabolic changes that occur after bariatric surgery and its effect on proatherogenic lipoproteins , the aimThis meta-analysis was performed based on the 2009 preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines . From inOnly original peer-reviewed studies written in English were considered. All forms of bariatric surgery procedures  which reported circulating Lp(a) levels before and after surgery were studied. The exclusion criteria were abstracts only, letters, case reports, comments, meta-analyses, duplicate studies, animal studies, reviews, non-English language papers, studies with no surgical intervention, and studies without outcomes.After deleting duplicate studies, two independent authors examined the titles and abstracts of the remaining papers for eligibility. The full texts of the eligible studies were collected. If two (or more) papers on the same research topic were published by the same organization and/or authors, the more recent study with a larger sample size was included. Any disagreements were resolved by authors' discussion and consensus. The following information was extracted: (1) first author's name, (2) year of publication, (3) type of surgery, (4) study design, (5) characteristics of the patients, (6) levels of Lp(a), and (7) duration of follow-up.The Newcastle-Ottawa Scale (NOS) was applied to evaluate study quality in this meta-analysis . Three fn), where “n” represents the number of participants. To analyze the influence of each study on the overall effect size, a sensitivity analysis was done using the leave-one-out approach  [Q test and I2 statistic as a measure of variability.This meta-analysis was performed using Comprehensive Meta-Analysis (CMA) V2 software  . Informanalysis) , 36. StaA metaregression analysis was performed to investigate the impact of changes in body mass index (BMI) and postsurgery follow-up duration with the estimated effect size of surgery on Lp(a) concentrations.p value nonsignificant was calculated by the “fail-safe N” approach as another indicator of publication bias [To investigate the presence of publication bias, the funnel plot, Begg's rank correlation, and Egger's weighted regression tests were used. When funnel plot asymmetry was detected, potentially missing studies were inserted using the “trim and fill” approach. In case of a significant result, the number of potentially missing studies needed to render the ion bias .A thorough database search identified 99 published papers, 49 of which were directly related to the topic of this meta-analysis. After careful consideration, 36 studies were excluded: 10 studies were reviews, 10 studies did not meet the inclusion criteria, 15 studies did not report sufficient data, and one was a study protocol only. Therefore, 13 studies which evaluated the levels of Lp(a) before and after bariatric surgery were included . The stuBecause most of the studies did not have a control group, they were not evaluated for selection of controls, definition of controls, comparability, the same method of ascertainment, and nonresponse rate. However, all studies which were included met the ascertainment of exposure criteria. In most of the included studies, serum Lp(a) was assessed using the enzyme-linked immunosorbent assay (ELISA) . One stup < 0.001, I2: 94.05%)  after bariatric surgery  . The red 94.05%) .2, 95% CI: -16.308, -11.895, p < 0.001, I2: 99.69%)   as well as significant reduction in LDL-C levels   . Also, 3 93.90%) . Meta-an Figures .p = 0.507) or duration of follow-up . To investigate the impact of potential confounders on the Lp(a) lowering effect of bariatric surgery, random-effects metaregression was used. The results did not indicate any significant association between the changes in Lp(a) and percentage of BMI change  and Begg's rank correlation test  did not indicate the presence of publication bias in this meta-analysis of bariatric surgery effects on circulating Lp(a). Trim-and-fill analysis indicated that among all papers included in this meta-analysis, there could be five missing studies. The “fail-safe N” test showed that 842 missing studies were required to reduce the effect size to a nonsignificant (p < 0.001) value. Statistical heterogeneity was observed as Cochran's Q-test and I2 .This meta-analysis showed a significant reduction in circulating Lp(a) levels after bariatric surgery. Several meta-analyses have analyzed these effects particularly in patients with type 2 diabetes. Favourable effects have been shown on serum triglycerides, total cholesterol, LDL-C, and HDL-C concentrations following bariatric surgery depending on its type and the anatomic alterations unique to each procedure –54.Although an elevated Lp(a) level is independently associated with the incidence of cardiovascular events in the general population and it is an established predictor of cardiovascular events in patients with ASCVD , 56, theLPA gene promoter contains IL-6-responsive elements consistent with Lp(a) acute phase response of apo (a) [In this meta-analysis, bariatric surgery was shown to reduce Lp(a) levels despite the heterogeneity of the included studies. It has to be stressed that there was no association between changes in Lp(a) levels and weight loss or follow-up duration. An important question is: what mechanisms may cause these findings? One possibility is the consistent reduction in the obesity proinflammatory state indicated by lower levels of C reactive protein  and inte apo (a) . HoweverPrevious findings on the reduction of LDL-C and atherogenic dyslipidemia –12 and LLPA gene [One of the limitations of this study was that the methods for measuring Lp(a) concentrations in some studies were different, and this might explain the heterogeneity in our findings. However, using SMD as the summary statistic in this meta-analysis could reduce this error. Indeed, because of the structural properties of Lp(a), none of the available commercial assays for Lp(a) quantification is 100% inherently isoform-sensitive . We wereLPA gene . BesidesLPA gene . We wereObesity is associated with an increased ASCVD risk, and this association is consistent between sexes and across different parts of the world. This meta-analysis suggests that bariatric surgery significantly decreases circulating Lp(a) concentrations. Since elevated Lp(a) is independently associated with ASCVD, the results of this study may have clinical implications for severely obese individuals with high cardiovascular risk. However, it is worth mentioning that the estimates of the magnitude reduction required to achieve an ASCVD benefit are roughly 55 mg/dL .


To determine the relationship between childhood overweight/obesity and early puberty in both boys and girls. Specifically, this is the first time to conduct a meta-analysis of the relationship between childhood overweight/obesity and early puberty in boys.Relevant studies were identified from PubMed, Web of Science, and EMBASE searches. The exposure of interest was overweight/obesity in childhood. Childhood was defined internationally as the age range of 0–18 years. The overall risk estimates were pooled using random effects models. Subgroup and sensitivity analyses were performed to explore possible sources of heterogeneity and to assess the robustness of the results.A total of 10 studies involving 13,338 girls and 12,796 boys were included. Results showed that childhood overweight/obesity were associated with a significantly higher risk of early puberty in girls . Although without statistical significance, a higher risk of early puberty was also found in boys who were overweight/obese in childhood . Heterogeneity in the risk estimates of early puberty was partially explained by study design, sample size, follow-up duration, definitions of early puberty and confounders controlled. Sensitivity analyses validated the robustness of the findings.Our findings showed that for girls the associate between overweight/obesity and early puberty is definite or strong whereas for males, such an association is possible, prompting that future studies need to further explore the possible relationship between overweight/obesity and early puberty in boys.https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021264649, PROSPERO CRD42021264649. Overweight/obesity in childhood is a global public health problem that is prevalent in both developing and developed countries , 2. As rChildhood overweight/obesity is widely regarded as a risk factor for comorbidities in childhood or later in life, such as type two diabetes, hypertension, dyslipidemia, coronary heart disease, hepatic and orthopedic problems, and psychosocial comorbidities . In addiA previous meta-analysis published in 2017, including five cohort studies with a total of 1,360 girls, has showed that early puberty was significantly associated with childhood overweight/obesity (RR = 2.44) . After tTherefore, the objective of this study was to perform a comprehensive meta-analysis regarding the association between childhood overweight/obesity and risk of early puberty in both girls and boys. The result of our study may lead to a better understanding of early puberty risk in children who are overweight or obese.We conducted the present meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement . Two aut(4) had sufficient information to calculate risk estimation and 95% confident intervals (CIs). Studies were excluded if they: (1) were reviews, case reports, letter to the editor, or abstracts; (2) provided vague or incomplete data; (3) were redundant publications; or (4) included children with any diseases which would affect pubertal development as participants. If there was more than one study from the same population, only the most comprehensive or most recent published one was included.In our study, the key exposure variable was overweight/obesity in childhood, and the key outcome variable was early puberty. Childhood was defined internationally as the age range of 0–18 years. The inclusion of titles and abstracts was intentionally expanded with a view to obtaining more relevant studies. First, studies would be taken into account if they reported on overweight/obesity and early puberty and were published in English. Then, full texts of the selected studies were reviewed. Studies were included if they: (1) were observational in design; (2) had clear definitions of exposure and outcome; (3) reported on the association between overweight/obesity in childhood and early puberty; and Two reviewers independently extracted and evaluated the data for each included article using a self-designed data abstraction form. Any disagreements between the two reviewers will be resolved through discussion or consultation with a third reviewer. The following data were extracted: first author, year of publication, study period, geographic region, gender, study design, length of follow-up, and age of enrolment (for cohort studies only), sample size, definition of overweight/obesity, definition of early puberty, and adjustments and matches made. The most important difference between cohort studies and case-control studies is the ability to demonstrate causation. Cohort studies group subjects according to whether they are exposed to a particular study factor and observe whether a specific outcome occurs in each group after longitudinal observation. This sequence conforms to the law of natural development of causality, so it has a strong ability to test the etiology hypothesis. However, case-control studies divided subjects into groups according to whether they suffered from a specific disease or not, and analyzed the association between exposure and outcome through retrospective collection of exposure to a specific factor in the past in each group. It was often difficult to determine the time sequence of exposure and outcome, so its causal verification ability was weak. Secondly, case-control studies are prone to recall bias. For example, when case-control studies are used to explore the relationship between smoking and lung cancer, lung cancer patients are likely to have recall bias on their past smoking dose and frequency due to the long incubation period of lung cancer.The methodological quality of studies was assessed using the Newcastle-Ottawa Scale (NOS) for quality assessment of cohort and case-control studies by two researchers (XZ and YH.) independently. The NOS was composed of eight items. It ranged from 1–9 stars and assessed the quality of each study based on three modules: selection, comparability, and outcome (cohort studies) or exposure (case-control studies). A final median score of ≥ 6 was regarded as high quality.p < 0.05 represented statistically significant heterogeneity) and I2 statistic  . Separate subgroup analyses were performed on the different categories to detect possible sources of heterogeneity, including geographic region , study design , sample size , follow-up duration , age at enrolment , type of exposure , definition of overweight/obesity , definition of early puberty [e.g., age of menarche, age of breast stage II stage, three criteria in the study, age of each Tanner stage, puberty development scale (PDS) score > Odds ratio (OR) was used as a reference value to measure the association between overweight/obesity and early puberty. Random effects model meta-analysis was used as a tool to calculate combined ORs and 95% CIs . Heteroggeneity) , 24. TheA total of 5,150 articles were retrieved through the system search and manual search. Of these, 3,409 articles were left after eliminating the duplicate publication, 3,316 articles were excluded after screening the title and abstracts, and 83 of them were excluded after screening the full text. Finally, 10 articles were included in meta-analysis see  13, 19,, 25–31.The characteristics of the 10 included studies are shown in the , 2. InclI2 = 94%, p < 0.001). Begg's test did not show a potential publication bias . Sensitivity analysis were performed by repeating the meta-analysis after the exclusion of each included study; results showed that exclusion of any single study did not materially alter the risk estimate of early puberty in girls , follow-up duration , definition of early puberty , and confounders controlled  were shown to be associated with the between-study heterogeneity. In studies with a case-control design, the risk of early puberty related to childhood overweight/obesity  was significantly higher than that in studies with a cohort design . It should be noted that overweight/obese children were at greater risk of early puberty when the study sample size was greater than 2000 or the follow-up duration was longer than 8 years. When stratified by definition of early puberty, positive associations between childhood overweight/obesity and early puberty were still found in studies defined early puberty by age of breast stage II stage , age of each Tanner stage , age of menarche , PDS score >p = 0.001) when compared with studies that had one or more confounders controlled . Moreover, through subgroup analysis, we found that overweight girls  enter puberty earlier than obese girls .Subgroup analyses for the association between childhood overweight/obesity and early puberty in girls are shown in Qualitative analysis identified that boys with high BMI trajectories had a greater risk of early puberty than boys with low BMI trajectories . FurtherI2 = 68%, p = 0.01). Begg's test did not show a potential publication bias . Sensitivity analysis were performed by repeating the meta-analysis after the exclusion of each included study; results showed that exclusion of any single study did not materially alter the risk estimate of early puberty in boys  and confounders controlled  were shown to be associated with the between-study heterogeneity. In studies with a sample size greater than 2,000, obese children were at higher risk of entering puberty early . When stratified by confounders controlled, positive associations between childhood overweight/obesity and early puberty were still found in studies that have none of the confounders controlled , and studies that had one or more confounders controlled .Subgroup analyses for the association between childhood overweight/obesity and early puberty in boys are shown in In this study, by combining the results of all available data with the conventional method of meta-analysis, we provided evidence that childhood overweight/obesity were associated with a higher risk of early puberty in girls. Specifically, childhood overweight and obesity in girls may increase the risk of early puberty by 4.67-fold, and 2.22-fold, respectively. An increased risk of early puberty related to childhood overweight/obesity was also found in boys, although the estimate was not statistically significant. As far as we know, this study is the most up-to-date and comprehensive meta-analysis evaluating the relationship between childhood overweight/obesity and early puberty in both boys and girls, which can supply helpful information to both parents and primary health care providers, and help to guide relevant policy and advocacy efforts.To our knowledge, several potential mechanisms have been proposed to explain the relationships between childhood overweight/obesity and early puberty de Ridder et al. suggested obesity in preadolescent children may lead to the improvement of aromatase activity, which can accelerate the conversion of androgens to estrogen . MeanwhiOR = 4.67) had a higher risk of early puberty than those who were obesity in childhood (OR = 2.22), which is consistent with the results of a cohort and sibling-matched analyses   . The difctively) . Of noteThe strength of this meta-analysis is the large sample size which involving 13,338 girls and 12,796 boys, and thereby can enhance statistical power, providing more precise and reliable risk estimates. Compared with previous the meta-analysis, our study is more comprehensive since we assessed the association between childhood overweight/obesity and risk of early puberty in both girls and boys. To prevent the omission of relevant literature, a comprehensive and specific search strategy was used at the beginning of this study. Then, a set of more rigorous selection criteria was used in the screening of the selected studies. Besides, detailed analyses were conducted for more diverse subgroups. Finally, more recent studies were contained, which makes our results more reliable to present practices.On the basis of a large sample size, we received a more convincing result. However, some limitations must be considered. Firstly, only articles published in English were included in our study, which may lead to the omission of articles published in other languages and articles that have not yet been published. Secondly, substantial heterogeneity was found in this meta-analysis. Although subgroup analysis revealed several important sources of heterogeneity, such as study design, sample size, follow-up duration, definition of early puberty and confounders controlled, we still cannot ignore the existence of heterogeneity. Meanwhile, since some subgroup categories contained only one or very few studies, the statistical power is weakened. Thirdly, significant unmeasured confounders might be involved in the observed relation between childhood overweight/obesity and early puberty. Out of the 10 included studies, seven studies have controlled for one or more confounders, such as parental education, family income, and urban or rural. The reproducibility between the confounding factors controlled across these studies was also limited. Considering that some studies included in this meta-analysis have not controlled for the key confounders of early puberty, such as race, birth weight and physical activity, it is possible that the increased risks found in this study partly due to differences in these risk factors of early puberty between overweight/obesity in childhood and the reference groups. Fourth, both case-control and cohort studies were included in our study, case-control studies may appear reverse causality. Case-control studies are widely considered to be prone to recall and selection biases, which restrict the strength and quality of evidence. Compared to studies with a cohort design (OR: 1.24), subgroup analyses showed that the risk of early puberty related to childhood overweight/obesity was significantly higher in case-control studies (OR: 4.80). Fifth, different types of markers of puberty timing and obesity that may have been obtained at a single time-point and/or self-reported, which may lead to measurement errors, for example, the use of BMI as an indirect measure of fat mass in epidemiological studies has its limitations. Children with high muscle mass, such as tall and athletic boys, are incorrectly classified as overweight/obesity based on their BMI, which can lead to false link between overweight/obesity in childhood and early puberty . More noOur finding of an association between childhood overweight/obesity and the risk of early puberty has significant implications for child and adolescent health. In addition, the common view is that early puberty is a complex phenomenon caused by many environmental and genetic factors, as well as interactions among these . HoweverIn conclusion, based on the available evidence, our systematic review and meta-analysis showed that for girls the associate between overweight/obesity and early puberty is definite or strong whereas for males, such an association is possible, prompting that future studies need to further explore the possible relationship between overweight/obesity and early puberty in boys.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.LC and TW: study concept and design and study supervision. XZ, YH, ZY, ZG, SZ, XL, YC, and CY: acquisition, analysis, or interpretation of data. XZ and YH: statistical analysis and drafting of the manuscript. LC, TW, XZ, and YH: critical revision of the manuscript for important intellectual content. LC obtained funding administrative, technical, or material support. All authors contributed to the article and approved the submitted version.This study was supported by National Natural Science Foundation Program of China (Grant Nos. 81973137 and 82173608).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.