Sepsis is a clinical syndrome caused by the host reaction disorder induced by infection, which leads to serious organ function damage. Sepsis is a serious disease with high mortality, which is the main reason of death caused by infection. Single nucleotide polymorphisms (SNP) is one of the most common genetic variants in human, and is closely related to the genetic susceptibility, early diagnosis, disease development and prognosis of sepsis. This article makes a review on the relationship between CD14, Toll like receptor (TLR), tumor necrosis factor (TNF), interleukins (IL-1 and IL-6), plasminogen activator inhibitor 1 (PAI-1), angiotensin converting enzyme (ACE) and other gene polymorphisms and genetic susceptibility of sepsis, in order to affect in sepsis on the early prediction, diagnosis, and treatment.

OBJECTIVE: To compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM). METHODS: We retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient. RESULTS: In total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897 vs 0.859; P < 0.01). The interobserver agreement did not differ significantly between ccLS v1.0 and ccLS v2.0 (0.56 vs 0.60; P > 0.05). CONCLUSION ccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.
Female ; Male ; Humans ; Adult ; Middle Aged ; Aged ; Carcinoma, Renal Cell/diagnosis* ; Retrospective Studies ; Kidney ; Carcinoma ; Kidney Neoplasms/diagnosis*