Background: Sepsis-induced myocardial injury (SIMI) is a common organ dysfunction and is associated with higher mortality in patients with sepsis. We aim to construct a nomogram prediction model to assess the 28-day mortality in patients with SIMI. . Method: We retrospectively extracted data from Medical Information Mart for Intensive Care (MIMIC-IV) open-source clinical database. SIMI was defined by Troponin T (higher than the 99th percentile of upper reference limit value) and patients with cardiovascular disease were excluded. A prediction model was constructed in the training cohort by backward stepwise Cox proportional hazards regression model. The concordance index (C-index), area under the receiver operating characteristics curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration plotting and decision-curve analysis (DCA) were used to evaluate the nomogram. Results: 1312 patients with sepsis were included in this study and 1037 (79%) of them presented with SIMI. The multivariate Cox regression analysis in all septic patients revealed that SIMI was independently associated with 28-day mortality of septic patients. The risk factors of diabetes, Apache II score, mechanical ventilation, vasoactive support, Troponin T and creatinine were included in the model and a nomogram was constructed based on the model. The C-index, AUC, NRI, IDI, calibration plotting and DCA showed that the performance of the nomogram was better than the single SOFA score and Troponin T. Conclusion: SIMI is related to the 28-day mortality of septic patients. The nomogram is a well-performed tool to predict accurately the 28-day mortality in patients with SIMI.

Objective: To analyze the association between serum uric acid (UA) levels and bone turnover markers. Methods: 62 ankylosing spondylitis (AS) and 50 healthy controls were enrolled. Bone turnover markers were detected by electrochemiluminescence method. The laboratory measurements of AS were collected. The relationship between UA and bone turnover markers were analyzed. Results: The mean level of serum UA was 409.96±93.06 umol/L in healthy controls, and 348.89±68.95 umol/L in AS patents. The levels of UA were significantly higher in healthy controls than in AS patients(P=0.000). In healthy controls, UA was significantly negative correlated with osteocalcin (OC) and C-terminal crosslaps of type I collagen (β-CTX) (P<0.05). However, UA was significantly positive correlated with β-CTX in AS patients with low bone mineral density (BMD). Conclusion: UA could reflect bone resorption in AS patients with low BMD. UA could be used as a marker for the treatment of AS with low BMD and following-up.