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Objective:To explore the relationship between the levels of serum complement C3 and C4 and the degree of renal pathological injury in patients with IgA nephropathy (IgAN).Methods:It was a retrospective study. The clinical and pathological data of patients with primary IgAN diagnosed by renal biopsy in the Department of Nephrology of the Second People's Hospital of Qujing City, Yunnan Province from December 1, 2019 to December 31, 2022 were collected. According to the IgAN Oxford classification criteria, the patients were divided into mild renal pathological injury group (mild group, <3 pathologic types) and severe renal pathological injury group (severe group, ≥3 pathological types). The levels of serum C3 and C4 and other clinical data were compared between the two groups. Spearman correlation method was used to analyze the correlation between serum C3, C4 levels and estimated glomerular filtration rate (eGFR) during renal biopsy.Multivariate logistic regression model was used to analyze the influencing factors of the pathological injury degree in IgAN patients and the forest map depicted the effect of risk factors.Results:A total of 164 IgAN patients were included in the study, including 77 males (47.0%), aged (35.5±12.9) years old. There were 60 patients in the mild group and 104 patients in the severe group. Compared with the mild group, the patients in the severe group were older, had higher levels of serum C4, serum uric acid, low density lipoprotein cholesterol and 24 h urinary protein, higher proportions of hypertension, glucocorticoids/immunosuppressant therapy, C3 deposition in renal tissues and microscopic hematuria, and had lower hemoglobin and serum C3 level (all P<0.05). The results of Spearman correlation analysis showed that the level of serum C3 was positively correlated with eGFR ( r=0.303, P<0.001), and the level of serum C4 was negatively correlated with eGFR ( r=-0.238, P=0.002). Multivariate logistic regression analysis results showed that serum C3 (every 0.01 g/L increase, OR=0.976, 95% CI 0.957-0.996, P=0.018), serum C4 (every 0.01 g/L increase, OR=1.091, 95% CI 1.020-1.166, P=0.011), hemoglobin ( OR=0.969, 95% CI 0.950-0.988, P=0.002), and serum uric acid ( OR=1.005, 95% CI 1.001-1.009, P=0.012) were independent related factors of renal pathological damage (severe injury /mild injury) in IgAN patients. Conclusions:Serum C3 and C4 are independent related factors of the severity of renal pathological injury in IgAN patients.
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Objective:To explore the prognostic risk factors of patients with multiple injuries and establish a nomogram prediction model.Methods:The clinical data of 291 patients with multiple injuries admitted to the Emergency Intensive Care Unit (EICU) of General Hospital of Ningxia Medical University were collected, including sex, age, open injury, norepinephrine use, mechanical ventilation, time to hospital after injury, distance to hospital, relative lymphocyte value, platelet count, lactic acid, injury severity score (ISS), acute physiology and chronic health evaluationⅡ (APACHE Ⅱ), Glasgow coma scale (GCS), number of blood transfusions, number of operations, and previous history of diabetes, hypertension and smoking within 24 h after admission. According to whether the condition worsened during the hospitalization of EICU, the patients were divided into the deterioration group and improvement group. SPSS26.0 software was used for statistical analysis of the data, univariate and multivariate analysis were used to screen the factors affecting the prognosis of patients with multiple injuries, receiver operating characteristic (ROC) curve and forest chart were drawn, and the influencing factors in binary Logistic regression model were used to make the nomogram.Results:Mechanical ventilation, norepinephrine use, age, relative lymphocyte value, lactic acid, APACHE-II score, GCS score, and number of operations were significant for predicting the prognosis of patients with multiple injuries ( P<0.05). The independent influencing factors obtained by binary Logistic regression model were age, lactic acid, APACHE-Ⅱ score and number of operations. ROC curve analysis showed that the area under the curve was the largest in multi-factor combined prediction, followed by APACHE-Ⅱ score. The diagnostic cut-off value of each index was as follows: age >58 years old, relative lymphocyte value≤ 8.62%, lactic acid >1.72, APACHE-Ⅱ score >16, GCS score≤ 6, and number of operations≤ 0. The R software was used to establish a nomogram of the influencing factors in the binary Logistic regression model, which had good predictive value. Conclusions:The nomogram constructed by age, relative lymphocyte value, lactic acid, APACHE-Ⅱ score, GCS score, number of operations, mechanical ventilation, and norepinephrine use has a good predictive value for the prognosis of patients with multiple injuries, and is worthy of promotion..