血清DBil、Ca、TCO₂联合LDH对早期重症 急性胰腺炎的预测价值

Predictive Value of Serum DBil, Ca, TCO₂ Combined with LDH for Early Severe Acute Pancreatitis

摘要: 目的：探讨血清DBil、Ca、TCO₂联合LDH对急性胰腺炎(AP)患者病情严重程度的预测价值，并建立预测模型。方法：本研究为回顾性研究，分析2019年1月至2023年7月我院收治的499例急性胰腺炎患者的临床资料，根据患者出院诊断将患者分为非重症急性胰腺炎(Non-severe acute pancreatitis, NSAP)组(轻症急性胰腺炎(MAP)加中重度急性胰腺炎(MSAP))和重症急性胰腺炎(severe acute pancreatitis, SAP)组，其中非重症急性胰腺炎共349例(MAP + MSAP组)，重症急性胰腺炎共150例(SAP组)。比较两组患者基线资料与入院48 h内实验室结果的差异(包括WBC、N%、L%、CRP等)。统计分析血清DBil、Ca²⁺、TCO₂、LDH水平与急性胰腺炎患者病情严重程度的相关性。结果：两组间比较显示，重症急性胰腺炎(SAP)组患者血清直接胆红素(DBil)、总二氧化碳浓度(TCO₂)及乳酸脱氢酶(LDH)检测值显著高于非重症组，重症急性胰腺炎组血清Ca²⁺水平显著低于非重症急性胰腺炎组，两组间差异均具有统计学意义(P < 0.001)。将收集的数据通过单因素分析，从而初步筛选出有意义的变量，随后通过LASSO回归模型的十折交叉验证，确定最佳惩罚项系数λ，在λ处筛选，最终筛选出9个潜在的相关因素，分别为：DBil、Crea、BUN、PT、Ca、TCO₂、LDH、BS、HbA1c，经二元多因素Logistic回归分析显示，DBil、Ca、TCO₂、LDH是重症急性胰腺炎的独立危险因素，列线图预测模型的C-index为0.793，受试者工作特征(ROC)曲线分析显示，DBil、Ca、TCO₂、LDH三者联合检测对重症急性胰腺炎的诊断有较高的敏感度(0.660)和特异度(0.854)，约登指数为0.514，Hosmer-Lemeshow拟合优度P值为0.122，大于0.05。结论：根据DBil、Ca、TCO₂、LDH建立的预测模型可用于评估急性胰腺炎患者的病情严重程度。

Abstract: Objective: To investigate the predictive value of serum direct bilirubin (DBil), calcium (Ca), total carbon dioxide (TCO₂), and lactate dehydrogenase (LDH) for the severity of acute pancreatitis (AP) and to establish a predictive model. Methods: This retrospective study analyzed clinical data from 499 patients with acute pancreatitis admitted to our hospital from January 2019 to July 2023. Patients were divided into two groups based on their discharge diagnosis: a non-severe acute pancreatitis (NSAP) group (comprising mild acute pancreatitis (MAP) and moderately severe acute pancreatitis (MSAP), n = 349) and a severe acute pancreatitis (SAP) group (n = 150). Baseline data and laboratory results within 48 hours of admission (including WBC, N%, L%, CRP, etc.) were compared between the two groups. The correlation between serum levels of DBil, Ca²⁺, TCO₂, LDH and the severity of acute pancreatitis was statistically analyzed. Results: Intergroup comparison showed that serum levels of direct bilirubin (DBil), total carbon dioxide (TCO₂), and lactate dehydrogenase (LDH) were significantly higher in the severe acute pancreatitis (SAP) group compared to the non-severe group, while serum Ca²⁺ levels were significantly lower in the SAP group. These differences were statistically significant (P < 0.001). Univariate analysis was performed on the collected data to preliminarily screen for significant variables. Subsequently, ten-fold cross-validation via the LASSO regression model was used to determine the optimal penalty term coefficient λ. At this λ value, 9 potential relevant factors were ultimately selected: DBil, Crea, BUN, PT, Ca, TCO₂, LDH, BS, and HbA1c. Binary multivariate Logistic regression analysis indicated that DBil, Ca, TCO₂, and LDH were independent risk factors for severe acute pancreatitis. The nomogram prediction model had a C-index of 0.793. Receiver operating characteristic (ROC) curve analysis showed that the combined detection of DBil, Ca, TCO₂, and LDH had high sensitivity (0.660) and specificity (0.854) for diagnosing severe acute pancreatitis, with a Youden index of 0.514. The Hosmer-Lemeshow goodness-of-fit test yielded a P-value of 0.122 (>0.05). Conclusion: The predictive model established based on DBil, Ca, TCO₂, and LDH can be used to assess the severity of illness in patients with acute pancreatitis.