Objective:To evaluate the effects of high versus low positive end-expiratory pressure (PEEP) for lung-protective ventilation strategies through a meta analysis.Methods:Web of Science, the Cochrane Library, PubMed, EBSCO, Embase, Medline, CNKI, Wanfang data and VIP data were searched from inception to July 15, 2019 for prospective randomized controlled trials involving comparing the effects of ventilation with different levels of PEEP for lung-protective ventilation strategies during operation.Evaluation indexes included: incidence of postoperative pulmonary complications and other complications, and incidence of intraoperative hypotension.After two reviewers independently identified the literature and conducted data extraction and quality evaluation, RevMan 5.3 software was used to analyze the data.Results:Eight prospective randomized controlled trials involving 3 324 participants were included.Compared with low PEEP group, no significant change was found in the incidence of postoperative pulmonary complications and other complications ( P>0.05), and the incidence of intraoperative hypotension was significantly increased in high PEEP group ( P<0.05). Conclusion:The effect of lung-protective ventilation strategy with high PEEP is not superior to that with low PEEP.

Objective To develop a predictive model for postoperative acute kidney injury(AKI)in elderly patients using machine learning methods.Methods The preoperative information and postopera-tive follow-up information of elderly patients who underwent surgery from June 2019 to July 2020 were col-lected,and the laboratory examination results were extracted.A total of 115 preoperative variables were in-cluded.A model of postoperative AKI was constructed using five methods:extreme gradient boosting(XGB),gradient boosting machine(GBM),random forest(RF),support vector machine(SVM),and elastic net logistic regression(ELA).The performance of the model was evaluated using area under the re-ceiver operating characteristic curve(AUROC),area under the precision recall curve(AUPRC),and Brier score.To simplify the model for clinical application,the original model was obtained and some varia-bles with low correlation were removed,and the model was evaluated again using the above method.Results This study ultimately included 5 929 elderly patients,3 359 males(56.7％)and 2 570 females(43.3％),aged 65-99 years.Among them,154 patients(2.6％)experienced postoperative AKI.Among the prediction models constructed using five machine learning methods,XGB has the highest AUROC and AU-PRC,with values of 0.798(95％CI 0.705-0.888)and 0.230(95％CI 0.079-0.374),respectively.Its Brier score is the lowest among all models,the score is 0.023(95％CI 0.014-0.029).After simplifying the XGB model,72 variables were retained.The AUROC of the simplified model was 0.790(95％CI 0.711-0.861),slightly lower than that of the original model.The AUPRC was 0.176(95％CI 0.070-0.313),and the Brier score was 0.024(95％CI 0.017-0.033),and there was no significant statistical difference,indicating that there was no significant difference in the predictive ability of the simplified model compared to the original model.Conclusion Among the five machine learning methods used to construct postoperative AKI prediction models,XGB has the best predictive performance.The simplified XGB predic-tion model still retains high predictive performance and is easier to be promoted in clinical practice.

Objective:Using bibliometrics to study the international literature on fat transplantation in recent 10 years, and to explore the research status, hot spots and development trend in this field.Methods:Literatures related to fat transplantation research from 2011 to 2020 were searched through the core collection of Web of Science database, and the literatures were screened strictly according to inclusion and exclusion criteria. Statistical analysis was conducted on the year, journal, first author, number of articles published by countries and institutions, and distribution of disciplines by bibliometrics. Citespace5.7.R5W software was used for co-citation analysis of the included literatures. Cooccurrence analysis and emergent word analysis were also carried out on the keywords in the literature. VOSviewer1.6.16 software was used to perform visual clustering of terms in the title and abstract of the included literature to reveal hot topics and research frontiers.Results:A total of 4 901 papers were included, and the number of annual publications continued to increase from 2011 to 2020. The top three publications during the study period were Plastic and Reconstructive Surgery (320 papers), Aesthetic Surgery Journal (171 papers), and PLoS One (113 papers). The first authors were Rafael Denadai (13 papers), Gentile Pietro(12 papers), Khouri Roger(6 papers). The most productive countries and institutions in this field were the United States (1 646 papers), China (853 papers), and Italy (383 papers). The organizations with the largest number of publications were the University of Pittsburgh (96 papers), Shanghai Jiao Tong University (78 papers), and Milan University (63 papers). There were 87 research categories in the literature related to fat transplantation, of which surgery was involved mostly. Visual analysis of Cites Pace5.7.R5W software showed that 4 901 references had established a co-citation network consisting of 381 nodes, 608 links and 12 clusters. There were 69 599 keywords in the literature, and the top five keywords from high to low were "transplantation" "adipose tissue" "stem-cell" "tissue" , and "obesity" . In the literature, the keywords with the highest intensity of outburst was "outcome" , and the keywords with the longest duration of outburst was "cartilage" . In recent years, the five keywords with outburst were "liver disease" "trial" "stromal vascular fraction" "outcome" , and " Akkermansia muciniphila" . VOSviewer1.6.16 software visualization clustering result showed that the application of fat transplantation in plastic surgery, the source of adipose tissue and its survival mechanism in vivo, and the laboratory research on fat regeneration were the three hot spots in the field of fat transplantation technology. Conclusions:The research on fat transplantation is on the rise in the world, and research institutions at home and abroad are conducting in-depth exploration on fat transplantation. Recent research focuses on improving the long-term survival rate of fat transplantation, and the research level is gradually in-depth at the molecular level.

Objective:Using bibliometrics to study the international literature on fat transplantation in recent 10 years, and to explore the research status, hot spots and development trend in this field.Methods:Literatures related to fat transplantation research from 2011 to 2020 were searched through the core collection of Web of Science database, and the literatures were screened strictly according to inclusion and exclusion criteria. Statistical analysis was conducted on the year, journal, first author, number of articles published by countries and institutions, and distribution of disciplines by bibliometrics. Citespace5.7.R5W software was used for co-citation analysis of the included literatures. Cooccurrence analysis and emergent word analysis were also carried out on the keywords in the literature. VOSviewer1.6.16 software was used to perform visual clustering of terms in the title and abstract of the included literature to reveal hot topics and research frontiers.Results:A total of 4 901 papers were included, and the number of annual publications continued to increase from 2011 to 2020. The top three publications during the study period were Plastic and Reconstructive Surgery (320 papers), Aesthetic Surgery Journal (171 papers), and PLoS One (113 papers). The first authors were Rafael Denadai (13 papers), Gentile Pietro(12 papers), Khouri Roger(6 papers). The most productive countries and institutions in this field were the United States (1 646 papers), China (853 papers), and Italy (383 papers). The organizations with the largest number of publications were the University of Pittsburgh (96 papers), Shanghai Jiao Tong University (78 papers), and Milan University (63 papers). There were 87 research categories in the literature related to fat transplantation, of which surgery was involved mostly. Visual analysis of Cites Pace5.7.R5W software showed that 4 901 references had established a co-citation network consisting of 381 nodes, 608 links and 12 clusters. There were 69 599 keywords in the literature, and the top five keywords from high to low were "transplantation" "adipose tissue" "stem-cell" "tissue" , and "obesity" . In the literature, the keywords with the highest intensity of outburst was "outcome" , and the keywords with the longest duration of outburst was "cartilage" . In recent years, the five keywords with outburst were "liver disease" "trial" "stromal vascular fraction" "outcome" , and " Akkermansia muciniphila" . VOSviewer1.6.16 software visualization clustering result showed that the application of fat transplantation in plastic surgery, the source of adipose tissue and its survival mechanism in vivo, and the laboratory research on fat regeneration were the three hot spots in the field of fat transplantation technology. Conclusions:The research on fat transplantation is on the rise in the world, and research institutions at home and abroad are conducting in-depth exploration on fat transplantation. Recent research focuses on improving the long-term survival rate of fat transplantation, and the research level is gradually in-depth at the molecular level.