C. pneumoniae and human papillomavirus (HPV) and the risk of lung cancer.Lung cancer is the leading cause of cancer morbidity and mortality worldwide. Apart from tobacco smoke and dietary factors, microbial infections have been reported as the third leading cause of cancers globally. Deciphering the association between microbiome and lung cancer will provide potential biomarkers and novel insight in lung cancer progression. In this current study, we performed a meta-analysis to decipher the possible association between Literature search was conducted in most English and Chinese databases. Data were analyzed using CMA v.3.0 and RevMan v.5.3 software (Cochrane-Mantel-Haenszel method) by random-effects (DerSimonian and Laird) model.OR = 2.33, 95% CI = 1.57–3.37, p < 0.001). Base on subgroup analysis, HPV infection rate was significantly higher in Asians , in tissues  and blood samples  of lung cancer patients but non-significantly lower in males  and among lung cancer patients at clinical stage I-II . The overall pooled estimates from C. pneumoniae studies revealed that C. pneumoniae infection is a risk factor among lung cancer patients who are IgA seropositive  and IgG seropositive . All seronegative IgA  and IgG  titers are not associative risk factors to lung cancer.The overall pooled estimates for HPV studies revealed that HPV infections in patients with lung cancer were significantly higher than those in the control group  and IgG seropositive titers of  According to the GLOBOCAN report, LC is the most diagnosed cancer type  CI: 4.7–10.6) of LC cases are associated with HPV16 and almost 6% (95% CI: 3.5–9.0) are associated with HPV18 Human papillomaviruses (HPV) are small DNA viruses belonging to the Papillomaviridae family. They are non-enveloped, circular, epitheliotropic, double-stranded DNA viruses which are widely known for its importance in cervical cancer and other anogenital and oropharyngeal cancers Chlamydia pneumoniae is an obligate, intracellular, gram-negative bacillus with small and dense elementary body that causes pneumonia and other chronic respiratory tract infections and has been implicated to cause LC C. pneumoniae infection and LC risk have reported different risk estimates (ranges from 0.7 to 9.0) among individuals with seropositive titers C. pneumoniae infections and the risk of LC, there exists a knowledge gap that must be addressed due to the inconsistent results emanating from various studies. In this current study, we seek to answer the research question; what is the extent of the association between human papillomavirus (HPV) and chlamydia pneumoniae infections with the risk of developing lung cancer and how does this association vary across different populations by performed a meta-analysis to decipher the possible association between these organisms and the risk of lung cancer.Regardless of the achievements made by different scholars in their effort to advance knowledge regarding association between human papillomavirus infection or 2.This research complied with the specified systematic reviews and meta-analyses (PRISMA) protocols and reporting requirements 2.1.Chlamydia pneumoniae”, “C. pneumoniae”, “human papillomavirus”, “HPV”, “lung cancer”, “lung neoplasm”, “lung carcinoma and lung lesions”.Several English databases, including EMBASE, Cochrane Library, Web of Science, Medline/PubMed, Chinese Biomedical Literature Database (CBM) and Google scholar were searched for relevant literature. The search was done using the following search terms; “2.2.C. pneumoniae/LC. Prospective and retrospective cohort and case control studies were included. In vitro and animal studies, duplicate publications, conference proceedings, editorials were not included in the analysis.To be included, a study needed to have published findings on either human papillomavirus/LC or 2.3.The extracted information from the final selected studies included sample size, period of study, location of study, publication year, study type, first author's name, age, gender, smoking status, clinical stage of cancer and cancer type.2.4.The studies were evaluated by three authors using a quality rating scale. Discrepancies that arose during the review process were discussed and settled constructively. Studies were considered legitimate if they received a rating of 5 or above on the “Newcastle-Ottawa scale (NOS)” for non-randomized studies 2.5.CI) of the total pooled estimate. Quantification of the degree of heterogeneity was done by 2I statistics with the level of significance set at 0.05. Heterogeneity was achieved when 2I was greater than 50%. Random effect model was adopted when heterogeneity was present; otherwise, a fixed effect model was used. Publication bias was evaluated using the funnel plots for visual analysis, and the Egger's test for quantitative significance. Data were analyzed using CMA v.3.0 and RevMan v.5.3 software by random-effects (DerSimonian and Laird) model.To estimate an association between the various microbial infections and LC risk, the Cochrane-Mantel-Haenszel method for dichotomous outcome variables and random-effects (DerSimonian-Laird) model were used 3.3.1.pneumoniae/LC). 583 articles were eliminated after data examination and screening for duplication. After reviewing the abstracts and study titles, seven hundred fourteen (714) articles were further excluded. 324 articles were subjected to the full-text evaluation, after which 283 articles were subsequently removed. The principal purposes for eliminating studies included in-vitro studies (83), animal studies (59), editorials (63) and conference proceedings (78). The eligibility requirement for this study were met by 41 studies; including 17 studies on C. pneumoniae/LC and 24 studies on HPV/LC. The Prisma diagram  were nested case-control studies (1389 cases and 1696 controls) while thirteen studies (13) studies involving 1976 cases and 1988 controls were case control studies   followed by Americans  and Europeans   and blood  samples of LC patients than the control group. Apart from LBMA , all other detection techniques were significantly able to detect higher HPV rates in the LC group than in the control groups. From OR = 1.62, 95% CI: 0.62–4.29), smokers  and patients with age less than 55years . Patients infected with HPV type 16 are at a higher risk of developing lung cancer than those infected with type 18 . On the contrary, HPV infection was not a risk factor in male LC patients  and among LC cancer patients at stage I–II .The overall pooled estimates among 5004 cases and 6381 controls revealed that HPV infection was significantly higher among LC patients compared with their counterparts in the control group (57–3.37)  and this57–3.37) , where p57–3.37) . Base on88–1.88) . From thC. pneumoniae infection and the risk of LC revealed that the overall pooled estimates among patients with IgA seropositive    and retrospective studies  were reported. There was a border line significant on the seropositive titers of IgG among prospective studies that estimated the association between C. pneumoniae infections and the risk of LC   and IgG  titers are not associative risk factors among LC patients.The analysis between studies)  and IgG studies)  were sigstudies) . For nes3.3.p-values for all the pooled estimates were greater than 0.05 . The reliability or sensitivity of the pooled estimates analysis was then assessed using a leave-1-out sensitivity analysis. The statistical significance of the results did not change when a particular study was eliminated, demonstrating the reliability and validity of our study's conclusions.The publication bias of the selected papers included in the study was evaluated using the Egger's test and Begg's funnel. The funnel plots obtained from the analysis conducted in this research are symmetrical, demonstrating that biased selection had no impact on our findings. Furthermore, the findings of the Egger test demonstrated that no substantial bias existed among our selected studies, since the 4.C. pneumoniae/HPV infections and LC risk.Certain microbial infections may be potential risk factors for the development and progression of certain cancers. Therefore, in other to facilitate the prevention and to improve the treatment strategies of cancer, there should be a holistic study to understand the mechanistic procedures of infection-mediated cancers. Because most single studies use small sample size and have less statistical power, meta-analysis which combines the results of these individual studies into a unified pooled effects can increase the sample size and the statistical power, help to detect modest risk differences among study groups and enable the evaluation of the association between According to a publication by Luo et al., oncoviruses, such as HPV accounts for about 12% of most cancers in humans OR = 2.33, 95% CI = 1.57–3.37, p < 0.001). This finding of this study confirms the results obtained by Xiong et al. and Maria et al. In this study, there was a significant association of HPV infection and the risk of LC  and blood  samples of LC patients than in the control group. In other to achieve high sensitivity during HPV DNA detection, lung tissues have been recommended as the best sample type to use OR = 0.56, 95% CI = 0.12–2.59, p = 0.46), all other detection techniques were significantly able to detect higher HPV rates in the LC group than in control groups. During the detection of HPV-Host DNA integration, PCR techniques are considered the ideal detection method. Also, the type of samples used during the detection process is of key importance. Serological samples and lung tissue samples whether fresh, paraffin embedded, formalin fixed or frozen can be utilized. For the serological sample, techniques such as BMSM or LBMA can be used OR = 3.64; 95% CI: 2.60–5.08), with most of the studies used in this meta-analysis adopted PCR as the detection technique HPV types 16 and 18 are the most predominant types that persist among LC patients. A meta-analysis by Zhai et al. has shown that the risk of developing SCC is strongly associated with lung infections that are caused by HPV16 and HPV18 OR = 1.41, 95% CI = 0.78–2.57, p = 0.26) when compared with non-smokers. Results from IARC (2007) revealed that HPV high-risk types were detection at a relatively high frequency among LC patients with AC histological type. Despite the fact that cigarette smoking has being reported as the primary risk factor for LC, nearly 15%–35% of non-small cell lung cancers (NSCLC) occur in non-smokers The epidemiology of LC may vary merely due to differences in environmental conditions, gene polymorphism and other factors such as smoking, HPV prevalence and sexual behavior which may contribute to higher HPV infection rates in LC patients. A synergistic relationship has been reported between microbial infections and cigarette smoking. Smoking can decrease the population of Langhans cell; an antigen presenting cell in epithelial tissue, which can lead to immune deficiency. Also, smoking weakens the active immune response system by releasing interleukin (IL)-4. Interleukin (IL)-4 thereby causes the release of T-helper (Th2) cells. These cells have an ineffective microbial clearing power in the lungs which consequently increases the microbial colonization in the lungs of patients that smoke C. pneumoniae infection is a potential risk factor for the progression of lung cell carcinoma C. pneumoniae may down-regulate apoptosis during chronic infections by increasing the release of IL-10 C. pneumoniae co-associate with other factors to facilitate carcinogenesis C. pneumoniae is known as an effective inducer of TNF-α, IL-1β and IL-6 in host monocytic cells and has the potential to induce carcinogenesis. C. pneumoniae, which proliferates in the monocytes and macrophages, initiates pathogenesis. Pathogenesis involves a series of processes which includes adaptive and non-adaptive immune response to the antigenic material, infection of new monocytes, endothelial cells and macrophages in the intima and smooth muscle cells in the media layer which activates the release of cytokines and acute-phase proteins to produce chronic inflammation. This inflammation may result in cell injury and in an attempt to repair the injury, cell division occurs uncontrollably and this increases the risk of mutation which may lead to cancer Littman et al, through an epidemiological study iterated that C. pneumoniae in LC, a series of research conducted to confirm the possible association between C. pneumoniae infection and the risk of LC has yielded inconsistent results pneumoniae infection may cause primary lung cancer in the Chinese Han populace Despite the above mechanistic evidence of C. pneumoniae antibodies were elevated in LC patients as compared with their control counterparts. This was in agreement with Littman et al. who iterated that patients with higher titers of IgA are at a 10-fold higher risk of SCC and AC of the lung C. pneumoniae infection varies among studies with some using combination of antibody titers In this study, it was found that the titers of C. pneumoniaeIn a retrospective study, baseline exposure be it suspected risk or protection factor, is assessed at some point in the past through historical records that is established at the start of the study. In a prospective study, baseline exposure is assessed at the beginning of the study and is followed into the future. It minimizes any selection bias and generally includes better adjustment of potential confounding factors. To investigate whether there was heterogeneity among the type of studies, subgroup analysis was performed and the results iterated that there was a significant heterogeneity among both retrospective and prospective studies. In this section of this meta-analysis, subgroup analyses were not performed on age, gender and smoking status. These variables are potentially important confounders and are strongly associated with LC and elevated levels of IgA and IgG titers of C. pneumoniae is a bacterium that can cause respiratory tract infections, including pneumonia. On the other hand, human papillomavirus (HPV) types 16 and 18 are known to be high-risk types of HPV associated with various types of cancer, including lung cancer C. pneumoniae and the presence of HPV types 16 and 18 in the lungs may be potential risk factors associated with lung cancer C. pneumoniae and HPV infections can cause chronic inflammation in the lungs. Chronic inflammation creates an environment that promotes the growth and progression of cancer cells. It can lead to DNA damage, cellular mutations and an impaired immune response, all of which can contribute to the development of cancer C. pneumoniae, increased IgA and IgG seropositive titers suggest an ongoing or past infection. Elevated antibody levels may indicate a prolonged immune response and persistent infection Both C. pneumoniae and HPV infections may have a synergistic effect on promoting lung cancer development C. pneumoniae and HPV infections have been associated with DNA damage and genomic instability. C. pneumoniae can directly infect lung epithelial cells, leading to DNA damage Furthermore, evidence suggest that 4.1.C. pneumoniae/LC risk based on smoking status, age, cancer histological types or gender due to a lack of primary study data. Additionally, some of the studies included were only fair quality. Most of the study adopted a retrospective approach which makes them potentially biased towards certain groups. This study is only partially able to show a causal association because it was impossible to present a targeted account taking into account all confounders.The use of two important organisms to demonstrate risk associations and the implementation of a very comprehensive searching approach are the strengths of this study. Sensitivity analysis, which systematically omitted one test at a time, showed that the results of this study were consistent, signifying the study's reliability. The inclusion of publications from America, Asia and Europe increased the generalizability and reliability of our findings. This study has some limitations, including the inability to do subgroup analyses for 5.C. pneumoniae, may play a role as potential risk factors in the development and progression of lung cancer (LC). The oncogenic properties of HPV, particularly types 16 and 18, have been found to be associated with an increased risk of LC. The prevalence of HPV infection varies across geographical regions and histological subtypes of LC. Detecting HPV DNA in lung tissues using PCR techniques has been recommended for high sensitivity. On the other hand, chronic C. pneumoniae infection has been implicated in LC by down-regulating apoptosis and inducing chronic inflammation, which can lead to cell injury and an elevated risk of mutation. However, it is important to note that the association between these infections and LC risk is influenced by various factors such as environmental conditions, gene polymorphism, smoking and sexual behavior.In conclusion, the available evidence suggests that certain microbial infections, specifically HPV and Governments should develop policies to promote regular screening programs for lung cancer, including targeted screening for high-risk populations such as smokers and individuals with a history of viral infections like HPV. These programs can help identify cases at an early stage when treatment options are more effective. Health policies should focus on comprehensive prevention strategies that address both viral infections and risk factors like smoking. This can involve public awareness campaigns, education programs and initiatives promoting healthy lifestyle choices including smoking cessation programs and vaccination against HPV. Health policies should emphasize non-pharmaceutical measures to control the spread of HPV and associated cancers. This can include promoting safe sexual practices such as condom use and reducing the number of sexual partners. Additionally, policies should encourage regular health check-ups and HPV testing to detect infections early and provide appropriate interventions. Governments should allocate resources and funding to support research on the relationship between viral agents, particularly HPV and lung cancer. Collaboration between researchers, healthcare institutions and policymakers can facilitate the development of targeted therapies and innovative treatment approaches to combat HPV-associated lung cancers.The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.Click here for additional data file.


The real causal relationship between human gut microbiota and T1D remains unclear and difficult to establish. Herein, we adopted a two-sample bidirectional mendelian randomization (MR) study to evaluate the causality between gut microbiota and T1D.We leveraged publicly available genome-wide association study (GWAS) summary data to perform MR analysis. The gut microbiota-related GWAS data from 18,340 individuals from the international consortium MiBioGen were used. The summary statistic data for T1D  were obtained from the latest release from the FinnGen consortium as the outcome of interest. The selection of instrumental variables conformed strictly to a series of preset inclusion and exclusion criteria. MR-Egger, weighted median, inverse variance weighted (IVW), and weighted mode methods were used to assess the causal association. The Cochran’s Q test, MR-Egger intercept test, and leave-one-out analysis were conducted to identify heterogeneity and pleiotropy.P = 0.044) in the IVW analysis. When it comes to their subcategories, Bacteroidia class , Bacteroidales order , and Eubacterium eligens group genus  were observed to have a causal relationship with T1D in the IVW analysis. No heterogeneity and pleiotropy were detected.At the phylum level, only Bacteroidetes was indicated to have causality on T1D (OR = 1.24, 95% CI = 1.01-1.53, Eubacterium eligens group genus, which belongs to the Firmicutes phylum, causally decreases T1D risk. Nevertheless, future studies are warranted to dissect the underlying mechanisms of specific bacterial taxa’s role in the pathophysiology of T1D.The present study reports that Bacteroidetes phylum, Bacteroidia class, and Bacteroidales order causally increase T1D risk, whereas  In EuroThe microbiota of human gut harbors numerous microbes including bacteria, archaea, eukarya, viruses, and parasites, with bacteria as the dominant population . SpecifiMendelian randomization (MR) utilizes genetic variants which are robustly associated with the exposure as instrumental variables (IVs) to infer causality between a risk factor and a healthy outcome . The app22.1https://www.ncbi.nlm.nih.gov/guide/taxonomy/) to consult the taxonomy tree for every microbial taxon. Among 211 taxa, there are 2 classes, 3 orders, 3 families, and 10 genera which belonged to Actinobacteria; 1 class, 1 order, 5 families, and 12 genera which belonged to Bacteroidetes; 4 classes, 5 orders, 14 families, and 87 genera which belonged to Firmicutes; and 4 classes, 5 orders, 6 families, and 7 genera which belonged to Proteobacteria. The detailed categorization can be seen in The gut microbiota-related GWAS data were obtained from the international consortium MiBioGen , which c2.2via the formula F = R2(n-k-1)/k(1-R2), where R2 represents the proportion of variance explained by instruments, n represents the sample size, and k is the number of selected IVs. We set a conventional threshold value of F statistic > 10 to avoid potential weak instrument bias in this study  tests, which are optimally applicable when a horizontal pleiotropy is found in less than 50% of the instruments, were performed to detect and remove outlier instruments (P < 5×10−8) as instruments in reverse MR analysis. The rest of filtering steps were the same as the former one. The study flowchart is presented in To identify the causal effect from human gut microbiota on T1D, we selected SNPs that showed an association at analysis . Then, itruments . Only SN2.4P value (P < 0.05) derived from any of these four methods in the MR analysis was detected.We performed the MR analysis using four different approaches  to calculate causal estimates between gut microbiota composition and the risk of T1D. MR-Egger can give a consistent causal effect estimate even when all the genetic variants have a pleiotropic effect as long as the association of each genetic variant with the exposure is independent of the pleiotropic effect . WeighteP value (P > 0.05) was defined as the absence of heterogeneity or pleiotropy. In addition, we also applied the leave-one-out analyses to check whether the causal estimates could be biased or driven by a single SNP through removing each instrumental SNP in turn to repeat the IVW analyses.Sensitivity analysis had also been performed for significant estimates to detect potential heterogeneity and pleiotropy. The Cochran’s Q test was used to identify heterogeneity. The MR-Egger intercept test was conducted to assess horizontal pleiotropy. An insignificant P values < 0.05. When considering the causal relationship between subcategories of each phylum and T1D risk, a false discovery rate P value (PFDR), calculated based on the Benjamini–Hochberg (BH) method, was used to adjust for multiple testing. Significant results were those with the PFDR < 0.1; meanwhile P <0.05 but PFDR > 0.1 was considered as nominally significant.All the analyses were completed with R (version 4.2.1). R package “TwoSampleMR” (version 0.5.6) and “stats” (version 4.2.1) were utilized. At the phylum-level test, significant results were those with the 33.1P = 0.044) in the IVW analysis.At the phylum level, 15 index SNPs were selected to genetically predict Actinobacteria, 10 index SNPs were selected to genetically predict Bacteroidetes, 14 index SNPs were selected to genetically predict Firmicutes, and 12 index SNPs were selected to genetically predict Proteobacteria. The F statistics were calculated for each SNP and were all larger than the threshold value of 10, indicating strong instruments . Among fSubsequently, 2 classes, 3 orders, 3 families, and 10 genera of Actinobacteria; 1 class, 1 order, 5 families, and 12 genera of Bacteroidetes; 4 classes, 5 orders, 14 families, and 87 genera of Firmicutes; and 4 classes, 5 orders, 6 families, and 7 genera of Proteobacteria were included in the MR analysis to further explore the causal relationship between gut microbiota and T1D. We identified several significant and nominally significant taxa, which had causal effects on T1D, and these taxa mainly belonged to Bacteroidetes and Firmicutes 2. The fOlsenella (genus), showed a nominally significant correlation with T1D  in the IVW analysis. Nevertheless, the reverse MR analysis failed to exclude the possibility that T1D is causally associated with Olsenella.For Actinobacteria  and Bacteroidales  had a causal relationship with T1D in the IVW analysis; meanwhile, no heterogeneity or pleiotropy was detected. When it comes to the family level, nominal significance was found in Prevotellaceae  and Rikenellaceae  using the MR-Egger method. However, both P-values of MR-Egger intercept tests were <0.05, indicating that there was horizontal pleiotropy observed.For Bacteroidetes (Eubacterium eligens group (genus) and 11 nominally significant taxa, which included Clostridia (class), Family XI (family), Peptococcaceae (family), Veillonellaceae (family), Butyricicoccus (genus), Dorea (genus), Holdemania (genus), Lachnospiraceae UCG008 (genus), Ruminococcaceae UCG010 (genus), Ruminococcus2 (genus), and Veillonella (genus). The genetically predicted Eubacterium eligens group was significantly associated with decreased risk of T1D  in the IVW analysis, with no detected heterogeneity or pleiotropy. Among 11 nominally significant taxa, heterogeneity was observed with the Cochran Q-derived P-values < 0.05 for Ruminococcus2 and Veillonella, and pleiotropy was found with the MR-Egger intercept test-derived P-value < 0.05 for Holdemania. The detailed results for the rest of eight nominally significant taxa are represented in For Firmicutes (For Proteobacteria (3.2P = 0.037); nominal significance was observed in class Mollicutes  and order NB1n . However, significant heterogeneity or horizontal pleiotropy was detected in the three taxa since the Cochran Q-derived P-values < 0.05 or the MR-Egger intercept test-derived P-value < 0.05.To obtain more extensive information on the causality between human gut microbiota and T1D, we also included the less abundant bacterial taxa  at different levels in the MR analyses. The results are summarized in 4Eubacterium eligens group genus, belonging to the Firmicutes phylum, significantly decreased the risk of T1D. The findings in the current study allow for gut microbiota being not only a potential indicator for the earlier identification of higher-risk individuals of T1D but also a breakthrough point for achieving more optimized preventive and treatment strategies.The role of gut microbiota has been implicated in the occurrence or development of T1D from a multiple-evidence chain in previous studies. Nonetheless, the real causal relationship between human gut microbiota and T1D remains difficult to establish ascribing to intrinsic defects of the observational study and potential ethic issues limiting the experimental study conducted in human beings. Thus, our study aimed to assess the causal relation of genetically predicted gut microbiota and T1D using the two-sample bidirectional MR method. The results of our study suggested that Bacteroidetes phylum, Bacteroidia class, and Bacteroidales order significantly increased the risk of T1D, whereas the P value (1×10-5 rather than 5×10-8) for the selection of IVs and a larger sample size for the T1D GWAS data used. The value we used was identified as the optimal threshold for selection of genetic predictors associated with the gut microbiome since it led to a larger variance explained and it had been applied in many gut microbiota-related MR studies , revealed that a higher relative abundance of the Bifidobacterium genus was associated with a higher risk of T1D. Our study reported quite different results; this discrepancy may be attributed to a more relaxed threshold of  studies . Current studies . Our stu studies . In agre studies . Althougbenefits . In addivia modulating the formation of short-chain fatty acids (SCFAs), altering intestinal permeability, and regulating immune and inflammatory response. Previous experiments reported a rapid disease onset and high T1D incidence in non-obese diabetic (NOD) mice under germ-free conditions, indicating that the existence of diabetes-protective commensal microbes  in the former GWAS data; b. it possesses the largest sample size and most bacterial taxa among currently available gut microbiota-related GWAS data; c. it had been used for MR analysis in convincing studies. Secondly, the original study on gut microbiota only meta-analyzed microbial taxa at five levels, namely, phylum, class, order, family, and genus, and consequently lacked GWAS summary statistics at the species level. Therefore, we failed to determine taxa at the species level causally related with T1D, which helps identify an optimal gut microbiota more accurately. Thirdly, the nominally significant taxa identified in our study should be treated dialectically. The 5Eubacterium eligens group genus, which belongs to the Firmicutes phylum, causally decreases T1D risk. The findings enable innovative interventions such as oral administration of probiotics/prebiotics and FMT as a means to restore a healthy microbiota, thereby reducing T1D risk. Nevertheless, future studies are warranted to further profile an optimal gut microbiota composition and dissect the underlying mechanisms of specific bacterial taxa’s role in the pathophysiology of T1D.In conclusion, the study comprehensively analyzes the causal relation of genetically predicted gut microbiota at different levels and T1D using the two-sample bidirectional MR method. Our estimates reveal that Bacteroidetes phylum, Bacteroidia class, and Bacteroidales order causally increase T1D risk, whereas the The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ML designed the study and wrote the first draft of the manuscript. ML, XL, QC, TZ, and JW gathered data and conducted statistical analyses. MS, TW, SZ, and XS participated in data interpretation. JQ and ML revised the manuscript for intellectual content. All authors read and approved the final manuscript.


Results: There was a 41.2% risk reduction for cerebrovascular disease. CVD incidence had a 29% reduced risk. CVD mortality had a 13.8% risk reduction, while IHD incidence had a 24.1% reduction, but with high heterogeneity. IHD mortality showed a significant 32.1% risk reduction. Ischemic stroke had a significant 32.9% risk reduction across six studies. Stroke incidence showed a significant 39.1% risk reduction in a single study. There was a non-significant 11.6% risk reduction for stroke mortality with moderate heterogeneity. Conclusion: Healthier diets are associated with reduced risks of cerebrovascular disease, CVD incidence, IHD mortality, and ischemic stroke. However, evidence quality and consistency vary, emphasizing the need for more research. Policymakers and healthcare professionals should prioritize promoting healthy diets for CVD prevention.Background: Cardiovascular diseases (CVDs) are leading global causes of mortality. Unhealthy diets have been linked to an increased risk of CVD, while plant-based diets have shown potential protective effects. This umbrella review summarizes the evidence on the association between vegetarian diets and cardiovascular and cerebrovascular diseases. Methods: PubMed, Scopus, Embase, CINAHL, Cochrane, and Web of Science were consulted. Meta-analyses grouped by author and outcome were performed. The heterogeneity was evaluated using I Cardiovascular diseases (CVDs), including coronary artery disease (CAD), heart failure, and cardiac death, significantly burden the global population. According to the World Health Organization (WHO), cardiovascular diseases are the leading cause of death globally, accounting for approximately 17.9 million deaths annually . Among tCerebrovascular diseases, such as strokes, significantly impact global health. Strokes occur when the blood supply to the brain is interrupted or reduced, leading to brain damage . They caGiven the substantial impact of cardiovascular and cerebrovascular diseases on individual health and global healthcare systems, there is a critical need to explore effective preventive measures and identify modifiable risk factors . UnhealtFurthermore, the rise in popularity of vegan and vegetarian diets has led to growing interest in exploring their potential benefits for primary and secondary prevention of cardiovascular health . Recent Cochrane Handbook, use systematic reviews (SRs) methodology on existing SRs or meta-analyses [We propose an umbrella review of published meta-analyses to understand better the available evidence for the association between vegetarian diets and cardiovascular outcomes. Umbrella reviews of existing systematic reviews and/or meta-analyses, called overviews in the analyses . Other uanalyses ,17,18. Ianalyses  summarizThe present study aims to summarize the available evidence on the existing meta-analysis on the effect of vegetarian and vegan diets on cardiovascular and cerebrovascular disease risk.The preferred reporting items for systematic reviews and meta-analyses (PRISMA) ,20 guidehttps://sr-accelerator.com/#/polyglot (accessed on 15 July 2023) [https://searchfilters.cadth.ca/list?q=&ps=20&topic_facet=health%20technology%20assessments%20000000%7CHealth%20technology%20assessments&p=1 (accessed on 14 July 2023) [The search strategy was first created for PubMed and then translated into the other database languages with the help of the tool Polyglot, ly 2023) , enrichily 2023) ,25,26. TPubMed, Embase (through Ovid), Scopus, CINAHL, Web of Science, and Cochrane Database were searched from inception to July 2022.Studies were included according to the inclusion criteria enlisted in www.covidence.org) (accessed on 14 July 2023) to select the studies from title/abstract screening to the data extraction phase. The authors GB and DR independently reviewed the titles and abstracts of all the articles identified. GB and FN reviewed the full-text articles for eligibility. Both in title/abstract and full-text screening, disagreements were solved through discussion.The web-based collaboration software platform Covidence was used  risk of bias (RoB) tool and evaluation, number of cases and controls (in case-control studies), and number of events and population . Outcomes were categorized as follows: Cardiovascular (CVD) events, CVD mortality, coronary heart disease (including ischemic heart disease), CHD mortality , and ischemic stroke. GB and DR independently evaluated the methodological quality of the studies included using the AMSTAR 2 Checklist . The tooThe current study examines a single exposure factor with multiple outcomes of interest, and the analyses have been conducted at two levels of detail. First, the studies with the same outcome of interest were grouped within each meta-analysis. Second, the studies with the same outcome were grouped, regardless of their source meta-analysis. To conduct the meta-analysis, we gathered the following information for each study: (i) the risk measure used (either Risk Ratio—RR or Hazard Ratio—HR); (ii) the number of cases exposed (vegetarian); (iii) the number of cases non-exposed (non-vegetarian); (iv) the total number of exposed individuals; (v) the total number of non-exposed individuals; (vi) the estimate of RR or HR, along with their corresponding 95% Confidence Interval (95% CI); (vii) the Risk of Bias (RoB) tool; and (viii) the RoB score.Considering non-independence in the effect sizes involved three dependencies: hierarchical, multivariate, and partial ,29. HierWhen hierarchical dependence was present in the data, a combined effect size across dependent studies was computed . When multivariate dependence was present in the data, a combined effect size was computed across outcomes or time-points derived from the same units. More precisely, all dependent effect sizes derived from the same units are resumed to a unique effect size by estimating the non-weighted mean of all effect sizes . The corWhen partial dependence was present in the data, the shared group was split into several independent subgroups of smaller sample sizes, as described in the Cochrane Handbook . More prThe summary effect size and its 95% CI were estimated using random effects models. In the case of effect sizes expressed by different measures, the Odds Ratio (OR) was used as the main effect size measure, and RR and HR were converted into an OR; moreover, to facilitate the comparison of effect sizes between meta-analyses, we reported the estimated effect sizes also in the equivalent odds ratio (eOR) by the methods implemented in the {metaumbrella} R package .For the summary random effects, we estimated  the 95% prediction interval (PI), which further accounts for the degree of between-study heterogeneity and gives a range for which we are 95% confident that the effect in a new study examining the same association lies within .2 statistic [Statistical heterogeneity between studies was evaluated using the Itatistic .To detect any evidence of biased study effects, we performed the Egger’s regression asymmetry test  and the Finally, we stratified the evidence related to the observed associations according to the criteria described in Fusar-Poli & Radua . This clThe search identified 1202 articles: 417 were removed as duplicates, and 673 were excluded from title/abstract screening. Of the 112 articles included in the full-text screening phase, 103 were excluded . Table SThe nine systematic reviews assessed cardiovascular events ,37,38, CFor what concerns cardiovascular events, Quek et al.  found thQuek  determinGlenn et al.  found thDinu et al. , Dybvik Quek et al. , Glenn eConversely, Dybvik et al.  found thVegetarian and vegan dietary patterns have different characteristics in relation to food selection and reasons that motivate the adoption of such patterns . The stuAmong the studies considered in the meta-analysis included were reported 14 prospective cohorts: Adventist Health study 1, Adventist Mortality study in the meta-analysis of Jabri et al. ; Adventi2) of the results, the classification of the study as proposed by Fusar-Poli & Radua [ & Radua  (Class), & Radua ; all theDinu et al.  analyzedDybvik  investigJabri et al.  studied Jafari et al.  investigFor Ischemic Stroke, Lu et al.  analyzedQuek et al.  investign = 3), CVD incidence (n = 1), CVD mortality (n = 7), IHD incidence (n = 4), IHD mortality (n = 15), stroke incidence (n = 1), stroke mortality (n = 6). For cerebrovascular disease, the pooled analysis of three studies showed a significant 41.2% reduction in risk  among individuals with healthier dietary patterns. Similarly, one study on CVD incidence demonstrated a 29% reduced risk  associated with healthier diets.The association between dietary patterns and CVD mortality showed some heterogeneity, with a 13.8% reduction in risk . On the other hand, the relationship between dietary patterns and IHD incidence was less conclusive, with a 24.1% reduction in risk , but with high heterogeneity across the four included studies.Regarding IHD mortality, the meta-analysis of 15 studies showed a significant 32.1% reduction in risk  associated with healthier dietary patterns, though the results had moderate heterogeneity.Ischemic stroke demonstrated a significant 32.9% reduction in risk  across six studies, but again, there was notable heterogeneity in the findings.For stroke incidence, a single study indicated a significant 39.1% risk reduction  with healthier diets, but this finding should be interpreted with caution due to the limited number of studies.Lastly, for stroke mortality, the meta-analysis of six studies showed a non-significant 11.6% reduction in risk , and moderate heterogeneity was observed in the results.In A vegetarian diet is associated with a reduced risk of all cardiovascular outcomes, especially for CVD incidence , IHD mortality , MI incidence , stroke incidence , cerebrovascular disease , and ischemic stroke . Instead, for CVD mortality , stroke mortality , and IHD incidence , the vegetarian diet is less protective . According to the AMSTAR-2 assessment, one meta-analysis was considered of high quality , two of 2 represents the degree of heterogeneity across studies, where higher values indicate greater variability among study results; it varies between 50.19% and 96.30%, grouping by outcome in each meta-analysis  and 29%  risk reductions, respectively. Our findings align with those of Oussalah et al.  concerniHowever, it is essential to note that the association between dietary patterns and CVD mortality exhibited some heterogeneity, with a 13.8%  risk reduction. This variability in results might be influenced by factors such as differences in study populations, dietary assessment methods, and other confounding variables not accounted for in the meta-analysis.Furthermore, the relationship between dietary patterns and IHD incidence could have been clearer-cut, with a 24.1%  risk reduction and high heterogeneity across the included studies. This discrepancy highlights the need for more consistent and rigorous research to understand better the impact of dietary choices on the incidence of ischemic heart disease.On the positive side, the meta-analysis of IHD mortality showed a significant 32.1%  risk reduction associated with healthier dietary patterns, indicating that conscious dietary choices could favor heart-healthy outcomes.While the meta-analysis demonstrated a significant 32.9%  reduction in the risk of ischemic stroke associated with healthier diets, the limited number of studies in the stroke incidence analysis warrants cautious interpretation. More studies are needed to validate this finding and to establish more substantial evidence for the preventive effects of dietary patterns on stroke incidence.p-value, the publication bias was not significant for all outcomes of interest. The measure derives from the Eggers test, a statistical method used to assess the presence of publication bias or small study effects by examining the relationship between study effect sizes and their precision (inverse of standard error). None of the studies are in Class I. The quality of meta-analysis relies on the quality of included studies, so the results derived in this umbrella should be interpreted cautiously, especially for outcomes with few studies and of poor quality. All the included SRs evaluate the RoB with tools considered appropriate in the field of nutrition [The results of the methodologic quality of the meta-analysis included in this study suggest that the current meta-analysis still needs to achieve a medium-to-high-quality score. According to the Eggers utrition , except utrition . Moreoveutrition , Jabri eutrition , and Jafutrition  also useThe results of this umbrella review should be interpreted cautiously, considering it suffers from several biases. First, most studies related to nutrition use a nonrandomized observational study design, which brings difficulties in detecting small effect sizes, accounting for confounding variables, inaccurate diet measurements, and reporting bias . To solvMoreover, individuals who opt for plant-based diets might be more health-conscious and informed about nutrition. However, a plant-based diet does not mean a healthy one, since some foods are classified as ultra-processed foods (UPFs) . This coAnother limit relies on the variability in diet definitions, populations, and duration of interventions. The studies considered vegetarians and vegans altogether or considered high intakes of vegetables. The definitions of the outcomes could vary according to the different studies. These differences provide estimates with wider confidence intervals, which strengthens the robustness of the protective effect. These variations introduce a certain level of uncertainty or “variability” into the results of the studies. However, rather than weakening the findings, this increased variability can strengthen the results’ significance. When the individual studies being analyzed in a meta-analysis have diverse methodologies, definitions, and outcomes, it can create a broader range of possibilities regarding the observed effects. So, this increased variability reinforces the significance of the findings. A wider confidence interval suggests more uncertainty about the true effect, but it also means that the effect could be larger or smaller than initially estimated. This uncertainty prompts researchers to be cautious and encourages them to consider a range of scenarios.In the included meta-analysis, the same study cohorts were often considered; this is challenging in terms of exposure. In the analysis, we have taken into account three types of dependency effect sizes: hierarchical, multivariate, and partial. Other limitations are related to the nature of the umbrella review. In the realm of scientific inquiry, umbrella reviews are a powerful tool for synthesizing existing research findings. However, one must acknowledge that a notable challenge resides intrinsically within this methodology. This challenge pertains to the inherent complexity of integrating diverse studies and their outcomes into a cohesive narrative. In particular, the quality of our results relies on the reporting of the included studies . AddressThis umbrella review provides a comprehensive analysis of the published meta-analyses in relation to vegetarian diets and cardiovascular disease. Overall, these findings highlight the importance of healthy dietary patterns in preventing certain CVD outcomes. These findings should be interpreted with the emphasis that dietary recommendations for preventing cardiovascular disease (CVD) should shift towards promoting healthy dietary patterns, rather than solely focusing on individual food groups or nutrients .In summary, when grouped by outcome, the results suggest that adopting healthier dietary patterns may be associated with reduced risks of cerebrovascular disease, CVD incidence, IHD mortality, and ischemic stroke. However, the evidence’s quality and the consistency of the findings varied across different outcomes, with some results showing significant reductions in risk and others needing to be more conclusive and non-significant. Further research and high-quality studies are required in order to better understand the role of dietary patterns in preventing different cardiovascular diseases.Policymakers and healthcare professionals can utilize these findings to emphasize the importance of promoting healthy dietary habits in cardiovascular disease prevention initiatives and public health campaigns.


P. chabaudi or P. yoelii is best explained by stochasticity  rather than by host factors or experimental design. Third, we find that for P. berghei the impact of immune perturbation is increased when young or female mice are used and is greatest when effector molecules  are disrupted (up to an 18% difference in peak parasitaemia). Finally, we find little evidence of publication bias suggesting that our results are robust. The small effect sizes we observe, across three parasite species, following experimental perturbations of the innate immune system may be explained by redundancy in a complex biological system or by incomplete (or inappropriate) data reporting for meta-analysis. Alternatively, our findings might indicate a need to re-evaluate the efficiency with which innate immunity controls parasite replication early in infection. Testing these hypotheses is necessary to translate understanding from model systems to human malaria.Decades of research have probed the molecular and cellular mechanisms that control the immune response to malaria. Yet many studies offer conflicting results on the functional impact of innate immunity for controlling parasite replication early in infection. We conduct a meta-analysis to seek consensus on the effect of innate immunity on parasite replication, examining three different species of rodent malaria parasite. Screening published studies that span four decades of research we collate, curate, and statistically analyze infection dynamics in immune-deficient or -augmented mice to identify and quantify general trends and reveal sources of disagreement among studies. Additionally, we estimate whether host factors or experimental methodology shape the impact of immune perturbations on parasite burden. First, we detected meta-analytic mean effect sizes (absolute Cohen’s h) for the difference in parasite burden between treatment and control groups ranging from 0.1475 to 0.2321 across parasite species. This range is considered a small effect size and translates to a modest change in parasitaemia of roughly 7-12% on average at the peak of infection. Second, we reveal that variation across studies using  For example, P. chabaudi is a model of chronic recrudescing infection whereas P. berghei can cause experimental cerebral malaria leading to rapid host mortality  following an experimental perturbation of the innate immune system. For example, approaches to study the impact of NOS2  include infecting genetically attenuated mice  or mice ortality . Furtherortality .P. chabaudi or P. yoelii are likely explained by stochasticity  rather than by the effects of experimental perturbations. However, in the P. berghei model, experimental perturbations have a bigger impact in young or female mice, and an 18% difference in peak parasitaemia can be observed between control and treatment groups when effector molecules  are disrupted.Meta-analyses quantitatively synthesize results from multiple studies using the standard effect size to reveal general patterns in the literature . By pool22.1Plasmodium OR rodent malaria) NOT mosquito* NOT human – in four databases  in January 2020. We filtered for research articles only and applied no restriction in the year of publication. We screened each article for inclusion in the dataset by first removing duplicates among searches, and then assessed the title and abstract of each article to check the experimental design and results consider a relevant topic. We then assessed the full content (where the full article was available) and retained articles that met the set of criteria based on PICO-defined elements  separately because parasite multiplication rate (and hence infection dynamics) differs markedly between them. When articles included multiple experiments, each suitable experiment was included individually. All data points from figures were extracted using Datathief III v1.7 (2015). AHM conducted all data extraction and TK validated data points. Classification of the immune covariates was determined by AHM and PJS. The full datasets used in our analyses are available in Our study focuses on analysing patterns of parasite replication under different innate immune perturbations in rodent malaria infections. The best metric for parasite burden is density  but this is rarely reported so instead we extracted parasitaemia , and we required studies to report multiple temporally spaced samples for both control and treatment groups. We only included infections initiated via direct blood challenge  to specifically examine the impact of innate immunity on asexual replication during the pathogenic blood cycle. Mosquito-transmitted infections were omitted because the number of parasites that egress from the liver to initiate the blood cycle cannot be standardised or accurately estimated, which is likely to confound the analysis of infection dynamics. We focused on the acute phase of infection to minimise the influence of other host factors  that can mask the direct impact of the immune response on parasitaemia. Thus, we include data up to the peak of infection for 2.3We used Cohen’s h, a standardized effect size, to quantify the difference between proportions . We calc2.42.4.22 statistic   .2.4.3P. berghei dataset revealed residual heterogeneity , which allowed us to conduct meta-regression analyses to explore sources of this variation. Moderator information was only available for subsets of data so we carried out a series of univariate meta-regression analyses to examine the moderating effects of host, immunological and experimental design factors on the impacts of immune interventions. Univariate models proved the most appropriate approach due to missing data and/or small sample sizes (Only the le sizes . Meta-reHost factors○Genetic background (C57BL/6 or other)○Age ○Sex Immunological factors ○Cell lineage ○Cytokines/chemokines or their receptors○Effector function ○Position in signalling network (receptor to transcription factor (termed input) or downstream targets of transcription factors (termed output))Experimental design factors○Sampling regime (day post-infection)○Route of infection ○Infecting dose (number of parasitised RBC inoculated)○Method of immune manipulation (genetic modification (GM), drug administration, surgery, cell transfer or mixed (any combination of these four categories))in vivo experiments; we therefore pooled these studies with those that explicitly stated they used both sexes. This allowed us to place each experiment into one of three non-overlapping categories – female only, male only, or mixed/unreported.Host genetic background was evaluated as a binary variable (C57BL/6 or other) because most studies used a single strain . By pooling all other strains we prevented sample sizes from being disproportionately skewed but precluded a full comparison across genetic backgrounds. Also, not all studies reported the sex of the mice used in their Examining immunological moderators was inevitably difficult because molecules or pathways that often have pleiotropic effects required categorisation. We, therefore, approached this task as follows: if the experimental manipulation only affected cells that derive from common myeloid or common lymphoid progenitors , studies were classified as ‘myeloid’ or ‘lymphoid’, respectively. In cases where cell types derived from both lineages could reasonably be expected to be modified , studies were classified as ‘both’. Studies where cytokine or chemokine signalling cascades were targeted were categorised according to whether they manipulated the chemical messenger (‘cytokine/chemokine’) or the ‘receptor’. We next categorised studies according to whether they modified a pathway that could directly trigger or amplify inflammation (such as TNF), regulate the host response (such as lymphotoxin) or control the ‘trafficking’ or migration of immune cells (such as CXCL10). This allowed us to ask whether experiments that target the ‘inflammatory’ response have bigger effect sizes since these mechanisms of host defence are frequently cited as providing early control of parasite replication. Note that ‘regulatory’ does not necessarily mean suppressive in this context. Finally, we examined whether the position of a molecule within a signalling network had a measurable impact on effect size. Here, we simply categorised studies according to whether the experimental manipulation would alter signalling cascades before (‘input’) or after (‘output’) the induction of transcription factors (or their binding to target DNA sequences). We hypothesised that there would be greater redundancy in upstream signalling molecules  than effector molecules (such as death receptors).Full details of how each study was used to assess the moderating effects of the host, immunological and experimental design factors can be found in 33.1P. berghei, which was the only species for which we detected non-zero heterogeneity. Here we explored the effect of biological and methodological moderators using a series of univariate meta-regressions. Finally, we assessed publication bias graphically and using statistical tests.Our meta-analysis began with a systematic literature search. We then assessed the suitability of individual articles for inclusion before data were extracted from suitable studies and effect sizes calculated Figure 13.2Plasmodium species investigated . Like Cohen’s h, these back transformations are agnostic of the direction of the effects .Our meta-analysis found consistent effects of innate immune perturbations on parasite growth dynamics across all three stigated Figure 2ectively . Back-tr3.3P. chabaudi, P. yoelii lethal and P. yoelii non-lethal , which is consistent with the notion that random variation due to small sample sizes is responsible for the observed variability . In contrast, the P. berghei dataset contained comparatively higher heterogeneity , suggesting that factors beyond stochasticity may underpin this variation. We, therefore, probed for potential sources of variation using a series of univariate meta-regressions, which we report in the following sections  having a significantly larger effect than those modifying input signals (receptor to transcription factor) F = 16.8373, p-value < 0.001, 3.3.32 = 10.4520, p-value = 0.0012) or experiments that combined more than one methodology . Note that it wasn’t possible to estimate the relative effect of adoptive cell transfer or surgery alone because too few studies used these techniques. Finally, we found no moderating effects of the sampling regime, route of infection, or infecting dose  generated the largest impact Figure 53.4P. chabaudi, P. yoelii lethal or P. yoelii non-lethal. As we found an indication of publication bias in the P. berghei dataset  are targeted (translating to an ~18% difference in peak parasitaemia). In contrast, there is extremely low heterogeneity across the P. chabaudi and P. yoelii datasets, which means that variation between studies is better explained by stochasticity  than by host factors or experimental approaches.We present a broad-ranging meta-analysis of studies spanning four decades of experimental manipulation to identify the role of innate immunity in controlling parasite replication early in infection. Because some studies manipulate immune function in ways that might facilitate parasite replication, whereas others would be expected to decrease parasitaemia, we quantify effect sizes on the absolute scale, which reports the magnitude (not the direction) of the difference between control and treatment groups. Overall, we reveal effect sizes (Cohen’s h) that are considered small for all four datasets, which span three parasite species Figure 2+ T cells and antibodies), which occurs later in infection , which is often considered to be a poor model for studies of host immunity; experimental cerebral malaria is a common outcome of infection, which is lethal at a relatively low parasitaemia. How do we explain this counter-intuitive finding? P. berghei is not used more often than other parasite species and P. berghei experiments do not have larger sample sizes , which may play a more dominant role in longer infections that can reach a higher pathogen load. Nonetheless, it is important to note that in all cases, the effect of manipulating the innate immune system was surprisingly modest and while P. berghei might reveal a greater role for innate immunity in controlling parasite replication this model may not reflect malaria more broadly or provide a good model for human infections.We detected low heterogeneity across studies, indicating that the majority of variability is attributable to stochastic variation due to small sample sizes . Underpoerations . Howevererations . This meWe did not detect a moderating effect of either the timing of sampling or the infectious dose on the impact of immune perturbations. An impact of timing was expected because the possible difference in parasitaemia between control and treatment groups is smaller at the lower boundary. For example, when parasitaemia is low early in infection there is less scope for this to be reduced by immune augmentation as compared to at a higher parasitaemia, which is reached later in infection. Fortunately, standard effect sizes, like Cohen’s h, allow for the examination of effects free from this constraint, making our inference about the timing of sampling robust . The lacP. berghei model; immune perturbations had a greater impact in young and female mice  is widely used as a proxy for parasite burden. However, this metric is problematic for several reasons. Most importantly, the proportion of infected RBC is confounded by the number of circulating RBC, which decreases as infection progresses. Parasites exploit and deplete RBC, and innate immune mechanisms clear RBC (including uninfected cells) and suppress RBC production . Thus, lAdditional insight is also likely to be gained by diversifying the hosts used to assess innate immunity to malaria. All but one study used inbred laboratory mice and the majority were housed under Specific Pathogen Free (SPF) conditions. Standard laboratory mouse husbandry has profound effects on the development of the immune system by reducing the diversity of the microbiota and eliminating natural exposure to pathogens, which continuously shape and remodel immune cell function , 53. ForP. falciparum is comparable in naïve human hosts infected by mosquito bite versus blood challenge . Perhaps the capacity for rodent parasites to replicate to much higher densities causes resource limitation to play a larger role in limiting parasite burden. No study system perfectly marries within-host ecological realism, translational value and tractability. Yet perhaps the rapid development of human challenge models will allow for the role of innate immunity early in infection to be tested experimentally by integrating human data with mathematical modelling to test long-standing  hypotheses. Certainly, combining a more integrative approach with larger-scale experiments that report more comprehensive data will help resolve conflicting reports on the role of innate immunity in malaria.Our meta-analysis summarized four decades of research to probe the effect of innate immunity manipulation in rodent models of malaria. We detected a small overall effect of perturbing the innate immune system on infection dynamics and revealed that manipulating effector molecules in young female mice by administering drugs  has the largest impact on the replication of The original contributions presented in the study are included in the article/Conceptualization, all authors; Analysis, AHM and TK; Writing-Original Draft, AHM, TK, SR; Writing-Review and Editing, all authors; Supervision, TK, SR.


Coronary artery disease (CAD) and its outcome, myocardial infarction, is yet a significant etiology of mortality and morbidity nowadays. The aortic propagation velocity (APV) can be a simple, straightforward and novel echocardiographic index for the risk stratification in the evaluation of CAD. In this meta-analysis, we evaluated the predictive role of APV in CAD.Relevant electronic bibliographies  were explored. Related reports were selected according to the inclusion and exclusion criteria. Meta-analysis was performed using the Comprehensive Meta-analysis 2.0 software.P < .001, I2: 84%, Q: 19.03). The diagnostic value of APV in predicting CAD showed 86.3% sensitivity  and 83.8% specificity .Eventually, 5 articles met the inclusion criteria and included in the meta-analysis. Five studies with 490 patients reported the APV mean in CAD and non-CAD groups. A random-effect model was used and the pooled findings demonstrated a significant higher APV in non-CAD group compared to CAD group (SMD: 2.39, 95% CI: 1.70–3.07, There was a predictive role of APV in CAD with suitable specificity and sensitivity. Moreover, aortic distensibility and aortic strain were significantly different in CAD and non-CAD patients. APV could be used as a good noninvasive tool for screening CAD. Coronary artery disease (CAD) and its outcome i.e. myocardial infarction, is yet a significant etiology of mortality and morbidity nowadays. Optimal risk stratification of patients with acute myocardial infarction has a critical role in suitable care of patients. Risk prediction can be performed according to clinical, electrocardiography, two-dimensional echocardiography and biochemical parameters.Arterial wall stiffness is an index of vascular aging and an important cause of predisposing patients to atherosclerosis and correlated with cardiovascular events. Atherosclerotic plaque starts early in life and grows slowly over decades. Although atherosclerosis is almost common in the modern world, most plaque remains asymptomatic lifelong. Despite systemic tendency of some patients to plaque erosion independent of conventional risk factors, traditional risk factors and consequent chronic inflammation lead to the development of atherosclerosis. Collagen and elastin are the 2 major effective proteins in the vascular wall establishment and flexibility. Their content is balanced in a dynamic process of production/degradation. If this balance is altered by any trigger of inflammatory process, it leads to an increase of abnormal collagen and a decrease in normal elastin quantity. Several cardiovascular risk factor such as aging, hypertension, diabetes mellitus, and chronic kidney disease contributed in over-production of collagen, considering their different times of exposure. Another mechanism for stiffening of arterial wall is endothelial dysfunction, caused by changes in endothelial cell signals and cell tone of smooth muscles of vessels, further to structural alterations. Endothelial dysfunction is secondary to various factors such as any local imbalance between vasodilator nitric oxide and vasoconstrictors, increased expression of asymmetrical dimethylarginine, and activation of reactive oxygen species.Atherosclerosis is a complex, chronic and multi-factorial disease, which can affect the whole arterial system.–8 By aging, CAD risk factors accumulate and vessel flexibility decreases. The aortic propagation velocity (APV) might be decreased with growing arterial stiffness and lowering strain and distensibility.Variables like aortic strain (AS), aortic distensibility (AD), pulse pressure, and augmentation index, and pulse wave propagation velocity were recently applied to determine aortic stiffness.APV can be a simple, easy and novel echocardiographic parameter for the risk stratification in the evaluation of CAD. The purpose of this meta-analysis was to assess the predictive value of APV in CAD as an index of arterial stiffness.Relevant electronic databases  were searched (up to November 2022) using the following terms: CAD, APV, echocardiography, aortic stiffness, atherosclerosis, and aortic velocity). Literature selecting was performed by reading the article title and abstract, eliminated the studies not meeting the inclusion/exclusion criteria. For those that were more ambiguous, full text was accessed and then a choice was made. General data includes published information, patient information, the quality information, the index and data of result etc. was extracted. Literature selecting and data extraction processes were independent, then the results were cross-checked.The inclusion criterion was cross sectional studies that used APV index in predicting CAD. Studies were excluded if APV was assessed for another purpose like other specific types of angina pectoralis or congenital heart disease, and repeated literatures. Only English literatures were used.CAD diagnosis was based on medical history of documented myocardial infarction, coronary revascularization or epicardial CAD detected during coronary angiography for symptomatic patients or typical electrocardiographic changes.Two reviewers independently extracted data and reached a consensus on all items. The following information was achieved from each study: the first author’s name, publication date, ethnicity, population, characteristic of target population, treatment protocol, definition of cases, outcomes and study period.Aortic propagation velocity (APV), left ventricular ejection fraction, AS, and aortic dispensability (AD) were studied. All parameters were defined in a previously published study.,11 Any disagreement was checked by a third reviewer. We used these items for study assessment: the study ability to correctly respond to study question; well-defined sampling method (for both the subjects and setting); enough sample size; checking for selection bias; accurately outcome measurement; accurately outcome analysis; reporting the findings with confidence interval (CI); and rationalizing the conclusion according to the findings. In accordance with the appraiser agreement, a response of “yes” demonstrated low risk of bias and coded as “1” and “no” indicated high risk of bias and coded as “0.” If an item was unclear, it means an unknown risk of bias. A score of 0 to 8 was assigned to each investigation. Studies that achieved 6 or more scores were rated as high quality, while 4 to 5 was considered as moderate quality.Quality control was performed by 2 independent authors based on the Strengthening the Reporting of Observational Studies in Epidemiology checklist for cross sectional studies.2 test and I2 test to judge statistical heterogeneity. When P > .1, I2 < 50%, and each study did not show significant heterogeneity, we used the fixed effect model. When P ≤ .1, I2 ≥ 50%, and each study showed significant heterogeneity, we made the subgroup analysis (according to the possible factors of heterogeneity) or sensitivity analysis. If the heterogeneity still existed and data based on the clinical significance view could be merged, we used the random effect model and explain the results cautiously. Continuous variables used the standard mean difference (SMD) as analysis statistics. 95% confidence interval (95% CI) was be used as effective size for the combined analysis. Hypothesis testing was carried out with u test, which was represented by Z and P. When P ≤ .05, it indicated that there was a significant difference between the 2 groups. Heterogeneity of the results between studies was assessed graphically by forest plots and statistically using the quantity I2 that describes the percentage of total variation across studies attributable to heterogeneity rather than chance. Statistical analyses were performed using Comprehensive Meta-analysis software version 2 .Analyzed the clinical and methodological heterogeneity of the included studies, used χA total of 20 applicable studies were recognized according to primary search criteria. Eleven irrelevant studies were excluded by initial screening of titles and abstracts. Gray studies were not found and no additional articles were added after the reference review. Finally, 5 articles met the inclusion criteria and entered the meta-analysis. The search process and literature selection are demonstrated in a PRISMA flow diagram Fig. .In total, these studies included 299 participants in CAD groups and 191 in non-CAD groups. The sample size of these studies ranged from 70 to 127. Eligible studies were published between 2008 and 2022 and performed in India, Turkey, and Iran. All 5 studies were designed as cross-sectional and echocardiographic parameters including APV, AS, and AD were compared between CAD and non-CAD groups. A definitive diagnosis of CAD was performed based on the results of coronary angiography. The demographics and characteristics of the included studies are demonstrated in Table The methodological quality of the included studies is shown in Table P value < .001, I2: 84%, Q: 19.03)  and 83.8% specificity  . There was statistically significant difference in mean of AD between CAD and non-CAD groups   Fig. .I2: 95%, Q: 15.50, P value < .001). AS was significant lower in CAD group rather than non-CAD group, statistically   Fig. .P value < .001). APV was adversely correlated with SYNTAX score  (Fig. Three studies with 157 patients revealed the correlation of APV with SYNTAX score. A random effect model was used (Q: 0.231, To best of our knowledge, this is the first investigation to evaluate the effects of APV in predicting CAD. Our results showed that lower APV could significantly distinguish CAD from non-CAD patients. It has an 86.3% sensitivity and 83.8% specificity in diagnosis of CAD. Moreover, AD and AS were significantly different between CAD and non-CAD groups. Another major finding was negative significant correlation between SYNTAX score and APV. even in subjects with no symptoms of overt CVD. Moreover, the quality of hypertension management and difference between various kinds of anti-hypertensive drugs can be directly assessed by measuring arterial stiffness. As atherosclerosis progresses, AD and AS diminish. Atherosclerosis decreases the arterial wall consistency and the aorta flexibility. By atherosclerosis progression, tunica media would be thicker and stiffer. Consequently, it is very important to determine atherosclerosis prior to be presented, non-invasively.Arterial stiffness is a major predictor of cardiovascular events and all-cause mortality,APV is one of the easiest echocardiographic parameters that correlates with significant CAD and aortic stiffness and distensibility. While aortic stiffness and AD are more correlated with conventional risk factors such as hypertension and increased age, APV correlates much with the extent of CAD and left ventricular dysfunction. As the severity of LV dysfunction increases, the APV decreases. It can be used for follow-ups to evaluate the increment in APV as the systolic function improves following treatment of CAD based on guideline management. It seems that the most useful indication of APV would be noninvasive cardiovascular risk stratification for better planning treatment of patients and detect high-risk ones.,12–15 showed a predictive value of APV in CAD with suitable specificity and sensitivity. It was also revealed that both AD and AS were significantly lower in CAD rather than non-CAD patients. Results of other similar studies confirmed this hypothesis in our meta-analysis. In Yildirim et al investigation, it was shown that APV level was lower in patients with severe risk factors in the past 10 years compared to those with moderate or low risk patients. It was revealed that atherosclerotic plaques in the thoracic aorta were indicators of CAD. Another report demonstrated that aortic plaques imaged by trans-esophageal echocardiography had a 93% sensitivity and 82% specificity for significant CAD. Atherosclerosis has been shown to escalate arterial resistance by a thickened and stiffened arterial wall. Bakirci et al demonstrated that a lower APV is one of the independent predictors of CAD severity in patients with stable CAD.Combined results of previous studies, and by using the APV index as an available marker, risk stratification of CAD patients would be easier, especially for transferring patients for invasive procedures.To the best of our evaluations, there are limited investigations in such field and there is scarce assessment of the SYNTAX score and arterial stiffness correlation. APV was significantly correlated with STNTAX score inversely, which demonstrates that as APV decreases, the SYNTAX score will be increase. SYNTAX score is an indicator of CAD severityFurthermore, the APV decreases due to the increased resistance that develops secondary to atherosclerosis in the descending thoracic aorta. Thus, the APV is an easy and simple echocardiographic parameter, which can be used to assess atherosclerosis in the thoracic aorta.This was the first meta-analysis of the predictive effect of APV in CAD. Five articles were included in this study with a total of 490 patients. Our meta-analysis shows that APV has a predictive role in CAD using a simple and noninvasive procedure. However, each meta-analysis has its own limitations of methodology or research object. Because of lack of more studies in the field of APV in CAD, our included articles were limited.A predictive value of APV in CAD was established with suitable specificity and sensitivity. Moreover, AD and AS indices were significantly lower in CAD and non-CAD patients. Nonetheless, higher quality and large-scale studies are expected to further quantify the predictive effect of APV. According to the results of this study, APV could be used as a good noninvasive tool for CAD screening.Conceptualization: Fereshteh Ghaderi, Hoorak Poorzand, Hedieh Alimi, Laila Bigdelu, Afsoon Fazlinezhad, Faeze Keihanian.Data curation: Fereshteh Ghaderi, Shabnam Niroomand, Faeze Keihanian.Formal analysis: Shabnam Niroomand.Investigation: Faeze Keihanian.Methodology: Shabnam Niroomand.Project administration: Faeze Keihanian.Writing – original draft: Shabnam Niroomand, Faeze Keihanian.Writing – review & editing: Fereshteh Ghaderi, Faeze Keihanian.


This study aimed to conduct a meta-analysis to determine whether post-term birth has an increased risk of ASD.To retrieve eligible studies regarding the effect of post-term and ASD in children, major databases including PubMed, Scopus, and Web of Science were searched. A random effect model was used for meta-analysis. For assessing the quality of included studies, the GRADE checklist was used.I2 = 6.6%, P = 0.301). There was high heterogeneity in the studies reported risk of ASD based on OR .In total, 18 records were included with 1,412,667 sample populations from 12 countries. The pooled estimates of RR and OR showed a significant association between post-term birth and ASD among children, respectively  and . There was no heterogeneity among the studies that reported the risk of ASD among children based on RR (Post-term births still occur relatively frequently (up to 5–10%) even in developed countries. Our results showed that post-term birth is an increased risk of ASD, although high heterogeneity was found among the studies reported based on adjusted and crude forms, however, after subgroup analysis by gender, this heterogeneity disappeared among males. Autism spectrum disorder (ASD) is defined by severe social communication deficits and stereotyped, repetitive behaviors. Recognizing that the social problems that characterize ASD can occur in different forms, depending on language skills, general ability level, the severity of symptoms, context, and coexistence disorders, has led to a dramatic increase in the number of children with ASD .The pathophysiology of ASD is not fully understood, ASD was previously thought to be mainly genetic, however, genetic factors alone have been found to account for 20–30% of ASD cases, whereas the remaining 70–80% are due to a complex interaction between environmental risk factors such as prenatal and postnatal environments and genetic predisposition [A post-term birth extends beyond 42 weeks (294 days) from the first day of the last menstrual period, although the routine use of ultrasound to confirm the date of pregnancy can reduce the incidence of post-term birth, however, post-term birth still occur relatively frequently (up to 5–10%) even in developed countries  and assoA prior systematic review has reported an overall prevalence of 0.6% of ASD in people with post-term birth . Some st-Analysis (PRISMA) guidelines [This meta-analysis was performed considering the Preferred Reporting Items for Systematic Reviews and Metaidelines . The numTo retrieve eligible studies regarding the effect of post-term birth on ASD, major databases including PubMed, Scopus, and Web of Science were searched by the following keywords: post-term OR postterm OR postmature*) and (autism OR autistic OR autism spectrum disorders OR ASD).Only original research articles were considered and other types of articles including letters to the editor, case reports, and other systematic reviews were excluded. However, the reference list of such papers was investigated carefully for finding missed sources during database searching. Studies focused on the causal relationship between ASD and post-term birth including cases was included. There was no restriction on the language or the publication date of retrieved sources. Furthermore, only peer-reviewed articles (in published or in-press status) were considered.Two independent authors (A.S and E.J) performed the search procedures. Any conflict regarding the retrieved sources was resolved by discussion between authors. A PECOS  model was used for finding eligible studies. The Participants were all newborns, the Exposure was post-term birth, the Comparison was term birth, the Outcome was ASD and the Study design was observational study. After the title, abstract and full-text screening and adding the retrieved sources found by manual searching or found by checking the reference list of eligible studies, an electronic form was used for extracting information embedded in each source. The information included the first author's name, publication date, the country that the study was performed, study design, sample size, the measure that was used for effect size estimation, the age range of participants, diagnostic criteria that were used for autism, and quality of each study.The evaluation of the studies that were included in the analysis was conducted using a tool called the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) . The assI2. This process was repeated for a new set of n-1 studies, and continued until I2 dropped below the intended threshold of 50%. If there were multiple studies that could potentially result in I2 dropping below the threshold, we reported the minimum I2.In situations where there was high between-study heterogeneity, we employed a sequential algorithm  to deterA random effect model was used for meta-analysis. The effect size was calculated using the odds ratio (OR) and relative risk (RR) with a 95% confidence interval . All analyses were performed using STATA, version 13 . Furthermore, for all statistical analyses, the significance level was adjusted to 0.05. To investigate the source of heterogeneity, subgroup analyses for the type of study design, gender, and quality of studies were also performed.I2 statistic [I2 determines the heterogeneity between studies in a way that for I2 > 50% a significant between-study heterogeneity exists; otherwise, when I2 merges to zero, between-study heterogeneity is non-significant. The Cochrane Q-test determines the statistical significance of the heterogeneity. For assessing publication bias, the funnel plot was used as a graphical tool. The symmetrical distribution of studies in a funnel plot implies the absence of publication bias. Furthermore, Egger's [The between-study heterogeneity was calculated based on tatistic  and Coch Egger's  and Begg Egger's  tests weIn total, 746 records were identified by initial search Fig. . We remoI2 = 6.6%, P = 0.301). There was high heterogeneity in the studies reported risk of ASD based on OR .The association between post-term birth and ASD is presented in Fig. P values were 0.910 and 0.341 based on Begg’s and Eggerʼs regression, respectively.The funnel plot is presented in Fig. The results of this evaluation can be found in Table I2 threshold of 50% .To ensure between-study homogeneity, we conducted a sensitivity analysis using the sequential algorithm. By omitting the two studies , 23 fromI2 = 97.5%). There was no significant association between post-term birth and ASD in the studies with low quality . The subgroup analysis based on the child's gender showed that a significant association was found between post-term birth and ASD among male children . This association was homogenous, while there was no significant association between post-term birth and ASD among female children . There was a significant association between post-term birth and ASD in the studies that publication year was after 2000 . There was not a significant association between post-term birth and ASD in the studies based on continent and autism diagnosis criteria , but there was no significant difference in publication year between before and after 2000 and continent between Europe/USA and Asian .The subgroup analysis was performed based on the design of the studies, the quality of the studies, the child's gender, publication year, continent, and autism diagnosis criteria. OR in case–control and cohort studies were reported 0.94  and 1.30 , respectively. A significant association was found between post-term birth and ASD among cohort studies  . HoweverPost-term birth contributes to severe morbidities for the mother and child, including macrosomia, shoulder dystocia, birth injury, fourth degree perineal laceration, fetal compromise, antenatal and postpartum hemorrhage, fetal dysmaturity, labor  > 24 h and newborn respiratory distress syndrome .Post-term birth is considered a complex biological process, which is related to factors such as the duration of pregnancy, the delivery, the fetus status of the intrauterine, and the gender and fetal–placental system. Studies showed its prevalence in Austria, Belgium, Germany, Turkey, and Denmark to be 0.4%, 0.6%, 2.3%, 0.76%, and 8.1%, respectively, this rate varies between 1 and 2.5% in America and Canada and 1.16% in China .In some studies, it has been found that the occurrence of post-term birth is more common in female fetuses . HoweverPost-term birth and ASD have not yet been fully elucidated, and there are several reasons and pathways for it. First, a post-term birth typically has a higher risk for perinatal problems such as prolonged labor, cephalopelvic disproportion, and shoulder dystocia, which are associated with perinatal oxygen deficiency followed by neurobehavioral problems . A seconThirdly, it is possible that a disturbance of the ‘placental clock’, which regulates the duration of pregnancy, is involved. A marker of this clock is the placental secretion of corticotrophin-releasing hormone, which is lower in post-term deliveries than in term deliveries, is a sign of this clock, and its principal regulator of the maternal–fetal hypothalamic–pituitary–adrenal (HPA) axis. It has been suggested that placental endocrine dysfunction or maternal stress at critical times during fetal development may influence the fetal HPA axis, leading to neuroendocrine abnormalities that could increase the child more susceptibility to neurobehavioral disorder later in life , 48. AlsHowever, some researchers have raised doubts about the connection between perinatal and neonatal issues and autism, questioning whether it is a direct cause. They suggest that the correlation may be influenced by birth order, as complications during these periods are more common in first-born, fourth-born, and later offspring. It has been noted that individuals in these birth orders have a higher likelihood of developing autism .This study has some limitations. First, a high heterogeneity among the results of our study was the limitation of this meta-analysis. However, with subgroup analysis based on gender, this heterogeneity was resolved in males. This study included 1,412,667 participants who reported that post-term birth was a risk factor for ASD. In addition, publication bias did not occur among the results and these were strengths of the present meta-analysis.Post-term birth still occurs relatively frequently (up to 5–10%) even in developed countries. Our results showed that post-term birth is an increased risk of ASD, although high heterogeneity was found among the studies reported based on adjusted and crude forms, however, after subgroup analysis by gender, this heterogeneity disappeared among males.


The aim of this meta-analysis is to assess the effect of different independent predictors on acute kidney injury (AKI) after transcatheter aortic valve implantation (TAVI). This meta-analysis adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A comprehensive database search was conducted using PubMed, Web of Science, and Scopus for the period from January 1, 2015, to August 15, 2023. The following key terms were employed: "transcatheter aortic valve implantation" OR "transcatheter aortic valve replacement" AND "acute kidney injury" OR "acute renal failure." Our search was limited to studies published exclusively in the English language. The statistical analysis was conducted using RevMan version 5.4.1 (The Cochrane Collaboration). Estimates were presented as odds ratio (OR) with 95% confidence interval (CI) for categorical variables, while continuous variables were reported as mean difference (MD) with 95% CI. A total of 19 studies met the selection criteria and were included in the meta-analysis. The pooled incidence of AKI was reported as 20% (95% CI: 18-20%). Factors significantly associated with post-TAVI AKI encompass hypertension, chronic kidney disease (CKD), low estimated glomerular filtration rate (eGFR), high baseline creatinine levels, peripheral vascular disease (PVD), Society of Thoracic Surgeons (STS) score, European System for Cardiac Operative Risk Evaluation (EUROscore) II, and the transfemoral surgical approach.  Transcatheter aortic valve implantation (TAVI) is a contemporary and extensively researched approach for addressing symptomatic individuals afflicted by severe aortic stenosis (AS) . A multiTAVI is typically performed on elderly and high-risk patients, who often present with both a high prevalence of chronic kidney disease (CKD) and heart failure . AdditioAlthough the majority of TAVI-related AKI cases are mild, the impact is particularly pronounced in older, more frail patients with established or potential underlying kidney dysfunction. This risk is compounded in scenarios where the patient necessitates additional common angiographic procedures . TAVI paThe aim of this meta-analysis is to assess the effect of different independent predictors on AKI after TAVI. By understanding the impact of different factors on AKI after TAVI, it will help physicians to identify patients at high risk of AKI; thus, early management can prevent the development of AKI in this population.MethodologyThis meta-analysis adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).Search Strategy and Study SelectionA comprehensive database search was conducted using PubMed, Web of Science, and Scopus for the period from January 1, 2015, to August 15, 2023. The following key terms were employed: "transcatheter aortic valve implantation" OR "transcatheter aortic valve replacement" AND "acute kidney injury" OR "acute renal failure." Our search was limited to studies published exclusively in the English language. All articles centered on risk factors associated with post-TAVI AKI. The reference lists of all included studies were also manually reviewed.All eligible records were imported into EndNote X9. After eliminating duplicates, initial screening was performed based on abstracts and titles, followed by full-text screening using predefined inclusion and exclusion criteria. We encompassed studies in which participants underwent TAVI and studies that evaluated factors linked to post-operative AKI. Our inclusion encompassed studies regardless of the criteria utilized to diagnose AKI. We excluded reviews, editorials, meta-analyses, and expert opinions.Data Extraction and Quality AssessmentTwo authors independently extracted the following data from the included studies: first author, publication year, study setting, sample size, number of patients who developed AKI, criteria employed to diagnose AKI, and patients' characteristics. The quality assessment of the included studies was carried out using the Newcastle-Ottawa Scale. This scale allocates stars based on three pivotal criteria: selection of study groups, comparability of groups, and ascertainment of exposure/outcome. The scale facilitates the identification of bias risk in observational studies, offering a standardized evaluation of study quality across diverse research articles.Data Analysis2 statistic. A random-effects model was applied regardless of heterogeneity to address variations due to study settings, study populations, and AKI diagnostic criteria. All p-values were two-sided, and significance for heterogeneity was considered at a p-value <0.05. The statistical analysis was conducted using RevMan version 5.4.1 (The Cochrane Collaboration).Estimates were presented as odds ratio (OR) with 95% confidence interval (CIs) for categorical variables, while continuous variables were reported as mean difference (MD) with 95% CI. Study heterogeneity was assessed using the IResultsFigure Factors Associated With AKITable Table DiscussionThe current meta-analysis evaluates the risk factors linked to AKI in patients undergoing TAVI. Factors significantly associated with post-TAVI AKI encompass hypertension, CKD, low estimated GFR (eGFR), high baseline creatinine levels, PVD, SSC score, EUROscore II, and the TF surgical approach. Notably, the meta-analysis underscores a notable, independent risk associated with a previous history of CKD.This finding aligns with studies by Wang et al.  and WessOur analysis indicates that previous occurrences of PVD and hypertension stand as risk factors for post-TAVI AKI. Wang et al.'s multivariable regression  further Our meta-analysis highlights a decreased AKI risk associated with TF access in TAVI. A recent observational meta-analysis identified a higher mortality risk in transapical TAVI compared to TF access . MoreoveA limitation of this meta-analysis is substantial heterogeneity, likely stemming from diverse AKI diagnostic criteria and study settings. Additionally, in clinical practice, TAVI procedures predominantly employ TF access, reserving the transapical approach for infeasible cases. Notably, most transapical TAVI patients have PVD. A recent study confirmed pre-existing PVD as an independent AKI risk factor post-TAVI. While our findings also indicate an increased AKI risk with transapical TAVI, it is crucial to note that the transapical method itself might not adversely affect kidneys; antecedent PVD, rather than the method, amplifies AKI risk. To comprehensively grasp the transapical access and post-TAVI AKI correlation, contrasting AKI occurrences in transapical TAVI patients without PVD versus those with PVD is imperative.In conclusion, this meta-analysis offers comprehensive insights into the risk factors associated with AKI in patients undergoing TAVI. Through the rigorous evaluation of a substantial dataset, the analysis has illuminated critical factors contributing to AKI occurrence post-TAVI. Notably, the pooled incidence of AKI was determined to be 20% (95% CI: 18-22%), underscoring the significance of this complication. Factors significantly associated with post-TAVI AKI, including hypertension, PVD, high creatinine, low GFR, CKD, EUROscore II, STS score, and TF approach. Further research addressing the limitations of heterogeneity and refining our understanding of the interplay between PVD and surgical approach will continue to enhance our comprehension of AKI dynamics in this patient population.