Analysis of risk factors affecting the prognosis of patients with sepsis and construction of nomogram prediction model.

OBJECTIVE: This study analyzed the clinical data of 200 sepsis patients, exploring the risk factors that affect patient prognosis and providing the basis for clinically targeted intervention to improve patient prognosis. PATIENTS AND METHODS: 200 septic patients were admitted to Yulin Second Hospital, and they were divided into a survival group of 151 patients and a death group of 49 patients, according to their clinical outcomes on admission. The relevant clinical parameters within 24 h of admission were collected, and the independent risk factors affecting the prognosis of septic patients were analyzed by multivariate Logistic regression. R language 4.21 software was used to construct a nomogram prediction model. The receiver operating characteristic curve was used to evaluate the discrimination of the nomogram model, and decline curve analysis was drawn to evaluate the effectiveness of the model. RESULTS: In the nomogram prediction model, age, the Acute Physiology and Chronic Health Scoring System Domain (APACHE II) score, the Sequential Organ Failure Assessment (SOFA) score, C-reactive protein (CRP), total bilirubin, albumin (Alb), urea nitrogen, creatinine, and lactate (Lac) were independent risk factors for death in septic patients. The area under the receiver operating characteristic (ROC) curve for predicting the prognosis of septic patients was 0.597-1.000, and the calibration curve tends to be the ideal curve. The model had good discrimination and calibration and had high accuracy in evaluating septic patients. The modeling curves in the decline curve analysis (DCA) were all above the two extreme curves, which had good clinical value. CONCLUSIONS: Nine clinical variables have been found to be independent risk factors for death in septic patients. The prediction model established based on this has good accuracy, discrimination, and consistency in predicting the prognosis of sepsis patients.

Aberrant Expression of a Proliferation-Inducing Ligand Underlies Autoimmune Mechanisms in Immune Thrombocytopenia.

PURPOSE: To study the relationship between surface membrane-bound APRIL and ITP. METHODS: The peripheral blood of all subjects, 50 patients diagnosed with ITP and 25 healthy controls, was collected. Flow cytometry was used to detect the expression of membrane-bound APRIL on immune cells and platelets. ELISA was used to detect the content of soluble APRIL in plasma. RESULTS: Membrane-bound APRIL was only expressed on the surface of platelets in both ITP patients and controls. APRIL expression on the platelet surface was significantly lower in newly diagnosed (P < 0.001) and chronic (P < 0.001) ITP patients than in controls. Platelet surface APRIL level was significantly enhanced in patients with complete remission after treatment (P = 0.02) but not in those with no response after treatment. Platelet surface APRIL level in ITP patients was negatively correlated with serum APRIL level (r = -0.09765, P = 0.0424). CONCLUSIONS: Platelet surface APRIL may play a key immunoregulative role. Platelet surface APRIL is likely to be one source of the excessive serum APRIL in ITP patients. The effectiveness of treatment may be measured by determining the platelet surface APRIL levels in ITP patients.