PDF(Pubmed)
Abstract：
UNASSIGNED: Early detection of hyperlipidemic acute pancreatitis (HLAP) with exacerbation tendency is crucial for clinical decision-making and improving prognosis. The aim of this study was to establish a reliable model for the early prediction of HLAP severity.
UNASSIGNED: A total of 225 patients with first-episode HLAP who were admitted to Fujian Medical University Union Hospital from June 2012 to June 2023 were included. Patients were divided into mild acute pancreatitis (MAP) or moderate-severe acute pancreatitis and severe acute pancreatitis (MSAP+SAP) groups. Independent predictors for progression to MSAP or SAP were identified through univariate analysis and least absolute shrinkage and selection operator regression. A nomogram was established through multivariate logistic regression analysis to predict this progression. The calibration, receiver operating characteristic(ROC), and clinical decision curves were employed to evaluate the model\'s consistency, differentiation, and clinical applicability. Clinical data of 93 patients with first-episode HLAP who were admitted to the First Affiliated Hospital of Fujian Medical University from October 2015 to October 2022 were collected for external validation.
UNASSIGNED: White blood cell count, lactate dehydrogenase, albumin, serum creatinine, serum calcium, D-Dimer were identified as independent predictors for progression to MSAP or SAP in patients with HLAP and used to establish a predictive nomogram. The internally verified Harrell consistency index (C-index) was 0.908 (95% CI 0.867-0.948) and the externally verified C-index was 0.950 (95% CI 0.910-0.990). The calibration, ROC, and clinical decision curves showed this nomogram\'s good predictive ability.
UNASSIGNED: We have established a nomogram that can help identify HLAP patients who are likely to develop MSAP or SAP at an early stage, with high discrimination and accuracy.
UNASSIGNED: A total of 225 patients with first-episode HLAP who were admitted to Fujian Medical University Union Hospital from June 2012 to June 2023 were included. Patients were divided into mild acute pancreatitis (MAP) or moderate-severe acute pancreatitis and severe acute pancreatitis (MSAP+SAP) groups. Independent predictors for progression to MSAP or SAP were identified through univariate analysis and least absolute shrinkage and selection operator regression. A nomogram was established through multivariate logistic regression analysis to predict this progression. The calibration, receiver operating characteristic(ROC), and clinical decision curves were employed to evaluate the model\'s consistency, differentiation, and clinical applicability. Clinical data of 93 patients with first-episode HLAP who were admitted to the First Affiliated Hospital of Fujian Medical University from October 2015 to October 2022 were collected for external validation.
UNASSIGNED: White blood cell count, lactate dehydrogenase, albumin, serum creatinine, serum calcium, D-Dimer were identified as independent predictors for progression to MSAP or SAP in patients with HLAP and used to establish a predictive nomogram. The internally verified Harrell consistency index (C-index) was 0.908 (95% CI 0.867-0.948) and the externally verified C-index was 0.950 (95% CI 0.910-0.990). The calibration, ROC, and clinical decision curves showed this nomogram\'s good predictive ability.
UNASSIGNED: We have established a nomogram that can help identify HLAP patients who are likely to develop MSAP or SAP at an early stage, with high discrimination and accuracy.
摘要：
■早期发现有加重倾向的高脂血症性急性胰腺炎（HLAP）对临床决策和改善预后至关重要。本研究的目的是建立早期预测HLAP严重程度的可靠模型。
■共纳入2012年6月至2023年6月福建医科大学附属协和医院收治的225例首发HLAP患者。将患者分为轻度急性胰腺炎（MAP）或中重度急性胰腺炎和重度急性胰腺炎（MSAPSAP）组。通过单变量分析和最小绝对收缩和选择算子回归确定了进展为MSAP或SAP的独立预测因子。通过多变量逻辑回归分析建立列线图来预测这种进展。校准，接收机工作特性(ROC)，并采用临床决策曲线评估模型的一致性，分化,和临床适用性。收集2015年10月至2022年10月福建医科大学附属第一医院收治的93例首发HLAP患者的临床资料进行外部验证。
■白细胞计数,乳酸脱氢酶,白蛋白,血清肌酐,血清钙，D-二聚体被确定为HLAP患者进展为MSAP或SAP的独立预测因子，并用于建立预测列线图。内部验证的Harrell一致性指数（C指数）为0.908（95％CI0.867-0.948），外部验证的C指数为0.950（95％CI0.910-0.990）。校准，ROC,临床决策曲线显示该列线图具有良好的预测能力。
■我们建立了一个列线图，可以帮助识别早期可能发展为MSAP或SAP的HLAP患者，具有很高的辨别力和准确性。
■共纳入2012年6月至2023年6月福建医科大学附属协和医院收治的225例首发HLAP患者。将患者分为轻度急性胰腺炎（MAP）或中重度急性胰腺炎和重度急性胰腺炎（MSAPSAP）组。通过单变量分析和最小绝对收缩和选择算子回归确定了进展为MSAP或SAP的独立预测因子。通过多变量逻辑回归分析建立列线图来预测这种进展。校准，接收机工作特性(ROC)，并采用临床决策曲线评估模型的一致性，分化,和临床适用性。收集2015年10月至2022年10月福建医科大学附属第一医院收治的93例首发HLAP患者的临床资料进行外部验证。
■白细胞计数,乳酸脱氢酶,白蛋白,血清肌酐,血清钙，D-二聚体被确定为HLAP患者进展为MSAP或SAP的独立预测因子，并用于建立预测列线图。内部验证的Harrell一致性指数（C指数）为0.908（95％CI0.867-0.948），外部验证的C指数为0.950（95％CI0.910-0.990）。校准，ROC,临床决策曲线显示该列线图具有良好的预测能力。
■我们建立了一个列线图，可以帮助识别早期可能发展为MSAP或SAP的HLAP患者，具有很高的辨别力和准确性。
