Environmental pollutants, particularly toxic trace metals with neurotoxic potential, have been related to the genesis of autism. One of these metals that stands out, in particular, is lead (Pb). We conducted an in-depth systematic review and meta-analysis of peer-reviewed studies on Pb levels in biological materials retrieved from autistic children (cases) and neurotypical children (controls) in this work. A systematic review was conducted after the careful selection of published studies according to established criteria to gain a broad insight into the higher or lower levels of Pb in the biological materials of cases and controls, and the findings were then strengthened by a meta-analysis. The meta-analysis included 17 studies (hair), 13 studies (whole blood), and 8 studies (urine). The overall number of controls/cases was 869/915 (hair), 670/755 (whole blood), and 344/373 (urine). This meta-analysis showed significantly higher Pb levels in all three types of biological material in cases than in controls, suggesting a higher body Pb burden in autistic children. Thus, environmental Pb exposure could be related to the genesis of autism. Since no level of Pb can be considered safe, the data from this study undoubtedly point to the importance of regularly monitoring Pb levels in autistic children. Autism is a complex neurodevelopmental disturbance primarily characterized by difficulties in social communication and interaction, together with restricted and/or repetitive behaviors or interests ,2. The iThe etiology of autism is most likely multifactorial; a genetic component and environmental triggers have been suggested in the development of autism . Among tToxic trace elements are an integral part of the environment, although accelerated and uncontrolled industrialization has dramatically increased their levels in the last 50 years ,15. Not Lead (Pb) is one of the most extensively researched trace elements in autism. It is a heavy, non-essential metal and non-threshold neurotoxicant ,20. AlthLead exposure in children has been a long-standing public health issue in many countries. It is primarily taken into the body by ingestion and inhalation ,29. LeadLead has a strong and irreversible effect on children’s health; it is a powerful initiator or promoter of multiple diseases, even at small levels . Young cThe “Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement”  was follFor this study, four databases were initially examined: PubMed, ScienceDirect, SCOPUS, and Google Scholar. Due to the overlap of publications from these databases in a relevant percentage, we selected two of the most representative databases for the search, PubMed and ScienceDirect.The primary purpose of this study was to identify all papers that examined Pb levels in the hair, whole blood, serum/plasma, red blood cells (RBCs), urine, and teeth collected from autistic children (cases) and non-autistic people . The literature search encompassed 2005 to the present. We used the following Mesh terms in the search: “autism” AND “autistic” AND “autism spectrum disorder” AND “child” AND “preschool” AND “school” AND “adolescent” AND “heavy metals” AND “toxic metals” AND “lead” AND “Pb” AND “hair” AND “blood” AND “serum/plasma” AND “red blood cells” AND “urine” AND “teeth”. We also screened the reference lists of retrieved results. Inclusion criteria were original research studies reporting Pb levels in the mentioned biological materials from cases and controls. Exclusion criteria were studies that considered adults, studies in which the diagnosis of autism was not confirmed, studies in which cases and controls were not from the same place of residence, studies in which additional pathology was reported in addition to autism, studies not written in English, studies that did not offer sufficient numerical data, and studies with extremely abnormal Pb values. Additional exclusion factors are listed in PRISMA procedures were followed in the selection of papers, which included identification, screening, eligibility, and inclusion. This paper selection process is graphically illustrated in Quality assessment of the included studies was performed using the Newcastle–Ottawa scale (NOS) according to . Quality2) and the associated Cochran’s Q test [2 value of 75% was considered a high level of heterogeneity, and because of the low power of the Q test to detect heterogeneity, p < 0.1 was considered significant. When heterogeneity was more than 70%, the pooled estimates were analyzed using the random-effects model. All analyses were conducted using the random-effects model, since we expected the true effect sizes to vary across studies. According to [2) also indicates heterogeneity. τ2 close to 0 indicates low heterogeneity and τ2 greater than 1 indicates substantial heterogeneity [p values less than two-sided 0.05 were considered significant. Statistical analysis was performed using Comprehensive Meta-Analysis software .The heterogeneity of the selected studies was estimated using the I-squared  [p < 0.001) [2 = 95.874%, Q16 = 387.831, and τ2 = 1.056, p < 0.001, indicating high heterogeneity between the true mean effects.Pooling data under the random-effects model showed significant differences between the two groups (cases and controls), with Hedges’s g = −0.427  and < 0.001)  to 0.421< 0.001)    to 14.68< 0.001)  to 5.75 17 = 3.972, p = 0.001; and Begg and Mazumdar rank correlation: Kendall’s τ = −0.389, p = 0.029. In summary, the pooling size effect shows significantly higher hair Pb levels in cases than in controls (p < 0.001).The funnel plot  indicateThe meta-analysis of whole blood Pb levels in controls and cases included 13 studies with a sample size of 670 neurotypical children and 755 autistic children . In two p < 0.001, with effect sizes in individual studies ranging from −6.355  [p < 0.001) [2 = 94.800%, Q12 = 230.788, and τ2 = 0.799, p < 0.001, which indicated high heterogeneity in whole blood and which was intermediate regarding the heterogeneity that we found in hair and urine.The pooling of data under the random-effects model is presented in < 0.001)  to 0.233< 0.001) . Relativ< 0.001)  to 28.56< 0.001) . Standar< 0.001)  to 4.610< 0.001) . Heterog13 = 3.040, p = 0.011; and Begg and Mazumdar rank correlation: Kendall’s τ = −0.461, p = 0.033. In conclusion, the pooling size effect shows significantly higher whole blood Pb levels in cases than in controls (p < 0.001).The funnel plot  indicateThe meta-analysis of urine Pb levels in controls and cases included eight studies with a sample size of 344 neurotypical children and 373 autistic children . In two p < 0.001, with effect sizes in individual studies ranging from -1.220  [p < 0.001) [2 = 96.267%, Q7 = 187.502, and τ2 = 1.423, p < 0.001, indicating high heterogeneity, which was higher than that found in hair and in whole blood.The pooling of data under the random-effects model is presented in < 0.001)  to 5.150< 0.001) . Relativ< 0.001)  to 23.11< 0.001) . Standar< 0.001)  to 11.45< 0.001) . Heterog8 = 4.225, p = 0.0056; and Begg and Mazumdar rank correlation: Kendall’s τ = −0.857, p = 0.003. In conclusion, the pooling size effect shows significantly higher urine Pb levels in cases than in controls (p < 0.001).The funnel plot  indicateIn all three types of biological materials, we obtained high heterogeneity between the true mean effects (urine > hair > whole blood). This implies that practically all of the observed variability was due to real differences measured in the studies.It is suspected that autistic children have a reduced ability to excrete Pb and other toxic trace metals, leading to a high body burden and accumulation in various organs, including the central nervous system ,75,76. DIn 1989, the Environmental Protection Agency (EPA) stated that hair is a meaningful and representative tissue for the quantification of toxic metals . The NatMost studies reported higher levels of Pb in the hair of case children than in controls, in Saudi Arabia ,73, OmanAccording to some studies, hair Pb levels can differ based on demographic or environmental factors. Thus, Mohamed et al.  reportedWe would like to point out that some studies were not included in our meta-analysis since they lacked a control group. However, these studies primarily looked at hair Pb levels and autism severity. For example, Fiore et al.  analyzedThree studies were excluded from our meta-analysis owing to a lack of numerical data, an insufficient control group, or an unsubstantiated diagnosis of autism. For example, Harchaoui et al.  did not The findings from our current meta-analysis study, showing higher hair Pb levels in autistic children than in controls, did not accord with the previous meta-analysis by Guo et al. . This caSince Pb has a half-life in the circulation of weeks to months, it swiftly departs from the blood and accumulates in the bones and other organs. Because biopsies of these tissues are invasive, the assessment of Pb exposure in autistic people must be considered in available clinical samples .Most studies reported higher Pb levels in the whole blood of autistic children than in neurotypical controls, including in the USA , SloveniChanges in whole blood Pb levels in autistic children according to sex, age, and other demographic factors have not been elucidated so far. An exception is the study of Hawari et al. , who fouOne study was not included in our meta-analysis since there was no control group , while oThe results of this study were in agreement with Saghazadeh and Rezaei  and ShiaIn addition to the whole blood, Pb was also analyzed in RBCs. El-Ansary et al.  reportedFive of the six studies reported higher serum/plasma Pb levels in case children than in neurotypical controls ,62,67,98Total urine Pb levels reflect approximately two thirds of the blood filtered by the kidneys during the last few days to weeks before sampling. Urine Pb levels, on the other hand, could offer information on long-term exposure if assessed in relation to bone turnover rates  and the release of Pb from the bone into the circulatory system. Because bone remodeling happens more often in youngsters than in adults, these effects are unmistakably strong in younger people . Higher Some studies were not included in our meta-analysis due to several shortcomings. Abd Wahil et al.  reportedLead was also analyzed in teeth. Abdullah et al.  used enaAlthough rigid criteria were used to select participants and exclude publications with very high Pb levels in biological materials, we were unable to segregate individuals based on sex, age, or country, because the dimensionality required for a meta-analysis was lost. However, in terms of Pb levels, the participant’s country and micro-location of residence could be a crucial aspect that should be studied further. As a result of our meta-analysis, we believe that more research on larger numbers of individuals with properly sex-, age-, and residence-matched controls and a wider range of biological materials is required.Data from this systematic review and meta-analysis revealed that, compared with control children, autistic children had higher Pb levels in hair, whole blood, and urine, indicating a high body burden of this heavy metal. As a result, Pb exposure could be a risk factor in the genesis of autism, or other, unknown mechanisms could be at play that explain this difference. Since no Pb level can be considered safe, the data from this study undoubtedly point to the importance of monitoring Pb levels in autistic children in the future, namely in hair, whole blood or its parts , and urine. Other biological materials, such as teeth, appear to be promising. Additional research is needed to shed light on the reliable reduction of Pb levels in the bodies of children with autism and, thereby, reduce or prevent the harmful effects. Overall, we hope that the information given here will aid in the planning of future research on the adverse consequences of environmental Pb exposure and a better understanding of its involvement in autism.


Mental disorders, characterized as products of biopsychosocial interactions, have emerged as a leading contributor to the worldwide rise in overall morbidity and disability rates. Life's essentials can affect nearly every aspect of our lives, from physical to mental health. In this study, we try to identify the associations between life's essentials and mental disorders.Three assumptions of Mendelian randomization (MR) were applied to obtain the genetic instruments associated with smoking, sleep, and body mass index (BMI) in genome-wide association studies. Then, we conducted univariable MR (UVMR) and multivariable MR (MVMR) two-sample analyses to estimate the causal effects of these life's essentials on two mental disorders namely, major depressive disorder (MDD) and bipolar disorder (BD). Additionally, multiple sensitivity analyses were performed to evaluate the reliability and stability of the study results.p = 0.004], sleep , and BMI  were all considered as risk factors for MDD and were independent of each other . Additionally, 78, 38, and 297 genetic instruments were obtained in the MR analysis of smoking, sleep, and BMI with BD, respectively. Causal associations were observed between smoking , sleep , and BD, and smoking  might be a mediator in the causal effects of sleep on BD. Finally, there was no inconsistency between sensitivity and causality analysis, proving that our results are convincing.In the MR analysis of the association of smoking, sleep, and BMI with MDD, we obtained 78, 39, and 302 genetic instruments, respectively. Smoking [odds ratio (OR), 1.03; 95% confidence interval (CI), 1.01–1.06; The study results provide strong evidence that smoking, sleep, and BMI are causally related to MDD and BD, which need further research to clarify the underlying mechanism. The WHO defines mental health as “a state of sustained and positive development of the mind in which people are well-adapted and fully reach their physical and mental potential” . HoweverLife's essentials, including a healthy diet, participation in physical activity, avoidance of nicotine, healthy sleep, healthy weight, and healthy levels of blood lipids, blood glucose, and blood pressure, constitute a novel framework defined by the American Heart Association to help doctors shift their focus from solely treating diseases to promoting positive psychological health . TherefoMR is a recently developed statistical tool that uses genetic variants as instrumental variables (IVs) to estimate the causal effect of exposure on the outcome without any bias from residual confounding or reverse causality . MoreoveWe performed univariable MR (UVMR) and multivariable MR (MVMR) analyses to estimate the causal effects of life's essentials on mental disorders. In these analyses, smoking, sleep, and BMI were considered as exposures, and major depressive disorder (MDD) and bipolar disorder (BD) were considered as outcomes.https://gwas.mrcieu.ac.uk), a publicly accessible online tool containing GWAS summary data, was used to obtain data on three of life's eight essentials and two mental disorders. GWAS of exposure 1  included 280,508 cases and 180,558 control individuals; GWAS of exposure 2  included 462,341 samples; and GWAS of exposure 3  included 336,107 samples. Additionally, GWAS of outcome 1  included 8,276 cases and 209,308 control individuals. GWAS of outcome 2  included 20,352 cases and 31,358 control individuals. GWAS data for exposures 1 and 2 were obtained from the MRC-IEU consortium, and exposure 3 data were collected from Neale Lab. GWAS data for outcome 2 were gathered from the Bipolar Disorder Working Group of the Psychiatric Genomics Consortium. The GWAS data employed in this study had been approved by the relevant ethics committees with informed consent from participants.The flowchart for UVMR and MVMR analyses is shown in p < 5 × 10−8 was set as an association threshold to select eligible single nucleotide polymorphisms (SNPs). We used the clumping method among the selected SNPs with R2 < 0.001 and physical distance < 10,000 kb to avoid linkage disequilibrium (LD). In addition, for SNPs representing incompatible alleles or with palindromic characteristics and intermediate allele frequencies, we employed the SNP harmonization method to harmonize their effects (F = β2/se2) to evaluate the power of the test of the remaining SNPs and removed SNPs with weak power (F statistics < 10)  .In UVMR analysis, inverse variance weighted (IVW) , MR-Eggep < 0.05 were considered statistically significant.Sensitivity analysis is an essential part of MR analysis and includes heterogeneity and pleiotropy analyses. We employed Cochran's Q statistics, along with IVW and MR-Egger regression, to test the heterogeneity of IVs . In addiFollowing the comprehensive and rigorous selection process, a total of 78, 39, and 302 SNPs were identified as IVs in the causal effect analysis of the association between smoking, sleeplessness/insomnia, BMI, and MDD. Furthermore, 78, 38, and 297 SNPs were obtained for BD . All SNPp = 4.10 × 10−3]. Similar results were obtained in the weighted median analysis . As for the MR-Egger test, smoking could be regarded as a risk factor, but the p-value was not significant . Furthermore, the logOR of MDD increased 1.04-fold with one SD increase in sleeplessness/insomnia in the IVW analysis  and weighted median analysis . The value of MR-Egger analysis was not statistically significant . As for BMI, both IVW  and weighted median  analyses showed the existence of causal effects between BMI and MDD, while the MR-Egger analysis found no significant causal effect  (p = 0.139), while heterogeneity existed between sleeplessness/insomnia, BMI, and MDD . MR-PRESSO and MR-Egger intercept tests did not find pleiotropy in IVs of smoking , while there was pleiotropy in IVs of sleeplessness/insomnia  and BMI ; in the MR-PRESSO distortion test, BMI had a p-value of 0.802, indicating that there was no significant difference between the results before and after outlier correction  of MDD increased 1.03-fold with one standard deviation (SD) increase in smoking [95% confidence interval (CI), 1.01–1.06, = 0.232) . The resrrection . A leaverrection .p = 0.017) and weighted median  identified smoking as a risk factor for BD, while the result of MR-Egger analysis was not significant . As for sleeplessness/insomnia, IVW , weighted median , and MR-Egger  analyses were conducted, indicating a causal relationship between sleeplessness/insomnia and BD. Regarding BMI, none of the methods revealed a causal effect: IVW , weighted median , and MR-Egger  (p = 3.70 × 10−11), sleeplessness/insomnia , and BMI . The results of the MR-PRESSO global test indicated the existence of directional pleiotropy in IVs of smoking (p = 3.33 × 10−4), sleeplessness/insomnia (p = 0.001), BMI (p = 3.33 × 10−4), and BD, while the MR-PRESSO distortion test showed that outlier SNPs did not bias the results for smoking (p = 0.746), sleeplessness/insomnia (p = 0.741), and BMI (p = 0.861)  . In Coch= 0.861) . The res= 0.861) . The sca= 0.861) –S4.p = 8.29 × 10−3; sleeplessness/insomnia: OR, 1.03, 95% CI, 1.01–1.05, p = 1.03 × 10−3; and BMI: OR, 1.01, 95% CI, 1.01–1.02, p = 1.48 × 10−7), indicating these exposures might be independent risk factors for MDD. The results of the causal effects of these life's essentials on BD showed that smoking  might increase the risk of BD, while sleeplessness/insomnia  and BMI  were not significantly associated with BD (In the MVMR analysis, strong evidence was found for the causal effects of smoking, sleeplessness/insomnia, and BMI on MDD based on the IVW method (smoking: OR, 1.03, 95% CI, 1.01–1.06,  with BD .The UVMR analysis indicated that smoking, sleeplessness/insomnia, and BMI are risk factors for MDD, and the MVMR analysis further confirmed their independence from each other. Furthermore, smoking and sleeplessness/insomnia were associated with an increased risk of BD, with the possibility of sleeplessness/insomnia affecting BD through smoking mediation. Conversely, no causal effect between BMI and BD was observed. These findings suggest that increasing attention should be paid to these three life's essentials in preventing MDD and BD.The debate about whether mental disorders lead to smoking or whether smoking leads to mental disorders is ongoing . A meta-Adequate and high-quality sleep has been proposed as a potential factor in preventing mental disorders in both young and older adults , 29. MorDecades of research have illustrated the causal effect of BMI on cancer , cardiovWe should consider the study's limitations. First, providing more detailed information about ancestry subgroups in GWAS can help mitigate uncontrolled confounding from familial effects . In addiNonetheless, this study possesses several strengths. First, to the best of our knowledge, this MR analysis is the first attempt to explore the causal effects of life's essentials on mental disorders, highlighting the significance of life's essentials in improving mental health. Second, we obtained adequate SNPs as IVs and used multiple analysis methods, which may be conducive to minimizing the effect of bias and obtaining robust results. Third, the MVMR analysis aimed to detect any independent risk factors for mental disorders among life's essentials.In conclusion, this study provides strong evidence that life's essentials, such as smoking, sleep, and BMI, are causally related to MDD and BD. However, the causal relationship between BMI and BD needs further exploration.The original contributions presented in the study are included in the article/Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/ participants or patients/participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.RW and XL designed this study. MH performed the statistical analysis of data. JZ conducted the draft of the manuscript. All authors read and approved the final manuscript.


Sarcopenia is defined as the generalized and progressive loss of skeletal muscle strength and mass that may be affected by metabolic factors, although this relationship has been poorly studied. The aim of this review and meta-analysis was to analyze the relationship among the different metabolic risk factors and sarcopenia in people older than 65 years. Following the PRISMA 2020 guide, we searched for articles that studied the relationship among sarcopenia and metabolic risk factors in adults over 65 years of age, published between 2012 and 2022 in four databases: PubMed, Web of Science, Cochrane Plus, and CINAHL. A total of 370 articles were identified in the initial search, of which 13 articles were selected for inclusion in this review. It was observed that metabolic risk factors such as Body Mass Index, systolic and diastolic blood pressure, glucose, cholesterol, or triglycerides had a significant association with sarcopenia. There is evidence of the association of different metabolic risk factors with sarcopenia in adults over 65 years of age, so it is necessary to carry out studies that investigate different strategies that reduce the appearance of sarcopenia, and with it, the incidence of metabolic diseases. The world population is aging dramatically. Since 1980, the number of people aged 60 years or more has reached 810 million and is expected to increase to 2 billion by 2050, with 22% of the total population predicted to be over 60 years of age and 5% over 80 years of age by that year . To defiThe concept of sarcopenia was first proposed by Dr. Irwin Rosenberg in 1989 , but it Sarcopenia is a complex disease involving genetic and environmental factors, and its occurrence involves many mechanisms and risk factors, among which metabolic risk factors stand out, since sarcopenia is closely related to other diseases such as cardiovascular and metabolic diseases , with anConsidering that during the aging process, changes in body composition, an increase in fat mass, and a reduction in skeletal muscle may increase the risk of metabolic diseases—and with it, a functional deterioration—the aim of this work was to analyze the relationship among different metabolic risk factors and sarcopenia in people over 65 years of age.The present study was conducted following PRISMA 2020 guidelines ,20 and tData collection was performed in the months of November and December 2022 in the following databases: Pubmed, Web of Science, CINAHL, and Cochrane. Different keywords were used for the search, as well as the Boolean operators “AND” and “OR”, resulting in the following search string: (“Sarcopenia”) AND  AND (“older adults” OR “older women” OR “older men” OR “elderly” OR “seniors” OR “aging”).The inclusion criteria for this systematic review and meta-analysis were as follows: cross-sectional articles studying the association of metabolic risk factors with sarcopenia; conducted in participants older than 65 years of age. The search was limited to studies within the last 10 years and with human participants. Articles that did not report or measure metabolic risk factors in subjects with or without sarcopenia, as well as studies that did not present a clear definition or criteria for the diagnosis of sarcopenia, were excluded. First, duplicate articles and those without abstracts were discarded. Two independent authors (M.C.C.-F. and F.H.-C.) selected the titles and abstracts based on the eligibility criteria and two other authors (A.A.-A and M.M.C.F.) reviewed the full texts. Finally, discrepancies were resolved by consensus with a third author (D.F.A.-R). Data on authors, year of publication, country, setting, study design, sample size, sex, definition of sarcopenia, and adjustments were included.For the assessment of the methodological quality of the studies included in this review, the critical appraisal tool of the Joanna Briggs Institute (JBI), frequently used in systematic reviews, was used . The JBIData analyses were performed using the Comprehensive Meta-Analysis Software (CMA-V4). A random-effects meta-analysis was performed to calculate the association among metabolic risk factors and sarcopenia with 95% confidence intervals (95% CI) by measuring the Odds ratio (OR); values less than 1 indicate a negative association, values greater than 1 indicate a positive association, and values equal to 1 indicate no association. p-value associated with the statistic. A subgroup analysis by sex was performed. To address possible publication bias, graphical analyses were performed using funnel plots and their distribution.The results of the meta-analysis are presented through the forest plot, recording the first author, the date of publication, the individual effects, the 95% CI, and the overall effect with the 95% CI, as well as the A complete search was carried out in different databases, resulting in a total of 340 articles. Subsequently, a filtering for duplicate articles was performed, leaving a total of 237 unique articles. These articles were then examined considering the title and abstract and the eligibility criteria; only 13 articles were included ,33,34,35The methodological quality of the studies was assessed using the JBI scale. The scores obtained from the 13 articles were calculated manually and all the scores were ≥6 points, considered as good quality, with 5 of the studies ,29,32,35The articles selected in this systematic review and meta-analysis were cross-sectional studies published in South Korea ,30,31,32A total of 1,480,466 people participated in the selected studies, of whom 452,501 had sarcopenia and 867,991 did not have sarcopenia. The sample size of the 13 articles included in this systematic review with meta-analysis varied from 173  to 1,4572 and the article by Buchmann et al. [Dual-energy X-ray absorptiometry is a low radiation technique that is frequently used for the evaluation of body composition . Most ofn et al.  measure 2 [Furthermore, several studies consider other outcomes measures for the assessment and diagnosis of sarcopenia such as muscle strength assessed through hand grip strength using a dynamometer ,28,29, sIn all the selected studies, the relationship among different metabolic risk factors and sarcopenia was analyzed, and in all of them, a significant association could be observed. In two of the selected articles ,35, the p = 0.003) was found. Likewise, Chung et al. [2 = 27.36, p < 0.010 vs. females, . In two studies ,29, the g et al.  found thg et al. ,32 showeg et al. ,30,31,32g et al. ,31,32 reg et al. ,27,30 ang et al.  found a Regarding blood pressure, three studies ,27,31 anFinally, Park et al.  addressep < 0.001) was found   .To handle the predominance of the Korean population, a meta-regression was used, from which it was possible to adjust for the population as a possible confounding factor to evaluate whether it could influence the effect size; as a result of the regression, the coefficient for this covariate was obtained and was close to zero (0.02), which discards its influence in the estimation of the effect size. Likewise, the coefficient of determination (R-squared) was equal to zero, and the estimated effect size in OR was 1.1 with a pe of 0.99, thus indicating that the population covariate included in the model is not significantly affecting the results.A sensitivity analysis was carried out excluding studies that contained duplicate individuals or data and then comparing the results against those obtained from the complete meta-analysis. Therefore, it was possible to evidence that there were no differences in this regard. The analysis was performed using the funnel plot, including all the articles of the meta-analysis, which revealed an expected publication bias, as there were articles that diverged with respect to the measure of association and modified the OR by 25%. However, when the analysis of subgroups by sex was performed, the heterogeneity was reduced, which allowed a greater symmetry in the distribution to be evidenced, remaining within the confidence interval.p < 0.001), regardless of sex .This systematic review with meta-analysis, performed with the aim of determining the relationship among metabolic risk factors and sarcopenia in persons over 65 years of age, considered 13 studies ,33,34,35Sarcopenia is very common among older people because several changes occur with age, such as a significant decrease in muscle mass, strength, and physical activity —factors The loss of muscle mass is related to age, which at the same time is associated with physical disability, metabolic alterations, and an increased mortality . RegardiAdditionally, due to the decrease in muscle mass associated with sarcopenia, the metabolic rate is reduced, which can lead to an increase in body fat, and with it, metabolic disorders, and functional disability . In agreDecreased muscle strength leads to increased incidence of both sarcopenia and sarcopenic obesity and the occurrence of cardiovascular and metabolic diseases . PreviouThe findings found in this review are intimately related to aging, considering the age of the participants (older than 65 years). As could be observed in one of the selected studies , in addip < 0.001), being higher for men  than for women . Finally, the meta-analysis performed suggests that metabolic syndrome or its risk factors   are a riThis systematic review has several strengths such as having included studies with good methodological quality (measured by JBI); the selected articles mainly had a large sample size and in total represent 1,480,707 persons older than 65 years, including both sexes, which may be a representative sample; most of the studies used the same definition of sarcopenia, which gives consistency to the categorization of the studies and their comparison. However, it is possible to identify a geographical bias, as the articles included are from Europe, Africa, and Asia without including research conducted in the Americas or Australia, which possibly limits the generalizability of the results of this review.Sarcopenia has become an important health condition associated with aging. The present systematic review with meta-analysis revealed that there is a significant association among the metabolic risk factors studied  and sarcopenia in persons older than 65 years in both sexes, although the risk is higher for men than for women. Finally, the association between sarcopenia and metabolic syndrome in older adults could benefit from cohort studies as it would allow the assessment of risk during follow-up and the influence of time of exposure to the factors as well as studies with detailed data stratified by types of sarcopenias.


MicroRNA-1246 (miR-1246), an oncomiR that regulates the expression of multiple cancer-related genes, has been attracted and studied as a promising indicator of various tumors. However, diverse conclusions on diagnostic accuracy have been shown due to the small sample size and limited studies included. This meta-analysis is aimed at systematically assessing the performance of extracellular circulating miR-1246 in screening common cancers.  We searched the PubMed/MEDLINE, Web of Science, Cochrane Library, and Google Scholar databases for relevant studies until November 28, 2022. Then, the summary receiver operating characteristic (SROC) curves were drawn and calculated area under the curve (AUC), diagnostic odds ratio (DOR), sensitivity, and specificity values of circulating miR-1246 in the cancer surveillance. P = 0.007). No significant publication bias in DOR was observed in the meta-analysis .  After selection and quality assessment, 29 eligible studies with 5914 samples (3232 cases and 2682 controls) enrolled in the final analysis. The pooled AUC, DOR, sensitivity, and specificity of circulating miR-1246 in screening cancers were 0.885 : 0.827-0.892), 27.7 (95% CI: 17.1-45.0), 84.2% (95% CI: 79.4-88.1), and 85.3% (95% CI: 80.5-89.2), respectively. Among cancer types, superior performance was noted for breast cancer  compared to colorectal cancer , esophageal squamous cell carcinoma , hepatocellular carcinoma , pancreatic cancer , and others (AUC = 0.887, DOR = 27.5,  Extracellular circulating miR-1246 may serve as a reliable biomarker with good sensitivity and specificity in screening cancers, especially breast cancer. Despite improvements in diagnosis and treatment, cancer is still burdened disease globally with the increased new cases and deaths over the years , 2. AnnuIn recent years, liquid biopsy materials, including microRNAs  in the blood and body fluids, have been attracted and extensively studied as potential biomarkers for cancer diagnosis and prognosis . These aThis meta-analysis was conducted according to the guideline of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) .We searched electronic databases of PubMed/MEDLINE, Web of Science, Cochrane Library, and Google Scholar for relevant studies up to 28 November 2022. The keywords used in searching were “miR-1246,” “miR1246,” “miRNA-1246,” “miRNA1246,” “microRNA-1246,” and “microRNA1246.” Also, we reviewed citation reports of potential studies to find additional articles. After searching, all relevant studies were saved as an EndNote list. By removing duplicates (2772 records), 5690 remained for later evaluations . SubsequThe quality of included studies was assessed by three independent researchers using the QUADAS-2  tool regarding the risk of bias and applicability  15]. Fo. Fo15]. J index extracted from the receiving operating characteristic curve.Data extracted from articles include author names and country, year of publication, cancer, and control type, sample type, sample size, techniques used in experiments, and the AUC value in diagnosis. Besides, the true-positive, false-positive, true-negative, and false-negative numbers were extracted directly from articles or calculated indirectly using sensitivity and specificity corresponding to the maximum Youden's B = 2000 resampling iterations). The heterogeneity of diagnostic test accuracy between studies was measured by Higgins and Thompson's I2-statistic, which is significant if I2 ≥ 50%. Subsequently, the Leave-One-Out analysis was used to detect outlier studies, while meta-regression was performed to explore heterogeneity sources. Moreover, we used the funnel plot asymmetry statistic and the skewness of the standardized deviates to assess publication bias. All data analyses were done with the guidance of Shim et al., Noma et al., and Harrer et al. [P < 0.05 was considered statistically significant.We used the random-effects model to estimate pooled DOR, sensitivity, specificity, positive likelihood ratios, and negative likelihood ratios of circulating miR-1246 in cancer screening. Also, we constructed SROC curves and calculated summary AUC values, then compared them between groups using the bootstrap test . That is why we applied the random-effects model for the analyses.The analyzed results indicated that circulating miR-1246 can differentiate cancers with 84.2% sensitivity (95% CI: 79.4-88.1) and 85.3% specificity . We performed subgroup analyses and observed that cancer type, control type, sample type, sample size, technique used, and data extraction method could contribute to the sensitivity, specificity, and DOR differences between studies , healthy control type , and RT-qPCR technique  are independent sources  and signaling pathways  related to the cell proliferation, angiogenesis, antiapoptosis, carcinogenesis, invasion, migration, metastasis, and therapy resistance [miR-1246 has been evidenced as an oncogene that regulates multiple genes (sistance . Accordisistance . The stusistance .We conducted a systematic review and performed a meta-analysis on 29 individual studies from 9 countries, including 12 cancer types, over 5900 samples, and confirmed that extracellular circulating miR-1246 has good sensitivity, specificity, and robust performance in screening cancers . ImpressThis study highlights the diagnostic power of extracellular circulating miR-1246 for cancers. However, most included studies comprise healthy individuals as the control group , which iThe results of this study indicated that extracellular circulating miR-1246 has good sensitivity, specificity, and robust performance, which might serve as a reliable biomarker in screening cancers, especially breast cancer.


To review the current evidence on the risk of gestational diabetes mellitus (GDM) in women with endometriosis, taking into account relevant confounders such as the higher frequency of Assisted Reproductive Technologies (ART) conceptions. Database searches on PubMed, Medline, Embase and Scopus through June 2022, using combinations of relevant keywords. A total of 18 studies, involving N = 4,600,885 women, were included. The overall risk of GDM in endometriosis patients was significantly higher than in controls . This significant association persisted in natural pregnancies  but not in pregnancies conceived through ART . Based on the limited number of studies that examined this association in relation to endometriosis phenotype, an increased risk was found in more severe stages  but independently from localization of the lesions. Endometriosis increases the risk of GDM, with a possible progressive effect in more advanced stages of the disease. Although the effect magnitude may be limited in some subgroups, this finding has a clinically relevant impact due to both the strong biological plausibility and to the relatively high incidence of both endometriosis and GDM. The scientific literature defines GDM as a state of hyperglycemia developing in pregnancy and resolving following delivery, caused by insulin resistance or reduced insulin production. Risk factors for GDM encompass pre-pregnancy overweight and obesity, advanced maternal age, excessive weight gain during pregnancy, a family history of T2DM, previous pregnancies with GDM, having given birth to a baby weighing over 4000 g and having multiple pregnancies.Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in obstetrics and a growing public health concern, given its strong prediction of future type 2 diabetes mellitus (T2DM) in both mothers and infants2. The inflammatory response reduces both insulin action and pancreatic β-cell compensatory reaction, promoting the development of GDM3. Uncontrolled maternal hyperglycemia contributes to obstetric complications, such as polyhydramnios, macrosomia, labor anomalies or premature birth, to adverse neonatal outcomes, such as hypoglycemia and delayed lung maturation, with long-term consequences for the offspring, like an increased risk of obesity, T2DM and cardiovascular diseases later in life4.In GDM, the pregnant woman’s metabolism influences both maternal and fetal heath. Excessive carbohydrates/lipids intake raise glucose levels stimulating maternal pancreas to release additional insulin with production of excessive body fat. Immune and inflammatory responses are generated within white adipose tissue, resulting in a low-grade, systemic, chronic metabolic inflammation7, leading to a three-fold increase in risk11. PCOS determines pre-existing insulin resistance and compensatory hyperinsulinemia, which lead to hyperandrogenemia that exacerbates hyperglycemia14. The resulting inflammation impairs β-cell function, further contributing to hyperglycemia during pregnancy15.GDM is the most frequently reported pregnancy complication among women with polycystic ovary syndrome (PCOS)18; within this line of research, the association between endometriosis and GDM remains unclear. Based on evidence that chronic inflammation and prolonged cytokine exposure increase the risk of GDM19, it is plausible that the subclinical inflammation underneath endometriosis might also exhibit this positive association. Notably, available findings are largely influenced by relevant confounders, such as the frequent need of affected women to undergo Assisted Reproductive Technologies (ART) procedures, which ‘per se’ increase the risk of GDM20; (2) a novel hypothesis by evolutionary biologists supporting the idea that endometriosis and PCOS represent extreme and diametric (opposite) outcomes of variations in the hypothalamic-pituitary–gonadal axis development and activity, with endometriosis mediated by low prenatal testosterone and PCOS mediated by high prenatal testosterone22. This diametric disorder hypothesis predicts that women with PCOS and those with endometriosis might display opposite hormonal and metabolic phenotypes also during pregnancy.The rationale for our research question is based upon two observations: (1) the growing interest in adverse pregnancy and neonatal outcomes among women with endometriosisThe purpose of this systematic review and meta-analysis was to synthesize the best available evidence regarding the association between GDM and endometriosis. The influence of medically assisted reproduction in assessing this association was also considered.40, involving N = 4,600,885 women, met the original inclusion criteria. Fifteen cohort studies40  and 3 case–control studies37 (N = 869) were included. Among the cohort studies, 10 were retrospective40 (with 2 of them31 employing a multicentric design), 2 were prospective36, 2 were based on a historical cohort29 and 1 was a nationwide study39. Out of the 3 case–control studies, 2 had a retrospective design33, while 1 was a prospective study37. A comprehensive summary of the characteristics of the included studies can be found in Table The PRISMA flow diagram of the review process is illustrated in Fig. 40 studies included in the qualitative synthesis, two studies29 were based on the same historical cohort and study period, suggesting a high likelihood of data redundancy. Consequently, the quantitative synthesis was performed by omitting the study by Luke et al.28.Out of the 18N = 4,114,833 patients  came from the largest study39 whereas only N = 88 women (n = 40 with endometriosis and n = 48 controls) were included in the smallest24.The population size of the included studies was highly variable: a total of 38, the diagnosis of endometriosis was based on surgical and histological confirmation of the disease. However, only two studies35 provided a complete description of the anatomical localizations of endometriosis lesions, whereas five studies38 reported data on endometriosis severity according to the revised American Fertility Society (r-AFS) staging system41. Notably, two studies focused exclusively on women with deep endometriosis (DE)31: one study26 included women with nodules surgically treated by segmental bowel resection, while another study31 evaluated women still exhibiting a posterior DE lesion of at least 2 cm on ultrasound assessment after a previous incomplete surgical excision.In most of the included studies36 performed a diagnostic laparoscopy to rule out the disease in controls. Regarding diagnosis of gestational diabetes, 8 studies40 used a positive oral glucose tolerance test (OGTT) as the criterion. Specifically, one study25 followed the Canadian Guidelines42, one32 followed the Japanese Guidelines43, one38 adhered to the Polish Guidelines44, and another40 followed the American Guidelines45. Interestingly, one study diagnosed gestational diabetes in cases and controls through self-administered questionnaires36; the Authors reported that, according to their previous large prospective cohort study, self-reported adverse pregnancy outcomes are validly reported, with a 94% confirmation rate for GDM47.In most studies, controls were defined as women without endometriosis; however, only one study40 were at low risk of bias, 839 had a moderate risk of bias, and the remaining one24 was at high risk of bias  with moderate heterogeneity (I2 = 53.43%) and non-significant publication bias   Fig. .Figure 240 met the inclusion criteria: 2 were retrospective cohort studies40, 2 were retrospective case–control studies33, 1 was a prospective case–control study37 and 2 were historical cohort studies29. Population sizes varied significantly: the total sample ranged from N = 92 women (n = 49 with endometriosis and n = 43 controls) in the smallest study23 to N = 2,307 women  in the largest29.In total, 7 studies33 considered ART cycles with pregnancies achieved through both fresh and frozen embryo transfers. One study included only fresh cycles37, and another included only frozen ART cycles40. For the majority of the included studies, we were able to extract data on our primary outcome specifically for male factor infertility controls40. General characteristics of the included studies are summarized in Table Most included studies40 were judged at low risk of bias, and three33 had a moderate risk of bias  . Symmetry was observed upon visual inspection of the funnel plot  and Begg’s test  showed no evidence of a small-study effect. Subgroup analyses according to predefined moderators did not find any group difference in the pooled risk estimates .Overall, only 3 studies24 also included conceptions through first-level infertility treatments (ovulation induction and intrauterine insemination). However, infertility treatments were reported to be comparable between the groups. Since conceptions through in-vitro fertilization (IVF) were excluded a priori, we did not consider any of the pregnancies evaluated by Mekaru et al.24 as obtained by ART. General characteristics of the studies included in this comparison are summarized in Table Notably, the study population of Mekaru et al.39 and one had a high risk of bias24   and a non-significant small-studies effect  , while the smallest38 included only N = 64 women .Overall, 4 studies met the inclusion criteria39 included ART cycles with pregnancies obtained by both fresh and frozen embryo transfers; the remaining two studies38 did not mention if ART cycles included only fresh or only frozen embryo transfers or both. Notably, data from Warzecha et al.38 for natural conception also included first-level infertility treatments (intrauterine insemination). General characteristics of the included studies are summarized in Table Of all, 2 studies38, while the remaining three were at moderate risk of bias39 , with no heterogeneity in pooling data (I2 = 0%)  showed absence of significant publication biases  . Both had a retrospective design; one was a cohort study35 and one was a case–control study33. The overall study population was relatively small (N = 350). Interestingly, the prevalence of DE in the original study populations was 15.3% in the study by Mannini et al.35 and 43.4% in that by Jacques et al.33. General characteristics of the included studies are summarized in Table Overall, only 2 studies35 and the other was at moderate risk of bias33 , with no heterogeneity (I2 = 0%) . The prevalence of stage III–IV endometriosis patients according to the r-AFS classification41 was similar in the two study populations: 57.81% in Warzecha et al.’s cohort38 and 46.85% in Jacques et al.’s sample33. General characteristics of the two included studies are summarized in Table Overall, only two studies provided complete data on the prevalence of GDM according to endometriosis severitymall N = 75. The p38, and the other study was at moderate risk of bias33 . Patients with advanced stages of the disease showed more than threefold increase in the risk of the outcome, with no study heterogeneity (I2 = 0%) . On the other hand, ovulatory disorders, in general, have been shown to be associated with GDM49 and could have been represented consistently within the control groups of the ART studies. In any case, our results confirm the suggested role of ART as a major confounder in interpreting current research data and the imperative need to weigh comparisons according to this eventual parallel risk factor for GDM in controls.To account for ART influence on pooled risk estimates, in this meta-analysis we stratified comparisons of endometriosis to unaffected controls according to the method of conception; interestingly, results remained stable only when accounting for spontaneous conceptions. Infertile PCOS women, who are known to carry a higher risk of GDM50, this does not seem to happen for GDM. Our findings, supporting no differences in risk estimates between endometriosis pregnancies conceived naturally or by ART, strengthen the idea that endometriosis itself and not ART treatment determines an increase in GDM risk in women affected by the disease. This is in line with recent findings suggesting that endometriosis is associated with adverse pregnancy outcomes independently from infertility diagnosis or fertility treatment51.Interestingly, unlike pregnancy outcomes related to placental dysfunctions in which endometriosis and ART conceptions somehow present additive risks41 of endometriosis and GDM was observed in this meta-analysis. This is quite interesting considering that endometriosis progression has been related to increased levels of circulating and peritoneal fluid interleukins, systemic inflammation, and immune activation, with an overall higher prevalence of autoimmune diseases52.An effect gradient between r-AFS stage54. GDM itself is not only related to increased insulin resistance and glucose intolerance, but also to low-grade systemic inflammation55. While adipose tissue is increasingly recognized as a legitimate immune organ in PCOS patients, in endometriosis patients, the disease itself contributes to the production of inflammatory effectors such as leptin, tumor necrosis factor-alpha and interleukin-6 with reduced production of adiponectin, potentially leading to insulin resistance. Leptin levels are increased and those of adiponectin decreased in women with endometriosis56, particularly during pregnancy when the mother frequently increases carbohydrates intake.The possible etiology of GDM in endometriosis patients is likely linked to the systemic inflammation associated with the disease22, which suggests that PCOS and endometriosis would arise as maladaptive extremes due to variation in hypothalamic–pituitary–gonadal axis development and intrauterine androgens levels. According to this hypothesis, the metabolic and endocrine alterations observed in PCOS, such as GDM, would not be present in women with endometriosis22. On the other hand, we cannot exclude that GDM in endometriosis arises as a phenomenon secondary to sustained inflammation and immune dysregulation and therefore would be totally unrelated to the mechanisms underlying the disease etiology. Indeed, endometriosis is a lifelong disease in which chronic inflammation acts as one of the main drivers possibly involved not only in the genesis and maintenance of endometrial ectopic lesions, but also in the establishment of a susceptibility status for several comorbidities in the life course of women affected.Our results do not seem to support the diametric model proposed by the Crespi’s groupThe major strength of our work is the high biological plausibility justifying the association found, and the fact that the incidence of both endometriosis and GDM is such that the emerged risk increase has a significant impact on clinical practice. The finding that endometriosis increases GDM risk further supports the idea that women with endometriosis may represent a unique population at greater risk for adverse outcomes across pregnancy. If currently GDM diagnosis is based on evaluation of blood glucose levels at late stages of pregnancy, the presence of endometriosis should potentially modify this criterion. Therefore, endometriosis may be considered as a red flag and should be included among the routinely early assessed risk factors for GDM. In this sense, the earlier and more specific detection of GDM in women with endometriosis could improve pregnancy management and final maternal–fetal outcomes. Indeed, elucidating pathways for prevention, screening and intervention in pregnancies of women with endometriosis will be critical to improve the health of these women and their children.57 to date has specifically investigated the association between endometriosis and GDM, concluding that endometriosis had no significant effect on GDM risk. Our analysis has several added values, including the fact that we have incorporated more recent data. Even more importantly, the novelty of our meta-analysis is that results were provided weighting and stratifying the estimates accounting for clinically relevant confounders, managing the possible over-estimate of the effect at a population level. Third, the estimation of the certainty of the evidence following GRADE guidelines58 allowed us to identify missing gaps in current knowledge. Forth, the estimation method59 adopted allowed us to produce a robust, unbiased, nonnegative estimate of between-study variability. In this meta-analysis there are also some limitations that must be acknowledged. First, the evidence was mainly generated by observational studies, so the quality of the evidence is moderate to low according to GRADE guidelines58. Secondly, sample sizes of original studies were quite heterogeneous, with very large study populations that could have strongly influenced our results. To limit the larger weight in risk estimate from larger studies, sensitivity analysis was obtained by omitting one study at time, giving consistent results. Thirdly, substantial heterogeneity across studies was observed particularly in the population under study and the definition of endometriosis and/or GDM. These limitations were managed with subgroup analysis, even if the number of studies available was limited and the resulting quality of the evidence was graded as low, hindering generalization of some results. This suggests that further research is needed, possibly standardizing the reporting of disease prevalence by endorsing major international guidelines to reach more robust conclusions.This study presents other important strengths. First, only one meta-analysis60. We can also speculate on the possibility of GDM prevention based upon adequate treatment of endometriosis with pharmacological or surgical methods. More research is required to examine this topic in more detail, including investigations of the underlying mechanisms explaining the association of endometriosis with GDM.In conclusion, this systematic review and meta-analysis showed that endometriosis is associated with an increased rate of GDM. Therefore, a positive anamnesis for endometriosis must be considered in the prevention, early diagnosis and management of GDM, both in clinical practice and in research settings. It is important to consider the risk of other coexisting conditions frequently encountered in patients with endometriosis, such as autoimmune diseases, as clearly these risks contribute to the risk of adverse pregnancy outcomes61 and the Meta-analysis Of Observational Studies in Epidemiology (MOOSE)62 guidelines. The study protocol was prospectively registered  on the publicly accessible database PROSPERO with the registration ID CRD42022309113.This is a systematic review and meta-analysis performed according to the Preferred Reporting Item for Systematic Reviews and Meta-analysis (PRISMA)https://endnote.com, accessed on 02 July 2022). The literature search and the article eligibility were independently assessed by two Authors (N.S. and L.L.P). Disagreements were resolved by discussion with a third reviewer (P.V.).A systematic literature search from April 2022 through June 2022 was performed using the following databases: PubMed, Medline, Embase and Scopus. MeSH terms for PubMed and comparable terms for other databases were used. Literature search was based on the following search terms’ combination:  OR (pregnancy diabetes) OR (pregnancy complication) OR  OR (pregnancy out-comes)) AND ((endometriosis) OR (endometrioma)) AND ((IVF) OR (ICSI) OR (ART) OR  OR (spontaneous conception)) and limited to studies on humans. No restrictions for year of publication and geographic location were applied. Only full-length manuscripts written in English language and published in peer-reviewed journals were screened. Bibliography of relevant papers was also examined to identify any relevant article not captured by the electronic searches. Duplicates were removed by Endnote Software (available online: Case–control and cohort studies reporting the incidence of GDM in pregnant women with diagnosis of endometriosis compared with a control group were included. We did not include descriptive studies (case-reports and case-series) and studies that did not reported original results .66, suggesting absence of infertility issues for the female partner . Controls with PCOS diagnosis were always excluded, in light of our research question. Additionally, studies where the entire population of controls was reported to have PCOS and/or altered glucose tolerance or insulin-resistance were a priori excluded. Studies in which for controls it was impossible to ascertain that infertility was unrelated to endometriosis were excluded.We included only original studies reporting a confirmed diagnosis of endometriosis in cases; women with endometriosis were included regardless of their medical/surgical treatment history or symptoms before pregnancy. The controls were women without a diagnosis of endometriosis, including both fertile and infertile women referred to a specialized Fertility Centre. When original studies reported data in controls stratified by specific indications for ART, we used the reference group whose infertility was due to male factor as the first option or, as a second option, to other indications for ART with no diagnosis of endometriosis. Male factor infertility was used as a reference group in several other studies of ART outcomesMedically assisted reproduction was defined as a pregnancy achieved by second-line ART treatments, including IVF or intracytoplasmic sperm injections (ICSI) procedures. Studies not mentioning the mode of conception  for endometriosis cases and/or controls were excluded.41; type of controls ; mode of conception ; type of ART ; demographic data  and parity); other possible confounding variables at multivariate analysis.Data from original studies were extracted by two independent reviewers (N.S. and L.L.P). The following data were collected and tabulated: author; publication year; study country; study design; sample size; frequency of GDM in cases and controls; diagnostic modality for endometriosis; criteria followed to define gestational diabetes; endometriosis localization ; endometriosis severity according to r-AFS67. Based on answers to the signaling questions of the seven bias domains for ROBINS-E tool68, an overall judgment was reached so that each study was classified as follows: low risk of bias, when the study was considered comparable to a well-performed randomized trial; moderate risk of bias, for studies providing sound evidence for a non-randomized study but still not comparable to those coming from a well-performed randomized trial; serious risk of bias, when the study had one or more important problems ; critical risk of bias, when the study was judged as too problematic to provide any useful evidence.The risk of bias within and across studies was assessed referring to the Risk of Bias In Non-randomized Studies of Exposures (ROBINS-E) tool from the updated Cochrane collaboration guidelines58: high, moderate, low or very low. Risk of bias was evaluated by two independent reviewers (N.S. and L.L.P); where disagreement occurred, consensus was reached with input from a third team member (P.V.).To guide interpretation of the confidence in the effect estimates, the certainty of the evidence was graded into four levels according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines69, studies where the diagnosis of diabetes occurred during the 1st trimester of pregnancy were not included. In light of the absence of a worldwide adopted diagnostic criteria for GDM, we planned a subgroup analysis for the primary outcome according with the diagnostic modality for GDM reported in original studies.The a priori planned primary outcome of the current meta-analysis was the incidence of GDM in pregnancies from endometriosis patients compared to unaffected controls. Original studies enrolling women with pre-gestational diabetes or conditions characterized by altered glucose metabolism not satisfying the diagnosis of GDM  were excluded. Also, according with American Diabetes Association59. When the assumption of study homogeneity was reasonable, a fixed-effects (FE) model using Mantel–Haenszel method was also performed70.To provide a theoretical underpinning of the qualitative synthesis, a quantitative synthesis of included studies was also performed by an independent reviewer (N.S.). Original data on binary outcome measures were extrapolated so that Log Odds Ratios (ORs) with 95% Confidence Intervals (CIs) and corresponding standard errors (SEs) were computed from original data and pooled together. A random-effects (RE) meta-analysis model was performed to estimate pooled effect sizes and a restricted maximum likelihood (REML) estimation method was used to compute between-study variabilities  was used for all statistical analyses. A p-value < 0.05 was considered to be statistically significant.The primary analysis to answer the research question was obtained comparing pooled data on the risk of GDM in endometriosis patients versus controls, independently from mode of conception . Pooled risk estimates for the primary outcome were also provided separately according to the following groups comparisons: (1) pregnancies from endometriosis patients conceived by ART versus pregnancies from controls conceived by ART; (2) spontaneous pregnancies in endometriosis women versus spontaneous pregnancies in controls; (3) pregnancies in endometriosis patients conceived by ART versus pregnancies in endometriosis cases conceived by natural conception; (4) DE versus all other localizations of endometriosis; (5) cases affected by stage III-IV endometriosis versus stage I-II endometriosis.71 and the adjusted rank correlation test proposed by Begg et al.72.To investigate the impact of publication bias and small-study effects on final results, funnel plots were implemented scattering the logarithm of the study-specific effect sizes (log ORs) against their SEs. Funnel plot asymmetry was tested using both the linear regression-based method according to Egger et al.2 statistics which estimates the percentage of total variation across studies that is due to between-studies heterogeneity rather than to sampling variation73. I2 index values were interpreted as follows: 0–25%, insignificant heterogeneity; 25–50%, low heterogeneity; 50–75%, moderate heterogeneity; > 75%, high heterogeneity1. The Chi-squared statistic was also interpreted as a result of heterogeneity, so that a low p-value (< 0.10) questioned the validity of the pooled risk estimates74.Between-study heterogeneity was explored throughout the I75 to explore the level of heterogeneity explained by study-level covariates. We planned to carry out subgroup-analyses accounting for the following study moderators: study design, study country, endometriosis diagnosis , GDM diagnosis , age of population (≤ 35 years or > 35 years or unknown), BMI categories  and parity (both multiparous and nulliparous or only nulliparous). For subgroup-analyses performed selectively on ART population, the following covariates were also included: type of control for endometriosis cases  and type of ART cycle (fresh and frozen or only fresh or only frozen).Subgroup-analyses were performed according to Wang et al.Supplementary Information.


In recent decades, diverse nomograms have been proposed to predict extraprostatic extension (EPE) in prostate cancer (PCa). We aimed to systematically evaluate the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting EPE in PCa. The purpose of this meta-analysis is to provide baseline summative and comparative estimates for future study designs.The PubMed, Embase, and Cochrane databases were searched up to May 17, 2023, to identify studies on prediction nomograms for EPE of PCa. The risk of bias in studies was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Summary estimates of sensitivity and specificity were obtained with bivariate random-effects model. Heterogeneity was investigated through meta-regression and subgroup analysis.Forty-eight studies with a total of 57 contingency tables and 20,395 patients were included. No significant publication bias was observed for either the MRI-inclusive nomograms or clinical nomograms. For MRI-inclusive nomograms predicting EPE, the pooled AUC of validation cohorts was 0.80 . For traditional clinical nomograms predicting EPE, the pooled AUCs of the Partin table and Memorial Sloan Kettering Cancer Center (MSKCC) nomogram were 0.72  and 0.79 , respectively.Preoperative risk stratification is essential for PCa patients; both MRI-inclusive nomograms and traditional clinical nomograms had moderate diagnostic performance for predicting EPE in PCa. This study provides baseline comparative values for EPE prediction for future studies which is useful for evaluating preoperative risk stratification in PCa patients.This meta-analysis firstly evaluated the diagnostic performance of preoperative MRI-inclusive nomograms and clinical nomograms for predicting extraprostatic extension (EPE) in prostate cancer (PCa) (moderate AUCs: 0.72–0.80). We provide baseline estimates for EPE prediction, these findings will be useful in assessing preoperative risk stratification of PCa patients.• MRI-inclusive nomograms and traditional clinical nomograms had moderate AUCs (0.72–0.80) for predicting EPE.• MRI combined clinical nomogram may improve diagnostic accuracy of MRI alone for EPE prediction.• MSKCC nomogram had a higher specificity than Partin table for predicting EPE.• This meta-analysis provided baseline and comparative estimates of nomograms for EPE prediction for future studies.The online version contains supplementary material available at 10.1186/s13244-023-01486-7. Oncologic radicality and good functional outcomes are two clinical priorities for the surgical treatment of prostate cancer patients. Nerve-sparing surgery could be chosen to preserve urinary continence and erectile function for low-risk patients. However, nerve-sparing surgery in high- or moderate-risk patients is associated with an increased risk of positive surgical margins (PSMs) in postoperative specimens. Therefore, planning the therapeutic schedule for PCa patients must be based on comprehensive risk assessment and staging. Making these clinical decisions depends on the predicted probability of EPE of prostate cancer. EPE is associated with a high risk of PSMs and early biochemical recurrence and can cause a worse prognosis than organ-confined tumors , 2. ConsThere are several widely used clinical prediction tools for evaluating EPE, such as the Partin table , the CanThe previous study has summatively determined the accuracy of MRI for diagnosing EPE . To our This systematic review and meta-analysis was registered with PROSPERO (CRD42022361098). This study was conducted following the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies .A systematic literature search was performed on the PubMed, Embase, and Cochrane databases up to May 17, 2023. The search terms included prostate cancer, prostate neoplasm, prostate carcinoma, extranodal extension, extraprostatic extension, extracapsular extension, nomogram, risk model, Partin table, and prediction. No language restriction was applied. We also manually reviewed the reference lists of the included studies.Two investigators (both with 6 years of research experience) independently assessed all citations according to the predefined inclusion and exclusion criteria. Disagreements were resolved through discussion and consensus. The following inclusion criteria were used: (1) primary studies for developing, validating, or updating preoperative nomograms/models  to predict pathological EPE (pT3 stage) of PCa patients; and (2) studies published in English.One investigator (with > 6 years of research experience) extracted the characteristics of all included studies independently, including study type; country; reference standards; patient age; sample size; clinical and MRI predictors; and TP, FN, TN, and FP values. To reduce the risk of data duplication and overlapping cohorts, for studies that reported multiple readers, we only extracted the results of reader 1 as a representative and incorporated them into the meta-analysis. For studies that reported multiple sensitivities/specificities of the same cohort based on different algorithms, we only extracted the highest sensitivity/specificity. For studies that reported multiple sensitivities/specificities based on different cohorts or different nomograms, we extracted all of them as independent contingency table results.We assessed eligible studies for adherence to reporting guidelines according to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist, which consists of 37 items in 22 criteria to aid transparent reporting of studies that develop and/or validate prediction models . Five itThe Prediction model Risk Of Bias ASsessment Tool (PROBAST)  was usedI2 estimate [p < 0.05 indicated the presence of bias. Univariate meta-regression analysis was performed to investigate potential heterogeneity from predictors of nomograms, as well as other baseline parameters, including side-specific or whole-gland pathological EPE-based, pathological EPE rate, MRI predictor and slice thickness. Meta-analysis was conducted with Stata version 15.0.Meta-analysis was performed with the recommended bivariate random-effects meta-analysis model . Statistestimate . Contingestimate . Funnel The search strategy yielded a total of 671 results . After duplicates were removed (101), 570 studies were screened. After screening abstracts and full texts, 522 articles were excluded; the exclusion criteria are shown in Fig. A total of 20,395 patients were included. The main characteristics, demographics, and MRI information for the MRI-inclusive nomograms and clinical nomograms are presented in Tables According to TRIPOD items Fig. , the totThe risk of bias and applicability concerns of all studies were assessed by PROBAST Fig. . For thep < 0.05). Two studies showed that the MRI + MSKCC/Partin nomogram provided no additional risk discrimination over the clinical nomogram alone (p > 0.05) [A summary of the qualitative analysis is presented in Supplementary Table  > 0.05) , 12. TheP= 0.17); however, significant funnel plot asymmetry was observed for studies with clinical nomogram . The pooled sensitivities, specificities, and AUCs estimated by the HSROC curve . The source of heterogeneity of pooled specificity did not be found from EPE basing, pathological EPE rate, slice thickness, MRI time, or AI-based predictors . For clinical nomograms, the pooled specificity of the MSKCC nomogram was significantly higher than that of the Partin table (p < 0.001); there was no significant difference of pooled sensitivity between the Partin table and MSKCC nomogram.Meta-regression analysis was performed for all validation cohorts to identify the source of pooled heterogeneity Table . For MRIFagan plots were drawn to calculate the posttest probabilities of all validation cohorts for MRI-inclusive nomogram and clinical nomogram respectively Fig. . Within This present meta-analysis first systematically evaluated the diagnostic performance of preoperative MRI-inclusive nomograms and traditional clinical nomograms for predicting pathological EPE of PCa. Our meta-analysis based on validation cohorts showed that both MRI-inclusive nomograms and traditional clinical nomograms had moderate AUCs (0.72–0.80) for predicting EPE. We found that the pooled specificity of MSKCC nomograms was higher than that of Partin table. Our study provides baseline summative estimates for EPE prediction in PCa as well as provide comparative estimates for future study designs. These findings will be useful in the assessment of preoperative risk stratification and individual treatment strategies for PCa patients.There are multitudinous studies that tried to head-to-head compare the diagnostic performance of the MRI-inclusive nomogram and traditional clinical nomogram for EPE prediction and suggested that MRI combined clinical nomogram can improve the diagnostic performance of traditional clinical nomogram. However, in our systematic review of 22 studies, we found that most of these studies were TRIPOD 1 type, which means they were limited to developing model. As we know, the overfitting of prediction model generally exists in development cohorts, particularly in a small data set. And the degree of overfitting can vary widely depending on the type of internal validation techniques employed, such as cross-validation or bootstrapping, leading to biased or over-optimistic performance results . TherefoCompared with a previous meta-analysis by de Rooij et al. , which rIn particular, although our regression analysis did not find significant diagnostic superiority of nomogram which using AI/radiomics-based MRI predictors in EPE prediction, this may be due to the limited statistic power given the small number of studies on AI/radiomics-based MRI predictors In our meta-regression analysis, no significant difference in sensitivity was observed between the Partin tables and MSKCC nomogram. The specificity of the MSKCC nomogram was significantly higher than that of the Partin table (0.77 vs. 0.60). One difference between the MSKCC nomogram and the Partin table is the addition of the biopsy-positive core ratio. It has been reported that using continuous risk variables in nomograms rather than binary variables can substantially improve predictive accuracy , which mI2). Third, we could not explain the heterogeneity completely because many studies did not report sufficient information for all characteristics. Finally, there are no established MRI assessment criteria for EPE; therefore, the imaging predictors varied widely. To overcome these issues, we suggest that studies should be devoted to establishing a standardized MRI-EPE evaluation system, which would be helpful to improve diagnostic accuracy and repeatability. Moreover, nomograms need to be updated, and new biomarkers need to be added to further improve the diagnostic performance. In addition, no studies have focused on predicting microscopic EPE, which is the most relevant for RP purposes, as overt EPE is presumably easily found on MRI; thus, more studies should be carried out to evaluate microscopic EPE in the future.Some limitations existed in our study. First, the number of eligible studies included was small, and a large number of studies were excluded due to a lack of data to calculate TP, FN, FP, and TN. Second, there was significant heterogeneity in patient populations, clinical characteristics, and MRI practice, which increased the risk of intrinsic bias and led to significant heterogeneity  for predicting EPE. MRI combined clinical predictors can improve diagnostic value to MRI alone, which could aid urologists in making decision protocols for local PCa patient treatment.Additional file 1. Supplementary material. Supplementary Figures. Supplementary Tables.


The pooled SMD values were not substantially altered in sensitivity analysis. There was no publication bias. In conclusion, our meta-analysis has shown that serum paraoxonase, but not arylesterase, activity is significantly lower in psoriasis, suggesting an impaired antioxidant defense in these patients.Human serum paraoxonase-1 (PON-1) is a critical antioxidant defense system against lipid oxidation. Decreased PON-1 activity has been associated with systemic oxidative stress in several disease states. We conducted a systematic review and meta-analysis of plasma/serum concentrations of PON-1 paraoxonase and arylesterase activity in psoriasis, a chronic immune-mediated and inflammatory skin disease. The electronic databases PubMed, Web of Science, and Scopus were searched from inception to November 2021. In total, 14 studies in 691 psoriatic patients and 724 healthy controls were included in the meta-analysis. Serum paraoxonase activity was significantly lower in psoriatic patients (SMD = − 2.30, 95% CI − 3.17 to − 1.42;  Psoriasis is a chronic and disabling immune-mediated and inflammatory skin disease. The vulgaris form, representing 90% of cases, manifests as erythematous-desquamative plaques that are well delineated from normal skin . The psoPrevious studies have demonstrated the presence of alterations in plasma lipids, lipoproteins, lymphocytes, polymorphonuclear leukocytes and platelets in psoriatic patients , 3. In pFurthermore, increased production of reactive oxygen species (ROS) and inflammatory cytokines contribute to the development and progression of psoriatic lesions. Increased concentrations of biochemical markers of lipid peroxidation and a concomitant decrease in cellular and extracellular antioxidants have been demonstrated in subjects with psoriasis .Human serum paraoxonase-1 (PON-1), also known as arylesterase (ARE), is a critical antioxidant defence system against lipid oxidation. It is a glycoprotein of 43–45 kDa and its gene is located in the long arm of chromosome 7 (q21–q22) in humans. PON-1 is an antioxidant and anti-inflammatory calcium-dependent esterase, associated with high-density lipoprotein (HDL), that is used as a marker of lipid peroxidation , 10.PON-1 hydrolyzes the organophosphate substrate paraoxon , the toxic metabolite of the insecticide parathion and aromatic esters, such as phenylacetate  .PON-1 is expressed in the liver and excreted in the blood with the HDL particle . Serum PDecreased PON-1 activity is considered a marker of increased systemic oxidative stress and increased conversion of HDL to a dysfunctional pro-inflammatory and pro-atherogenic state. Not surprisingly, decreased PON-1 activity has been associated with the development of cardiovascular disease  and the In order to capture and interpret the available evidence regarding the relationship between psoriasis and PON-1 activity, we conducted a systematic review and meta-analysis of studies reporting plasma/serum concentrations of PON-1 paraoxonase and arylesterase activity in psoriatic patients and control groups.A systematic search of publications in the electronic databases PubMed, Web of Science and Scopus from inception to November 2021, was conducted using the following terms and their combination: “Paraoxonase” or “PON” or “Paraoxonase-1” or “PON-1” or “arylesterase” and “psoriasis.” Abstracts were screened independently by two investigators to establish relevance. If relevant, the two investigators independently reviewed the full articles. Eligibility criteria were: (i) assessment of paraoxonase and arylesterase activity in plasma or serum; (ii) comparison of subjects with psoriasis and healthy controls (case–control design); (iii) sample size ≥ 10 patients with psoriasis; (iv) English language; and (v) full-text publications. The references of the retrieved articles and reviews were also searched to identify additional studies. Any disagreement between the reviewers was resolved by a third investigator. The risk of bias was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for analytical studies. A score of ≥ 5, 4 and < 4 indicated low, moderate and high risk, respectively .The certainty of evidence was assessed using the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) Working Group system. GRADE considers the study design , the risk of bias (JBI checklist), the presence of unexplained heterogeneity, the indirectness of evidence, the imprecision of results , the effect size   and the Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were used to express forest plots of continuous data and assess differences in PON-1 or ARE concentrations in psoriatic patients vs. healthy controls due to the different units of measurement  used to express the paraoxonase or arylesterase concentrations in studies.p value < 0.05 was considered statistically significant. When necessary, the means and standard deviations were extrapolated from medians and interquartile values (or ranges), as previously reported by Wan et al. and Hozo et al. [A o et al. , 22, or Q statistic (significance level at p < 0.10). The I2 statistic, a quantitative measure of inconsistency across studies, was also calculated [I2 statistic value ≥ 50% [Heterogeneity of SMD across studies was tested by using the lculated , 24. StaSensitivity analysis was conducted to investigate the influence of each study on the overall risk estimate, by sequentially excluding individual studies .p < 0.05 level of significance [To evaluate the presence of potential publication bias, the associations between study size and magnitude of effect were analyzed by means of Begg’s adjusted rank correlation test and Egger’s regression asymmetry test at the ificance , 27. Theificance . UnivariA flowchart describing the screening process is presented in Fig. Twelve studies in 537 patients  and 562 healthy controls with a mean age of 34 years  were evaluated , 34–42. The risk of bias was considered low in 10 studies and moderate in the remaining two Table .Table 2TI2 = 96.9%, p < 0.001). Thus, random-effects models were used. Overall, pooled results showed that PON-1 activity was significantly lower in psoriatic patients . In sensitivity analysis, the corresponding pooled SMD values were not substantially altered when individual studies were sequentially omitted  with a persistent extreme heterogeneity .The forest plot of PON-1 activity in patients with psoriasis and healthy controls is shown in Fig. p = 0.12 and Egger tests p = 0.06). Accordingly, the “trim-and-fill” method did not identify missing studies to be added in the funnel plot  and publication year . However, a significant relation was observed with gender . In sub-group analysis, reported in Fig. p = 0.001; I2 = 94.8%, p < 0.001) but not in studies conducted in Asia  or America .In univariate meta-regression, no significant associations were observed between the effect size and age . After considering the low risk of bias in 10 out of 12 studies (no rating change required), the extreme and unexplained heterogeneity (downgrade one level), the lack of indirectness (no rating change required), the relatively low imprecision , the relatively large effect size  and the absence of publication bias (no rating change required), the overall level of certainty remained low .Eight studies in 435 patients  and 504 healthy controls  were identified , 38–40. The risk of bias was considered low in seven studies and moderate in the remaining one.I2 = 90.1%, p < 0.001). Thus, random-effects models were used. Overall, pooled results showed no significant differences in serum ARE activity between patients and controls . Sensitivity analysis showed that the corresponding pooled SMD values were not altered when individual studies were sequentially omitted . After considering the low risk of bias in seven out of eight studies (no rating change required), the extreme and unexplained heterogeneity (downgrade one level), the lack of indirectness (no rating change required), the relatively high imprecision , and the lack of assessment of publication bias (downgrade one level), the overall level of certainty was downgraded to very low .t-tests did not show publication bias. Similarly, the “trim-and-fill” method did not identify potentially missing studies to be added to the funnel plot to ensure symmetry. In meta-regression analysis, only gender was significantly associated with the SMD for PON-1 activity. This observation is in line with studies in type-2 diabetes reporting a gender-specific effect on PON-1 activity [In our systematic review and meta-analysis, serum PON-1 paraoxonase, but not arylesterase, activity were significantly lower in psoriatic patients when compared to healthy controls. The relatively large SMD values for PON-1 activity indicate an effect size that is likely to be of biological and/or clinical relevance. Despite the extreme heterogeneity observed, in sensitivity analysis the effect size of PON-1 activity was not significantly affected when each study was in turn removed. The study by Shakoei et al.  influencactivity .In addition, only European studies detected a significant decrease in serum PON-1 activity in psoriatic patients. As studies have reported that a paraoxonase-1 gene polymorphism significantly affects paraoxanase activity levels in the general population , our res. [. [Although the exact mechanisms responsible for the lower serum concentrations of PON-1 activity in psoriasis are unclear, the presence of a chronic inflammatory state might play an important role. This proposition is supported by studies reporting that anti-psoriasis treatment was associated with a significant reduction in inflammatory markers and a significant increase in PON-1 activity . However.  did not . [.  did not . [Several PON-l gene polymorphisms may affect PON-l activity. One such polymorphism, L55M, involving a change of TTG codon into ATG in exon 3 of the gene, has been associated with reduced PON-l activity . Notably.  reportedA reduced PON-1 activity has been observed in several chronic inflammatory disease states. In a large prospective cohort of patients with atherosclerosis undergoing coronary angiography, those with the lowest PON-1 activity had a 3.4 times greater hazard of major cardiovascular events compared to those with the highest PON-1 activity . ImpaireBy our data, no significant differences were observed in serum ARE activity between patients and controls. However, the relatively small number of studies identified prevented meta-regression and sub-group analyses to investigate associations between SMD values and several study and patient characteristics.Husni et al.  showed tThe extreme between-study heterogeneity represents a limitation of our meta-analysis. However, there was no evidence of publication bias, and the overall effect size was not significantly influenced in sensitivity analyses. In addition, the comprehensive evaluation of the risk of bias and the certainty of evidence according to GRADE significantly strengthens the conclusion of our study.. The use of specific medications influencing PON-1 activity, such as etanercept or methotrexate, was not reported in the studies included in the analysis. Other preanalytical and analytical factors, such as the time required for sample processing or sample storage (different time and temperature), and the protocols and procedures of analytical method might also account for the heterogeneity.The lack of significant associations between study, clinical, and demographic characteristics and the SMD, barring the associations between gender and the SMD for PON-1 activity, suggests that other unreported factors might contribute to the observed heterogeneityIn conclusion, our systematic review and meta-analysis has shown that serum concentrations of PON-1 activity are significantly lower in psoriatic patients. Additional prospective studies are required to investigate the clinical impact PON-1 activity in this group.


Dear Editor,1. Therefore, we read with great interest the recently published meta-analysis in the International Journal of Surgery that compared the safety and efficacy of remimazolam with that of the traditional sedative propofol2. While we commend Zhao et al. for this timely work, which provides a high level of evidence for remimazolam use in endoscopic procedures, we would like to point out several issues regarding the statistical framework used in this meta-analysis that may compromise the reliability of their conclusions.As a new ultra-short-acting benzodiazepine anesthetic, remimazolam is exerting an important impact on endoscopic sedation3. How to include studies comparing multiple experimental groups for meta-analysis needs to be treated with caution. For example, for a study with ‘dose1 versus control’ and ‘dose2 versus control’ (two comparisons share the same control group), if several comparisons are simply entered into a meta-analysis, participants in the shared group will be double-counting, thus leading to a serious unit-of-analysis problem3. Specifically, three of the seven studies included in the present meta-analysis had multiple experimental groups based on the dose of remimazolam, but they all had only one control group, the constant-dose propofol group2. The authors simply included several comparisons from the same study together in the meta-analysis, which meant that the propofol group was double-counted among the participants. The double-counting of participants spuriously increased precision and resulted in an elevated risk of false positive conclusions. Unfortunately, 75% of adverse events  and 100% of secondary outcomes  meta-analyses in the study by Zhao et al. were affected by this bias. Take the hypotension outcome, for example the included Dai-2020 and Tan-2022 reported three and two remimazolam groups with different doses, respectively, while both had only one propofol group. Therefore, when pooling effect sizes, participants in the propofol groups of the two studies were repeatedly included three and two times, respectively. Ultimately, the effect sizes of these two studies accounted for 63.8% of the meta-analysis weights, while the number of their participants accounted for only 29.4% of the five studies included2. In fact, the Cochrane Handbook has provided several ways to address such multi-arm studies3:Combine multiple relevant experimental groups to create a single pairwise comparison. In most situations, this approach is recommended.Choose one pair of interventions while excluding others.Split the ‘shared’ group into several groups with smaller sample sizes and include all reasonably independent comparisons.Perform network meta-analyses.Firstly, the unit-of-analysis problem needs to be considered in this meta-analysis4. Zhao et al. used the funnel plot to examine publication bias and claimed that its risk was low for all endpoints except the time to discharge2. However, the funnel plot seems not to be applicable to the present meta-analysis. As a graphical tool relying on visual inspection, the funnel plot can only be used if the number of included studies is ten or more, otherwise it does not have sufficient testing power4. However, the authors included only seven studies in total, and even among the seven endpoints using the funnel plot, most (4/7) included fewer than five studies. Thus, the funnel plot may not provide reliable estimates of publication bias for the present meta-analysis. For example, the funnel plots for hypotension and bradycardia were not as symmetrical as the authors stated, and perhaps the small-study effects should be suspected2.Secondly, the methodology for assessing the risk of publication bias was incorrectly applied. Publication bias is a common problem in clinical research, which can lead to overestimation of benefits and underestimation of harmsI2<50% and P=0.1 as the criteria for no substantial heterogeneity and used the fixed-effects model2. However, P=0.1 is not reasonable, and here perhaps it should be P>0.1. In the subsequent meta-analysis of bradycardia, the fixed-effects model was incorrectly used in cases of heterogeneity as high as I2=59% and P=0.09. The opposite error occurred in the subgroup analyses of time for discharge, with I2<50% and P>0.1 for both subgroups, but incorrectly using the random-effects model instead of fixed-effects.Thirdly, the authors set Fourthly, the screening process seems flawed, as the sum of included and excluded studies doesn’t equal the initial records.et al. for this excellent work. Meta-analyses can provide the highest level of evidence for evidence-based medicine and guide clinical practice, but appropriate methodology is required. We hope to raise the above issues so that readers of the IJS will have a more accurate understanding of the results of the comparison between remimazolam and propofol.In conclusion, we thank Zhao Not applicable.Not applicable.None.K.L. and J.C.: conceived this manuscript; J.C. and H.Z.: wrote the manuscript.There are no conflicts of interest.Name of the registry: not applicable.Unique identifying number or registration ID: not applicable.Hyperlink to your specific registration (must be publicly accessible and will be checked): not applicable.Prof Kai Liu, MD.Not applicable.Not commissioned.