Development and validation of a nomogram diagnostic model for the diagnosis of Prosthetic Joint Infections based on serum and joint fluid inflammatory markers / 中华骨科杂志

ABSTRACT

Objective:To construct a column-line diagram diagnostic model based on serum and joint fluid inflammatory markers for the diagnosis of periprosthetic joint infections (PJI) after joint arthroplasty and to validate its predictive ability.Methods:The clinical data of 181 patients diagnosed with PJI or aseptic loosening in the Department of Orthopedics of the First Affiliated Hospital of Chongqing Medical University from January 2015 to June 2020 were retrospectively collected as a modeling group. The best indicators for diagnosing PJI were screened by lasso regression, single-factor and multifactor analysis. By comprehensively considering the weights and intrinsic connections of the indicators, a column-line diagram diagnostic model was constructed and used to develop a clinical decision support system (CDSS). Prospectively, the clinical data of patients diagnosed with PJI or aseptic loosening in the Department of Orthopedics of the First Hospital of Chongqing Medical University from July 2020 to December 2022 were collected as a validation group, and the diagnostic performance of the column-line diagram model was externally validated by methods such as receiver operating characteristic curve (ROC).Results:There were 85 cases of PJI in the 181 cases modeling group and 23 cases of PJI in the 49 cases validation group. Among the 27 potential factors analyzed by lasso regression analysis, body mass index (BMI), blood tests including platelet (PLT), absolute lymphocyte value, interferon γ (IFN-γ), ESR, IL-6, C-reactive protein, D-dimer, and joint fluid tests including C-reactive protein, IL-1, IL-4, IL-6, percentage of multinucleated neutrophils (PMN%), and CD64 may be potential indicators for the diagnosis of PJI. Univariate found significant differences between hematologic tests including sedimentation, C-reactive protein, IL-6, D-dimer and joint fluid tests including C-reactive protein, joint fluid CD64 index, C-reactive protein, IL-1, IL-4, IL-6, PMN%( P<0.05). Further multifactorial regression analysis screened serum IL-6, D-dimer, joint fluid CD64 index, C-reactive protein, IL-1, IL-4, IL-6, and percentage of multinucleated neutrophils, and based on that, the column-line graph model and CDSS system were constructed. The area under the ROC in the validation group was 0.978, and the AUC in the internal validation was 0.995; the C-index of the calibration curve was 99.50%, and the C-index of the internal validation was 99.53%, suggesting that the column-line diagram model has a good predictive ability. Conclusions:The column-line diagram for diagnosing PJI based on multiple diagnostic indicators showed good diagnostic performance. The CDSS system constructed by column-line diagrams could assist clinicians in diagnosing PJI and making reasonable strategies in time.