Frontiers in pediatrics · 2026
A recurrence prediction model based on serological indicators in children with acute pancreatitis without pancreaticobiliary anatomical abnormalities.
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Hu Xueyi, Zhang Tao, Cheng Yuan, Qi Shiqin, Pan Zhubin
Аннотация
OBJECTIVE: To explore the related influencing factors of recurrent acute pancreatitis in children and provide a reference for clinical early identification of high-risk children with recurrent acute pancreatitis (RAP).
METHODS: A retrospective case-control study was designed to collect the clinical data of 101 children who were diagnosed with acute pancreatitis (AP) and hospitalized in Anhui Children's Hospital from July 2020 to December 2025. The children were divided into two groups according to the recurrence of the disease: the acute pancreatitis group (only one hospitalization due to AP during the study period, n = 68) and the recurrent acute pancreatitis group (hospitalization due to repeated AP history with an interval of at least one month between any two AP-related hospitalizations, n = 33). Demographic data and serological indicators were compared between the two groups. Differential indicators were screened by univariate analysis, and independent related factors of RAP were identified by multivariate binary Logistic regression model. The diagnostic value of independent factors was analyzed by receiver operating characteristic (ROC) curve, and a combined diagnostic model and nomogram were constructed and their efficacy was verified.
RESULTS: Univariate analysis showed that there were statistically significant differences in triglyceride (TG), high density lipoprotein (HDL), blood glucose (BG) and D-dimer levels between the two groups (P < 0.05). Multivariate binary Logistic regression analysis indicated that HDL (OR=0.037, 95% CI: 0.003-0.384, P = 0.006), BG (OR=2.503, 95% CI: 1.413-4.435, P = 0.002) and D-dimer (OR=1.525, 95% CI: 1.199-1.938, P < 0.001) were independent related factors for RAP in children. ROC curve analysis showed that the areas under the curve (AUC) of HDL, BG and D-dimer for single diagnosis of RAP were 0.778, 0.830 and 0.825, respectively, and the AUC of the combined diagnosis of the three was 0.943 (95% CI: 0.902-0.983, P < 0.001). At the maximum Youden index, the sensitivity and specificity of the combined diagnostic model were 0.82 and 0.84, respectively. The calibration curve of the nomogram model constructed based on the above three independent factors had a high coincidence with the diagonal line, suggesting a good predictive efficacy of the model.
CONCLUSION: HDL is an independent protective factor for RAP in children, while BG and D-dimer are independent risk factors. Clinical combined detection of these three indicators can improve the accuracy of early diagnosis of RAP and provide a basis for precise intervention in high-risk children.
METHODS: A retrospective case-control study was designed to collect the clinical data of 101 children who were diagnosed with acute pancreatitis (AP) and hospitalized in Anhui Children's Hospital from July 2020 to December 2025. The children were divided into two groups according to the recurrence of the disease: the acute pancreatitis group (only one hospitalization due to AP during the study period, n = 68) and the recurrent acute pancreatitis group (hospitalization due to repeated AP history with an interval of at least one month between any two AP-related hospitalizations, n = 33). Demographic data and serological indicators were compared between the two groups. Differential indicators were screened by univariate analysis, and independent related factors of RAP were identified by multivariate binary Logistic regression model. The diagnostic value of independent factors was analyzed by receiver operating characteristic (ROC) curve, and a combined diagnostic model and nomogram were constructed and their efficacy was verified.
RESULTS: Univariate analysis showed that there were statistically significant differences in triglyceride (TG), high density lipoprotein (HDL), blood glucose (BG) and D-dimer levels between the two groups (P < 0.05). Multivariate binary Logistic regression analysis indicated that HDL (OR=0.037, 95% CI: 0.003-0.384, P = 0.006), BG (OR=2.503, 95% CI: 1.413-4.435, P = 0.002) and D-dimer (OR=1.525, 95% CI: 1.199-1.938, P < 0.001) were independent related factors for RAP in children. ROC curve analysis showed that the areas under the curve (AUC) of HDL, BG and D-dimer for single diagnosis of RAP were 0.778, 0.830 and 0.825, respectively, and the AUC of the combined diagnosis of the three was 0.943 (95% CI: 0.902-0.983, P < 0.001). At the maximum Youden index, the sensitivity and specificity of the combined diagnostic model were 0.82 and 0.84, respectively. The calibration curve of the nomogram model constructed based on the above three independent factors had a high coincidence with the diagonal line, suggesting a good predictive efficacy of the model.
CONCLUSION: HDL is an independent protective factor for RAP in children, while BG and D-dimer are independent risk factors. Clinical combined detection of these three indicators can improve the accuracy of early diagnosis of RAP and provide a basis for precise intervention in high-risk children.