Our study is carried out strictly in accordance with the criterion of the preferred report items of systematic review and meta-analysis report. The research scheme is determined by all the authors, and the steps of literature retrieval, literature quality evaluation, data statistics, result merging, and report writing are completed in turn.
Retrieval strategy
Under the guidance of the Cochrane Review method, two authors (Haitao Zhang and Xingyang Zhu) search online databases such as PubMed, Embase, Web of Science, and Cochrane Library. The search subject words and Mesh words are as follows: “periprosthetic joint infection” or “prosthesis-related infections” stands for disease, “D-dimer” or “D-dimer fibrin” or “D-dimer fragments” or “fibrin fragment D1 dimer” or “fibrin fragment DD” or “fibrin fragment D-dimer” represents target index. The range of retrieval dates is from the establishment of the database to April 2020. When searching, we only include English literature. After database screening, we manually searched some of the references included in the literature to obtain the valuable literature for this study.
Study selection
The title, abstract or full text of all search results are reviewed by two censors (Haitao Zhang and Xiaobo Sun) in detail. When there is still a disagreement between the two examiners after reading the full text, it will be left to Professor (Yirong Zeng) to make the final decision. The inclusion criteria of the literature are as follows:(1) Using D-Dimer as an index for the diagnosis of PJI;(2) Have integrated data (including true positive, false negative, false positive, and true negative) to construct a 2×2 table;(3) There is a definite gold standard such as Musculoskeletal Infection Society (MSIS) or International consensus on infection(ICM) to compare the diagnostic accuracy with D-dimer.
Data extraction and quality assessment
The following data extraction and literature quality evaluation are completed by (Pengfei Xin and Ke Jie), two researchers who are familiar with the knowledge of statistics, back to back, and the extracted data are input into a table in Excel. The data include: the author of the study, the year, the country or region in which the article was published, the design type of the study, the number of cases, sex ratio, patient's age and BIM index, the gold standard used in the study, the detection method and the cut-off value of D-dimer. In addition, the diagnostic accuracy of D-dimer (AUC) and the true positive, false positive, true negative, and false negative data used to construct 2 × 2 table were also recorded in detail.
The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) in Revman (Version5.3) software was used to evaluate the quality of all the literature included in the study. QUADAS-2 is an updated version of the original QUADAS, including four aspects of patient selection, index test, reference standard, and flow and timing, which has a more accurate bias level and applicability to the original research than the original QUADAS.
Statistical analysis
All data analysis and picture production are carried out by using the commands in the Stata14.0 software. The bivariate random effect model was selected to analyze the tp, fp, fn, tn values of 2 × 2 table extracted in the study and to test the heterogeneity. The sensitivity, specificity, positive likelihood ratio (PLR), Negative likelihood ratio (NLR), diagnostic score, and diagnostic odds ratio (DOR) were obtained after integration. Among them, the higher the value of DOR, the higher the diagnostic value.
Additionally, the summary receiver operating characteristic (SROC) was drawn by the Midas command, and the area under the curve (AUC) was calculated. AUC represents the diagnostic accuracy of D-dimer.
The heterogeneity is expressed as the inconsistency index (I2) statistic, the smaller the I2, the smaller the heterogeneity. When I2 is 75%, 50% and 25% respectively, it corresponds to large, medium and small literature heterogeneity, respectively. If the heterogeneity is large, meta-regression and subgroup analysis are performed to identify the source of heterogeneity. We believe that the variables that may affect the heterogeneity are the type of study design, the threshold used in the study, the number of cases, the index of diagnostic gold, the sample type, and the country or region in which the literature is published.
In order to definitely judge the publication bias, the funnel chart (Deeks' funnel plot) was drawn. Besides, the change of the diagnostic value of D-dimer on the incidence of PJI can be clearly shown by drawing a Fagan plot diagram.