BackgroundIt still remains unclear whether subxiphoid video-assisted thoracoscopic surgery (SVATS) thymectomy is safe and reasonable. This meta-analysis aims at assessing the effectiveness and safety of SVATS for thymoma in comparison with that of intercostal video-assisted thoracoscopic surgery (IVATS) thymectomy.MethodsAll the relevant data systematically analyzed in this thesis were retrieved from PubMed, the Cochrane Library, web of science, EMBASE, and ClinicalTrials.gov. The time span for data retrieval was from the date of database establishment to March 2022. The outcome indicators include operation time, intraoperative blood loss, duration of postoperative drainage, postoperative hospital days, visual analogue scale (VAS) score on the day of operation, VAS score on postoperative day 3, and VAS score on postoperative day 7; postoperative complications were analyzed in our meta-analysis.ResultsIn 13 studies of this paper, there were 1,198 cases included. Among them, 563 cases were treated by SVATS thymectomy and 635 cases by IVATS thymectomy. There was no significant difference in the operation time [113.38 vs. 119.91  min, 95% confidence interval (CI): −0.70–0.15, p = 0.20) and the incidence of intraoperative and postoperative complications (RR = 0.82, 95% CI: 0.58–1.15, p = 0.25) between SVATS thymectomy and IVATS thymectomy. However, SVATS thymectomy significantly reduced the amount of intraoperative blood loss (47.68 vs. 66.69  mL, SMD = −0.57, 95% CI: −0.95 to −0.18, p = 0.004), postoperative drainage days (2.12 vs. 2.72 days, SMD = −0.46, 95% CI: −0.74 to −0.18, p = 0.001), postoperative hospital stays (4.53 vs. 5.91 days, SMD = −0.64, 95% CI: −0.96 to −0.31, p = 0.0001), and VAS scores after the operation.DiscussionSVATS thymectomy is safe and feasible, and the perioperative effect is better than IVATS thymectomy to a certain extent, which is worthy of popularization and further research.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/

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Single-nucleotide polymorphism (SNP) involves the replacement of a single nucleotide in a deoxyribonucleic acid (DNA) sequence and is often linked to the development of specific diseases. Although current genotyping methods can tag SNP loci within biological samples to provide accurate genetic information for a disease associated, they have limited prediction accuracy. Furthermore, they are complex to perform and may result in the prediction of an excessive number of tag SNP loci, which may not always be associated with the disease. Therefore in this manuscript, we aimed to evaluate the impact of a newly optimized fuzzy clustering and binary particle swarm optimization algorithm (FCBPSO) on the accuracy and running time of informative SNP selection. Fuzzy clustering and FCBPSO were first applied to identify the equivalence relation and the candidate tag SNP set to reduce the redundancy between loci. The FCBPSO algorithm was then optimized and used to obtain the final tag SNP set. The prediction performance and running time of the newly developed model were compared with other traditional methods, including NMC, SPSO, and MCMR. The prediction accuracy of the FCBPSO algorithm was always higher than that of the other algorithms especially as the number of tag SNPs increased. However, when the number of tag SNPs was low, the prediction accuracy of FCBPSO was slightly lower than that of MCMR (add prediction accuracy values for each algorithm). However, the running time of the FCBPSO algorithm was always lower than that of MCMR. FCBPSO not only reduced the size and dimension of the optimization problem but also simplified the training of the prediction model. This improved the prediction accuracy of the model and reduced the running time when compared with other traditional methods.